Citation
Emotion and the Defense Cascade: Modulation of Voluntary and Involuntary Movement

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Title:
Emotion and the Defense Cascade: Modulation of Voluntary and Involuntary Movement
Creator:
COOMBES, STEPHEN A. ( Author, Primary )
Copyright Date:
2008

Subjects

Subjects / Keywords:
Amygdala ( jstor )
Blinking ( jstor )
Dyskinesia ( jstor )
Emotional expression ( jstor )
Mental stimulation ( jstor )
Monkeys ( jstor )
Motor ability ( jstor )
Motor cortex ( jstor )
Neurons ( jstor )
Signals ( jstor )

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Source Institution:
University of Florida
Holding Location:
University of Florida
Rights Management:
Copyright Stephen A. Coombes. Permission granted to University of Florida to digitize and display this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Embargo Date:
8/31/2006
Resource Identifier:
476200337 ( OCLC )

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Full Text












EMOTION AND THE DEFENSE CASCADE: MODULATION OF
VOLUNTARY AND INVOLUNTARY MOVEMENT
















By

STEPHEN A. COOMBES


A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA


2006

































Copyright 2006

by

STEPHEN A. COOMBES















ACKNOWLEDGMENTS

I thank Dr. Christopher Janelle for his continued support and supervision of my

academic development as well as his invaluable wisdom on matters of real life. Likewise,

I thank Dr. Jim Cauraugh whose continued enthusiasm and keen interest have been hugely

appreciated. I also thank my committee members, Dr. Mark Tillman and Dr. Ira Fischler

for their patience, input, and support.

Finally I thank my family, the wonderful Christine, and my great friends on both

sides of the Atlantic.
















TABLE OF CONTENTS

page

A C K N O W L E D G M E N T S ................................................................................................. iii

L IST O F F IG U R E S .... ...... ................................................ .. .. ..... .............. vii

ABSTRACT .............. .......................................... ix

CHAPTER

1 IN TR OD U CTION ............................................... .. ......................... ..

E m otion an d M ov em ent ............................................................... .......................... 1
D defensive B behavior .............................. .... ................... ..... .............2
Orienting of Attention: Valence or Arousal?..............................................................3
EM G and Force M measures .................................................. .............................. 4
A acoustic Initiated M ovem ents......................................................... ..................... 6
H ypotheses ................................................ 8

2 EM OTION AND M OVEM ENT ............................................ .......................... 9

Cortical Control of M ovem ent......................................................... ............... 10
Prim ary M otor Cortex (M ) ........................................................ ............ ...... 10
The Supplementary Motor Area (SMA)...........................................................14
Subcom ponents of the SM A ........................................... .......... ............... 14
T he Prem otor C ortex (PM )...................................................................... .. .... 17
Subcom ponents of PM cortex .................................. .............................. ....... 19
Cingulate M otor A reas .................................................... ............................ 22
Self- Versus Externally-Paced Movements........................................ 26
Summary: Cortical Control of Movement........................................................29
Subcortical Control of Movement .............. ......................................31
B asal G anglia ................................................ ................. .. 3 1
The D defense Cascade .................................. ................. ..... ....... 37
Basal Ganglia and Emotion ................................ .......................... 40
Brainstem R eticular Form ation ........................................ ....................... 43
Sum m ary: The M otor System ........................................ ........................ 45
E m option ............... .................................................................................... ...... 4 5
Biphasic Theory of Emotion .................................. .......................... 47
Em otional Circuitry ............................................. ........ ...... ................. 47
T h e lim b ic sy stem ................................ .... ...... .. .................. ..............4 7









A m y g d a la ............................................................................................... 4 9
Periacqueductal central grey ............................................. ............... 52
A acoustic Startle and M ovem ent............................................ ........... ............... 56
Startle C ircu it........................ ..................... ................56
Acoustic Startle and Involuntary Movement...........................................58
Acoustic Startle and Voluntary Movement ...................................................59
Acoustic Startle, Emotion, and Movement........................................ ............... 65
Acoustic Startle, Emotion, and Involuntary Movement............................... 65
Cacioppo's Evaluative Space M odel............................................................... 70
Emotion and Voluntary Movement............... ................................................71
Acoustic Startle, Emotion, and Voluntary Movements.................. ............74
C on clu sion ................................................................................................... 7 5

3 M E T H O D S ........................................................................................................... 7 7

P a rtic ip a n ts ........................................................................................................... 7 7
Instrumentation ............... ......... .......................77
A ffe ctiv e S tim u li ........................................................................................... 7 7
T a sk ..............................................................................7 8
A cou stic Stim u li .............................................................7 8
V voluntary M ov em ent..................................................................................... 79
Blink reflex .......... .. ............ .... ...............79
P ro cedu re ......... .... .............. .................................... ...........................80
D ata R e d u ctio n ..................................................................................................... 8 0
Voluntary movement ...................... ......... ................80
Blink reflex .......... .. ................ ...............82
Statistical Analyses .................. ........ ..................83

4 R E S U L T S .............................................................................8 5

Voluntary Movement ...... ................ ..................... 85
Prem otor R action Tim e (PRT)................................................. 85
E M G R isetim e (E M G risetime) .......................................................................... 86
EMG Peak Normalized T-scores (EMGamp) ........................................................ 86
E M G Slope (E M G slope) .................................................................................. 87
Force Risetime (Frisetime) ........... .....................................88
Peak Force Normalized T-scores (Famp) ..................................... ...............88
Force Slope (Fslope) .......................................................88
Involuntary M ovem ent (Blink Reflex) ....................................................... 89
Prem otor R action Tim e (PRT)................................................. 89
P eak E M G T sco re ......................................................................................... 8 9
Peak latency ................ .... ......... ..................90
E M G slope ............. .... .... ........................ ........... ... ......... ........91
Correlations: Voluntary and Involuntary Movement ..................................... 91
Prem otor R action Tim e (PRT)................................................. 92
P eak E M G T score......................................................................................... 92
EMG slope ................ ... ......... .................. 93


v









5 D IS C U S S IO N ...............................................................................................9 4

Voluntary Movement..................................................................... ...............95
Prem otor R action Tim e.................................................. ........................ 95
Peak EMG and Peak Force Amplitude ............................................................100
Summary .............. .......................................................... ..............101
Unpleasant and Neutral Stimuli Similarly Modulate Movement? ..........................103
Voluntary and Involuntary Movements: Is there a relationship? ..........................104
Premotor RT .................................... .............................. ........ 104
P e a k E M G ................................................................. ................................1 0 4
EMG Slope ............................................... .............. .......... 105
S u m m a ry .................................................................................................. 1 0 5
L im itatio n s .................................................................................................... 1 0 5
Future Research .......................................... ................... .... ........ 108
C o n c lu sio n ..................................................................................................... 1 1 0

L IST O F R E F E R E N C E S ........................................................................................... 112

BIOGRAPHICAL SKETCH .............................................................. ...............133
















LIST OF FIGURES


Figure pge

2-1 Im aging the prem otor areas.............................................................. ...............18

2-2 Schematic of the two frontal regions implicated in monitoring functions...............27

2-3 M otor circuit of the basal ganglia ..................................... ........................ ......... 32

2-4 The cortico-STN-pallidal "hyperdirect" pathway .......................................... 35

2-5 Possible neuronal mechanisms of integration of volitional, emotional and
automatic control of motor behaviors .......................................... ...............36

2-6 A schematic presentation of the defense response cascade............... ...................38

2-7 Integration of volitional, emotional and automatic control of motor behaviors.......41

2-8 Rats with lesions of the dPAG or the vPAG in comparison with sham-lesioned rats
showed enhanced or decreased levels of freezing, respectively ..............................53

2-9 Linking the Amygdala, reticular formation, and the Periacqueductal Central
G rey ......................................... .. .. ...................................................5 4

2-10 The prim ary acoustic startle reflex...................................... ......................... 57

2-11 Affective modulation of startle circuitry: priming motor function ........................66

2-12 The Evaluative Space M odel......................................................... ............... 69

2-13 P rim ing m otor function ........................................ .............................................75

3-1 Experimental setup .............. .... ...... ........ ........................... ........ 81

3-2 Calculation of dependent variables: voluntary movement .................................... 83

3-3 Calculation of dependent variables: blink reflex ............... ............. ...............84

4 1 P R T ..................................................................................................................... 8 6

4-2 E M G amp. ....................................................................................87









4 -3 F o rc eam p ...................................................................8 9

4-4 Blink reflex prem otor reaction tim e................................ ................................. 90

4-5 M ean blink peak T score ............................................... ............................... 91

4-6 Peak EMG latency of the blink reflex.................... ........ ................. 92

4-7 EMG slope of the startle blink reflex....................... ..........................93















Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy

EMOTION AND THE DEFENSE CASCADE: MODULATION OF
VOLUNTARY AND INVOLUNTARY MOVEMENT


By

Stephen A. Coombes

August 2006

Chair: Christopher M. Janelle
Major Department: Applied Physiology and Kinesiology

Evidence indicates that voluntary and involuntary movements are altered by

affective context, the characteristics of an initiating stimulus, as well as the duration

between affective context onset and initiating cue. The purpose of the present study was

to delineate the central and peripheral mechanisms that contribute to this phenomenon.

During the presentation of attack, erotic, household object and blank images, participants

(N = 35) were instructed to respond to auditory stimuli (startle, 107dB; or probe, 80dB)

presented at varying time intervals following picture onset (500, 1500, 3000-5000 msec)

by initiating a bimanual isometric contraction of the wrist and finger extensor muscles

against two independent load cells. The startle blink response was also measured to

provide an index of how valence and probe interval modulate involuntary movement.

Analyses of electromyography and force measures revealed that (1) voluntary and

involuntary movements are sensitive to short lead interval prepulse effects, (2) the

intensity of an acoustic startle stimulus accelerates temporal components and strengthens









magnitude components of voluntary movement, (3) faster and stronger voluntary

movements occurred approximately 1500 msec post image onset, when initiated to startle

cues with a strong trend indicating that this pattern was accentuated during exposure to

attack images. Collectively, these findings carry significant implications for those seeking

to facilitate the speed and force of voluntary movement (i.e., movement rehabilitation),

and for those seeking to regulate emotional input so as to optimize the quality of intended

movements.














CHAPTER 1
INTRODUCTION

Emotion and Movement

Rapidly identifying emotionally salient information in threatening and dangerous

contexts, and demonstrating the ability to translate that information into successful and

appropriate behaviors is critical to survival. A primary function of emotion, therefore, is

the preparation for action (Schupp, Junghofer, Weike, & Hamm, 2003a). The link

between primitive emotions and overt motor actions was first noted by (Cannon, 1929),

who suggested that when confronted with a dangerous situation, an organism elicits an

"emergency reaction" composed of either a fight or flight survival response. The basic

principle of Cannon's work remains intact today. Modulated by the threat from predators,

defensive behaviors have been classified into three categories that traverse the entire

animal kingdom: freezing, fleeing, and fighting (defensive attack: Eilam, 2005).

Demonstrating the impact these defensive predispositions have on voluntary and

involuntary movement is the primary purpose of this proposal.

The utility of understanding defensive predispositions is two fold. First, activating

emotional circuits that predispose humans to execute specific motor actions may be an

effective method to forge new pathways between intention and movement for those

suffering motor impairment (e.g., stroke). For example, despite increased research efforts

and rehabilitation options, over 65% of individuals with stroke have residual motor

impairments one-year post (Wade, Langton-Hewer, Wood, Skilbeck, & Ismail, 1983). As

such, understanding how emotions modulate movement may lead to emotional









manipulations being fused into existing rehabilitation techniques to enhance their

effectiveness.

Second, within a wide range of performance contexts, movements have to be

executed during dynamic states of emotional flux. In consequence, predisposed

movements may be incongruent with intentional movements. Understanding how

emotions predispose movement, therefore, will be essential in tailoring regulatory

strategies to combat emotion driven dispositions. In short, understanding how active

defensive circuitry alters overt motor behavior holds considerable promise for emotion

regulation as well as movement rehabilitation.

Defensive Behavior

Animal models indicate that the amygdala and the dorsal and ventral

periaqueductal gray (PAG) mediate the expression of defensive behaviors according to

the nature of the threat, including its 1) type (i.e., immediate/innate/ conditioned), 2)

proximity, and 3) complexity. The defense cascade model, conceptualized within an

evolutionary perspective of the relative position of predator and prey (Bradley & Lang,

2000; Fanselow, 1994; Lang, Bradley, & Cuthbert, 1997; Wade et al., 1983), proposes

three distinct defensive phases: pre-encounter, post-encounter (freezing), and circa-

strike/defensive fighting/fleeing.

Within picture-viewing paradigms, exposure to an unpleasant cue results in a stable

pre-encounter condition that is then superseded by a post-encounter state reflected in an

initial "orienting of attention" and a rapid increase in skin conductance response

(arousal). Oriented attention typically manifests in strong inhibition of the startle blink

reflex for highly arousing visual stimuli (Bradley, Cuthbert, & Lang, 1993), cardiac

deceleration (Bradley, Codispoti, Cuthbert, & Lang, 2001), and a reduction in postural









sway (Azevedo et al., 2005). Cardiac acceleration and potentiation of the startle blink

reflex (accentuated in unpleasant contexts) signal the transition from a post encounter

freezing phase to defensive mobilization (approx. 800 msec).

Orienting of Attention: Valence or Arousal?

Although activation of defensive circuitry (e.g., startle blink potentiation) has been

demonstrated early in the viewing period when phobic's view objects relating to their

phobias (Globisch, Hamm, Esteves, & Ohman, 1999), startle blink inhibition among

controls typically coincides with highly arousing affective foregrounds, independent of

valence (Bradley et al., 1993). The notion, however, that attention rather than valence

modulates the early blink reflex (<800 msec) has recently been contested. Specifically,

Stanley and Knight (2004) demonstrated that relative to positive and neutral contexts,

blink potentiation occurred at both early (300msec) and late (2-5 s) probe times during

exposure to threat images. Conversely, exposure to disgust images only resulted in a

main effect of blink potentiation relative to positive contents. As such, averaging across

"unpleasant" foregrounds rather than analyzing specific categories (i.e., threat, disgust)

within broad time windows may prevent threat-related blink potentiation from emerging.

Consequently, acute specification of emotional context, as well as probe interval

duration, are essential in understanding the time course of active defensive circuitry. The

primary goal of this proposal, therefore, is to confirm threat related startle blink

potentiation across freezing and defense mobilization phases, and to determine how this

progression simultaneously alters voluntary movement.

The innate predisposition to protect oneself from danger (active defensive system)

is complemented by the instinctive tendency to approach pleasant stimuli (active

appetitive system). Capturing the polarity between approach and avoidance, Lang,









Bradley and colleagues (Lang et al., 1997) have proposed the Biphasic Theory of

emotion. The extent to which emotions alter the direction (approach/withdrawal), speed,

magnitude, and accuracy of voluntary movements has been captured within a number of

behavioral protocols. Specifically, relative to activation of appetitive circuitry, activation

of defensive circuitry accelerates avoidance movements (i.e., pushing a lever away from

the body, Chen and Bargh, 1999; Duckworth et al., 2002; Marsh et al., 2005), accelerates

the speed and decreases the accuracy of a controlled motor task (Coombes, Janelle, &

Duley, 2005), and leads to greater force production during a sustained isometric

contraction without sacrificing movement variability (Coombes, Cauraugh, & Janelle,

2006).

In addition to force production, EMG measures are routinely used to index

voluntary (Carlsen, Chua, Inglis, Sanderson, & Franks, 2004a; Valls-Sole, Rothwell,

Goulart, Cossu, & Munoz, 1999; Valls-Sole et al., 1995) and involuntary movements

(Hillman et al., 2004; Stanley and Knight 2004). Combining EMG and force measures

offers a unique approach to indexing the effect of emotion on movement. Indeed,

understanding the physiology of EMG and force production ensures that findings can be

interpreted according to physiological mechanisms.

EMG and Force Measures

Amplitude of surface EMG is routinely used to quantify voluntary and involuntary

muscular contraction (Bolton, Cauraugh, & Hausenblas, 2004; Hillman, Rosengren, &

Smith, 2004; Moore, Drouin, Gansneder, & Shultz, 2002; Rau, Schulte, & Disselhorst-

Klug, 2004; Stanley & Knight, 2004). Surface EMG amplitude and latency is sensitive to

the number and rate of motor unit contractions (Andreassi, 2000), as well as the size and

location of motor unit activation relative to the position of the corresponding sensors









(Keenan, Farina, Merletti, & Enoka, 2005). In addition, the size of the evoked muscle

potential is influenced by sarcolemmal conduction velocity, axonal conduction velocity,

variability in the activation times of motor neurons, and shape of the intracellular action

potential (Keenan et al., 2005).

Although numerous variables alter EMG amplitude, startle elicited blink

amplitudes consistently vary according to affective valence. For example, greater peak

EMG amplitude, reflecting a stronger muscular contraction, has been associated with

startle elicited blink reflexes during exposure to threat images (relative to neutral and

pleasant) at early (300msec: Stanley & Knight, 2004) and late probe intervals (>

2000msec: Lang, Bradley, & Cuthbert, 1990; Stanley & Knight, 2004). In addition, we

(Coombes et al., in review) have demonstrated a similar effect on voluntary movement,

such that exposure to unpleasant images interacts with the presentation of movement

initiating startle cues (relative to an 80db tone) resulting in greater peak amplitude

relative to all valence tone probe conditions. Further, peak EMG voluntary and

involuntary latencies attenuate when movements are executed to startle cues during

exposure to unpleasant images (Lipp, Siddle, & Dall, 1997). Collectively, EMG indices

of voluntary and involuntary movement have been interpreted as indicating that an

evolutionary/survival advantage maybe gained from the execution of strong, rapid muscle

contractions.

The force produced by a muscle depends on the number and size of active motor

units and the rate at which those units discharge action potentials (Macefield, Fuglevand,

& Bigland-Ritchie, 1996; Moritz, Barry, Pascoe, & Enoka, 2005). Specifically, two

mediating mechanisms have been proposed to account for muscular force production









(Kamen & Du, 1999); the "size principle" and "rate coding." By sequentially increasing

the number of active motor units within the motoneuron pool, from the smallest motor

units to the largest, the total force output increases (size principle) (Aimonetti, Vedel,

Schmied, & Pagni, 2000; Henneman, 1979; Schmied, Aimonetti, & Vedel, 2002;

Schmied, Morin, Vedel, & Pagni, 1997). This recruitment order has been confirmed for

isometric contractions with a high correlation between recruitment force threshold and

twitch force (Riek & Bawa, 1992). Second, although motor unit discharge rates have

been associated with variations in force production (rate coding: (Milner-Brown, Stein, &

Yemm, 1973), given that motor units vary according to threshold and spike amplitude, it

is not a simple linear relationship between discharge rate and force production (Hamada,

Kimura, & Moritani, 2004; Klein, Ivanova, Rice, & Garland, 2001). Nevertheless, we

have previously demonstrated that indices of force are modulated according to initiating

stimulus and valence. Specifically, peak forces are accentuated, onset to peak force

slopes are steeper, and latencies are shorter when ballistic wrist and finger extensions are

executed to startle relative to tone cues (Coombes et al., in review). Further, force onset

slopes are steeper, and latencies are shorter when ballistic movements are executed

during unpleasant relative to pleasant and blank exposure conditions. These data suggest

that startle initiating cues and activation of defensive circuitry increase the size and/or

number of active motor units.

Acoustic Initiated Movements

The acoustic startle reflex is a short-latency behavior elicited by a sudden and

intense acoustic stimulus (Grillon & Baas, 2003). Considered a primitive defensive

reflex, the acoustic startle serves as an interrupt of ongoing behavior (Lang et al., 1990).

The probable chain of activation of the primary acoustic startle reflex is generally









considered to consist of 3 synapses: (1) cochlear root neurons; (2) PnC neurons; and (3)

motor neurons in the spinal cord (Lang, Davis, & Ohman, 2000; Y. Lee, Lopez, Meloni,

& Davis, 1996). Direct links between the amygdala and the nucleus reticularis pontis

caudalis (PnC) and PAG are critical in potentiation for the startle reflex (Davis &

Whalen, 2001; Zhao & Davis, 2004).

Accelerating premotor reaction times by replacing "go" signals with startle cues

has been consistently replicated (Carlsen et al., 2004b; Valls-Sole et al., 1999; Valls-Sole

et al., 1995). To account for these findings the subcortical triggering hypothesis has been

proposed, and contends that startle cues initiate movements that are stored subcortically

within the reticular formation (Carlsen, Chua, Inglis, Sanderson, & Franks, 2004a).

Should this be the case, given that amygdala (via PAG) projections to the PnC are

responsible for potentiation of the startle blink, there is reason to believe that voluntary

movements executed from the PnC will be altered by emotion in a similar fashion to

involuntary movements. As such, we will determine how the characteristics of voluntary

and involuntary movements are altered according to varying initiating cues, affective

contexts, and probe intervals.

Participants will be exposed to attack, erotica, neutral, and blank images. Picture

onset will be a cue for participants to ready themselves to move. During image

presentation, participants will be instructed to initiate a simple RT ballistic movement at

the presentation of acoustic stimuli (either a startle, 107dB; or tone, 80dB). The

presentation period will run for 6 seconds, during which startle and tone cues will be

equally represented at 3 predetermined time intervals during the exposure period

(500msec, 1500msec, 3000-5000msec). Voluntary movements of the wrist and finger









extensors will be indexed via force transducers and EMG sensors on the fore-arms. An

index of the involuntary blink reflex will be captured via EMG sensors beneath the left

eye. Three hypotheses are offered.

Hypotheses

la) We predict that if valence modulates movement at all time intervals,

movements to acoustic cues during exposure to threat images will be significantly

different from erotica, neutral, and blank exposures (attack = accelerated times,

accentuated peaks, steeper slopes. 1)

lb) However, if arousal modulates movement early in the exposure period

(500msec), movements during exposure to attack and erotica images will be similar, and

each will be different compared to neutral and blank images (attack and erotica =

decelerated times, attenuated peaks, shallower slopes).

2) Relative to tone initiated voluntary movements, startle initiated movements at all

probe intervals will be significantly different from all tone initiated movements (startle =

accelerated times, accentuated peaks, steeper slopes. 1)

3) Significant positive correlations between corresponding voluntary and

involuntary dependent variables during startle trials will permit the interpretation that

voluntary and involuntary movements share similar subcortical pathways.








1 Accelerated times: faster voluntary and blink PMTs; faster voluntary and involuntary EMG
risetime; faster force risetime; faster peak blink EMG latency; Accentuated peaks: greater peak voluntary
and blink EMG; greater voluntary peak force; Steeper slopes: steeper slope to voluntary and blink peak
EMG; steeper slope to voluntary peak force














CHAPTER 2
EMOTION AND MOVEMENT

Overt coordinated motor behavior is the culmination of a complex interaction

between various functioning neural structures. To better understand the controlling

mechanisms of movement related decision making, movement preparation, movement

execution, and movement feedback, the major cortical and subcortical structures involved

in movement will be addressed. Specific attention will be paid to areas where emotion

may impact the motor system. The primary motor area (Ml), the supplementary motor

area (SMA), the dorsal premotor area (PMd), and the cingulated motor areas (CMA) are

included in a section concerning the role of the cortex in movement production.

Following a summary of the cortical regions, the basal ganglia and reticular formation are

evaluated in terms of their role in motor behavior.

Two major improvements have been made in the evolution of human motor

control; the capability to maintain an erect posture and the ability to move the fingers

independently (Canedo, 1997). While bipeds and quadrupeds boast neural mechanisms

that integrate bodily movement and associated postural adjustments, the postural

constraints imposed by bipedal locomotion are more demanding (Canedo, 1997). The

activity of distal, proximal, and axial muscles have to be controlled by some structure or

structures able to coordinate medial and lateral motor systems. Specific cortical and

subcortical regions, coupled with descending spinal tracts collectively permit the

necessary simultaneous activation of distal and postural muscles (e.g., Picard & Strick,









1996; Vulliemoz, Raineteau, & Jabaudon, 2005). Details of the cortical and subcortical

structures that permit such motor control are presented below.

Cortical Control of Movement

Large regions of the brain located on the lateral surface and on the medial wall of

each hemisphere participate in the generation and control of movement. Four distinct

areas have been identified: 1) Primary motor area (Ml, the precentral gyms), 2)

Supplementary motor area (SMA, adjacent to the premotor area, but on the medial

surface of the hemisphere), 3) Premotor area (anterior to Ml, on the lateral aspect of the

hemisphere), and 4) Cingulate motor area (in the anterior part of the cingulate sulcus,

adjacent to the inferior end of the SMA).

Primary Motor Cortex (Ml)

Located along the precentral gyms in Brodmans area 4, the Ml houses

considerable pyramidal neurons that directly link (via the corticospinal tract) with the

spinal cord. In consequence, the Ml is considered a key structure in the execution of

voluntary movement (Canedo, 1997; Cunnington, Windischberger, Deecke, & Moser,

2002; Lee, Chang, & Roh, 1999; Wildgruber, Erb, Klose, & Grodd, 1997). Traditionally,

the MI was thought to be exclusively involved in the execution of movements (Richter,

Andersen, Georgopoulos, & Kim, 1997). However, this conventional view was

challenged by the discovery of higher-order motor components in the MI of monkeys

(Georgopoulos, Taira, & Lukashin, 1993). Preparatory activity in the Ml in monkeys

stimulated corresponding questions to be asked of the Ml in humans. During completion

of a delayed cued finger movement task (i.e., a warning signal followed by a delay,

followed by a go signal) Richter et al. (1997) collected event-related fMRI data from Ml,

PM, and SMA and reported activity in all three areas during movement preparation and









movement execution. As predicted, activity in Ml was weaker during movement

preparation than during movement execution; and although activity was of similar

intensity during preparatory and execution periods in the secondary motor areas, during

the execution phase Ml activity was greater relative to activity in the secondary areas.

Although Ml activity during preparatory periods has been corroborated elsewhere

(Crammond & Kalaska, 2000; Mushiake, Inase, & Tanji, 1991), it should be noted that

the Ml cells sensitive to movement preparation have been located close to the dorsal PM

area (Crammond & Kalaska, 2000).

To date, however, Ml activity continues to be closely associated with movement

execution, best exemplified by the consequences of Ml lesions which result in impaired

voluntary movements of associated body parts (Lang & Schieber, 2003). Specifically, the

ability to move and control one body part exclusively of all others (e.g., the fingers) is

severely impaired, with attempted individual movements often accompanied by

considerable involuntary movements of adjacent body parts (Lang & Schieber, 2003;

Schieber & Poliakov, 1998). Additional support of the Mi's acute control of movement

is demonstrated in subtle finger movements; movements that can be temporarily

unattainable by reversible inactivation of small portions of the hand representation area in

Ml (Brochier, Boudreau, Pare, & Smith, 1999; Schieber & Poliakov, 1998).

Ml activation is not essential or alone, however, in its control of voluntary

movement as evidenced by the very limited involvement of the cat Ml during routine

locomotion across a regular surface (Beloozerova & Sirota, 1993; Marple-Horvat, Amos,

Armstrong, & Criado, 1993). Investigations into the many basic neuronal networks

regulating somatic movement have, in consequence, successfully focused on the









brainstem (Canedo, 1997). Under circumstances when automated movements have to be

modified online (i.e., traversing undulating surfaces), and alterations in exact placement

of the foot are demanded, the discharge of the pyramidal neurons in the motor cortex are

considerably accentuated; the more difficult the placement, the greater the discharge

(Beloozerova & Sirota, 1993). In consequence movements that demand acute online

adjustment, or the use of individual proximal body parts, require Ml input if successful

execution is to be realized.

A redeeming quality of the Ml that emanates across the majority of literature

concerns its physiological make-up. Evidence suggests that rather than specific portions

of the Ml unilaterally controlling specific movements, the diversity and overlapping

nature of the distributed network of neurons within each portion of the Ml ensure that

damage to one area can often be compensated for by adjacent areas (Donoghue & Sanes,

1988; Sanes & Donoghue, 2000). A considerable advantage of such a distributed network

permits the immense storage capability and richness of function as well as providing a

basis for network flexibility (Elbert, Pantev, Wienbruch, Rockstroh, & Taub, 1995; Sanes

& Donoghue, 2000). As such, the amount of brain matter devoted to any particular body

part is dynamic and flexible, with neural representations waxing or waning according to

use; in turn altering the level of control the associated portion of the Ml has over that

body part (Elbert et al., 1995).

The increase and decrease in limb specific cortical representation is termed neural

plasticity (Sanes & Donoghue, 2000). Maintaining or enhancing the cortical

representation of any body part is reliant upon continued use; a severe infarction or lesion

that prevents the flow of necessary information within the neural structures that permit









movement typically leads to catastrophic consequences (Wilson, Gandevia, Inglis,

Gracies, & Burke, 1999). If a limb cannot be used, its cortical representation diminishes

via cortical reorganization, sometimes with alarming consequences (Woodhouse, 2005).

On the opposite end of the continuum, however, the alternative is that neural

representation increases the more use a specific limb gets; the larger the corresponding

cortical representation, the finer the control one has over that specific limb (Elbert et al.,

1995).

This reciprocal cause and effect neural plasticity relationship has been elegantly

demonstrated in rats (Donoghue & Sanes, 1988). Following the amputation of a rats

forelimb at birth, 2-4 months following amputation the authors noted the occurrence of 3

organizational differences: 1) intact muscle groups had enlarged cortical representations,

2) normally weak connections from MI to the proximal musculature were strengthened,

and 3) muscles were grouped in unusual combinations in the reorganized cortical maps.

Evolving from work in rat models, observation of the dynamic substrate of the human

motor cortex is a relatively new phenomena, but one that warrants considerable optimism

within the movement rehabilitation domain. Indeed, current knowledge portrays Ml as a

distributed network of neurons that collectively demonstrate an innate ability to

reorganize according to physiological circumstance.

In conclusion, given an intact network between the cortex and limb, the Ml is

essential to the initiation and control of volitional movement. If emotion has the

capacity to alter movements, which one assumes it does, one must consequently ask,

exactly which part of the process does emotion modulate? Given the physiological

make-up, anatomical connections, and function of M1, there appears to be no direct









route via which emotion can alter the initiation of movements within the M1.

Although other brain regions were thought to influence motor output only by way of

efferent projections to Ml, recent evidence suggests that the secondary and cingulate

motor areas also have direct access to corticospinal tracts and the lower brain

mechanisms essential in the realization of volitional movement (Dum & Strick, 1991).

The Supplementary Motor Area (SMA)

Located in Brodman's area 6 the SMA lies medial to the premotor area and

projects to Ml and to the corticospinal and corticobulbar tracts. Removing portions of the

SMA produces specific deficits in bimanual coordination (Brinkman, 1984) or internally

guided or instructed movements (Kazennikov et al., 1998; Kermadi, Liu, Tempini, &

Rouiller, 1997), whereas chemical inactivation results in an inability to sequentially

execute multiple movements (Shima & Tanji, 1998). Likewise, clinical SMA lesion

studies have corroborated impairments similar to those induced via inactivation: the

failure of sequential motor performance (Laplane, Talairach, Meininger, Bancaud, &

Bouchareine, 1977; Laplane, Talairach, Meininger, Bancaud, & Orgogozo, 1977) and a

reduction in spontaneous movements (Krainik et al., 2001). The SMA therefore appears

to be charged with guiding sequential movements based on internal cues, and is often

associated with the performance of pre-learned motor sequences (Jenkins, Brooks, Nixon,

Frackowiak, & Passingham, 1994), or self paced motor behaviors (e.g., self paced finger

movements: (Larsson, Gulyas, & Roland, 1996).

Subcomponents of the SMA

The SMA may not function as a single unit, and the functions charged to the SMA

as a whole may be housed within independent functionally distinct regions. Specifically,

whereas lesions of the SMA lead to deficient sequential motor performance (Laplane,









Talairach, Meininger, Bancaud, & Bouchareine, 1977) and a reduction in spontaneous

movements (Krainik et al., 2001), lesions of the pre-SMA manifest in deficits in updating

sequential movements (Shima & Tanji, 1998) and the acquisition of sequential

procedures (Nakamura, Sakai, & Hikosaka, 1999). The functional difference between

different portions of the SMA emerged from the notion that cognitive demands)

associated with the motor task modulate regional SMA activity (Deiber et al., 1991).

In monkeys first, and more recently in humans, anatomical and functional data

(Geyer, Matelli, Luppino, & Zilles, 2000; Picard & Strick, 1996) have resulted in the

SMA being split into two distinct portions: 1) pre-supplementary motor area (caudal

portion of area 6), and 2) supplementary motor area proper (rostral portion of area 6).

The connectivity, physiology, and function of the pre-SMA suggest that it is more closely

aligned with prefrontal areas than with motor areas (Picard & Strick, 2001). Prefrontal

areas provide cognitive, sensory, and motivational inputs for motor behavior

(Walton, Devlin, & Rushworth, 2004), whereas the motor areas are concerned more with

the core fabric of movement (e.g. muscle patterns). The notion of splitting the SMA into

two separate areas is founded in two distinct differences in the anatomical connections of

the pre-SMA and SMA proper: 1) only the SMA proper is directly connected to Ml and

to the spinal cord (Dum & Strick, 1991; Wang, Shima, Sawamura, & Tanji, 2001), and 2)

only the pre-SMA is interconnected with the prefrontal cortex (Lu, Preston, & Strick,

1994; Luppino, Matelli, Camarda, & Rizzolatti, 1993). Notably, these distinct anatomical

characteristics are reflected in variations in task specific activity (Geyer et al., 2000).

Given increases in activation of the SMA with the acquisition of a motor

sequence task, the interpretation until recently, was that the SMA is associated with









learned sequential movements (Hikosaka et al., 1996). Recent accounts of task specific

pre-SMA activity, however, have altered the inferred role the SMA plays in the motor

domain. (Sakai et al., 1999) recently compared pre-SMA activation in closely matched

tasks requiring visuo-motor associations, but varied in motor and perceptual sequence

components. Activation of the pre-SMA occurred in all tasks that required visuo-motor

associations relative to tasks that required sequential processes. Moreover, pre-SMA

activation was greatest in the conditional task, in which non-sequential responses were

randomly determined by the color of visual cues. These data indicate that activation of

the pre-SMA has little to do with motor sequence learning, rather, that pre-SMA

activation reflects the establishing or retrieving of visuo-motor associations.

Functional differences between the SMA proper and pre-SMA have been further

corroborated (in monkeys) during the performance of a reaching task in which two visual

instruction cues were presented: 1) target location, and 2) reaching arm, separated with a

delay between the cues (Hoshi & Tanji, 2004a, 2004b, 2004c). The authors identified

four major differences in pre-SMA and SMA proper activation: 1) neuronal activity

preceding the appearance of visual cues was more frequent in the pre-SMA, 2) a

considerable portion of pre-SMA neurons (relative to SMA proper neurons) responded to

the first and second cue, reflecting the processing of visual stimuli and their associated

meaning (i.e., coupling target location and arm use), 3) during the motor planning period,

activity in the pre-SMA reflected target location, while activity in the SMA reflected

which arm to use, and 4) during movement execution, increased activity occurred in SMA

and was selective for the use of either the ipsilateral or contralateral arm. In contrast,

activity of the pre-SMA was suppressed. These findings provide further evidence for the









functional dissection of the SMA, corroborating previous claims that the pre-SMA is

more concerned with processing and integrating relevant internal and external

related stimuli (supported by its links to the prefrontal cortex; (Lu et al., 1994;

Luppino et al., 1993), while the SMA proper is integral to the motor planning

period, reflecting which limbs are being readied for movement, in addition to the

execution of movement those limbs.

Additional studies have extended the involvement of the pre-SMA to associations

based on auditory stimuli (Kurata, Tsuji, Naraki, Seino, & Abe, 2000). Visual and

auditory versions of a conditional choice reaction time paradigm generated pre-SMA

activations equal in magnitude (Sakai et al., 2000). The contribution of the pre-SMA to

sensory-motor associations, therefore, maybe considered modality-independent as well

as effector-independent, given that similar regions are activated in unimanual left and

right limb conditional motor tasks (Kurata et al., 2000; Sakai et al., 2000). This supports

the view that the pre-SMA operates at a more abstract level and is more closely related to

the processing, integration, and maintenance of relevant sensory information than

response selection or execution (Cunnington et al., 2002; Kurata et al., 2000; K. M. Lee

et al., 1999; Sakai et al., 2000). In stark contrast, SMA proper activation only occurs

during movement-related components of visual or auditory tasks, and appears to be more

involved with the pure movement portions of specified tasks (Boecker et al., 1998;

Cunnington et al., 2002; Stephan et al., 1995).

The Premotor Cortex (PM)

The premotor cortex lies anterior to the Ml in Brodman's area 6 and the

lower part of area 8 (See Figure 2-1). PM receives afferents from the thalamus and

projects onto portions of the corticospinal and corticobulbar tracts as well as to the Ml









(Dum & Strick, 1991). Dum and Strick also note that the total number of corticospinal

neurons in the arm representations of the PM equals or exceeds the total number in the

arm representation of the Ml. PM collectively comprise more than 60% of the cortical

area in the frontal lobe that projects to the spinal cord, and consequently, is the origin of a

substantial portion of the corticospinal system. Each of the PM areas has direct access to

the spinal cord, and as such, each has the potential to influence the generation and control

of movement independently of Ml.



CCZ caudal cingulate zone
CMAd dorsal cingulate motor
area
CMAr rostral cingulate motor
area
SCMAv ventral cingulate motor
area
FEF frontal eye field
fMIRI functional magnetic
resonance imaging
M1 Drimary motor cortex


Figure 2-1. Imaging the premotor areas. Motor areas of the frontal lobe in monkeys (a)
and homologous areas in the human (b). In humans, the border between areas
6 and 4 on the lateral surface is located in the anterior bank of the central
sulcus. For illustration, the border is drawn on the surface of the hemisphere
along the central sulcus (bottom, white dotted line). Except for the most
medial portion, M1 does not occupy the precentral gyrus.

The premotor cortex controls proximal and trunk muscles in addition to controlling

voluntary movement of the eyes via the frontal eye fields (Dum & Strick, 1991). Damage

to the premotor areas in humans leads to a syndrome termed apraxiaa" in which patients

are unable to perform skilled motor tasks (Hanna-Pladdy, Heilman, & Foundas, 2001;

Leiguarda & Marsden, 2000). The premotor area is activated during movements that are

primarily guided by visual, auditory, or somatosensory stimuli (Jenkins et al., 1994;









Larsson et al., 1996). Van Mier and colleagues (van Mier, Tempel, Perlmutter, Raichle,

& Petersen, 1998) reported increased activation in the dorsal premotor cortex (PMd)

during a battery of maze-tracing tasks (right- and left-handed) and suggested that PMd

activation was involved with the temporal aspects of movement planning (Halsband, Ito,

Tanji, & Freund, 1993), as well as the temporal aspects of the acquisition, execution

(Middleton & Strick, 2001; Seitz et al., 1994), and retention of motor tasks (Middleton &

Strick, 2001). Similar to pre-SMA activation patterns noted above (Kurata et al., 2000; K.

M. Lee et al., 1999; Sakai et al., 2000), van Mier et al. reported that PMd cortex activity

was similar for right- and left-handed performance, suggesting that activity in the PMd is

involved in abstract processes of complex tasks, rather than processes directly related to

the execution of those tasks. Research concerning the functioning PM in monkeys,

however, has guided more recent human research which has further distinguished

anatomical, physiological, and functional subdivisions within the area.

Subcomponents of PM cortex

Founded on anatomical and physiological differences, the dorsal part of the PMd in

primates has been divided into rostral (PMdr or pre-PMd) and caudal (PMdo or PMd

proper) subdivisions (Matelli, Luppino, & Rizzolatti, 1991). These differences are

comparable to those that determine the pre-SMA/SMA proper distinction noted above.

Indeed, the PMdc (PMd proper) shares three primary characteristics with the SMA

proper: 1) both areas project to the Ml and directly to the spinal cord (Dum & Strick,

1991; He, Dum, & Strick, 1993), 2) neither area has substantial interconnections with

prefrontal cortex (Lu et al., 1994), and 3) neurons in both regions are primarily involved

in aspects of motor control (Geyer et al., 2000). Likewise, the PMdr (pre-PMd) has much

in common with the pre-SMA, specifically: 1) neither of these areas project to the Ml or









to the spinal cord (Dum & Strick, 1991; He et al., 1993), rather 2) both regions are

interconnected with areas of prefrontal cortex and with the reticular formation (Geyer et

al., 2000; Lu et al., 1994) and finally, 3) results of neuronal recording and functional

imaging studies suggest that the pre-SMA and the PMdr are more involved in cognitive

than in motor processes. In short, the PMdc contains a high proportion of neurons that

display set- and movement-related activity whereas neurons in the PMdr are more

responsive to sensory cues, and fewer are active in relation to movement.

Functional PMd predictions founded in animal data have guided human research.

For example, Simon et al. (2002) predicted that the PMdr would primarily activate during

attention and/or memory processes whereas activity of the PMdc would correspond with

motor preparation/execution. Developed from the monkey reaching task noted above

(Hoshi & Tanji, 2004a, 2004b, 2004c) in which a first cue guided the focus of spatial

attention and memory, and the second instructed an arm movement, Simon et al.

modified the protocol to produce two tasks, during which fMRI data was collected. To

maximize spatial attention and memory demands the first task presented a series of 4, 8,

or 12 white squares. At the end of the series, motor execution was signaled by the

appearance of 1 red and 1 green square and a central fixation cross turning from white to

either green or red. At this point, one of two possible button presses was required (middle

finger = green/ index finger = red). For the experimental condition of task 1, the correct

response was determined by which execution cue held the same position as the last white

square in the sequence of 2, 8, or 12 white squares. The color of the square in the

matching position determined the correct response. For the control condition, the

response was determined by the color of the fixation cross.









The second task extended the motor preparation phase by lengthening and varying

the delay (between 1 and 5.5 s) between the instructional cue and movement execution.

Presentation of a single white square was followed by a fixed delay. Then the 2 execution

squares were presented for variable durations together with a green or red fixation cross.

For both the experimental and control conditions of task 2, the correct response was

determined by the color of the square that occupied the location of the final stimulus

(green in this example). However, for the experimental condition, subjects were required

to withhold their response until offset of the execution squares (and concomitant return of

the white cross), whereas, for the control, they were asked to respond immediately

following directional cue onset.

As expected, subjects' displayed significantly slower reaction times in the

experimental condition of the spatial/memory task (task 1: control experiment = -137

ms) given the required spatial matching that preceded movement execution.

Alternatively, but again in line with prediction, the manipulation of motor preparation

length in task 2 resulted in faster reaction times (control experiment = 283 ms)

suggesting that motor preparation did occur during the extended delay period, and

resulted in the manifestation of faster RTs. Concerning the pre-motor areas, as expected

the spatial attention/memory paradigm preferentially activated the PMdr, whereas the

motor preparation paradigm engaged the PMdc. Interpretations corroborated previous

evidence from both monkey and human studies. Similar to the pre-SMA and SMA

proper distinction, it appears that the human PMdr participates in spatial attention

and working memory (Coull & Nobre, 1998; Courtney, Petit, Maisog, Ungerleider,

& Haxby, 1998; Petit et al., 1996; Stern et al., 2000), while the PMdc is central to the









execution of movement. The simultaneous activation of other cortical areas also

confirmed expectation; findings will be discussed later in a summary section addressing

the nature of interactive activity across all cortical motor areas.

Cingulate Motor Areas

The majority of natural actions are selected voluntarily from many possible

options. Actions are often chosen based on their predicted consequences; predictions that

are based on the internal and external state of the organism. As stated, emotions influence

action and typically emerge in circumstances where adaptive control is required (Ekman

& Davidson, 1994). As such, all eyes point towards a structure or set of structures that

bridge emotion and action. The Ml, SMA, and PM, however, do not appear to be the

motor structures that directly link the emotion and movement domains. Motor control

research has been and continues to be successful in determining the complex

network of structures that plan, control, and execute movement (Simon et al., 2002),

but knowledge of the human motor system for the most part has developed

independently of the interacting influence that emotions may play. In terms of the

motor cortex, the progression that has been made in alleviating this issue has focused on

the cingulate motor area (CMA).

In addition to its role in movement execution, evidence suggests that it is the

CMA, given its anatomical position and functional connections with surrounding brain

areas (Vogt & Pandya, 1987), that decides, directs, and assesses the appropriateness of

motor function (Picard & Strick, 1996). The CMA is located within regions lining the

cingulate sulcus in the medial surface of the cerebral hemisphere and has been dissected

into rostral (CMAr) and caudal (CMAc) portions (Matelli et al., 1991). Distinguishing

itself from the primary, pre, and supplementary motor areas, the CMA receives









considerable afferent input from limbic structures (as well as the prefrontal cortex),

ensuring a flow of information to the CMA concerning motivation, the internal state of

the organism, as well as cognitive evaluation of the environment (Bates & Goldman-

Rakic, 1993; Lu et al., 1994; Morecraft & Van Hoesen, 1998).

With regard to the limbic system, the amygdala and ventral striatum project to the

anterior cingulate cortex and the cingulate gyrus, which in turn project to the CMAr

(Vogt & Pandya, 1987). These projections deliver information about reward values that

are directly connected to the goals of motor acts. In addition, the pathways that link the

prefrontal cortex to the CMAr (Lu et al., 1994) transmit information held in short-term

memory about the occurrence of events during the performance of previously performed

motor tasks (Goldman-Rakic, 1995). The CMA therefore, has access to affective

information that if processed correctly can influence the appropriate selection of a

voluntary motor action that is consistent with the current motivational state (Picard &

Strick, 1996). Once a selection has been made the CMAs send efferents to the primary

and secondary motor areas as well as brainstem structures that in turn help plan,

coordinate, and then via projection to the spinal cord, execute the movement (Dum &

Strick, 1991; He, Dum, & Strick, 1995).

Task specific activity of the monkey brain has advanced understanding of the role

of the CMA in decision making, planning, execution, and the control of motor action.

For example, Shima & Tanji (1998) trained three monkeys to either push or turn a

handle, in response to a visual trigger signal. The animals voluntarily selected one of the

two movements based on the amount of reward (grape juice) anticipated. During a series

of constant-reward trials, the monkeys continually selected a particular movement in









anticipation of its beneficial consequences. If the reward was reduced, conditioned

training was such that the monkeys learned to perform the alternate movement, and as

such, a cyclical process developed, with the monkeys altering their movements in an

effort to always obtain maximum reward. Event-related single-cell recording techniques

were used to record cellular activity from the CMAr, CMAc and Ml. CMAr and CMAc

activity was found to relate to movement initiation and movement preparation, while only

the CMAr showed activity specific to the occurrence of a reward. Shima and Tanji

concluded that the monkey CMAr plays a key role in choosing the most appropriate

action (given internal and external information garnered from the situation) in an effort to

achieve the greatest consequential gain from that action. The CMAc, however, was

exclusively involved in the execution of the chosen movement (Isomura, Ito, Akazawa,

Nambu, & Takada, 2003; Takada et al., 2001).

Transitional research into the human CMA has attracted considerable interest in

recent years (Isomura et al., 2003; Jenkins et al., 1994; Posner, Petersen, Fox, & Raichle,

1988; Ullsperger & von Cramon, 2004; Walton et al., 2004). Considered a possible

homolog of the rostral cingulate motor area (CMAr) in monkeys (Walton et al., 2004) the

human rostral cingulate zone (RCZ) of the dorsal anterior cingulate cortices (ACd) is

closely connected to the motor system, and is involved in monitoring self-generated

movements and in signaling the need for immediate changes of behavior (Jenkins et al.,

1994; Picard & Strick, 1996; Ullsperger & von Cramon, 2004).

The RCZ is thought to be intricately involved in focusing an individual's attention

to necessary cues. Specifically, attention for action, response selection, motor

preparation, and motor execution are all processes charged to the RCZ (Isomura et al.,









2003). Further justification has been found in evidence that lesions of cingulate areas

result in impairments of motor performance in human patients (Turken & Swick, 1999).

Corroboration of motor and cognitive related RCZ activity was reported by (Cunnington

et al., 2002), who compared brain activation during internally guided and externally

triggered finger movements. During each condition, predominant cingulate cortex

activation (in addition to SMA activation) was identified in the posterior end of the

CMAr, which is thought to be involved in motor tasks requiring internal movement

selection (Picard & Strick, 1996). Indeed, as with the pre-SMA, the CMAr shows greater

activation during internally generated movements (Deiber, Honda, Ibanez, Sadato, &

Hallett, 1999; Wessel, Zeffiro, Toro, & Hallett, 1997), is involved in early processes of

movement preparation (Ball et al., 1999) and in the internal representation or imagination

of movement (Stephan et al., 1995). Both the CMAr and the pre-SMA therefore appear to

be commonly involved in making the decision as to the most appropriate movement to

make given the circumstances. Analogous to the different portions of the SMA and PM

areas, the cingulate motor areas have been contrasted with the orbitofrontal cortex (OFC)

in terms of their anatomical connections and varying but related functions. In contrast to

the RCZ, the OFC is a rich recipient of afferents from sensory regions and is not directly

connected with the motor system. Functionally, the OFC appears to be involved in more

general monitoring of sensory events with respect to their significance to the individual

(Ullsperger & von Cramon, 2004).

Recent evidence has sought to further disentangle processes that culminate in

overt movement. Similar in fashion to the monkey reward task (Shima & Tanji, 1998),

Walton et al. (2004) required human participants to complete a number of response-









switching tasks that varied according to the extent to which participants had to make

choices and monitor feedback.' By varying whether participants needed to make choices

and monitor feedback, the authors demonstrated (with event related fMRI data) a

reciprocal relationship between the RCZ and OFC during the evaluation of the outcome

of a choice (See Figure 2-2). The nature of the relationship varied according to whether

the action was freely selected by the participant or guided by the experimenter, with

activation increasing in the RCZ and decreasing in the OFC when the action was freely

selected, and the reverse occurring when the action was selected by the experimenter. As

such, the neural mechanisms responsible for movement and appraisal of movement

consistently vary according to whether or not the performed movement is selected

internally or is forced externally.

The issue of how emotion modulates free-willed versus externally instructed motor

actions is attracting a growing interest and has been singled out as a goal of future

research across a broad array of disciplines (Ullsperger & von Cramon, 2004). The goal,

however, of eliciting real life quantifiable free-willed movements in response to an

emotive cue remains essential to the progression of our understanding of the

emotion-movement relationship.

Self- Versus Externally-Paced Movements

Functional brain imaging data in humans and single cell recordings in monkeys

have generally shown preferential involvement of the supplementary motor area (SMA)

1 GUESS condition: after a 's, iic I" cue, participants had both to decide upon an appropriate response and
to monitor the resultant feedback to determine which set of response rules was in place. FIXED condition:
participants were told always to make a particular finger press response on the first trial after the switch
cue. Unaware of which response set was subsequently in place, participants still had to monitor the
feedback from the instructed action (which was correct on 50% of trials) and use the information to work
out which set to use. INSTRUCTED condition: participants were informed by the switch cue which
response set was in place meaning they could switch sets without needing to monitor their responses.










in self-initiated movement (Deiber et al., 1999; Wessel et al., 1997) and strong bilateral

activation of lateral premotor areas for externally triggered movements (Catalan et al.,

1998; Van Oostende et al., 1997; Wessel et al., 1997).




Orbitofrontal cortex Rostral cingulate zone
Outcome monitoring Performance monitoring
Sensory events Ongoing motor actions
Future adjustments Immediate adjustments










Ann Thnmson


Figure 2-2. Schematic of the two frontal regions implicated in monitoring functions.
Taken from Nature Neuroscience 7, 1173 1174 (2004). Decision making,
performance and outcome monitoring in frontal cortical areas. (Ullsperger &
von Cramon, 2004).

Identifying the temporal sequalea of the activating motor areas during specific

tasks has been integral to better understanding the contributions) offered by each

distinctive portion of the motor cortex. For example, in a delayed cued movement task,

Richter et al. (1997) evidenced (via event-related fMRI) increased activity within both

the SMA and lateral premotor areas during the movement preparation period (delay

between a warning and GO signal), while the Ml showed only minimal activation during

the preparation period and greatest activation during movement execution. Likewise,

during self-paced movements Wildgruber et al. (1997) showed that the peak activation

within pre-SMA precedes activation within M1 and therefore pre-SMA activity most

likely reflects movement preparation.









In related works, Cunnington et al. (2002) used rapid event-related fMRI to

investigate the spatial location and relative timing of activation for self-initiated versus

externally triggered finger sequence movements. Each movement condition involved

similar strong activation of the pre-SMA, SMA proper, CMAr, and the contralateral Ml.

Although levels of SMA and CMAr activation did not differ significantly between

movement conditions, the timing of the hemodynamic response within the pre-SMA was

significantly earlier for self-initiated compared with externally triggered movements,

further confirming the notion that pre-SMA is involved in early processes associated with

the preparation of voluntary movement (Lee et al., 1999; Picard & Strick, 1996). Given

the lack of choice concerning which movement to make, differences in the cingulate

areas are not surprising as the CMA/RCZ has been associated with making reward driven

decisions when a number of possible movements are available. The lack of any activity at

all in the premotor cortex during either task, however, was reported, and stands as

contrary to other evidence collected in the same lab (Cunnington et al., 2002).

(Cunnington et al., 2002) offered task variations between this and other studies as a

potential explanation for this finding. Specifically, in Cunnington et al. (2002) the same

movement was always planned and executed; the only varying factor was the internal

versus external initiation of the task. As such the sequential nature of the movements

required (three alternating finger taps) demanded preparation and/or preprogramming,

and given that the movements were similarly accurate between initiation conditions, the

SMA and CMA were clearly capable of preparing, controlling, and executing the

necessary movements without assistance from the PMd. Given that performance accuracy

was high, it seems that exceptions to the sweeping generalizations concerning internally









(SMA) and externally (PMd) guided movements exist and are the result of what may

seem minor differences in experimental protocol. Rather than undermining previous

research, therefore, these data highlight how flexible and effective the human motor

system is.

Summary: Cortical Control of Movement

In recent years, the development of new techniques/methodologies has

considerably advanced our knowledge of the role the cortex plays in motor control.

Indeed, considerable progression has been made in attempting to understand which

cortical areas are involved in the numerous discrete processes that precede and then

accompany overt movement.

M1. The diversity and overlapping nature of the distributed network of neurons

within each portion of the Ml permits cortical reorganization; neural plasticity in Ml has

been evidenced following extended periods of training (Elbert et al., 1995) or following

injury (Donoghue & Sanes, 1988; Sanes & Donoghue, 2000). Although traditionally

considered to be exclusively involved in, and absolutely essential to the execution of

motor tasks, present day evidence concerning activity in the human brain suggests that

not only is the Ml active during the preparatory phase of movement, but also that

voluntary movements can be executed directly by secondary brain regions and perhaps

also sub-cortically. Nevertheless, the wealth of evidence is such that the Ml is primarily

involved in motor execution, and specifically, in permitting manipulation of distal

musculature.

SMA. The magnitude and temporal activation of the pre-SMA relative to the

SMA proper during a range of tasks are such that one can be considered as fundamentally

different from the other (Picard & Strick, 2001). The pre-SMA operates at a more









abstract level and is more closely related to the processing, integration, and maintenance

of relevant sensory information than response selection or execution (Cunnington et al.,

2002; Kurata et al., 2000; Lee et al., 1999; Sakai et al., 2000). Alternatively, SMA proper

activation only occurs during movement-related components of visual or auditory tasks,

and appears to be more involved with the pure movement portions of specified tasks

(Boecker et al., 1998; Cunnington et al., 2002; Stephan et al., 1995). Functionally and

anatomically distinct from the SMA proper, overt behavioral data coupled with

anatomical data suggest that the pre-SMA may be functionally considered as a region of

the prefrontal cortex (Picard & Strick, 2001). In conclusion, the two portions of the SMA

are such that the pre-SMA and SMA proper combined may well be capable of planning

and executing voluntary movements independent of Ml.

PMd. Human data has corroborated evidence from animal research suggesting a

functional segregation within the premotor cortex (Picard & Strick, 2001). Attention to

the short-term storage and processing of visuospatial information engages the PMdr

(Coull & Nobre, 1998; Courtney et al., 1998; Petit et al., 1996; Stem et al., 2000),

whereas motor planning, initiation, and execution engage the PMdc (Grafton et al., 1998;

Lee et al., 1999; Simon et al., 2002).

CMA/RCZ. Human movements are altered via the internal and external state of

the organism (including the emotional state of the organism via amygdala projections).

Considered a possible homolog of the CMAr in monkeys (Walton et al., 2004) the human

RCZ of the ACd is closely connected to the motor system, and is involved in monitoring

self-generated movements and in signaling the need for immediate changes of behavior

(Jenkins et al., 1994; Picard & Strick, 1996; Ullsperger & von Cramon, 2004).









Specifically, the CMAr/RCZ plays a key role in choosing the most appropriate action

(given internal and external information and the potential of freely choosing a number of

alternatives) in an effort to achieve the greatest consequential gain from that action. In

contrast, the CMAc (CCZ) is primarily involved in the execution of the chosen

movement (Isomura et al., 2003; Takada et al., 2001) thereby aligning itself more with

the SMA proper and the PMd,.

Subcortical Control of Movement

Basal Ganglia

The basal ganglia (BG) works in concert with the cortex to orchestrate and

execute planned motivated behaviors that require motor, cognitive, and limbic circuits

(Haber, 2003). Intricately involved in several aspects of goal-directed behaviors, BG

function bridges the emotion, motivation, cognition, and planning processes that lead to

movement, as well as performing a critical role in the expression of movement (Boecker

et al., 1998; Brown & Marsden, 1998; Haber, 2003). Deficits in motor behavior have

been associated and correlated with basal ganglia dysfunction (Greenberg, 2002).

Although a broad range of processes have since been pinned onto the BG [e.g., cognitive

sequence planning, Graybiel, (1997); learning, Jueptner et al., (1997); habit learning &

acquisition of non-motor dispositions and tendencies, Knowlton et al., (1996); executive

function, Peigneux et al., (2000); and creativity, Cotterill, (2001)] this review will focus

on the specific role that BG has on movement and emotion.

The basal ganglia are several groups of nuclei in each cerebral hemisphere which

include the striatum caudatee nucleus, putamen, and ventral striatum) and the pallidum or

globus pallidus (see Figure 2-3; internal and external segment GPi, GPe, and ventral










pallidum) (Greenberg, 2002). Closely related structures include the substantial nigra pars

reticulate (SNr), the ventral tegmental area, and the subthalamic nucleus (Haber, 2003).


Pre-Frontal & motor cortex w


( Thalamus )






S Amygdala &




g a Excitatroy
1 Inhibitory
Direct pathway Brainstem
S Indirect pathway




Figure 2-3. Motor circuit of the basal ganglia. The indirect and direct pathways are
presented along, with how the cortex communicates with BG. GPi = internal
segment of the globus pallidus; GPe = external segment of the globus pallidus
STN, = subthalamic nucleus; SNr = substantial nigra pars reticularis

The striatum is the main target of cortical, thalamic, and brainstem input to the basal

ganglia. In addition, the ventral striatum receives input from the limbic regions, including

the amygdala and hippocampus (Fudge et al., 2002), and in addition the CMA/RCZ has

been closely linked to the development of reward-based learning (Hassani et al., 2001).

The striatum projects to the GPi and GPe, and in turn the GPi projects to the thalamus.

The internal section is one of two main output nuclei of the basal ganglia, along with the

SNr, which also outputs to the thalamus (Wichmann & DeLong, 1993). Outputs from

these two structures are passed via the thalamus, back to the cortex (primarily the SMA,

and possibly also to the PM cortex; (Brotchie et al., 1991a, 1991b, 1991c), completing









what is referred to as the "direct" cortico-basal ganglia pathway. The GPe is connected to

the STN, which in turn projects back to the GPi; this connectivity is the "indirect"

cortico-basal ganglia pathway (Haber, 2003; Middleton & Strick, 2002). The motor

circuit of the BG and its associated direct and indirect pathways are displayed in Figure

2-3. Information cycles from the cortex, to the basal ganglia and thalamus, and back to

the cortex again, forming a functional loop that modulates movement. The collective

summation of activation/inhibition of these pathways modulates movement. Stimulation

of the direct pathway leads to increased inhibition of the GPi, which consequently

reduces the inhibitory tone on the thalamus, in turn facilitating excitation of the cortex

and facilitating movement. In contrast, stimulation of the indirect pathway leads to

increased inhibition of the GPe, which in turn leads to excitation of the STN; this

activates the GPi and so increases the inhibition of the thalamus and reduces excitation of

the motor cortex, inhibiting movement (Lewis et al., 2003). Appropriate balance between

these two pathways is essential for typical everyday movements; PD, for example, results

from a loss of the natural balance within this motor loop. Specifically, a decrease in

dopamine levels results in increased activity in GPi and SNr which prevents inhibition of

the thalamus, resulting in under-activation of motor cortical areas, as displayed overtly in

hypokinesis (Chase et al., 1998; Haber, 2003).

From an input-output analysis, therefore, the basal ganglia do not appear to

generate motions directly; they take input from the cortical and subcortical regions,

process this information and then pass it back to the cortex via the thalamus, for

execution (Cummings, 1993). Nevertheless, the importance of an intact BG system is

substantiated by the array of symptoms that manifest following damage or disease in the









BG: (1) hypokinesias: impairment of initiation, velocity, and amplitude of movement,

increase in muscle tension or hypertonia [e.g., Parkinson's Disease; Haber, (2003)]: (2)

hyperkinesia: disorganized or excessive movement (e.g., Huntington's Disease) and, (3)

dementias: cognitive and emotional dysfunctions.

Varying cortical structures have been offered as key to movement preparation

(see above; CMA, pre-SMA, PMCr). However, preparatory activity has been

demonstrated at several other sites outside the cerebral hemispheres, including the globus

pallidus (Turner & Anderson, 1997), the striatum (Alexander & Crutcher, 1990), and the

pallidal-receiving areas of the thalamus (Anderson et al., 1993). Motor preparation in

much the same way as motor execution (Sanes & Donoghue, 1997) should therefore be

considered a distributed phenomenon not limited to the cerebral cortex (Prut et al., 2001).

Given the range of motor dysfunctions that arise from or are related to BG

malfunction (e.g., Parkinson 's & Huntington's disease), substantial efforts have sought

to determine the exact role that BG play in motor function. Positron emission tomography

(PET) studies have reported increased regional blood flow prior to voluntary movements

not only in the SMA, Ml, and other cortical areas, but also thalamus, and the BG (Deiber

et al., 1996; Deiber et al., 1991; Jahanshahi et al., 1995; Wessel et al., 1997). BG appear

to be activated similarly preceding voluntary movements that are internally generated and

externally triggered (Cunnington et al., 2002; Jahanshahi et al., 1995; Jenkins et al.,

2000).

Corroboration of BG involvement in motor preparation has been echoed by

(Paradiso et al., 2004) who reported data from scalp and surgically implanted electrodes

in the subthalamic nucleus of Parkinson's patients while they completed wrist extension









movements. Readiness potentials in the subthalamic nucleus were present before

contralateral and ipsilateral hand movements. The authors thereby affirmed that in

parallel with the cortex, BG circuitry was activated during movement preparation.

A more detailed explanation of BG involvement in movement preparation has

been offered by (Nambu, Tokuno, & Takada, 2002) who have associated the initiation,

execution, and termination pattern of movement with varying BG circuits. Immediately

prior to cortically driven movement execution (planning = CMAr, pre-SMA, PMdr;

execution = CMAc, SMA proper, PMdc) an accompanying signal is sent from SMA and


Pre-Frontal & motor cortex


Thalamus





STN


*- Exitatroy @--- Inhibitory


Figure 2-4. The cortico-STN-pallidal "hyperdirect" pathway as proposed by (Nambu et
al., 2002). STN = Subthalamic nucleus; GPi external portion of the globus
pallidus. The additional pathway from the cortex to the STN is the cornerstone
of the hyperdirect pathway.

Ml to the GPi through a cortico-STN-pallidal "hyperdirect" pathway that

comprehensively activates GPi neurons. Consequently, large areas of the thalamus and

cortex related to the selected and competing motor program are inhibited (see Figure 2-

4). Next, a second signal is passed via the direct pathway (see Figure 2-3 above) to the

GPi to inhibit the specific set of pallidal neurons, dis-inhibiting the pathway between

thalamus and cortex; leading to the execution of the selected movement. Finally, a third









signal, passed via the "indirect" pathway (see Figure 2-3) broadly activates GPi neurons,

suppressing their targets and terminating the movement. As such, only the selected motor

program is initiated, executed, and terminated at the appropriate time, whereas other

competing programs in the surrounding area are quashed. Figure 2-5 outlines two BG

related systems that account for the phenomena that voluntary movements are always

associated


|Cerebral cortex| }, ,
Cereb r ai c t onal control
orti sal anlia loop





rainss em automatic
control




Spinal cord
Figure 2-5. Volitional and automatic control of locomotor movements. GABAergic basal
ganglia output to the thalamocortical neurons and the brainstem neurons
integrate volitional and automatic control processes of movements
(Takakusaki et al., 2004).

with automatic control processes which are performed unconsciously (Grillner & Wallen,

2004). (Hikosaka, Takikawa, & Kawagoe, 2000) propose that BG have two ways to

control movements using three output systems (direct, indirect, and hyperdirect

thalamocortical) to amalgamate the volitional control of movement with automatic

control processes (e.g. saccade: (Isa, 2002); locomotion: (Grillner & Wallen, 2004) which

are controlled via networks in the brainstem and spinal cord (Takakusaki, Saitoh, Harada,

& Kashiwayanagi, 2004). BG circuits, therefore, appear to be essential: 1) during the









preparatory state prior to movement, suppressing all movements, 2) during the execution

of movement, allowing only the desired movement to be executed, and 3) during

movement termination when all movements are completed and a resting state is desired.

Affective modulations of psychopysiological measures correspond with phases 1 and 2 of

this progression and have lead to the formulation of the defense cascade model.

The Defense Cascade

Emotions have the capacity to elicit a myriad of varying behavioral responses in

human beings. Evolved from primitive circuits in which a stimulus was typically

followed by a response in a very standardized fashion, the human brain has developed the

ability to use time. That is, humans can permit, suppress, accentuate, or abolish overt

behavioral responses to emotional cues (Lang et al., 1997). The complex interaction of

the neural circuitry that process emotions is such that a single response indicating

activation of the appetitive or defensive motivational system is not necessarily reflected

in a parallel way by all measures (i.e., HR, SCR, ERP). Instead as activation levels

associated with the eliciting stimulus increase, a cascade of different response events

occur ("defense cascade" see Figure 2-6; (Lang et al., 1997). Specific to activation of

defensive circuitry, a three stage sequence has been proposed, based on the relative

position of predator and pray (Bradley & Lang, 2000; Fanselow, 1994; Lang et al., 1997):

pre-encounter, post-encounter, and circa-strike. Circa-strike refers to defensive actions

when threat is proximal.

An important issue therefore, is to determine how movements are altered at

varying stages through the progression of the defense cascade. That is, will

movement be facilitated/debilitated monotonically as arousal increases across time,











or will movement be more affected by duration and proximity to valenced cues


carrying different affective quality?


As evident in Figure 2-6, overt action (i.e., a defensive response) follows stimulus


identification and then a freezing period. Following initial perception, as threat and


arousal simultaneously increase, SCR climbs, startle potentiation increases reflecting


defensive priming (via amygdala to PnC, to be discussed), and then immediately before


movement, cardiac acceleration signals a classic defensive response. Determining how


the fundamental structures governing this sequence of events alter the resulting


movement should be addressed in future research efforts. Once again, as is the case


in the majority of affective research, little is known beyond the processes that


precede "overt action" and consequently little is known concerning how affect


modulated movement increases an organism's chances of survival (LeDoux, 1998).


Considerable advances may be made in movement rehabilitation if emotional circuitry


can serve as a movement facilitator.


CALM AROUSED


A schematic presentation of the defense response cascade underlying
processing of increasingly arousing aversive stimuli. The arousal or intensity
dimension is viewed here as analogous to a dimension of predator imminence
that has been implemented in studies of animal fear. Reproduced from (Lang
et al., 1997).


Pre-encounler Post-encounter Circi-strike

OVERT
FREEZING OVERT
ACTION

SWEAT
GLANDS
i ltartleinhibiio n
STARTLE '
REFLEX

HEART
RATE ,,.nl I

I ~ C diB / Ie in
begins


LU

0

Ul)
z
a
o
a.




Figure 2-6


).









Cross referencing the defense cascade with BG activity, it is possible that the

progression from "freezing" to defensive action maybe reflected in BG activation. As

noted above, Nambu et al. (2002) suggest that BG control initial inhibition of movement

(e.g., freezing) via the hyperdirect pathway, while a decision is made concerning the most

appropriate movement to make (CMA/RCZ), followed by mobilization of the chosen

motor action (e.g., defensive response stimulated by an external motivationally relevant

stimulus) via the direct pathway, followed by final movement termination once the threat

has passed. In highly emotive situations the ability to control unnecessary

movements, to then execute the most appropriate movement at the most appropriate

time are essential within all movement domains.

Further support for converging emotion and movement systems comes from

reports concerning Parkinson's disease. Given the typical slowness of movement that

often signals PD (Haber, 2003), emotionally charged situations have been reported to

override bradykinesia and result in patients exhibiting "paradoxical kinesia"; a sudden

transient remission of bradykinesia when confronted with a life threatening emergency

(Zigmond, Stricker, & Berger, 1987). It is possible therefore, that intense emotions can

result in the intense focusing of attention, and thus motivation towards completing the

necessary movements) to ensure survival. The BG, therefore, maybe viewed as an

attentional center that can alter the flow of information from sensory input to motor

output, and in turn, simultaneously suppress and permit specific movements according to

situations (Brown & Marsden, 1998). To re-iterate, it seems that without directly

deciding, planning, or executing movements, the BG has enormous influence on

which movement, from a number of potential options, is amplified and executed,









and which movements) are inhibited to allow the primary movements) to execute

without interference. Such reports that intertwine the largely independent research lines

of emotion and movement beautifully exemplify the benefit of multi-disciplinary

research, and serve as motivation to further investigate the complex relationship between

emotion and movement. Focus will now turn to how emotionally rich information

reaches the BG.

Basal Ganglia and Emotion

The nucleus acccumbens is a dominant part of the ventral striatum and is the

leading sub-cortical candidate for the hub that integrates emotion, motivation, and

cognition with action (Greenberg, 2002). Divided into two principal parts, the nucleus

accumbens is composed of a central core that is associated with the extrapyramidal motor

system, and a peripheral shell that links with the limbic system (Sturm et al., 2003).

Receiving input from the hippocampus and the amygdala (Maclean, 1990) and projecting

onto the ventral pallidum, substantial nigra, thalamus, and cingulate cortex, the nucleus

accumbens is ideally located to serve as the key limbic-motor interface (Sturm et al.,

2003). (Graybiel, 1997) echoed the importance of the such a hub, stating that the

"...limbic basal ganglia system has a key function in translating action plans related to

drive states and homeostatic control into action repertoires" (p. 460). It seems

appropriate, therefore, to ask whether processes within the NA translate fear into

defensive action or positive affect into approach behavior?

Stimulation of different areas in the basal forebrain can evoke different types of

goal directed behaviors (Grillner, Georgopoulos, & Jordan, 1997); see Biphasic Theory

section). An important component of these motivated behaviors concerns the direction of









the resulting movements; movements that will transport an organism towards or away

from a given situation/cue depending on the valence of the stimuli (Grillner et al., 1997).

Cerebral cortex
/ -ptitional control




Srantomac


asysem



[Spinal cord

Figure 2-7. Possible neuronal mechanisms of integration of volitional, emotional and
automatic control of motor behaviors.

One underlying issue concerns whether such movement patterns are executed with

similar vigor; that is, are approach behaviors executed with the same speed and

force as defensive behaviors? Are attack behaviors executed as quickly, forcefully,

and accurately as escape behaviors? If emotion primes movement, do movements

vary according to valence, to arousal, or to a combination of each?

The concept of emotions serving as action dispositions continues to gain support.

de Gelder and colleagues (de Gelder, Snyder, Greve, Gerard, & Hadjikhani, 2004), for

example, exposed participants to affective images while simultaneously recording fMRI

activity. Along with amygdala and visual cortex activity, activity was also reported in the

RCZ as well as the nucleus accumbens. The burning question therefore is: exactly

what role, and to what extent do emotions alter the probability of specific action

dispositions leading to the execution of specific behaviors?









Traditionally the dopamine (DA) systems in the nucleus accumbens were thought

to directly mediate the rewarding or primary motivational characteristics of natural

stimuli such as food, water, and sex (Salamone, Correa, Mingote, & Weber, 2003;

Salamone, Correa, Mingote, & Weber, 2005; Salamone, Wisniecki, Carlson, & Correa,

2001). In terms of the link between emotion and action, however, rather than attenuating

the primary motivation for natural rewards such as food, obstructing DA transmission

within the NA disturbs the inclination of animals to engage in effortful responding to

obtain food. That is, rats with accumbens DA depletions remain directed towards the

acquisition and consumption of food. When not securing the food, however, the rats

display a less vigorous, more cautious set of behaviors (Cardinal, Pennicott, Sugathapala,

Robbins, & Everitt, 2001; Correa, Carlson, Wisniecki, & Salamone, 2002; Salamone et

al., 2003; Salamone et al., 2001). DA systems in the nucleus accumbens, therefore,

appear to be critically involved in activational aspects of motivation, and a key

modulator of response speed, vigor, and persistence in directed behavior; functions

that enable organisms to exert effort in reward-seeking behavior (Salamone et al.,

2005). Analogous to a gate, filter, or amplifier, the NA can be promoted to the role

previously given to the BG in general; that of altering emotion related information as it

travels from various cortical or limbic areas on its way to motor areas of the brain (Everitt

et al., 1999). An active NA, therefore, is thought to encode information related to the

predictive value of environmental stimuli and the specific behaviors required to respond

to them (Nicola, Yun, Wakabayashi, & Fields, 2004). That is, accumbens DA is

necessary for modulating the electrophysiological and the behavioral responses to

environmental cues (Yun, Wakabayashi, Fields, & Nicola, 2004).









In summary, although the role of the NA is becoming clearer in the rat brain,

study of NA activity in the human brain has continued to follow psychopathologies, with

the motor components taking a subsidiary role. If indeed the NA acts as a hub between

the emotional limbic system and the motor system, it is of paramount importance to

investigate how the NA may be used to facilitate movement.

Brainstem Reticular Formation

Extending into the spinal cord and diencephalons, the reticular formation refers to

a region of neural tissue in the brainstem (medulla, pons, and midbrain) consisting of

small areas of gray matter among fibers of white matter (Tortora & Grabowski, 2003).

Traditionally the reticulospinal system (reticular formation, reticulospinal tract) has been

charged with modulating automatic movements including the initiation and regulation of

locomotion (Matsuyama & Drew, 2000a, 2000b; Matsuyama et al., 2004), postural

control, vestibular reactions (Bolton et al., 1992; Matsuyama & Drew, 2000a, 2000b),

and head movements that permit gaze control (Cowie & Robinson, 1994; Cowie, Smith,

& Robinson, 1994). Without disputing the severe impairment of postural control that

results from lesioned reticulospinal fibers, such lesions also manifest behaviorally in the

impairment of gross limb movements (Lawrence & Kuypers, 1968).

More recently, the reticular formation (medial pontomedullary reticular formation

(mPMRF)) has been associated with the preparation and performance of voluntary

movements. Specifically, Buford & Davidson (2004) published single neuron data

collected from the mPMRF of monkeys while performing a two-dimensional reaching

task that included an instructed delay interval based on a color coded visuospatial cue.

Monkeys were positioned in a primate chair which limited postural movements, thus

allowing cells involved in preparatory activity to be distinguished from those involved in









movement-related activity. Given that preparatory areas of the secondary and cingulated

motor cortex (Pre-SMA, PMdr, CMAr) project to the reticulospinal system (Keizer &

Kuypers, 1989) the authors sought to determine whether or not cells within the reticular

formation may be sensitive to movement preparation. The authors reported that of the

176 neurons with movement-related activity, 109 (62%) displayed pure-movement

activity and 67 (38%) exhibited both preparatory and movement activity. Although lower

than ratios reported in SMA, PMd, and CMAd (Alexander & Crutcher, 1990; Backus,

Ye, Russo, & Crutcher, 2001), these data suggest that the reticular formation houses

cells that are sensitive to the planning of upper limb reaching movements, and as

such, the reticular formation may prove to be an alternative pathway for the

voluntary control of gross movement.

Given that subcortical regions maybe involved in motor planning, applying this

knowledge to situations where planning regions of the cortex have been damaged (i.e.,

stroke) holds considerable promise. However, consistently activating cells in the reticular

formation that are sensitive to preparing movements with a view to strengthening their

ability to compensate for damaged cortical regions, remains unknown. Further, activating

cells in the reticular formation may be reliant on descending signals from the cortex.

Furthermore, spatially cued, temporally specific planned movements originating in the

reticular formation seem unlikely given the myriad of processes preceding movement

preparation (e.g., stimulus perception/interpretation, rule learning). Overt displays of

planned movement in decerebreated primates would clarify whether activation of the

reticular formation can compensate for damaged cortical regions.









Summary: The Motor System

The cortical and subcortical structures that elegantly interact to produce motor

function are complex, flexible, and comprehensively integrated. Regardless of its novelty

and complexity, the planning, initiation, and execution of a motor task appears to be a

distributed process, requiring cortical, subcortical and intact spinal tracts if appropriate

motor actions are to be realized. Identifying hubs within the motor system where emotion

may potentially impact this complex network offers a tremendously fascinating task for

movement scientists. The cingulated motor areas, and the nucleus accumbens have

emerged as two potential candidates. With this in mind, the following section offers a

synopsis of the emotional system, with an emphasis placed on the structures that interact

with motor areas.

Emotion

Emotion is a mental state that arises subjectively, via activation of primitive

circuits that have been conserved throughout mammalian evolution (LeDoux, 2000)

rather than through conscious effort. Emotions are often accompanied by physiological

changes. Emotions, therefore, are held to be functional products of Darwinian evolution,

developed from primitive actions that facilitated the continued survival of living

organisms. Echoing this basic premise, Ohman, Hamm, & Hugdahl (p. 538, 2000)

eloquently state:

Evolution has primed organisms to be responsive to stimuli that more or less
directly relate to the overall task of promoting ones genes to prosper in
subsequent generations.... Stimuli of these types are embedded within emotional
systems that help regulate behavior within critical functional domains

Emotion-related behavioral and psychophysiological data have been interpreted as

reflecting approach/avoidance behaviors (Chen & Bargh, 1999; Duckworth, Bargh,









Garcia, & Chaiken, 2002; Hillman et al., 2004). Interpretations of self-report data have

resulted in the suggestion that many discrete emotions exist, ranging from sadness,

happiness, loss, and guilt (Lazarus, 2000). Imaging data continues to map the cortical and

subcortical neural circuitry of the emotional system including these discrete states.

Identifying the time course and physiological map of the startle reflex provides a fine

example of the emotion-related successes garnered from animal research (Davis,

Gendelman, Tischler, & Gendelman, 1982; Davis, Parisi, Gendelman, Tischler, & Kehne,

1982, to be discussed). Suffice to say, the emotion system is investigated with a divergent

array of methodologies.

Systems impacted via emotion are wide ranging, both in terms of when and how

the system is altered. That is, following onset of an emotional cue, demonstration of

affective modulation occurs at varying times according to the measure being used;

affective modulation of the startle blink response occurs 500msec following exposure;

Skin conductance responses are altered according to arousal level, and can be illustrated

physiologically 1-2 sec following initial exposure (Coombes, Janelle, & Duley, 2005);

Affective modulation in heart rate response is visible 1500msec post emotional cue onset

(Lang, Greenwald, Bradley, & Hamm, 1993). As such, depending on which branch of the

sympathetic NS is being monitored, the time frame within which emotion driven changes

will occur varies. In line with active lines of research concerning the temporal

characteristics of emotion modulated P3 responses, HR, and SCR (Schupp, Junghofer,

Weike, & Hamm, 2003a; 2003b), quantifying the emotional modulation of overt

voluntary motor function across time is a promising avenue for future research

(Coombes et al., 2005). Further, the robustness and validity of the Biphasic theory of









emotion lends itself well to the study of such phenomena (e.g., Coombes et al., 2005;

Hillman et al., 2004).

Biphasic Theory of Emotion

Biphasic theory (Lang et al., 1990; Lang et al., 1997; Lang, Bradley, & Cuthbert,

1998a, 1998b) posits that the broad array of emotions experienced and displayed by

human beings can be organized according to valence (i.e., appetitive or defensive) and

intensity (i.e., arousal level). When engaged, each system (appetitive, defensive) impacts

the functioning brain (including motor circuits), priming specific representations,

associations, and action programs that correspond to the immediate environmental

context. Hence, while not actions in themselves (Lang et al., 1997), emotions do

influence action and typically emerge in circumstances where adaptive control is required

(Ekman & Davidson, 1994). Thus, when conceptualizing affects as motivationally

tuned states of readiness (Lang et al., 1998b), Schupp and colleagues propose that a

key function of emotion is the preparation for action (Schupp et al., 2003a). In

addition to valence and arousal, motor activation has also been noted as a third factor

particularly helpful in describing primary emotions (Heilman & Gilmore, 1998). One

commonly used measure that provides an index of the modulatory impact of emotion on

involuntary motor function is the startle blink response.

Emotional Circuitry

The limbic system

The limbic system concept, an anatomical abstraction for an arched shape group

of structures, first emerged in the mid 1950's (Maclean, 1949, 1952), and since its

inception has been synonymous with efforts to explain and understand human emotion.

The roots of a limbic system are grounded in an evolutionary explanation of mind and









behavior (Isaacson, 1982; Maclean, 1952, 1954, 1955a, 1955b, 1972). Sometimes

referred to as the ancient, archicortex or primordial cortex (as opposed to the cerebral

cortex that is referred to as the neocortex or new cortex) the limbic region is located on

the medial border of the cerebral hemispheres.

The neocortex, found only in mammals, has been associated with thinking,

reasoning, problem solving, and memory, leaving hunger, thirst, and other primitive

internal urges to be attributed to the ancient cortex which is found in all vertebrates

(LeDoux, 2000; Panksepp, 2003). As such, independent anatomical regions were

traditionally paired with corresponding independent processes; emotion and cognition

(Maclean, 1952, 1955a, 1955b). Scoville & Milner (1957), however, reported that

damage to a central structure in the limbic system -the hippocampus- had a debilitating

effect on long-term memory rather than on emotional processes. In consequence, the

polarization of separate systems for cognition and emotion began, which in turn brought

into question components of, and hence, the existence of the limbic system.

Caution, therefore, should be exercised when associating the limbic system

exclusively with emotion. Indeed, with the fear system often bypassing the hippocampus,

LeDoux (2000) suggests that a "limbic system" grounded in tradition rather than data, is

a flawed and inadequate account of the emotional brain, and provides no more than an

"...off-the-shelf explanation of how the brain works" (p. 159). Aside from issues

concerning its authenticity, for those who support the limbic system account of emotion,

widespread agreement has yet to be reached concerning exactly which nuclei compose

the limbic system (Patterson & Schmidt, 2003). For example, given the abundant two-









way connections between limbic structures and the hypothalamus and thalamus, some

have included these later structures within the limbic system (Andreassi, 2000).

Nevertheless, widespread use of the term "limbic system" has permitted the

concept to remain prominent in contemporary discourse, with credible support for such a

system continuing undiminished (Panksepp, 2003). Revisiting the vertebrate/mammal

brain distinction, Panksepp (2003) retains and supports the notion that emotional

responses, including their intrinsic affective attributes, most likely emerge from "limbic"

regions that are more evolutionarily conserved in vertebrates than those that mediate

cognitive capacities (Maclean, 1990). Resolving the issue concerning whether or not a

"limbic system" exists is not the focus of this discourse, and hence, whether considered to

be, or not to be, components of the limbic system the following section outlines the

amygdala and the periacqueductal central grey given the integral role they play in the

physiological and behavioral manifestations of emotion.

Amygdala

The amygdala is a nuclear complex in the forebrain, positioned in the anterior

medial section of the temporal lobe consisting of about ten distinct nuclei that are

grouped into four regions: basolateral, lateral, central, and basomedial. The amygdala

receives highly processed sensory input from the neocortex and hippocampus via the

lateral and basolateral nuclei; in turn these nuclei project to the central nucleus which

then project (via the stria terminalis) to a variety of hypothalamic sites, the nucleus

accumbens (Graybiel, 1997; Maclean, 1990) and periaqueductal gray (Fendt & Fanselow,

1999), the cingulated motor areas (Morecraft & Van Hoesen, 1998; Vogt & Pandya,

1987), as well as the PnC (Davis, Gendelman, Tischler, & Gendelman, 1982; Lang et al.,









1990). These functional links collectively mediate the manifestation of emotion

modulated voluntary and involuntary movements.

Potentiation of the startle blink reflex according to emotional context provides

evidence of how emotion alters the execution of involuntary motor action; the rostral part

of the medial subdivision of the central nucleus of the amygdala contains cells that

project to the PnC, a nucleus in the acoustic startle circuit [Rosen, Hitchcock, Sananes,

Miserendino, & Davis, (1991); emotion and startle to be discussed later]. In a similar

fashion, the amygdala projects directly and indirectly to the nucleus accumbens and

CMA respectively, altering voluntary movements according to an organism's affective

context and the consequences of varying actions within that affective context. The

amygdala is involved in complex cognitive and behavioral functions, and serves to

process somatic states that emerge from primary unconditional or learned inducers

(Bechara, Damasio, & Damasio, 2003).

LeDoux defines the amygdala as a center for emotional evaluation (LeDoux,

1994, 2003; LeDoux, Cicchetti, Xagoraris, & Romanski, 1990), specifically involved in

the detection and manifestation of fear. In addition to reports that continue to support the

essential role of the amygdala in the fear system, this association should not be

considered unilateral. Indeed, when exposed to affective content, fMRI data have, in

addition to coupling amygdala activation with fear, also associated the processing of

positively valenced stimuli with significant amygdala activity (e.g., Garavan,

Pendergrass, Ross, Stein, & Risinger, 2001). Conflicting data exist, however, concerning

the link between amygdala activation and pleasant stimuli. For example, fMRI data

reported by (de Gelder et al., 2004) indicated significant amygdala activation during









exposure to unpleasant/fearful images relative to neutral images, but not during exposure

to pleasant as compared to neutral images. It is interesting to note though, that de Gelder

et al. did not report a direct statistical comparison between activation patterns during

exposure to unpleasant and pleasant stimuli.

The amygdala has a dual sensory input system. Information is taken in via sensory

channels and is streamed to the thalamus, at which point the inputs diverge; one pathway

leads directly to the amygdala (fast channel) while the other projects to the cortex (slow

channel). Providing the amygdala with raw sensory threat-related information via this

specialized fast channel circuit may offer distinct advantages in the interest of promoting

survival. (LeDoux, 1995) has described this fast channel route as a "quick and dirty"

subcortical pathway that allows for very rapid, but crude, analysis of stimulus features

from the incoming visual stream (LeDoux, 1995, 1996; Shi & Davis, 2001). This route,

involves direct thalamo-amygdala pathways allowing for a cursory but rapid analysis of

visual objects passing from the retina into the fear centers of the brain. The alternate

ascending route to the cortex permits acute processing of the sensory input to determine if

the sensory input is real, perceived, dangerous, or harmless. Although delayed, the result

of this more comprehensive cortical evaluation of sensory stimuli is projected back to the

amaygdala, reinforcing or suppressing initial amygdala activity.

Although not actions themselves, emotions may be considered action dispositions,

and while it is clear that the amygdala are central in the interpretation and evaluation of

emotion, it is the efferent amygdala projections that result in the covert and overt

consequences of an experienced emotion. Indeed, lesions of the central nucleus of the

amygdala block all conditional fear responses including behavioral, autonomic,









cardiovascular, and hormonal responses, whereas lesions of the pariacqueductal gray

(PAG) block only the automated behavioral responses to fear (LeDoux, 1996). It is

believed, therefore, that the central nucleus of the amygdala may be the final common

pathway of conditional fear responses and that its efferent targets, including the PAG,

mediate specific automated responses (see BG and CMA section above for information

concerning emotion and voluntary movement). Specifically, circastrike attack (overt

defensive action) is not initiated by direct stimulation of the central nucleus of the

amygdala (De Oca, DeCola, Maren, & Fanselow, 1998). In consequence, to understand

the chain reaction that begins with activation of emotional circuitry and leads to

involuntary overt movement, attention must turn to the periacqueductal gray.

Periacqueductal central grey

The periaqueductal grey (PAG) is a large structure in the midbrain (surrounding

the aqueduct of silvus) thought to be involved in two contrary patterns of defensive

action, one related to freezing, in which ongoing behavior is halted leading to complete

immobility except for that required for breathing (De Oca et al., 1998), and another

related to escape responses (Vianna, Graeff, Landeira-Fernandez, & Brandao, 2001). The

PAG receives afferents from the amygdala, nucleus stria terminalis, dorsal hypothalamus,

midline thalamus, periventricular grey and the dorsolateral and ventrolateral midbrain

tegmentum. In turn, the majority of efferent fibers leaving the PAG terminate in the

reticular formation, parabrachial nuclei, trigeminal motor nucleus, and nucleus

ambiguous. With regard to defensive freezing, evidence suggests that such behaviors are

modulated by afferent projections that the ventral PAG (vPAG) receives from forebrain

structures, especially from the amygdala (Bandler & Shipley, 1994; Carrive, 1993;










Fanselow, 1991; Fendt & Fanselow, 1999), while the dorsal portion of the PAG (dPAG)

appears to mediate both active and inhibitory behavioral patterns of defensive responses.

80 -0- SHAM
dlPAG
70 vPAG
e o
50
60-
40
30
M 20-
a-^

0
PRE-CAT CAT

Figure 2-8. Rats with lesions of the dPAG or the vPAG in comparison with sham-
lesioned rats showed enhanced or decreased levels of freezing, respectively,
when presented with a cat. Adpated from (De Oca et al., 1998)

In rats, lesions of the dPAG enhanced conditioned freezing (De Oca et al., 1998)

and reduced escape reactions to electrical footshock (Fanselow, 1991). Alternatively,

stimulating the dPAG by increasing current in a stepwise fashion elicits a freezing

response followed by vigorous escape reactions (Coimbra & Brandao, 1993; Schenberg,

Costa, Borges, & Castro, 1990). Vigorous escape reactions are not elicited by direct

stimulation of the central nucleus of the amygdala. Indeed, stimulation of the lateral and

central nucleus of the amygdala produces long-lasting, opioid-mediated inhibition of the

affective defensive response elicited by dPAG stimulation in the cat (Shaikh, Lu, &

Siegel, 1991a, 1991b). Importantly, this inhibition is selective to defensive behavior;

circling behavior (in cats) elicited by dPAG stimulation was unaffected by amygdala

stimulation. Thus, it may be necessary for the amygdala to be inhibited in order to engage

in active defensive behaviors.











dPAG
1) Inhibits presynaptic
amygdalar inputs to the
nucleus reticularis pontis
caudatis Expressinn of fvP
----------------vFA G
2) Lesions enhance
conditioned freezing and 1) Lesion of the vPAG
reduce escape reactions actvation of the dPAG disrupt the conditioned
Produces inhlbition freezing response
3) Stepwise stimulating odPAG ) v.rPA r
elicits a freezing response 2) Necessary fr
followed by vigorous postencounter freezing
escape reactions defensive behavior.






nucleus reticularis
pontis caudalis


Figure 2-9. Linking the Amygdala, reticular formation, and the Periacqueductal Central
Grey in a functional circuit that interact to modulate the overt involuntary
behavioral manifestation of emotion.

Anatomical connections between the vPAG, dPAG, and the amygdala maybe key

to the inhibition of a freezing response (see Figure 2-9). Specifically, activation of the

dPAG may briefly inhibit the amygdala and vPAG to interfere with the processing of

incoming sensory information, while also permitting active defensive behaviors.

Specifically, Walker & Davis (1997) suggest that an active dPAG inhibits presynaptic

amygdalar inputs to the PnC, a critical component in the execution of reflexive and

voluntary motor function (to be discussed), indicating an involvement of the dPAG in the

transition from freezing to defensive movements as threat levels increase. Concerning the

interconnectivity of the ventral and dorsal portions of the PAG, freezing and escape

responses induced by dPAG stimulation do not depend on the integrity of the vPAG

(Vianna et al., 2001), so whereas initial stimulation of the dPAG leads to an initial

freezing behavior, continued stimulation inhibits amygdala and vPAG, leading to active









defensive behaviors. The vPAG, alternatively, is specifically involved in post encounter

conditioned freezing response. The majority of efferent fibers leaving the PAG terminate

in the PnC (in addition to the parabrachial nuclei, trigeminal motor nucleus, and nucleus

ambiguous), likewise, coupled with amygdala afferents that also terminate in the PnC, the

inhibition/activation triumvirate pathway patterns between PAG, amygdala, and PnC all

contribute to the execution of overt emotionally driven behaviors. (Ratner, 1967)

proposed a description of defensive response topography that varied as a function of the

distance between predator and prey. Defensive behaviors varied between freezing, flight,

fight, and tonic immobility as the predatory distance decreased. Tonic immobility is a

prone, immobile position elicited in wild prey animals thought to inhibit further attack by

removing movement as an attack-eliciting cue (Sargeant & Eberhardt, 1975). Drawing on

the evolutionary strains of Biphasic theory and the defense cascade (see above), when

assessing the rate of approach of threat, a freeze-attack/escape-freeze may be the

appropriate dynamic sequalea for the continued survival of living organisms.

Specifically, when faced with threat, forebrain activity mediating freezing leads to

immobility as the animal freezes (activation of the sympathetic nervous system:

decreased HR, increased SCR), then as the threat draws nearer and physical contact is

made between predator and prey, the defensive needs of the animal may be best served by

complete midbrain control and activation of circastrike behaviors (inhibition of vPAG

and amygdala, activation of dPAG). Safe from the threat of direct physical attack,

forebrain activity (reduction in activation of dPAG with a simultaneous activation of

vPAG and amygdala) mediates the return to immobility and a second freezing response

that continues until safety is restored (Sargeant & Eberhardt, 1975). When the situation









alters to become non-threatening, homeostasis is realized via activation of the

parasympathetic system. The parasympathetic system returns the body back to a relaxed

state, culminating in the resumption of preferred activity within a safe environment

(Fanselow, Lester, & Helmstetter, 1988).

Acoustic Startle and Movement

Startle Circuit

The acoustic startle reflex is a short-latency behavior elicited by a sudden and

intense acoustic stimulus. Considered a primitive defensive reflex, the acoustic startle

serves as an interrupt of ongoing behavior (Lang et al., 1990). The subcortical neural

circuitry of the startle reflex has been mapped via techniques that focus on specific nuclei

in an effort to either eliminate (electrolytic lesion) or illicit (single pulse electrical

stimulation) a startle response.

Given the temporal characteristics of the acoustic startle (8ms in rats, from startle

to EMG activity) Davis and colleagues (Davis et al., 1982a; Davis et al., 1982b) initially

mapped what was then considered a simple pathway through four synapses, three in the

brainstem (ventral cochlear nucleus; an area medial and ventral to the ventral nucleus of

the lateral lemniscus; nucleus reticularis pontis caudalis [PnC]) and one synapse onto

motorneurons in the spinal cord. However in the intervening years since this 4-synapse

route was evidenced, re-evaluation (e.g., Lee et al., 1996) has suggested that cochlear

root neurons proceed directly too, and then terminate in the PnC. Accordingly, given that

cochlear root neurons terminate onto reflex critical PnC cells that in turn project to motor

neurons in the spinal cord (Lingenhohl & Friauf, 1994) the previously identified synapse

at the lemniscus is now bypassed (Lee et al., 1996). In summary, the chain of probable

activation of the primary acoustic startle reflex is generally considered to consist of 3










rather than 4 synapses: (1) cochlear root neurons; (2) PnC neurons; and (3) motor neurons

in the spinal cord (Lang et al., 2000; Lee et al., 1996).

Having established the central components of startle circuitry in animals (Davis et

al., 1982a; Davis et al., 1982b), more recent efforts have sought to decipher the transient

variables that contribute to, and the overt behavioral repercussions of, the human startle

reflex (Lang et al., 1990). In human subjects, early research concerning startle elicited

defensive movements identified a generalized bodily reflex following exposure to a gun

shot (Landis & Hunt, 1939). Contemporary startle research, however, typically centers on

neuroelectric activity (ERP) and/or electromyographic (EMG) indices of eye blink, neck,

shoulder, trunk, and/or leg flexion.




Electrlcal startle NUCLEUS
Ilstimulaton at these sites: RETICULARIS I lectral startle
I Fear potentlaion Is still PONTIS CAUDALIS t lt t te
lobserved eI- |Fear potentiation is not
Ioberved

COCHLEAR
NUCLEUS SPINAL CORDI



ABRUPT NOISE STARTLE
REFLEX


Figure 2-10. The primary acoustic startle reflex is generally considered to consist of 3
synapses: (1) cochlear root neurons; (2) PnC neurons; and (3) motor neurons
in the spinal cord

Due to its sensitivity and slow habituation rate, the eye-blink has captured

considerable attention. For example, guided by the biphasic theory of emotion, Hillman

and colleagues (Hillman, Hsiao-Wecksler, & Rosengren, 2005), reported a positive

association between the eye-blink reflex and postural reactions to an acoustic startle.

Likewise, in addition to homeostatic reflexive motor functions, a similar paradigm has









been used in a number of laboratories worldwide to study the impact of active startle

circuitry on voluntary motor function (e.g., Carlsen, Chua, Inglis, Sanderson, & Franks,

2003; Carlsen et al., 2004a, 2004b; Carlsen, Hunt, Inglis, Sanderson, & Chua, 2003;

Valls-Sole et al., 1999; Valls-Sole et al., 1995).

Acoustic Startle and Involuntary Movement

Hillman and colleagues (Hillman et al., 2005), reported evidence concerning the

impact of an acoustic startle on blink magnitude and postural sway, permitting

conclusions concerning the association between the magnitude and latency of the startle

blink, with the magnitude and latency of whole body postural movements. Specifically,

Hillman et al. required participants to stand passively on a force platform. Postural

adjustments (measured by changes in center of foot pressure) and the eye blink reflex

were time-locked to the presentation of an acoustic startle (96dB). Relative to a baseline

condition, beginning approximately 100 ms following the acoustic startle, participants

displayed an initial anterior movement followed by a posterior movement. A positive

association was reported between blink magnitude and the amount of movement in the

posterior direction only. The authors postulate that the acoustic startle probe triggered a

defensive reaction, and the resulting anterior-posterior response was an overt sign of

postural flexion, an evolutionary reaction promoting survival (Hillman et al., 2005).

The notion that an acoustic startle elicits involuntary movement is an often

validated phenomena specifically in terms of the blink reflex. Startle and movement

literature, however, has developed this relationship to include voluntary movement also.

The following section will detail the growing body of literature concerning acoustic

startle initiated voluntary movements.









Acoustic Startle and Voluntary Movement

Dependent on uniqueness and complexity, varying cortical and subcortical areas

of the brain have been charged with planning, executing, and controlling movement.

Evidence indicates however, that once a movement has been planned, movement maybe

initiated and completed significantly faster when an unexpected acoustic startle (approx

124dB) replaces or accompanies a visual GO signal (Valls-Sole et al., 1995). Valls-Sole

and colleagues (1995) implemented a simple RT task requiring participants to respond to

a visual GO signal. A visual warning signal (5 seconds before the GO signal) readied

participants to the imminent GO signal. However, during a portion of the experimental

trials, an unexpected acoustic startle (estimated at 150dB) was delivered at fixed time

intervals of 0, 25, 50, 75, 100 and 150 ms following the visual GO signal. For interval

durations between 0-75 ms post the GO signal, the acoustic startle resulted in faster pre-

motor and motor time, as well as faster task completion. Pre-motor, motor, and task

completion time increased monotonically as the time between the GO signal and the

startle increased. Acoustic startles were also presented preceding the GO signal, and

although the net result was movement initiation, the recorded RT was not as short as

trials in which the startle stimulus unexpectedly accompanied the visual GO signal. These

early reports suggest that pairing or replacing the GO signal with an acoustic startle leads

to faster PMT, MT, and overall task completion.

Given that voluntary movement was the focus of the Valls-Sole (1995) paper and

is the focus of this review, the factors that composed the speeded response deserve

attention. To determine whether the EMG signal underlying startle speeded RTs were

similar to normal RTs, Valls-Sole et al. (1999) modified their 1995 protocol to include

task related EMG activity and a second simple RT task. Two similar experiments were









reported, the only difference between them being the required behavioral response to the

GO signal (wrist flexion/extension or stand on tiptoe). As in the 1995 paper, a warning

signal preceded a 5 second silence, leading to a visual GO signal that was presented alone

or accompanied by a 130dB acoustic startle. Results corroborated previous findings

(Valls-Sole et al., 1995) indicating that regardless of the response (wrist, tiptoe), the

acoustic startle sped up the execution of the voluntary movement. However, the

comparison made between EMG patterning of movement with and without the startle

indicated that although a time shift was observed, as far as muscle activation was

concerned, the patterning was near identical. Hence, the voluntary reaction was driven

at the speed of a startle reaction while maintaining the characteristics of the motor

program. In light of identical EMG patterns between conditions, the authors concluded

that faster reaction times were the consequence of a rapid initiation of the movement

pattern rather than an early startle reflex coupled with a later voluntary response.

Therefore, having established a similarity between the EMG patterning of startle

and non-startle triggered movements, what and where is the mechanism driving the

facilitation of the pre-EMG phase of startle initiated preplanned movements?

When the subject is prepared to react, the excitability of the motor pathway to the

muscles involved in the planned reaction may be facilitated. As such Valls-Sole et al.

(1999) suggested that because the startle and GO signals were in different modalities, the

acoustic startle stimulus may not have been promoted into the thalamo-cortical sensory

motor system, but rather, could have been integrated into the bulbar reticular formation.

Coupled with a reduced threshold in the motor system, the startle may have triggered the

motor system at a level further downstream from where the visual GO would normally









initiate the same movement. The reticular formation, where the startle response

originates, logically becomes one potential candidate. Consequently, something akin to a

motor program maybe stored in brainstem and spinal centers, allowing the program to be

triggered (via startle) independently of the usual descending GO command from the

motor cortex. The issue of subcortical initiated movement remains an interesting one,

although to date, the mechanisms that permit an acoustic startle to initiate

subcortically stored voluntary movement have not been directly tested and are

therefore unknown.

In a series of related follow up studies Carlsen and colleagues (Carlsen et al.,

2004a, 2004b; Carlsen, Nagelkerke, Garry, Hodges, & Franks, 2000) have replicated and

extended the findings of Valls-Sole et al. (Valls-Sole et al., 1999; Valls-Sole et al., 1995).

Although the major premise of Valls-Sole et al.'s work has not been significantly altered,

a number of papers provide EMG, kinematic, simple and choice RT evidence that further

validate a startle elicited speeded RT. One potential explanation of the startle elicited

speeded RT is that the startle may increase neural excitability, decrease motor system

neural thresholds, summating to voluntary movement with shorter PMT. Accordingly,

any movement that is elicited via an acoustic startle should be characterized by shorter

PMT's.

To address this issue (Carlsen et al., 2004a) modified the Valls-Sole protocol,

adding two and four choice RT tasks to the simple RT task. Participants heard a warning

signal, followed by a short pause, and then at the onset of a visual target were required to

extend or flex the wrist to move a lever (represented by a cursor on a viewing screen) to

reposition the cursor on the target (also visible on viewing screen) as quickly and









accurately as possible. Onset of the target was randomly accompanied by a 127dB

acoustic startle, with potential target locations varying between 1, 2, and 4 potential

positions within each trial block, respectively. Again, if facilitated PMT were the result of

neural excitability, then during each trial block, PMT for target plus startle trials should

be faster than target alone trials. This, however, was not the case. As the number of

potential targets increased (1, 2, 4) PMT increased, however, only simple PMTs were

facilitated during startle compared to non startle trials, with no differences emerging

between control and startle conditions for either the 2 or 4 choice RT tasks (Carlsen et al.,

2004b). The authors proposed that the cortical processes of response selection inherent in

a choice reaction time task barred a preplanned motor program from being formulated

and stored, and subsequently initiated subcortically. In consequence, Carlsen et al. argued

that cortically initiated movements, relative to subcortical initiated movement, take

considerably longer to materialize. However, these data simply suggest that a preplanned

movement will be initiated faster if initiation is accompanied by a startle.

Speculating from these data, that a preplanned movement cannot be initiated from

the cortex so rapidly should be treated with considerable caution. Realistically, PMT's of

a preplanned cortically stored motor program cannot be inferred from performance on a

choice reaction time task because the PMT during a CRT task involves response selection

and movement execution rather than just movement execution. The second argument

offered by the authors to support the subcortical initiation of SRT's was that some PMT's

< 60ms. Fixed amounts of time are required for sensory transduction and neural

conduction to the cortex, and for neural conduction from the cortex to the arm. The first

volley of neural activity caused by acoustic stimuli takes 35 ms to reach the auditory









cortex (Erwin & Buchwald, 1986). In turn, the time it takes for the motor cortex to

communicate with the arm is 20-25 ms (Jones, Calancie, Hall, & Bawa, 1996; Valls-Sole

et al., 1999), suggesting a combined total of 60 ms. Given that Carlsen et al. reported

average times of 80ms for the startle initiated SRT condition, they infer that the 20ms

differential (80 35 25 = 20) is not adequate for the necessary cortical processing that

is required for cortical initiated movement. Further, given that only three startle trials

were included within each response category, variability and inherent error must be taken

into account. For example, when discussing issues on the scale of milliseconds across a

small number of trials, one must be certain that (among other technical issues) the

acoustic stimulus is recorded in the physiological trace at the exact point the stimulus was

actually presented. Error in the range of +10ms per trial will have considerable

consequences.

Methodological issues are also noted regarding the inclusion/exclusion criteria

concerning participants; from the 20 participants tested, 2 did not display a startle

response [as indexed by activity in the sternocleidomastiod (SCM) muscle, Carlsen et al.,

(2003a); Carlsen et al., (2003b)] and 4 failed to show decreased RTs during startle trials.

All 6 participants were removed from analysis. Although Carlsen et al. were specifically

interested in participants who showed facilitated RTs due to the presence of a startle

response, it is perhaps no surprise that startle and control initiated movements were

statistically differentiated, given that participants who did not display faster PMTs,

although demonstrating a startle response, were removed from the analysis. One must

ask: Is it ethical to remove participants who did not show rapid startle initiated









movements relative to a control tone, and then go onto conclude that startle

initiation of a preplanned movement results in speeded PMTs?

A second point of interest concerns the use of the SCM activity to infer a startle

response. (Carlsen et al., 2003a) suggest that the blink reflex is not an accurate measure

of the startle response (the SCM provides a more accurate representation) and as such,

the reliance on a modulated blink reflex in affective research should potentially be

discarded? Two important questions result: 1) Is the startle response an all or

nothing phenomena simply reliant on a stimulus threshold to be realized? Indexing

the behavioral impact of varying stimulus intensities offers a protocol via which this

issue can be evaluated. 2) Are the behavioral manifestations that occur in response

to a 127dB startle probe considerably different from those observed following a 95-

105dB startle?

Summary: Acoustic Startle and Movement

Carlsen et al.'s efforts to build an argument for the subcortical storage of

movement programs and the speeded startle initiation of subcortical movements (Carlsen

et al., 2004a) is weakened by indirect assumptions, and the exclusion of data that does not

support the hypothesized mechanism. Nevertheless, in the majority of participants, the

fact remains that PMTs are speeded if an acoustic startle acts as or accompanies a GO

signal. Further, evidence suggests that the speeded voluntary movement that is initiated

via startle is similar in EMG burst duration and timing, kinematic patterning (Carlsen et

al., 2004b; Valls-Sole et al., 1999) and accuracy (Carlsen et al., 2004b; Carlsen et al.,

2000), as the same movement performed in the absence of the startling stimulus. In short

the same voluntary movement occurs regardless of the initiating stimulus, the









difference being that an acoustic startle results in a voluntary movement being

completed at the more rapid rate of a startle reflex (Carlsen et al., 2004a, 2004b;

Valls-Sole et al., 1999; Valls-Sole et al., 1995).

Acoustic Startle, Emotion, and Movement

Acoustic Startle, Emotion, and Involuntary Movement

The influence of emotion on involuntary movements has attracted significant

interest in recent years. Below, the potential mechanism for such a relationship will first

be outlined, followed by data supporting the notion that emotions are capable of

modulating the magnitude and latency of involuntary movements.

Considerable data supports the notion that a direct pathway linking the amygdala

and PnC mediates fear potentiated startle (see Figure 2-10; Rosen et al., 1991). However,

the exact routes) via which signals from the amygdala reach the PnC (a crucial relay in

the primary acoustic startle circuit: (Lee et al., 1996; Rosen et al., 1991) are yet to be

resolved. The issue has emerged because in addition to the PnC, the amygdala also

projects to the rostral midbrain (Fendt, Koch, & Schnitzler, 1994b; Rosen et al., 1991)

including deep layers of the superior colliculus/deep mesencephalic nucleus (deep

SC/DpMe), the periaqueductal gray (PAG), and the lateral mesencephalic reticular

formation MRF), which all in turn project onto the PnC (Meloni & Davis, 1999). Lesions

within rostral midbrain regions block fear-potentiated startle (Fendt, Koch, & Schnitzler,

1994a; Yeomans & Frankland, 1996), suggesting that these areas serve as a relay

between the amygdala and the PnC. To determine the critical output relay between the

amaygdala and the PnC, Zhao & Davis (2004) locally infused an equal dose of a

glutamate non-NMDA receptor into the areas of interest within the rostral midbrain. In

short fear-potentiated startle was blocked following infusion of the receptor into the deep












SC/DpMe before testing but had no effect on baseline startle amplitude. The same dose


infused into the dorsalolateral PAG, the lateral MRF, or the superficial layers of the SC


did not affect fear-potentiated startle, although the treatment did reduce contextual


freezing when infused into the dorsal/lateral PAG. The authors concluded therefore, that


of the three potential candidates that act as the critical output relay between the


amaygdala and the PnC, the most likely mediating site for fear-potentiated startle is the


SC/DpMe, and furthermore, that glutamatergic transmission is required for this action


(Zhao & Davis, 2004).


SHOCK CONDITIONING
SHOCK SENSITIZATION
Elsctncal stimulation of
Leslons of the amygdal ithe amygdala enhances
;abo ish potentitiin of the the accoust c startle
startle reflex reflex
-" AMYGDALA K

Modulates two patterns of Ilnactivatln of the
defensive behavior: 1) -, superiDr colliculusdeep
freezing, 2) escape/atack \ 'PERIAQUEDUCTAL ...... msn.....phallnucleus
GREY Deep SCiDpMe Iblcks fear potentiated
.-------.-------.----~--- ---.------ I -I-~~~. l- rtle -


NUCLEUS
Elect cal startle RETICULARIS IElectncal stable
isdmuladon at these sites: PONTIS CAUDAL S stmulatlon at this site:
iFear polenli siIon is lll iFearpotentalton Is not
Ilobseryvec !- F p o served -

COCHLEAR
NUCLEUS SPINAL CORD




ABRUPT NOISE STARTLE
REFLEX


Figure 2-11. Affective modulation of startle circuitry: priming motor function. Reciprocal
activation/inhibition between the periaqueductal grey and amygdala modulate
PnC activity which in turn modulates startle potentiation and voluntary motor
function.


Animal literature has shown that startle reflex circuitry is directly influenced by


amygdala projections (assuming an intact SC/DpMe, Zhao & Davis, 2004). Crossing into


the human domain, evidence indicates that a localized lesion of the right amygdala results









in an inhibited reflex contralateral to the lesion (Angrilli et al., 1996). Furthermore, the

typical startle potentiation induced by an aversive emotive background does not manifest,

furthering the belief that the amygdala is involved with human startle and emotional

responses (Angrilli et al., 1996).

To determine whether the amygdala's role in affective processing extends beyond

negative stimuli, Garavan and colleagues (Garavan et al., 2001) collected fMRI data

while exposing subjects to high and low arousing pleasant and unpleasant pictures, in

addition to neutral control pictures. Amygdala activation, relative to a neutral picture

baseline, was significantly increased for both affective stimuli and did not differ for

pleasant and unpleasant categories. Furthermore, whereas arousal level appeared to

modulate the amygdala response for negative stimuli (increased arousal was associated

with increase in activity), regardless of arousal level, pleasant pictures produced

significant amygdala responses, suggesting that the amygdala plays a significant role in

the processing of affective stimuli indiscriminate of the motivational system activated

(Garavan et al., 2001). Increased activation of the amygdala, therefore, does not

necessarily increase startle blink reflex magnitude; increased amygdala activity merely

represents the modulatory impact the amygdala has on response characteristics,

potentially via its connections with the PAG. As such, Walker and Davis postulate that

the role of the dPAG in potentiated startle is during the performance of fear-

motivated behaviors and not during the acquisition and processing of fearful

stimuli.

The notion that affect, via activation of the amygdala, modulates startle has been

extensively examined (e.g., Schupp, Junghofer, Weike, & Hamm, 2004). According to a









motivational priming pattern of affective modulation, associated startle reflexes are

primed by the affective context well in advance of when a secondary probe is actually

presented. The magnitude of the eye-blink response (in addition to other physiological

processes, e.g., ERP) is modulated according to the affective valence of the context,

while the polarity of the response is influenced by arousal. For example, the startle blink

reflex is potentiated when humans are exposed to threat and violent death images, and is

inhibited when humans are exposed to erotica scenes. This pattern of blink magnitude is

robust across varying pleasant and unpleasant categories, with arousal levels controlling

the polarization of the response (Bradley, Cuthbert, & Lang, 1999).

Typical protocols present the startle stimulus between 2-4 s after image onset, and

indeed, the pattern of affective modulation is robust. However, blink magnitude is

sensitive to the length of time an individual is exposed to the image before the startling

stimulus occurs (Bradley et al., 1999). Specifically; (1) strong inhibitory effects are

obtained when blink reflexes are elicited immediately after picture onset, (2) at the point

of maximum inhibition (300 msec after picture onset), reflex inhibition is significantly

larger for arousing pictures, compared with neutral pictures, (3) 500 msec post picture

onset, reflexes are significantly augmented for unpleasant versus pleasant foregrounds,

suggesting affective modulation by this point. (4) inhibited reflexes characterize the first

3 s following picture onset, and following 3 s of exposure, the reflex magnitude appears

to asymptote for all conditions.















% "^








Figure 2-12. The Evaluative Space Model (Cacioppo et al., 1994, 1999) is useful to
illustrate how various local conditions may influence the dispositional
attributes of an organism.

Taking into account the temporal properties of the defense cascade (freeze

response to circastrike) the temporal sensitivity of emotion and attention processes

appear to directly influence the magnitude and latency of an involuntary movement.

Consequently, one can also predict that a similar pattern maybe evidenced

concerning the execution of voluntary movements. Therefore, indexing the

characteristics of a preplanned movement to an acoustic probe at varying intervals during

a fixed exposure period (in addition to or rather than just indexing the blink reflex)

appears to be one among many exciting future directions. Optimizing stimulus intensity

and the lead interval of an initiating stimulus as well as identifying the most appropriate

affective context for the execution of particular movements are critical manipulations that

could drive the investigation of alternative unique mechanisms that may ultimately

benefit movement rehabilitation domains (e.g., stroke, Parkinson's). Notwithstanding the

interacting impact of initiating stimulus, a growing body of literature has indexed the

overt behavioral consequences of affective context.









Cacioppo's Evaluative Space Model

Appropriately reacting to variable conditions in the environment is key to

survival. Biphasic theory posits that an organism will initiate approach or avoidance

behaviors when confronted with pleasant or unpleasant circumstances, respectively.

Related to this biphasic notion, Cacioppo and colleagues (Cacioppo, 1994; Cacioppo &

Berntson, 1999; Cacioppo, Crites, Gardner, & Bernston, 1994; Cacioppo & Gardner,

1999; Cacioppo, Uchino, & Berntson, 1994) predict that an organism's affect system may

be organized to achieve a dynamic balance between appetite and defense (Evaluative

Space Model, ESM; see Figure 2-12). The ESM suggests that positive and negative

information initiates the activation of two functionally separate evaluative processors

(i.e., positivity and negativity). Together, the summation of these processors equate to a

net predisposition to move toward or away from a given stimulus. Because these

processors are relatively distinct, each has the flexibility for the local environment to

shape its activation function (Cacioppo & Berntson, 1999). In the top-right corner of the

figure, each function's activation pattern is characterized. At a net predisposition of zero,

a small offset towards positivity can be noticed. Additionally, as activation increases for

either function, it can be seen that the slope for negativity increases faster than for

positivity. Together, these functions express what has been called positive offset and

negativity bias.

According to Cacioppo & Bernston (1999), "the process of natural selection may

also have sculpted a propensity to react more strongly to negative than positive stimuli"

(p.136). As the Evaluative Space model suggests, humans possess a fundamental

orientation to rapidly shift into defense at lower levels of activation than for positivity.

This predisposition, however, can be shaped by the local environment in the interest of









survival. The net effect of this movement bias has been investigated in a number of

situations across a range of motor actions [posture, Hillman et al., (2004); pinch grip,

Noteboom, Fleshner, & Enoka, (2001); lever pulling, Chen & Bargh, (1999); square

tracing, Coombes, Janelle, & Duley, (2005)].

Emotion and Voluntary Movement

Rapid conscious and non-conscious processing has been shown to influence overt

movement speed and direction. Chen and Bargh (1999) exposed participants to stimulus

words and instructed one group of participants with incongruent instructions by requiring

them to push a lever away from them (avoidance behavior) if the stimulus word presented

was positive (activation of appetitive circuitry), and to pull the lever toward them

(approach behavior) if the stimulus word was negative (activation of defensive circuitry);

the second group received opposite congruent instructions. Results indicated that faster

pulling of the lever coincided with positive initiating cues, while negative initiating cues

were associated with significantly faster responses when pushing the lever. In a second

experiment, participants were exposed to positive and negative stimuli and were

instructed to only pull (group 1) or push (group 2) the lever to pleasant and unpleasant

initiating cues. Again, results confirmed that negative stimuli resulted in faster pushing

movements, while positive stimuli led to significantly quicker pulling movements. These

valence effects are notable, given that negatively valenced cues resulted in faster

movement time, as compared to positively valenced cues, regardless of movement

direction (i.e., push or pull).

Interpreting these data within the Biphasic theory (Lang, 2000), it can be

argued that in the face of negative or threatening cues, activation of defensive

circuitry primes the human organism to move with greater haste. That is, when









exposed to negative cues, speeded movement may increase survival rate, permitting

notions that this functional relationship has, and may continue to provide an evolutionary

advantage to the human organism. Replication of movement speed findings have been

reported with stimuli being novel words rather than familiar words, corroborating the

notion that emotions can and will differentially impact movement speed and direction

(Duckworth et al., 2002). This sequence of studies draws attention to a number of

important issues: Is there different motor circuitry underlying defensive and

appetitive motivated behavior? Perhaps, alternatively, neural thresholds are

decreased throughout the motor system, or the basal ganglia amplifies movements

in unpleasant or threatening contexts?

Alterations in center of pressure (i.e., postural adjustments) resulting from

exposure to affective pictures were recorded by Hillman, Rosengren, & Smith (2004) in

an effort to determine whether activation of motivational systems alter the magnitude and

direction of postural movements. The authors reported gender-differences for postural

responses to unpleasant pictures; an effect not found for pleasant and neutral pictures. In

line with approach-avoidance predictions, females exhibited increased postural

movement away from the unpleasant cue, but contrary to prediction males exhibited

increased movement towards unpleasant pictures. Although gender differences in

postural sway corroborated the findings of Bradley and Colleagues (Bradley, Codispoti,

Sabatinelli, & Lang, 2001) who suggested that females have a broad disposition to react

with a greater defensive set during unpleasant, highly arousing pictures, testing broad

predictions of avoidance behaviors whenever an organism is faced with unpleasant,

threatening, or dangerous situations appears problematic. Revisiting the fight or









flight response, it is reasonable to assume that when coupling certain threatening or

dangerous situations (i.e., no escape route) with certain temperaments (i.e.,

aggression) whereas one individual may flee another may fight. Consequently,

although in each case safety may ultimately be reached, the means by which safety is

achieved contrasts significantly. The question therefore remains: do fight and flight

responses differ in terms of movement direction but remain identical in terms of

neural circuitry and movement force, speed, and accuracy?

With regard to stable sustained muscle activation, Noteboom and colleagues (e.g.,

Noteboom, Barnholt, & Enoka, 2001) required participants to perform a pinch grip task

across a 10 min period, asking only that their pinch remain constant; while error was

recorded and reported, time was not an issue within the protocol. The authors reported

associations between increased impairment of steadiness on a pinch grip task with

increases in arousal, trait anxiety, and intensity of a noxious stimulus (electric shock to

the hand). Conversely, protocols that include the lever pulling task mentioned previously

(Chen & Bargh, 1999) have not incorporated movement accuracy, but rather have

recorded speed of pulling or pushing the lever, with movement direction and time being

the dependent measures of interest.

As such, there is considerable data suggesting that the temporal and spatial

characteristics of voluntary movement are influenced by the affective state of the

individual, and that the speed and magnitude of startle elicited reflexive movements (e.g.,

blink reflex) vary according to affective states. Furthermore evidence suggests that

voluntary movements can be achieved at the pace of a reflexive movement if the

voluntary movement is initiated via an acoustic startle. To date however, startle initiated









voluntary movement and manipulated affective states have never been collectively

examined in a systematic fashion. Linking emotion driven behavioral alterations with an

underlying neural mechanism remains a formidable but exciting challenge for movement

scientists.

Acoustic Startle, Emotion, and Voluntary Movements

Overt behavioral movements that accompany the startle reaction are considered

reflexive (homeostatic) and are therefore typically considered to be exempt from

voluntary control (Valls-Sole et al., 1995). Startle reflex pathways, however, require

neural structures that are also intricately involved in voluntary motor action (e.g.,

reticulospinal system). Evidence for the facilitation of voluntary movement via

manipulation of affective context and initiating stimulus has been reported. For example,

Bradley, Drobes, & Lang (1996) exposed participants to pleasant, unpleasant, and neutral

images; at varying intervals during the exposure period participants were required to

make a simple button press following the presentation of an acoustic startle or tone.

Faster reaction times coincided with startle probes and RT were accelerated later in the

viewing period (i.e., at longer startle lead intervals). Specifically, longer RTs emerged

early in the viewing period (maximal at 300msec) and decreased as the exposure period

progressed. Similar to eye-blink magnitude (see above), RTs leveled off following 2-3 s

of exposure and remained relatively constant for the duration of the 6 s exposure period.

These findings (coupled with startle blink modification data presented above) represent

varying attentional and emotional processes in picture perception (Bradley et al., 1999).

In discussing the Bradley et al. (1996) abstract, Bradley et al. (1999) suggest that

following picture onset, processing resources were automatically allocated to stimuli that









engaged appetitive or defensive motivational systems, resulting in inhibited blink

magnitude and lengthy RT's, relative to neutral pictures. As such, an initial orientating

response may inhibit overt behavior, a phenomena magnified with activation of defensive

circuitry (i.e., freezing). During the continuing exposure period, once initial processing

has occurred attentional resources maybe freed up resulting in greater blink potentiation

and faster RT.


SHOCK CONDITIONING


Figure 2-13. Priming motor function: Amygdala activity projects to the PnC and nucleus
accumbens (NA) which in turn modulate reflexive and voluntary motor
function. CMA = cingulated motor area, NA = nucleus accumbens, Ml
primary motor area, SMA = supplementary motor area, PMd dorsal premotor
cortex.

Conclusion

Aside from one abstract (Bradley et al., 1996) and a brief synopsis of that abstract

(Bradley et al., 1999), startle elicited movements have not been systematically

investigated within varying affective contexts. The above review, however, amalgamates






76


largely independent but complementary bodies of literature that summate to provide

strong inference concerning the means by which the emotional system primes motor

actions, and the varying impact initiating cues have on overt movements (See Figure 2-

13). In closing, the above review justifies the necessity and importance of developing a

research line that can successfully delineate the mechanisms underlying how and if

affective states coupled with initiating cues impact the characteristics of voluntary motor

function.














CHAPTER 3
METHODS

Participants

Thirty five (females = 17; males = 18) undergraduate students from the University

of Florida were recruited to participate in this study, and received extra credit as

compensation. Participants reported no hearing loss or central nervous system disorders

that could affect movement. Written informed consent was obtained from all participants

prior to beginning the study. All Participants' self-reported dominant hand use. All left

handed participants (3, male) were excluded from the analyses to prevent confound due

to handedness. In addition, data points 3 SDs from the mean were considered extreme

scores and were removed prior to analysis. The repeated measures analyses were such

that participants missing one (or more) scores) were completely removed from each

separate analysis. Consequently, 29 participants were included in the PRT, EMG peak,

EMG risetime, and peak force analyses; 28 participants were included in the EMG slope

and force risetime analyses; and 25 participants were included in the force slope analysis.

With regard to analyses of the startle blink reflex, 26 participants were included in each

analysis.

Instrumentation

Affective Stimuli

Participants viewed a total of 64 digitized photographs selected from the

International Affective Picture System (IAPS; NIMH Center for the Study of Emotion

and Attention, 2005) representing three affective categories (16 erotic couples, 16 attack,









16 household objects1). Sixteen blank black images were also presented. All pictures

were visible for 6 seconds. Images were selected according to affective normative ratings

(CSEA) to ensure that erotic and attack images were similarly arousing, and that each

were significantly more arousing than neutral images (P = 6.57; U = 6.64; N = 2.56). For

valence, each category significantly differed from each other (P = 6.75; U = 2.4; N =

4.97). Each participant viewed each picture only once. Stimulus presentation order was

randomized and counterbalanced.

Task

While viewing each picture, participants were required to respond as quickly as

possible to any acoustic stimulus by initiating an isometric bimanual contraction of the

wrist and finger extensor muscles against two independent load cells (left/right limb).

Acoustic Stimuli

Created with custom built Labview software (7.1; National Instruments, Austin,

TX), the tone cue consisted of a 50 ms tone delivered at 80 dB. In contrast, the startle cue

stimulus was a 50 ms burst of white noise delivered at 107 dB with near instantaneous

rise time. Acoustic stimuli were presented binaurally through a set of calibrated

headphones (Radio Shack digital sound level meter: 33-2055, Fort Worth, TX). Acoustic

stimuli were presented at set intervals of 500, 1500, and between 3000-5000 msec post

picture onset (M= 4011.88, SD = 153.11, range = 3645.50-4345.25). Tone and startle

cues were equally represented within each picture category at each time period (2

startle/tones per category per time period). As such, each valence by acoustic cue by time


1 IAPS images: erotic couples:,4647, 4607, 4652, 4656, 4658, 4659, 4660, 4664, 4670, 4681, 4687, 4689,
4694, 4695, 4800, 4810; attack: 3530, 3500, 6260, 6540, 6313, 6550, 6243, 6370, 6510, 6200, 6560,
6360,6230, 6250, 6300, 6244; household objects: 7002, 7004, 7006, 7009, 7010, 7025, 7035, 7041, 7050,
7052,7055,7059,7080,7090,7150, 7175.









period combination was experienced twice. To prevent habituation and anticipation, catch

trials (no sound) occurred four times within each valence category. Intertrial intervals

varied from 10-14 s.

Voluntary Movement

Participants were prepared for measurement in accordance with the Society for

Psychophysiological Research guidelines (Putnam, Johnson, & Roth, 1992). EMG

surface electrodes (silver-silver chloride electrodes, 1 cm in diameter and 2 cm apart with

an epoxy-mounted preamplifier) were placed over the extensor communis digitorum and

extensor carpi ulnaris muscles of left and right arms. To index force generation during

each isometric wrist/finger extension, two 34.1 kg load cells embedded in cushioned

platforms were altered in height to accommodate individual hand sizes (see Figure 3-1).

Upper limb EMG (bandpass filter 1-500 Hz) and force data were amplified by 5 K and

collected at 1000 Hz via Biopac software (3.8.1, Biopac Systems Inc, Goleta, CA, USA).

Blink reflex

The eye-blink response to the acoustic startle probe was recorded by placing two

Biopac shielded 4 mm Ag/AgCl electrodes (ELS204S) over the orbicularis oculi muscle

beneath the left eye. The raw EMG signals were amplified by 5,000 using a Biopac

bioamplifier (EMG100B) and bandpass filtered from 90 to 250 Hz.

Trial onset and offset, and visual and auditory stimulus presentation were

controlled via a custom Labview program. The custom-written program simultaneously

sent a 5-volt digital marker into the physiological trace to indicate picture onset and

acoustic stimulus onset. Each separate 10 s trial (2 s baseline; 6 s picture presentation; 2 s

buffer) was streamed to disk for offline analyses.









Procedure

After all questions had been answered and informed consent had been obtained,

participants were seated in a comfortable chair positioned 1.0 m from a 19" LCD

presentation screen. Next, height of the force platforms was adjusted, load cells were

calibrated, and EMG sensors were attached to the forearms and beneath the left eye (see

Figure 3-1). Following calibration, participants were familiarized with the protocol via a

4 trial practice session (all blank images, 1 startle, 2 tone, and 1 catch trial). Participants

were instructed to (1) "look at each picture for the entire time it is on the screen", (2)

"consider picture onset as a cue to prepare to make the required wrist and finger

extension", and (3) "respond as quickly as possible to an acoustic stimuli by initiating a

short duration bimanual isometric contraction of the wrist and finger extensor muscles."

Following picture offset, participants were instructed to continue viewing the blank

screen as the next image would appear after a short break. At the conclusion of all trials,

hands were removed from the customized force platform, EMG sensors were removed,

and the participants were debriefed. From participant arrival to departure, the experiment

lasted approximately 30 minutes.

Data Reduction

Voluntary movement

EMG and force data were analyzed offline via a custom LabVIEW program.

EMG signals were rectified and filtered with a 25-Hz lowpass elliptic filter (Carlsen et

al., 2004b). Baseline EMG and force scores were calculated for each trial (mean score

during 150 ms preceding acoustic stimulus onset). Eight dependent measures were

calculated for each trial: (1) premotor reaction time: PRT, (2) force onset: Fonset, (3) EMG

amplitude: EMGamp, (4) force amplitude: Famp, (5) force risetime: Frisetime, (6) EMG































Figure 3-1. Experimental setup. Top: postures of arms, forearms, and shoulders before
and during the bimanual task. Bottom left: posture of hands relative to load
cells during movement preparation and ITI. Bottom right: posture of hands
relative to load cells during ballistic movement execution.

risetime: EMGrisetime, (7) force slope: Fslope, and (8) EMG slope: EMGsiope, (see Figure 3

for specific details and calculations). For each trial for each limb, the semi-automated

analysis program superimposed force and filtered EMG data over the digital trigger

signal. Visible on a computer monitor, the program automatically identified and then

inserted cursors at Famp and EMGamp locations within specified windows after acoustic

stimulus onset (EMG: 40-500 msec; Force: 40-800 msec). Baseline corrected normalized

Famp and EMGamp T-scores were calculated for each trial within each participant's data

prior to statistical analysis. Onset of muscle action was identified by locating the first

time point where EMG signal amplitude was greater than double the baseline value

(Wong & Ng, 2005). Likewise, onset of force production was identified as the first time

point where force data exceeded double the force baseline value (see Figure 3). Given the









strictness of the detection algorithm, coupled with intermittent intermediary EMG and/or

force noise between stimulus onset and movement onset, the location of each of these

threshold locations was visually verified and manually adjusted if necessary. Because of

excessive noise and/or no visible peak in EMG or Force within the specified windows, a

total of 19 trials were removed from 9 participants' data sets (range 1-4 trials per subject;

97.8% of the trials were included in the analysis). For each participant, no more than 1

trial was removed from each acoustic stimulus by valence condition. Summary statistics

were created by averaging left and right limb data for each dependent variable.

Blink reflex

The raw EMG signals were rectified and low pass filtered (25Hz) offline via a

custom built LabVIEW program. The semi-automated program identified and inserted a

cursor at peak EMG amplitude within a 20-150 ms window after startle stimulus onset.

Onset of muscle contraction was identified by locating the time point where EMG signal

amplitude first equaled and then surpassed double the baseline value (Wong & Ng, 2005)

2005). A cursor was displayed at this location. Baseline corrected peak t-scores were then

calculated for each trial within each participant's data prior to statistical analysis. Four











EMG
- -- FORCE


ACOUSTIC STIMULUS TIME

Figure 3-2. Calculation of dependent variables, voluntary movement. PRT: Delay
between acoustic stimulus onset and EMG threshold. Fonset: Delay between
acoustic stimulus onset and Force onset. EMGmp: Peak amplitude within a
40-500ms window following acoustic stimulus onset. Fmp: Peak amplitude
within a 40-800ms window following acoustic stimulus onset. EMGrisetime:
Latency between EMG onset and peak. Frisetime: Latency between Force onset
and peak. EMGsiope: EMG amplitude change from threshold to peak, divided
by time from threshold to peak. Fsiope: Force amplitude change from threshold
to peak, divided by time from threshold to peak.

dependent variable scores were calculated for each startle trial: premotor time, peak force

latency, peak amplitude, EMG slope (see figure 3-3). For each participant, data from

accepted trials were averaged for each level of valence for each level of probe interval.

Statistical Analyses

To establish whether startle initiated movements and activation of appetitive

and/or defensive circuitry alter voluntary and involuntary motor function, each dependent

variable was analyzed in 2 (ACOUSTIC STIMULUS: startle, tone) x 4 (VALENCE:

erotica, attack, household objects, blank) x 3 (PROBE INTERVAL: 500ms, 1500ms,

3000-5000ms) analysis of variance (ANOVA), with repeated measures on all three

factors.






















ACOUSTIC STIMULUS TIME r

Figure 3-3. Calculation of dependent variables, blink reflex. Threshold refers to the
location and amplitude in the EMG trace where values are greater than double
the corresponding baseline value. PMT: Delay between acoustic stimulus
onset and EMG threshold. Peak amplitude: Peak amplitude within a 20-
150ms window following acoustic stimulus onset. Peak latency: acoustic
stimulus onset to peak EMG amplitude. Slope: EMG amplitude change from
threshold to peak, divided by time from threshold to peak.

For F ratio interactions with valence and probe interval, if the sphericity

assumption was violated, then Geisser-Greenhouse corrections were used to obtain the

critical p-value. Follow-up analyses were conducted using simple effects tests and the

Tukey HSD procedure for significant interactions and main effects, respectively.

To illustrate the relationship between voluntary and involuntary startle triggered

movements, Pearson correlation coefficients were computed between corresponding

variables (voluntary and involuntary: PMT, EMG peak, peak EMG latency, EMG slope)

matched for valence, probe interval, and limb. For all analyses, the probability value was

set atp < .05.














CHAPTER 4
RESULTS

Voluntary Movement

Premotor Reaction Time (PRT)

A significant main effect of time (F (2, 56) = 28.82, p < .001) evidenced that

PRTs were faster following longer probe intervals (1500 and 3000-5000 msec) relative to

shorter probe intervals (500 msec). A significant main effect of acoustic stimulus

indicated that when movements were initiated following startle relative to tone cues,

premotor times were accelerated (F (1, 28) = 44.67, p < .001). Additionally, a significant

main effect of valence indicated that relative to erotic images, exposure to attack and

household object images resulted in faster PRT, F (3, 84) = 9.98, p < .001. Further, PRT

during exposure to scenes of household objects was faster as compared to attack and

blank conditions.

These significant main effects, however, were superseded by a Time x Valence

interaction (F (6, 168) = 3.55, p = .002). Follow-up analyses indicated that PRTs initiated

to cues 500 msec following erotic image onset were slower than all other Valence x Time

conditions aside from attack and blank conditions at 500 msec. In addition, exposure to

attack images at 500 msec resulted in slower PRT relative to blank conditions at 1500

and 3000-5000 msec intervals. Finally, PRTs to cues at 500 msec during blank exposure

periods were greater than during household object exposure periods with probe intervals

of 1500 and 3000-5000 msec. (see Figure 4-1). Remaining interactions did not reach

significance (p's > .05).









340 ---- STARTLE TONE

S320 -

E 300

E 280-
c 260
0o
240 -

220
0
E 200 -

180 -

160
E A N B E A N B E A N B
500 1500 3000-5000
Valence Probe Interval (msec)
Figure 4-1. PRT (+ 1SE) for startle and tone cues for each valence category for each
probe interval. E = erotica, A = attack, N = household objects, B = blank

EMG Risetime (EMGrisetime)

EMG onset to peak was significantly altered by initiating stimulus (F (1, 28) =

7.50, p = .012) with inspection of the means indicating that rise times were shorter to

startle relative to tone cues ([msec] Startle: M= 69.86, SE = 5.32; Tone: M = 80.60, SE=

8.90). Main effects of time, valence and remaining interactions did not reach significance

(p's> .05).

EMG Peak Normalized T-scores (EMGamp)

A significant main effect of acoustic stimulus was evidenced, indicating that

EMGamp was greater to startle relative to tone cues, F (1, 28) = 66.08, p < .001. This main

effect, however, was superseded by a significant Time x Acoustic Stimulus interaction (F

(2, 56) = 3.79, p = .029), and Time x Valence interaction (F (6, 168) = 3.55, p = .002)









(see Figure 4-2). Follow-up tests for the Time x Acoustic Stimulus interactions revealed

that peaks to startle cues at 1500 and 3000-5000 msec were greater than tone conditions

at the same intervals. In addition, peaks to startle cues at the 1500 msec interval were

greater than all tone conditions. Post-hoc tests to identify specific Time x Valence

differences were not significant. Main effects of time and valence did not reach

significance (p 's > .05).


58 STARTLE TONE

56 -

54-

c 52 -
I-


LJ
v 48

S46

44

42
E A N B E A N B E A N B
500 1500 3000-5000
Valence Probe Interval (msec)

Figure 4-2. EMGamp (normalized T-scores, + 1SE) for startle and tone cues for each
valence category for each probe interval. E = erotica, A = attack, N =
household objects, B = blank

EMG Slope (EMGslope)

Analyses revealed that EMGslope was significantly altered by acoustic stimulus,

such that slopes were of a steeper gradient when movements were initiated to startle

relative to tone cues (F (1, 27) = 7.28, p = .012) ([msec] Startle: M= .93, SE = .05; Tone:









M= .76, SE = .05). Main effects of time and valence and all higher order interactions did

not reach significance (p 's > .05).

Force Risetime (Frisetime)

Analyses revealed a significant effect of acoustic stimulus on the latency between

force onset and peak force (F (2, 56) = 3.97, p = .024), indicating that risetimes were

more rapid to startle relative to tone cues ([msec] Startle: M = 147.78, SE = 12.49; Tone:

M= 155.34, SE= 13.35).

Peak Force Normalized T-scores (Famp)

Analysis of normalized Famp scores evidenced a significant main effect of acoustic

stimulus (F (1, 28) = 97.19, p < .001), indicating that peaks were greater following startle

relative to tone cues. Analysis of Famp also revealed a significant Time x Acoustic

Stimulus interaction (F (2, 56) = 4.86, p = .011) with follow-up tests revealing greater

peaks following startle cues at 1500 and 3000-5000 msec probe intervals relative to tone

cues at the same intervals. In addition, peaks to startle cues at 1500 msec were greater

than tone conditions at 500 msec. (see Figure 4-3). Finally, a significant interaction

between time and valence was evidenced (F (6, 168) = 2.50, p = .025), although follow-

up tests including planned comparisons for attack images were not significant. Main

effects of time and valence and remaining interactions were not significant (p 's > .05).

Force Slope (Fslope)

Gradient of slope between Fonset and Famp was significantly affected by Acoustic

Stimulus (F (1, 24) = 33.75, p < .001). Follow-up analyses indicated that steeper slopes

coincided with all startle conditions (M= .42, SE = .04) relative to tone conditions (M=

.36, SE = .03). Neither main effects for time, valence, nor the remaining interactions

reached significance (p 's > .05).











500 msec 1500 msec 3000-5000 msec
54



-r
0








S48
-.



a)



Erotica Attack HHO Blank

Valence
Figure 4-3. Forceamp (normalized T-scores, + 1SE) collapsed across initiating stimulus
(startle, tone) for each valence category for each probe interval.

Involuntary Movement (Blink Reflex)

Premotor Reaction Time (PRT)

Significant main effects of time (F (2, 42) = 12.73, p < .001) and valence (F (3, 63)

= 7.26, p < .001) evidenced that PRT was longer at probe intervals of 500 msec relative

to all later probe intervals, and longer during exposure to pleasant stimuli relative to all

other categories. The time by valence interaction was not significant (F (6, 126) = .39, p

= .88).

Peak EMG T score

Analyses revealed that peak EMG of the startle blink reflex was significantly

altered by affective context (F (3, 63) = 5.86, p = .001), with follow-up analyses

evidencing smaller peaks during exposure to pleasant images relative to all other






90


categories. In addition, a significant main effect of time was also evidenced (F (2, 42) =

23.15, p < .001), with follow up analyses confirming that smaller peak scores at 500 msec

relative to peaks at 1500 msec and 3000-5000 msec. The time by valence interaction was

not significant (F (6, 126) = .93, p = .47).


S Erotica Attack HHO I Blank


500 1500 3000-5000

TIME
Figure 4-4. Blink reflex premotor reaction time for each probe interval for each valence
category. PRT's were longer at probe intervals of 500 msec relative to all later
probe intervals, and longer during exposure to pleasant relative to all other
stimuli.

Peak latency

Peak EMG latency of the startle blink reflex was not altered by time (F (2, 42) =

2.97, p = .062), valence (F (3, 63) = .30, p = .83), or from an interaction between these

two factors (F (6, 126) = .93, p = .47).




Full Text

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EMOTION AND THE DEFENSE CASCADE: MODULATION OF VOLUNTARY AND INVOLUNTARY MOVEMENT By STEPHEN A. COOMBES A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2006

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Copyright 2006 by STEPHEN A. COOMBES

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iii ACKNOWLEDGMENTS I thank Dr. Christopher Janelle for his continued support and supervision of my academic development as well as his invaluable wisdom on matters of real life. Likewise, I thank Dr. Jim Cauraugh whose continued enthusiasm and keen interest have been hugely appreciated. I also thank my committee member s, Dr. Mark Tillman and Dr. Ira Fischler for their patience, input, and support. Finally I thank my family, the wonderful Christine, and my great friends on both sides of the Atlantic.

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iv TABLE OF CONTENTS page ACKNOWLEDGMENTS.................................................................................................iii LIST OF FIGURES..........................................................................................................vii ABSTRACT....................................................................................................................... ix CHAPTER 1 INTRODUCTION........................................................................................................1 Emotion and Movement...............................................................................................1 Defensive Behavior......................................................................................................2 Orienting of Attention: Valence or Arousal?................................................................3 EMG and Force Measures............................................................................................4 Acoustic Initiated Movements......................................................................................6 Hypotheses....................................................................................................................8 2 EMOTION AND MOVEMENT..................................................................................9 Cortical Control of Movement....................................................................................10 Primary Motor Cortex (M1)................................................................................10 The Supplementary Motor Area (SMA)..............................................................14 Subcomponents of the SMA................................................................................14 The Premotor Cortex (PM)..................................................................................17 Subcomponents of PM cortex.............................................................................19 Cingulate Motor Areas........................................................................................22 SelfVersus Externally-Paced Movements.........................................................26 Summary: Cortical Control of Movement...........................................................29 Subcortical Control of Movement..............................................................................31 Basal Ganglia.......................................................................................................31 The Defense Cascade..........................................................................................37 Basal Ganglia and Emotion.................................................................................40 Brainstem Reticular Formation...........................................................................43 Summary: The Motor System.............................................................................45 Emotion.......................................................................................................................4 5 Biphasic Theory of Emotion...............................................................................47 Emotional Circuitry.............................................................................................47 The limbic system........................................................................................47

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v Amygdala.....................................................................................................49 Periacqueductal central grey........................................................................52 Acoustic Startle and Movement..................................................................................56 Startle Circuit.......................................................................................................56 Acoustic Startle and Involuntary Movement.......................................................58 Acoustic Startle and Voluntary Movement.........................................................59 Acoustic Startle, Emotion, and Movement.................................................................65 Acoustic Startle, Emotion, and Involuntary Movement......................................65 CacioppoÂ’s Evaluative Space Model...................................................................70 Emotion and Voluntary Movement.....................................................................71 Acoustic Startle, Emotion, and Voluntary Movements.......................................74 Conclusion..................................................................................................................75 3 METHODS.................................................................................................................77 Participants.................................................................................................................77 Instrumentation...........................................................................................................77 Affective Stimuli.................................................................................................77 Task.....................................................................................................................78 Acoustic Stimuli..................................................................................................78 Voluntary Movement...........................................................................................79 Blink reflex..........................................................................................................79 Procedure....................................................................................................................80 Data Reduction...........................................................................................................80 Voluntary movement...........................................................................................80 Blink reflex..........................................................................................................82 Statistical Analyses.....................................................................................................83 4 RESULTS...................................................................................................................85 Voluntary Movement..................................................................................................85 Premotor Reaction Time (PRT)...........................................................................85 EMG Risetime (EMGrisetime)................................................................................86 EMG Peak Normalized T-scores (EMGamp)........................................................86 EMG Slope (EMGslope)........................................................................................87 Force Risetime (Frisetime)......................................................................................88 Peak Force Normalized T-scores (Famp)..............................................................88 Force Slope (Fslope)..............................................................................................88 Involuntary Movement (Blink Reflex).......................................................................89 Premotor Reaction Time (PRT)...........................................................................89 Peak EMG T score...............................................................................................89 Peak latency.........................................................................................................90 EMG slope...........................................................................................................91 Correlations: Voluntary a nd Involuntary Movement.................................................91 Premotor Reaction Time (PRT)...........................................................................92 Peak EMG T score...............................................................................................92 EMG slope...........................................................................................................93

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vi 5 DISCUSSION.............................................................................................................94 Voluntary Movement..................................................................................................95 Premotor Reaction Time......................................................................................95 Peak EMG and Peak Force Amplitude..............................................................100 Summary............................................................................................................101 Unpleasant and Neutral Stimuli Similarly Modulate Movement?...........................103 Voluntary and Involuntary Movement s: Is there a relationship?.............................104 Premotor RT......................................................................................................104 Peak EMG.........................................................................................................104 EMG Slope........................................................................................................105 Summary............................................................................................................105 Limitations................................................................................................................105 Future Research........................................................................................................108 Conclusion................................................................................................................110 LIST OF REFERENCES.................................................................................................112 BIOGRAPHICAL SKETCH...........................................................................................133

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vii LIST OF FIGURES Figure page 2-1 Imaging the premotor areas......................................................................................18 2-2 Schematic of the two frontal regions implicated in monitoring functions...............27 2-3 Motor circuit of the basal ganglia............................................................................32 2-4 The cortico-STN-pallidal hyperdirect pathway....................................................35 2-5 Possible neuronal mechanisms of integr ation of volitional, emotional and automatic control of motor behaviors.......................................................................36 2-6 A schematic presentation of the defense response cascade......................................38 2-7 Integration of volitional, emotional a nd automatic control of motor behaviors.......41 2-8 Rats with lesions of the dPAG or the vPAG in comparison with sham-lesioned rats showed enhanced or decreased levels of freezing, respectively..................................53 2-9 Linking the Amygdala, reticular form ation, and the Periacqueductal Central Grey..........................................................................................................................5 4 2-10 The primary acoustic startle reflex...........................................................................57 2-11 Affective modulation of startle circuitry: priming motor function..........................66 2-12 The Evaluative Space Model....................................................................................69 2-13 Priming motor function............................................................................................75 3-1 Experimental setup...................................................................................................81 3-2 Calculation of dependent variables: voluntary movement.......................................83 3-3 Calculation of dependent variables: blink reflex......................................................84 4-1 PRT........................................................................................................................ ...86 4-2 EMGamp....................................................................................................................87

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viii 4-3 Forceamp....................................................................................................................89 4-4 Blink reflex prem otor reaction time.........................................................................90 4-5 Mean blink peak T score..........................................................................................91 4-6 Peak EMG latency of the blink reflex......................................................................92 4-7 EMG slope of the startle blink reflex.......................................................................93

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ix Abstract of Dissertation Pres ented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy EMOTION AND THE DEFENSE CASCADE: MODULATION OF VOLUNTARY AND INVOLUNTARY MOVEMENT By Stephen A. Coombes August 2006 Chair: Christopher M. Janelle Major Department: Applied Physiology and Kinesiology Evidence indicates that voluntary and involuntary movements are altered by affective context, the characte ristics of an initiating stim ulus, as well as the duration between affective context onset and initiating cue. The purpo se of the present study was to delineate the central and peripheral mechanisms that c ontribute to this phenomenon. During the presentation of attack, erotic, hous ehold object and blank images, participants (N = 35) were instructed to respond to a uditory stimuli (startle,107dB; or probe, 80dB) presented at varying time intervals foll owing picture onset (500, 1500, 3000-5000 msec) by initiating a bimanual isometric contraction of the wrist and finge r extensor muscles against two independent load cells. The star tle blink response was also measured to provide an index of how va lence and probe interval m odulate involuntary movement. Analyses of electromyography and force meas ures revealed that (1) voluntary and involuntary movements are sensitive to short lead interval prepulse effects, (2) the intensity of an acoustic star tle stimulus accelerates temporal components and strengthens

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x magnitude components of voluntary moveme nt, (3) faster and stronger voluntary movements occurred approximately 1500 msec pos t image onset, when initiated to startle cues with a strong trend indicating that th is pattern was accentuated during exposure to attack images. Collectively, these findings car ry significant implicati ons for those seeking to facilitate the speed and force of voluntar y movement (i.e., movement rehabilitation), and for those seeking to regulate emotional input so as to optimize the quality of intended movements.

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1 CHAPTER 1 INTRODUCTION Emotion and Movement Rapidly identifying emotionally salient information in threatening and dangerous contexts, and demonstrating the ability to tr anslate that information into successful and appropriate behaviors is critic al to survival. A primary func tion of emotion, therefore, is the preparation for action (Schupp, Junghof er, Weike, & Hamm, 2003a). The link between primitive emotions and overt motor actions was first noted by (Cannon, 1929), who suggested that when confronted with a dangerous situation, an organism elicits an “emergency reaction” composed of either a fi ght or flight survival response. The basic principle of Cannon’s work remains intact toda y. Modulated by the thr eat from predators, defensive behaviors have been classified into three categories that traverse the entire animal kingdom: freezing, fleeing, and figh ting (defensive attack: Eilam, 2005). Demonstrating the impact these defensive predispositions have on voluntary and involuntary movement is the prim ary purpose of this proposal. The utility of understanding defensive predis positions is two fol d. First, activating emotional circuits that predispose humans to execute specific moto r actions may be an effective method to forge new pathways be tween intention and movement for those suffering motor impairment (e.g., stroke). For ex ample, despite increased research efforts and rehabilitation options, over 65% of individuals with st roke have residual motor impairments one-year post (Wade, Langton-Hewer, Wood, Skilbeck, & Ismail, 1983). As such, understanding how emotions modulate movement may lead to emotional

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2 manipulations being fused into existing re habilitation techniques to enhance their effectiveness. Second, within a wide range of performance contexts, movements have to be executed during dynamic states of emotiona l flux. In consequence, predisposed movements may be incongruent with in tentional movements. Understanding how emotions predispose movement, therefore, will be essential in tailoring regulatory strategies to combat emotion driven dis positions. In short, understanding how active defensive circuitry alters ove rt motor behavior holds considerable promise for emotion regulation as well as movement rehabilitation. Defensive Behavior Animal models indicate that the amygdala and the dorsal and ventral periaqueductal gray (PAG) mediate the expression of defensive behaviors according to the nature of the threat, in cluding its 1) type (i.e., imme diate/innate/ conditioned), 2) proximity, and 3) complexity. The defense cascade model, conceptualized within an evolutionary perspective of the relative position of predat or and prey (Bradley & Lang, 2000; Fanselow, 1994; Lang, Bradley, & Cuthbe rt, 1997; Wade et al., 1983), proposes three distinct defensive phases: pre-enc ounter, post-encounter (freezing), and circastrike/defensive fighting/fleeing. Within picture-viewing paradigms, exposure to an unpleasant cue re sults in a stable pre-encounter condition that is then superseded by a post-enc ounter state reflected in an initial “orienting of attent ion” and a rapid increase in skin conductance response (arousal). Oriented attention typically manifests in strong in hibition of the startle blink reflex for highly arousing visual stimu li (Bradley, Cuthbert, & Lang, 1993), cardiac deceleration (Bradley, Codispoti, Cuthbe rt, & Lang, 2001), and a reduction in postural

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3 sway (Azevedo et al., 2005). Cardiac accelera tion and potentiation of the startle blink reflex (accentuated in unpleasant contexts) si gnal the transition fr om a post encounter freezing phase to defensive mobilization (approx. 800 msec). Orienting of Attention: Valence or Arousal? Although activation of defensiv e circuitry (e.g., startle bli nk potentiation) has been demonstrated early in the viewing period wh en phobic’s view object s relating to their phobias (Globisch, Hamm, Esteves, & h man, 1999), startle blink inhibition among controls typically coincides with highly arousing affective fore grounds, independent of valence (Bradley et al., 1993) The notion, however, that atte ntion rather than valence modulates the early blink reflex (<800 msec) has recently been contested. Specifically, Stanley and Knight (2004) demonstrated that relative to positive and neutral contexts, blink potentiation occurred at both early (300msec) and late (2-5 s) probe times during exposure to threat images. Conversely, exposur e to disgust images only resulted in a main effect of blink potentiation relative to positive contents. As su ch, averaging across “unpleasant” foregrounds rather than analyzi ng specific categories (i .e., threat, disgust) within broad time windows may prevent threat -related blink potentiation from emerging. Consequently, acute specificat ion of emotional context, as well as probe interval duration, are essential in unders tanding the time course of active defensive circuitry. The primary goal of this proposal, therefore, is to confirm threat related startle blink potentiation across freezing and defense mobiliz ation phases, and to determine how this progression simultaneously alte rs voluntary movement. The innate predisposition to protect onese lf from danger (active defensive system) is complemented by the instinctive tendenc y to approach pleasant stimuli (active appetitive system). Capturing the polarity between approach and avoidance, Lang,

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4 Bradley and colleagues (Lang et al., 1997) have proposed the Biphasic Theory of emotion. The extent to which emotions alte r the direction (appro ach/withdrawal), speed, magnitude, and accuracy of voluntary movement s has been captured within a number of behavioral protocols. Specifi cally, relative to activation of appetitive circuitry, activation of defensive circuitry acceler ates avoidance movements (i.e ., pushing a lever away from the body, Chen and Bargh, 1999; Duckworth et al., 2002; Marsh et al., 2005), accelerates the speed and decreases the accu racy of a controlled motor task (Coombes, Janelle, & Duley, 2005), and leads to greater force production during a sustained isometric contraction without sa crificing movement variability (Coombes, Cauraugh, & Janelle, 2006). In addition to force production, EMG m easures are routinely used to index voluntary (Carlsen, Chua, Inglis, Sanders on, & Franks, 2004a; Valls-Sol, Rothwell, Goulart, Cossu, & Munoz, 1999; Valls-Sol et al., 1995) and involuntary movements (Hillman et al., 2004; Stanley and Knight 2004). Combining EMG and force measures offers a unique approach to indexing the effect of emotion on movement. Indeed, understanding the physiology of EMG and for ce production ensures that findings can be interpreted according to phys iological mechanisms. EMG and Force Measures Amplitude of surface EMG is routinely us ed to quantify voluntary and involuntary muscular contraction (Bolton, Cauraugh, & Hausenblas, 2004; Hillman, Rosengren, & Smith, 2004; Moore, Drouin, Gansneder, & Shultz, 2002; Rau, Schulte, & DisselhorstKlug, 2004; Stanley & Knight, 2004). Surface EMG amplitude and latency is sensitive to the number and rate of motor unit contractions (Andreassi, 2000), as we ll as the size and location of motor unit activation relative to the position of the corresponding sensors

PAGE 15

5 (Keenan, Farina, Merletti, & Enoka, 2005). In addition, the size of the evoked muscle potential is influenced by sarcolemmal c onduction velocity, axonal conduction velocity, variability in the activation times of motor neurons, and shape of the intracellular action potential (Keenan et al., 2005). Although numerous variables alter EMG amplitude, startle elicited blink amplitudes consistently vary according to aff ective valence. For example, greater peak EMG amplitude, reflecting a stronger muscular contraction, has been associated with startle elicited blink reflexes during exposure to threat imag es (relative to neutral and pleasant) at early (300msec: Stanley & Knight, 2004) a nd late probe intervals (> 2000msec: Lang, Bradley, & Cuthbert, 1990; St anley & Knight, 2004). In addition, we (Coombes et al., in review) have demonstrat ed a similar effect on voluntary movement, such that exposure to unpleasant images in teracts with the presentation of movement initiating startle cues (relativ e to an 80db tone) resulting in greater peak amplitude relative to all valence tone probe cond itions. Further, peak EMG voluntary and involuntary latencies attenuate when moveme nts are executed to startle cues during exposure to unpleasant images (Lipp, Siddle, & Dall, 1997). Collectively, EMG indices of voluntary and involuntary movement have been interpreted as indicating that an evolutionary/survival advantage maybe gained from the execution of strong, rapid muscle contractions. The force produced by a muscle depends on the number and size of active motor units and the rate at which those units discharge action potentials (Macefield, Fuglevand, & Bigland-Ritchie, 1996; Moritz, Barry, Pascoe, & Enoka, 2005). Specifically, two mediating mechanisms have been proposed to account for muscular force production

PAGE 16

6 (Kamen & Du, 1999); the “size principle” a nd “rate coding.” By se quentially increasing the number of active motor units within the motoneuron pool, from the smallest motor units to the largest, the total force output increases (size principle) (Aimonetti, Vedel, Schmied, & Pagni, 2000; Henneman, 1979; Sc hmied, Aimonetti, & Vedel, 2002; Schmied, Morin, Vedel, & Pagni, 1997). This recruitment order has been confirmed for isometric contractions with a high correlati on between recruitment force threshold and twitch force (Riek & Bawa, 1992). Second, al though motor unit discharge rates have been associated with variations in force production (rate coding: (Milner-Brown, Stein, & Yemm, 1973), given that motor units vary acco rding to threshold and spike amplitude, it is not a simple linear rela tionship between discharge rate and force production (Hamada, Kimura, & Moritani, 2004; Klein, Ivanova, Rice, & Garland, 2001). Nevertheless, we have previously demonstrated that indices of force are modulated ac cording to initiating stimulus and valence. Specifically, peak forces are accentuated, onset to peak force slopes are steeper, and latencies are shorter wh en ballistic wrist and finger extensions are executed to startle relative to tone cues (Coom bes et al., in review). Further, force onset slopes are steeper, and latencies are shorte r when ballistic movements are executed during unpleasant relative to pleasant and bl ank exposure conditions. These data suggest that startle initiating cues a nd activation of defensive circu itry increase the size and/or number of active motor units. Acoustic Initiated Movements The acoustic startle reflex is a shortlatency behavior elicited by a sudden and intense acoustic stimulus (Grillon & Baas 2003). Considered a primitive defensive reflex, the acoustic startle serves as an in terrupt of ongoing behavior (Lang et al., 1990). The probable chain of activation of the prim ary acoustic startle reflex is generally

PAGE 17

7 considered to consist of 3 synapses: (1) coch lear root neurons; (2 ) PnC neurons; and (3) motor neurons in the spinal cord (Lang, Davi s, & Ohman, 2000; Y. Lee, Lopez, Meloni, & Davis, 1996). Direct links between the amygdala and the nucleus reticularis pontis caudalis (PnC) and PAG are critical in poten tiation for the startle reflex (Davis & Whalen, 2001; Zhao & Davis, 2004). Accelerating premotor reaction times by repl acing “go” signals with startle cues has been consistently replicated (Carlsen et al., 2004b; Valls-Sol et al., 1999; Valls-Sol et al., 1995). To account for these findings th e subcortical triggering hypothesis has been proposed, and contends that star tle cues initiate movements th at are stored subcortically within the reticular forma tion (Carlsen, Chua, Inglis Sanderson, & Franks, 2004a). Should this be the case, given that amygdala (via PAG) projections to the PnC are responsible for potentiation of the startle blink, there is reas on to believe that voluntary movements executed from the PnC will be altered by emotion in a similar fashion to involuntary movements. As such, we will dete rmine how the characte ristics of voluntary and involuntary movements are altered accord ing to varying initiating cues, affective contexts, and probe intervals. Participants will be exposed to attack, erotica, neutral, and blank images. Picture onset will be a cue for participants to ready themselves to move. During image presentation, participants will be instructed to initiate a simple RT ballistic movement at the presentation of acoustic stimuli (either a startle, 107dB; or tone, 80dB). The presentation period will run for 6 seconds, dur ing which startle and tone cues will be equally represented at 3 predetermined time intervals during the exposure period (500msec, 1500msec, 3000-5000msec). Voluntar y movements of the wrist and finger

PAGE 18

8 extensors will be indexed via force transduc ers and EMG sensors on the fore-arms. An index of the involuntary blink reflex will be captured via EMG sensors beneath the left eye. Three hypotheses are offered. Hypotheses 1a) We predict that if valence modulat es movement at all time intervals, movements to acoustic cues during exposure to threat images will be significantly different from erotica, neutral, and bl ank exposures (attack = accelerated times, accentuated peaks, steeper slopes. 1) 1b) However, if arousal modulates movement early in the exposure period (500msec), movements during exposure to attack and erotica images will be similar, and each will be different compared to neutra l and blank images (attack and erotica = decelerated times, attenuated peaks, shallower slopes). 2) Relative to tone initiat ed voluntary movements, startle initiated movements at all probe intervals will be signifi cantly different from all tone initiated movements (startle = accelerated times, accentuated peaks, steeper slopes. 1) 3) Significant positive correlations between corresponding voluntary and involuntary dependent variables during startle trials will pe rmit the interpretation that voluntary and involuntary movements sh are similar subcortical pathways. 1 Accelerated times : faster voluntary and blink PMTs; faster voluntary and involuntary EMG risetime; faster force risetime; faster peak blink EMG latency; Accentuated peaks : greater peak voluntary and blink EMG; greater voluntary peak force; Steeper slopes : steeper slope to voluntary and blink peak EMG; steeper slope to voluntary peak force

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9 CHAPTER 2 EMOTION AND MOVEMENT Overt coordinated motor behavior is th e culmination of a complex interaction between various functioning ne ural structures. To bette r understand the controlling mechanisms of movement related decisi on making, movement preparation, movement execution, and movement feedback, the major cort ical and subcortical structures involved in movement will be addressed. Specific attention will be paid to areas where emotion may impact the motor system. The primary motor area (M1), the supplementary motor area (SMA), the dorsal premotor area (PMd), and the cingu lated motor areas (CMA) are included in a section concerning the role of the cortex in movement production. Following a summary of the cortical regions, th e basal ganglia and reticular formation are evaluated in terms of their role in motor behavior. Two major improvements have been made in the evolution of human motor control; the capability to maintain an erect posture and the ability to move the fingers independently (Canedo, 1997). While bipeds and quadrupeds boast neural mechanisms that integrate bodily movement and associ ated postural adjustments, the postural constraints imposed by bipedal locomoti on are more demanding (Canedo, 1997). The activity of distal, proximal, a nd axial muscles have to be co ntrolled by some structure or structures able to coordinate medial and lateral motor systems. Specific cortical and subcortical regions, coupled with desce nding spinal tracts collectively permit the necessary simultaneous activation of distal and postural muscles (e.g., Picard & Strick,

PAGE 20

10 1996; Vulliemoz, Raineteau, & Jabaudon, 2005). Deta ils of the cortical and subcortical structures that permit such moto r control are presented below. Cortical Control of Movement Large regions of the brain located on the lateral surface and on the medial wall of each hemisphere participate in the generati on and control of movement. Four distinct areas have been identified: 1) Primary motor area (M 1, the precentral gyrus), 2) Supplementary motor area (SMA, adjacent to the premotor area, but on the medial surface of the hemisphere), 3) Premotor area (a nterior to M1, on the la teral aspect of the hemisphere), and 4) Cingulate motor area (in the anterior part of the cingulate sulcus, adjacent to the inferior end of the SMA). Primary Motor Cortex (M1) Located along the precentral gyrus in Brodmans area 4, the M1 houses considerable pyramidal neurons that directly link (via the corticospinal tract) with the spinal cord. In consequence, the M1 is c onsidered a key structure in the execution of voluntary movement (Canedo, 1997; Cunningto n, Windischberger, Deecke, & Moser, 2002; Lee, Chang, & Roh, 1999; Wildgruber, Erb, Klose, & Grodd, 1997). Traditionally, the MI was thought to be excl usively involved in the executi on of movements (Richter, Andersen, Georgopoulos, & Kim, 1997). Ho wever, this conventional view was challenged by the discovery of higher-order motor components in the MI of monkeys (Georgopoulos, Taira, & Lukashin, 1993). Prep aratory activity in the M1 in monkeys stimulated corresponding questions to be as ked of the M1 in humans. During completion of a delayed cued finger movement task (i.e., a warning signal followed by a delay, followed by a go signal) Richter et al. (1997) collected event-related fMRI data from M1, PM, and SMA and reported activity in all th ree areas during moveme nt preparation and

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11 movement execution. As predicted, activity in M1 was weaker during movement preparation than during movement executio n; and although activity was of similar intensity during preparatory and execution pe riods in the secondary motor areas, during the execution phase M1 activity was greater rela tive to activity in the secondary areas. Although M1 activity during preparatory pe riods has been corroborated elsewhere (Crammond & Kalaska, 2000; Mushiake, Inase, & Tanji, 1991), it should be noted that the M1 cells sensitive to movement preparati on have been located close to the dorsal PM area (Crammond & Kalaska, 2000). To date, however, M1 activity continues to be closely associated with movement execution, best exemplified by the consequences of M1 lesions which result in impaired voluntary movements of associated body pa rts (Lang & Schieber, 2003). Specifically, the ability to move and control one body part excl usively of all others (e.g., the fingers) is severely impaired, with attempted in dividual movements often accompanied by considerable involuntary movements of adjacent body parts (Lang & Schieber, 2003; Schieber & Poliakov, 1998). Additional support of the M1Â’s acute control of movement is demonstrated in subtle finger movements; movements that can be temporarily unattainable by reversible inactivation of sma ll portions of the hand representation area in M1 (Brochier, Boudreau, Pare, & Sm ith, 1999; Schieber & Poliakov, 1998). M1 activation is not essen tial or alone, however, in its control of voluntary movement as evidenced by the very limited involvement of the cat M1 during routine locomotion across a regular surface (Beloozerov a & Sirota, 1993; Marple-Horvat, Amos, Armstrong, & Criado, 1993). Investigations in to the many basic neuronal networks regulating somatic movement have, in c onsequence, successfully focused on the

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12 brainstem (Canedo, 1997). Under circumstances when automated movements have to be modified online (i.e., traversi ng undulating surfaces), and al terations in exact placement of the foot are demanded, the discharge of th e pyramidal neurons in the motor cortex are considerably accentuated; the more difficult the placement, the greater the discharge (Beloozerova & Sirota, 1993). In conseque nce movements that demand acute online adjustment, or the use of individual proxima l body parts, require M1 input if successful execution is to be realized. A redeeming quality of the M1 that eman ates across the majority of literature concerns its physiological make-up. Evidence su ggests that rather th an specific portions of the M1 unilaterally controlling specifi c movements, the diversity and overlapping nature of the distributed network of neurons within each portion of the M1 ensure that damage to one area can often be compensate d for by adjacent areas (Donoghue & Sanes, 1988; Sanes & Donoghue, 2000). A considerable a dvantage of such a distributed network permits the immense storage capability and ri chness of function as well as providing a basis for network flexibility (Elbert, Pa ntev, Wienbruch, Rockstroh, & Taub, 1995; Sanes & Donoghue, 2000). As such, the amount of brai n matter devoted to any particular body part is dynamic and flexible, with neural re presentations waxing or waning according to use; in turn altering the level of control th e associated portion of the M1 has over that body part (Elbert et al., 1995). The increase and decrease in limb speci fic cortical representation is termed neural plasticity (Sanes & Donoghue, 2000). Maintain ing or enhancing the cortical representation of any body part is reliant upon continued use; a severe infarction or lesion that prevents the flow of necessary informa tion within the neural structures that permit

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13 movement typically leads to catastrophi c consequences (Wilson, Gandevia, Inglis, Gracies, & Burke, 1999). If a limb cannot be us ed, its cortical repr esentation diminishes via cortical reorganization, sometimes w ith alarming consequences (Woodhouse, 2005). On the opposite end of the continuum, how ever, the alternative is that neural representation increases the more use a specif ic limb gets; the la rger the co rresponding cortical representation, the fine r the control one has over that specific limb (Elbert et al., 1995). This reciprocal cause and effect neural plasticity relationship has been elegantly demonstrated in rats (Donoghue & Sanes, 1988). Following the amputation of a rats forelimb at birth, 2-4 months following amputat ion the authors noted the occurrence of 3 organizational differences: 1) intact muscle groups had enlarged cortical representations, 2) normally weak connections from MI to the proximal musculatur e were strengthened, and 3) muscles were grouped in unusual combin ations in the reorganized cortical maps. Evolving from work in rat models, observation of the dynamic substrate of the human motor cortex is a relatively new phenomena, but one that wa rrants considerable optimism within the movement rehabilitation domain. Indeed, current knowle dge portrays M1 as a distributed network of neurons that collec tively demonstrate an innate ability to reorganize according to phys iological circumstance. In conclusion, given an intact network between the cortex and limb, the M1 is essential to the initiation and control of volitional movement. If emotion has the capacity to alter movements, which one assu mes it does, one must consequently ask, exactly which part of the process does emotion modulate? Given the physiological make-up, anatomical connections, and functi on of M1, there appears to be no direct

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14 route via which emotion can alter the in itiation of movements within the M1. Although other brain regions were thought to influence motor output only by way of efferent projections to M1, recent eviden ce suggests that the secondary and cingulate motor areas also have dir ect access to corticospinal tracts and the lower brain mechanisms essential in the realization of volitional move ment (Dum & Strick, 1991). The Supplementary Motor Area (SMA) Located in BrodmanÂ’s area 6 the SMA lie s medial to the premotor area and projects to M1 and to the corticospinal a nd corticobulbar tracts. Re moving portions of the SMA produces specific deficits in bimanual coordination (Brinkman, 1984) or internally guided or instructed movements (Kazennikov et al., 1998; Kermadi, Liu, Tempini, & Rouiller, 1997), whereas chemical inactivati on results in an inability to sequentially execute multiple movements (Shima & Tanji, 1998). Likewise, clinical SMA lesion studies have corroborated impairments simila r to those induced vi a inactivation: the failure of sequential motor performance (L aplane, Talairach, Meininger, Bancaud, & Bouchareine, 1977; Laplane, Talairach, Me ininger, Bancaud, & Orgogozo, 1977) and a reduction in spontaneous movements (Krainik et al., 2001). The SM A therefore appears to be charged with guiding sequential movements based on internal cues, and is often associated with the performance of pre-le arned motor sequences (Jenkins, Brooks, Nixon, Frackowiak, & Passingham, 1994), or self paced motor behaviors (e.g., self paced finger movements: (Larsson, Gulyas, & Roland, 1996). Subcomponents of the SMA The SMA may not function as a single unit, and the functions charged to the SMA as a whole may be housed within independent functionally distinct regions. Specifically, whereas lesions of the SMA lead to defici ent sequential motor performance (Laplane,

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15 Talairach, Meininger, Bancaud, & Bouchare ine, 1977) and a reduction in spontaneous movements (Krainik et al., 2001), lesions of th e pre-SMA manifest in deficits in updating sequential movements (Shima & Tanji, 1998) and the acquisition of sequential procedures (Nakamura, Sakai, & Hikosaka, 1999). The functional difference between different portions of the SMA emerged from the notion that cognitive demand(s) associated with the motor task modulate regional SMA activity (D eiber et al., 1991). In monkeys first, and more recently in humans, anatomical and functional data (Geyer, Matelli, Luppino, & Zi lles, 2000; Picard & Strick, 1996) have resulted in the SMA being split into two distinct portions : 1) pre-supplementary motor area (caudal portion of area 6), and 2) supplementary moto r area proper (rostral portion of area 6). The connectivity, physiology, and function of the pre-SMA suggest that it is more closely aligned with prefrontal areas than wi th motor areas (Picard & Strick, 2001). Prefrontal areas provide cognitive, sensory, and motivational inputs for motor behavior (Walton, Devlin, & Rushworth, 2004), whereas th e motor areas are concerned more with the core fabric of movement (e.g. muscle pa tterns). The notion of splitting the SMA into two separate areas is founded in two distinct differences in the anatomical connections of the pre-SMA and SMA proper: 1) only the SM A proper is directly connected to M1 and to the spinal cord (Dum & Strick, 1991; Wang, Shima, Sawa mura, & Tanji, 2001), and 2) only the pre-SMA is interconnected with the prefrontal cortex (Lu, Preston, & Strick, 1994; Luppino, Matelli, Camarda, & Rizzolatti, 1993). Notably, these distinct anatomical characteristics are reflected in variations in task specific activity (Geyer et al., 2000). Given increases in activation of the SMA with the acquisition of a motor sequence task, the interpretation until recently, was that the SMA is associated with

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16 learned sequential movements (Hikosaka et al., 1996). Recent accounts of task specific pre-SMA activity, however, have altered the inferred role the SMA plays in the motor domain. (Sakai et al., 1999) recently compared pre-SMA ac tivation in closely matched tasks requiring visuo–motor associations, but varied in motor and perceptual sequence components. Activation of the pre-SMA occurre d in all tasks that required visuo–motor associations relative to tasks that required sequential processe s. Moreover, pre-SMA activation was greatest in the conditional ta sk, in which non-sequential responses were randomly determined by the color of visual cues. These data indicate that activation of the pre-SMA has little to do with motor sequence learning, rather, that pre-SMA activation reflects the establishing or retrieving of visuo–motor associations. Functional differences between the SMA proper and pre-SMA have been further corroborated (in monkeys) during the performanc e of a reaching task in which two visual instruction cues were pres ented: 1) target location, and 2) reaching arm, separated with a delay between the cues (Hoshi & Tanji, 2004a, 2004b, 2004c). The authors identified four major differences in pr e-SMA and SMA proper activation: 1) neuronal activity preceding the appearance of visual cues was more frequent in the pre-SMA, 2) a considerable portion of pre-SMA neurons (rel ative to SMA proper ne urons) responded to the first and second cue, reflecting the processing of visual stimuli and their associated meaning (i.e., coupling target location and ar m use), 3) during the motor planning period, activity in the pre-SMA reflected target location, while activity in the SMA reflected which arm to use, and 4) during movement execution, incr eased activity occurred in SMA and was selective for the use of either the ipsilateral or contralateral arm. In contrast, activity of the pre-SM A was suppressed. These findings provide further evidence for the

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17 functional dissection of the SMA, co rroborating previous claims that the pre-SMA is more concerned with processing and inte grating relevant internal and external related stimuli (supported by its links to the prefrontal cort ex; (Lu et al., 1994; Luppino et al., 1993), while the SMA proper is integral to the motor planning period, reflecting which limbs are being rea died for movement, in addition to the execution of movement those limbs. Additional studies have exte nded the involvement of the pre-SMA to associations based on auditory stimuli (Kurata, Tsuji, Naraki, Seino, & Ab e, 2000). Visual and auditory versions of a conditional choice reaction time paradigm generated pre-SMA activations equal in magnitude (Sakai et al ., 2000). The contribution of the pre-SMA to sensory–motor associations, therefore, maybe considered modality-independent as well as effector-independent, given that similar regions are activated in unimanual left and right limb conditional motor tasks (Kurata et al ., 2000; Sakai et al., 2000). This supports the view that the pre-SMA operates at a more ab stract level and is more closely related to the processing, integration, and maintenance of relevant sensory information than response selection or executi on (Cunnington et al., 2002; Kurata et al., 2000; K. M. Lee et al., 1999; Sakai et al., 2000) In stark contrast, SMA proper activation only occurs during movement-related components of visual or auditory tasks, and appears to be more involved with the pure movement portions of specified tasks (Boecker et al., 1998; Cunnington et al., 2002; St ephan et al., 1995). The Premotor Cortex (PM) The premotor cortex lies anterior to the M1 in Brodman’s area 6 and the lower part of area 8 (See Figure 2-1). PM receives afferents from the thalamus and projects onto portions of the corticospinal a nd corticobulbar tracts as well as to the M1

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18 (Dum & Strick, 1991). Dum and Strick also not e that the total numb er of corticospinal neurons in the arm representations of the PM equals or exceeds the total number in the arm representation of the M1. PM collectively comprise more than 60% of the cortical area in the frontal lobe that projects to the spin al cord, and consequentl y, is the origin of a substantial portion of the corticospinal system Each of the PM areas has direct access to the spinal cord, and as such, each has the pot ential to influence the generation and control of movement independently of M1. Figure 2-1. Imaging the premotor areas. Motor areas of the frontal lobe in monkeys (a) and homologous areas in the human (b). In humans, the border between areas 6 and 4 on the lateral surface is located in the anterior bank of the central sulcus. For illustration, the border is drawn on the surface of the hemisphere along the central sulcus (bottom, wh ite dotted line). Except for the most medial portion, M1 does not occupy the precentral gyrus. The premotor cortex controls proximal and trunk muscles in addition to controlling voluntary movement of the eyes via the front al eye fields (Dum & Strick, 1991). Damage to the premotor areas in humans leads to a syndrome termed “apraxia” in which patients are unable to perform skilled motor task s (Hanna-Pladdy, Heilman, & Foundas, 2001; Leiguarda & Marsden, 2000). The premotor ar ea is activated during movements that are primarily guided by visual, a uditory, or somatosensory st imuli (Jenkins et al., 1994; CCZ caudal cingulate zone CMAd dorsal cingulate motor area CMAr rostral cingulate motor area CMAv ventral cingulate motor area FEF frontal eye field fMRI functional magnetic resonance imaging M1 p rimar y motor cortex

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19 Larsson et al., 1996). Van Mier and colleagues (van Mier, Tempel, Perlmutter, Raichle, & Petersen, 1998) reported incr eased activation in the dorsa l premotor cortex (PMd) during a battery of m aze-tracing tasks (rightand left-h anded) and suggested that PMd activation was involved with the temporal as pects of movement pl anning (Halsband, Ito, Tanji, & Freund, 1993), as well as the temporal aspects of the acquisition, execution (Middleton & Strick, 2001; Seit z et al., 1994), and retention of motor tasks (Middleton & Strick, 2001). Similar to pre-SMA activation pa tterns noted above (Kur ata et al., 2000; K. M. Lee et al., 1999; Sakai et al., 2000), van Mi er et al. reported that PMd cortex activity was similar for rightand left-h anded performance, suggesting that activity in the PMd is involved in abstract processes of complex tasks, rather than processes directly related to the execution of those tasks. Research concerning the functioning PM in monkeys, however, has guided more recent human res earch which has further distinguished anatomical, physiological, and functi onal subdivisions within the area. Subcomponents of PM cortex Founded on anatomical and physiological differe nces, the dorsal part of the PMd in primates has been divided into rostral (PMdr or pre-PMd) and caudal (PMdc or PMd proper) subdivisions (Matelli, Luppino, & Rizzolatti, 1991). These differences are comparable to those that determine the pre-SMA/SMA proper dist inction noted above. Indeed, the PMdc (PMd proper) shares three primar y characteristics with the SMA proper: 1) both areas project to the M1 and directly to the spinal cord (Dum & Strick, 1991; He, Dum, & Strick, 1993), 2) neither area has substant ial interconnections with prefrontal cortex (Lu et al ., 1994), and 3) neurons in both regions are primarily involved in aspects of motor control (Gey er et al., 2000). Likewise, the PMdr (pre-PMd) has much in common with the pre-SMA, specifically: 1) ne ither of these areas project to the M1 or

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20 to the spinal cord (Dum & Strick, 1991; He et al., 1993) rather 2) both regions are interconnected with areas of pr efrontal cortex and with the reticular formation (Geyer et al., 2000; Lu et al., 1994) and finally, 3) re sults of neuronal reco rding and functional imaging studies suggest that the pre-SMA and the PMdr are more involved in cognitive than in motor processes. In short, the PMdc contains a high proportion of neurons that display setand movement-related activity whereas neurons in the PMdr are more responsive to sensory cues, and fewer are active in relation to movement. Functional PMd predictions founded in anim al data have guided human research. For example, Simon et al. ( 2002) predicted that the PMdr would primarily activate during attention and/or memory processe s whereas activity of the PMdc would correspond with motor preparation/execution. Developed fr om the monkey reaching task noted above (Hoshi & Tanji, 2004a, 2004b, 2004c) in which a first cue guided the focus of spatial attention and memory, and the second inst ructed an arm movement, Simon et al. modified the protocol to pr oduce two tasks, during which fMRI data was collected. To maximize spatial attention and memory demands the first task presented a series of 4, 8, or 12 white squares. At the end of the series, motor execution was signaled by the appearance of 1 red and 1 green square and a central fixation cross turning from white to either green or red. At this point, one of two possible butt on presses was required (middle finger = green/ index finger = red). For the experimental condition of task 1, the correct response was determined by which execution cue held the same position as the last white square in the sequence of 2, 8, or 12 white squares. The color of the square in the matching position determined the correct response. For the c ontrol condition, the response was determined by the color of the fixation cross.

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21 The second task extended the motor prep aration phase by lengthening and varying the delay (between 1 and 5.5 s) between the instructional cue and movement execution. Presentation of a single white square was fo llowed by a fixed delay. Then the 2 execution squares were presented for variable durations together with a green or red fixation cross. For both the experimental and control condi tions of task 2, the correct response was determined by the color of the square that occupied the location of the final stimulus (green in this example). However, for the ex perimental condition, subjects were required to withhold their response until offset of the execution squares (and concomitant return of the white cross), whereas, for the control, they were asked to respond immediately following directional cue onset. As expected, subjects’ displayed signif icantly slower reaction times in the experimental condition of the spatial/memory task (task 1: control – experiment = -137 ms) given the required spatial matching that preceded movement execution. Alternatively, but again in lin e with prediction, the manipul ation of motor preparation length in task 2 resulted in faster re action times (control – experiment = 283 ms) suggesting that motor preparation did o ccur during the extended delay period, and resulted in the manifestation of faster RTs. Concerning the pre-motor areas, as expected the spatial attention/memory paradigm preferentially activated the PMdr, whereas the motor preparation paradigm engaged the PMdc. Interpretations corroborated previous evidence from both monkey and human studies. Similar to the pre-SMA and SMA proper distinction, it appears that the human PMdr participates in spatial attention and working memory (Coull & Nobre, 1998; Courtn ey, Petit, Maisog, Ungerleider, & Haxby, 1998; Petit et al., 1996; St ern et al., 2000), while the PMdc is central to the

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22 execution of movement. The simultaneous activation of other cortical areas also confirmed expectation; findings will be discus sed later in a summary section addressing the nature of interactive activity across all cortical motor areas. Cingulate Motor Areas The majority of natural actions are selected voluntarily from many possible options. Actions are often chosen based on thei r predicted consequences; predictions that are based on the internal and external state of the organism. As stated, emotions influence action and typically emerge in circumstances where adaptive control is required (Ekman & Davidson, 1994). As such, all eyes point towa rds a structure or set of structures that bridge emotion and action. The M1, SMA, and PM, however, do not appear to be the motor structures that directly li nk the emotion and movement domains. Motor control research has been and continues to be successful in determining the complex network of structures that plan, control, and execute movement (Simon et al., 2002), but knowledge of the human motor system for the most part has developed independently of the interacting influence that emotions may play. In terms of the motor cortex, the progression that has been ma de in alleviating this issue has focused on the cingulate motor area (CMA). In addition to its role in movement ex ecution, evidence sugges ts that it is the CMA, given its anatomical position and f unctional connections with surrounding brain areas (Vogt & Pandya, 1987), that decides, directs, and assesses the appropriateness of motor function (Picard & Stri ck, 1996). The CMA is locate d within regions lining the cingulate sulcus in the medial surface of the cerebral hemis phere and has been dissected into rostral (CMAr) and caudal (CMAc) portio ns (Matelli et al., 1991). Distinguishing itself from the primary, pre, and supplementary motor areas, the CMA receives

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23 considerable afferent input from limbic stru ctures (as well as the prefrontal cortex), ensuring a flow of information to the CMA concerning motivation, the internal state of the organism, as well as cognitive evalua tion of the environment (Bates & GoldmanRakic, 1993; Lu et al., 1994; Morecraft & Van Hoesen, 1998). With regard to the limbic system, the amygda la and ventral striatum project to the anterior cingulate cortex and the cingulate gyrus, which in turn project to the CMAr (Vogt & Pandya, 1987). These projections deliver information about reward values that are directly connected to the goals of motor acts. In additi on, the pathways that link the prefrontal cortex to the CMAr (Lu et al., 1994) transmit information held in short-term memory about the occurrence of events duri ng the performance of previously performed motor tasks (Goldman-Rakic, 1995) The CMA therefore, has access to affective information that if processed correctly can influence the appropr iate selection of a voluntary motor action that is consistent with the current motivational state (Picard & Strick, 1996). Once a selection has been made the CMAs send efferents to the primary and secondary motor areas as well as brains tem structures that in turn help plan, coordinate, and then via projection to the spinal cord, execute the movement (Dum & Strick, 1991; He, Dum, & Strick, 1995). Task specific activity of the monkey brain has advanced understa nding of the role of the CMA in decision making, planning, execu tion, and the control of motor action. For example, Shima & Tanji (1998) trained three monkeys to either push or turn a handle, in response to a visual trigger signal. The animals vol untarily selected one of the two movements based on the amount of reward (grape juice) anticipated. During a series of constant-reward trials, the monkeys contin ually selected a particular movement in

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24 anticipation of its beneficial consequen ces. If the reward was reduced, conditioned training was such that the monkeys learned to perform the alternate movement, and as such, a cyclical process developed, with th e monkeys altering their movements in an effort to always obtain maximum reward. Even t-related single-cell recording techniques were used to record cellular activity from the CMAr, CMAc and M1. CMAr and CMAc activity was found to relate to movement initiation and move ment preparation, while only the CMAr showed activity specific to th e occurrence of a reward. Shima and Tanji concluded that the monkey CMAr plays a key role in choosing the most appropriate action (given internal and external information ga rnered from the situation) in an effort to achieve the greatest consequential gain from that action. The CMAc, however, was exclusively involved in the execution of th e chosen movement (Isomura, Ito, Akazawa, Nambu, & Takada, 2003; Takada et al., 2001). Transitional research into the human CMA has attracted considerable interest in recent years (Isomura et al., 2003; Jenkins et al., 1994; Posner, Petersen, Fox, & Raichle, 1988; Ullsperger & von Cramon, 2004; Walton et al., 2004). Considered a possible homolog of the rostral cingulate motor area (CMAr) in monkeys (Walton et al., 2004) the human rostral cingulate zone (RCZ) of the dorsal anterior cingulate cortices (ACd) is closely connected to the motor system, and is involved in monitoring self-generated movements and in signaling the need for imme diate changes of behavi or (Jenkins et al., 1994; Picard & Strick, 1996; U llsperger & von Cramon, 2004). The RCZ is thought to be intricately invol ved in focusing an individualÂ’s attention to necessary cues. Specifically, attent ion for action, response selection, motor preparation, and motor execution are all proces ses charged to the RCZ (Isomura et al.,

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25 2003). Further justification has been found in evidence that lesions of cingulate areas result in impairments of motor performa nce in human patients (Turken & Swick, 1999). Corroboration of motor and cognitive rela ted RCZ activity was reported by (Cunnington et al., 2002), who compared brain activati on during internally gui ded and externally triggered finger movements. During each condition, predominant cingulate cortex activation (in addition to SMA activation) was identified in the posterior end of the CMAr, which is thought to be involved in motor tasks requiring internal movement selection (Picard & Strick, 1996) Indeed, as with the pre-SMA, the CMAr shows greater activation during internally generated move ments (Deiber, Honda, Ibanez, Sadato, & Hallett, 1999; Wessel, Zeffiro, Toro, & Hallett, 1997), is involved in early processes of movement preparation (Ball et al., 1999) and in the internal representation or imagination of movement (Stephan et al ., 1995). Both the CMAr and the pre-SMA therefore appear to be commonly involved in making the decision as to the most appropriate movement to make given the circumstances. Analogous to th e different portions of the SMA and PM areas, the cingulate motor areas have been cont rasted with the orbitofrontal cortex (OFC) in terms of their anatomical connections and varying but rela ted functions. In contrast to the RCZ, the OFC is a rich recipient of affere nts from sensory regions and is not directly connected with the motor system. Functionall y, the OFC appears to be involved in more general monitoring of sensory events with re spect to their significance to the individual (Ullsperger & von Cramon, 2004). Recent evidence has sought to further di sentangle processes that culminate in overt movement. Similar in fashion to the monkey reward task (Shima & Tanji, 1998), Walton et al. (2004) required human participants to complete a number of response-

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26 switching tasks that varied according to the ex tent to which participants had to make choices and monitor feedback.1 By varying whether participants needed to make choices and monitor feedback, the authors demonstr ated (with event related fMRI data) a reciprocal relationship between the RCZ a nd OFC during the evalua tion of the outcome of a choice (See Figure 2-2). The nature of the relationship varied according to whether the action was freely selected by the participant or guide d by the experimenter, with activation increasing in the RCZ and decreasi ng in the OFC when the action was freely selected, and the reverse occurring when the action was selected by the experimenter. As such, the neural mechanisms responsible for movement and appraisal of movement consistently vary according to whether or not the performed movement is selected internally or is forced externally. The issue of how emotion modulates free-will ed versus externally instructed motor actions is attracting a growing interest and has been singled out as a goal of future research across a broad array of disc iplines (Ullsperger & von Cramon, 2004). The goal, however, of eliciting real life quantifiable free-willed movements in response to an emotive cue remains essential to the pr ogression of our understanding of the emotion-movement relationship. SelfVersus Externally-Paced Movements Functional brain imaging data in humans and single cell recordings in monkeys have generally shown preferential involveme nt of the supplementary motor area (SMA) 1 GUESS condition: after a “switch” cu e, participants had both to decide upon an appropriate response and to monitor the resultant feedback to determine which set of response rules was in place. FIXED condition: participants were told always to make a particular fi nger press response on the first trial after the switch cue. Unaware of which response se t was subsequently in place, par ticipants still had to monitor the feedback from the instructed action (w hich was correct on 50% of trials ) and use the information to work out which set to use. INSTRUCTED condition: par ticipants were informed by the switch cue which response set was in place meaning they could switch sets without needing to monitor their responses.

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27 in self-initiated movement (Deiber et al., 1999; Wessel et al., 1997) and strong bilateral activation of lateral premotor areas for exte rnally triggered movements (Catalan et al., 1998; Van Oostende et al., 1997; Wessel et al., 1997). Figure 2-2. Schematic of the tw o frontal regions implicated in monitoring functions. Taken from Nature Neuroscience 7, 1173 1174 (2004). Decision making, performance and outcome monitoring in frontal cortical areas. (Ullsperger & von Cramon, 2004) Identifying the temporal sequalea of th e activating motor areas during specific tasks has been integral to better underst anding the contribution(s) offered by each distinctive portion of the motor cortex. For example, in a delayed cued movement task, Richter et al. (1997) evidenced (via eventrelated fMRI) increased activity within both the SMA and lateral premotor areas during the movement preparation period (delay between a warning and GO signal), while the M1 showed only minimal activation during the preparation period and gr eatest activation during move ment execution. Likewise, during self-paced movements Wildgruber et al (1997) showed that the peak activation within pre-SMA precedes activation within M1 and therefore pre-SMA activity most likely reflects movement preparation.

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28 In related works, Cunnington et al. (2002) used rapid event-related fMRI to investigate the spatial location and relative ti ming of activation for se lf-initiated versus externally triggered finger sequence movements. Each movement condition involved similar strong activation of the pre-SMA, SMA proper, CMAr, and the contralateral M1. Although levels of SMA and CMAr activa tion did not differ significantly between movement conditions, the timing of the hem odynamic response within the pre-SMA was significantly earlier for self-initiated compar ed with externally triggered movements, further confirming the notion that pre-SMA is in volved in early processes associated with the preparation of voluntary movement (Lee et al., 1999; Picard & Strick, 1996). Given the lack of choice concerni ng which movement to make, differences in the cingulate areas are not surprising as the CMA/RCZ has b een associated with making reward driven decisions when a number of po ssible movements are available. The lack of any activity at all in the premotor cortex during either task, however, was reported, and stands as contrary to other evidence collected in the same lab (Cunnington et al., 2002). (Cunnington et al., 2002) offered task variations between th is and other studies as a potential explanation for this finding. Speci fically, in Cunnington et al. (2002) the same movement was always planned and executed; the only varyi ng factor was the internal versus external initiation of the task. As such the sequential nature of the movements required (three alternating finger taps) de manded preparation and/or preprogramming, and given that the movements were similarl y accurate between initiation conditions, the SMA and CMA were clearly capable of preparing, controlling, and executing the necessary movements without assistance from the PMd. Given that performance accuracy was high, it seems that exceptions to the sweep ing generalizations co ncerning internally

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29 (SMA) and externally (PMd) guided movement s exist and are the result of what may seem minor differences in experimental pr otocol. Rather than undermining previous research, therefore, these data highlight how flexible and effective the human motor system is. Summary: Cortical Control of Movement In recent years, the development of new techniques/methodologies has considerably advanced our knowledge of the role the cortex plays in motor control. Indeed, considerable progression has been made in attempting to understand which cortical areas are involved in the numerous discrete processes that precede and then accompany overt movement. M1. The diversity and overlapping nature of the distributed network of neurons within each portion of the M1 permits cortical reorganization; neural plasticity in M1 has been evidenced following extended periods of training (Elbert et al., 1995) or following injury (Donoghue & Sanes, 1988; Sanes & Donoghue, 2000). Although traditionally considered to be exclusively involved in, a nd absolutely essential to the execution of motor tasks, present day evidence concerning activity in the human brain suggests that not only is the M1 active during the prepar atory phase of movement, but also that voluntary movements can be executed directly by secondary brain regions and perhaps also sub-cortically. Nevertheless, the wealth of evidence is su ch that the M1 is primarily involved in motor execution, and specifical ly, in permitting manipulation of distal musculature. SMA. The magnitude and temporal activation of the pre-SMA relative to the SMA proper during a range of tasks are such th at one can be considered as fundamentally different from the other (Picard & Stri ck, 2001). The pre-SMA operates at a more

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30 abstract level and is more closely related to the processing, integr ation, and maintenance of relevant sensory information than res ponse selection or execu tion (Cunnington et al., 2002; Kurata et al., 2000; Lee et al., 1999; Sakai et al., 2000 ). Alternatively, SMA proper activation only occurs during movement-related components of visual or auditory tasks, and appears to be more involved with the pure movement portions of specified tasks (Boecker et al., 1998; Cunnington et al., 2002; Stephan et al., 1995). Functionally and anatomically distinct from the SMA prope r, overt behavioral data coupled with anatomical data suggest that the pre-SMA may be functionally considered as a region of the prefrontal cortex (Picard & Strick, 2001) In conclusion, the two portions of the SMA are such that the pre-SMA and SMA proper combined may well be capable of planning and executing voluntary move ments independent of M1. PMd. Human data has corroborated evidence from animal research suggesting a functional segregation within the premotor cortex (Picard & Strick, 2001). Attention to the short-term storage and processing of visuospa tial information engages the PMdr (Coull & Nobre, 1998; Courtney et al., 1998; Petit et al., 1996; Stern et al., 2000), whereas motor planning, initiation, and execution engage the PMdc (Grafton et al., 1998; Lee et al., 1999; Simon et al., 2002). CMA/RCZ. Human movements are altered via the internal and exte rnal state of the organism (including the emotional state of the organism via amygdala projections). Considered a possible homolog of the CMAr in monkeys (Walton et al., 2004) the human RCZ of the ACd is closely connected to the motor system, and is involved in monitoring self-generated movements and in signaling th e need for immediate changes of behavior (Jenkins et al., 1994; Picard & Strick 1996; Ullsperger & von Cramon, 2004).

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31 Specifically, the CMAr/RCZ plays a key role in choosing the most appropriate action (given internal and external information and the potential of freely choosing a number of alternatives) in an effort to achieve the greatest consequent ial gain from that action. In contrast, the CMAc (CCZ) is primarily involved in the execution of the chosen movement (Isomura et al., 2003; Takada et al ., 2001) thereby aligni ng itself more with the SMA proper and the PMdc. Subcortical Control of Movement Basal Ganglia The basal ganglia (BG) works in concer t with the cortex to orchestrate and execute planned motivated behaviors that re quire motor, cognitive, and limbic circuits (Haber, 2003). Intricately involved in severa l aspects of goal-directed behaviors, BG function bridges the emotion, motivation, cognit ion, and planning processes that lead to movement, as well as performing a critical ro le in the expression of movement (Boecker et al., 1998; Brown & Marsden, 1998; Haber, 200 3). Deficits in motor behavior have been associated and correlated with basal ganglia dysfunc tion (Greenberg, 2002). Although a broad range of processes have si nce been pinned onto the BG [e.g., cognitive sequence planning, Graybiel, ( 1997); learning, Jueptner et al., (1997); habit learning & acquisition of non-motor dispos itions and tendencies, Knowlt on et al., (1996); executive function, Peigneux et al., (2000); and creativit y, Cotterill, (2001)] this review will focus on the specific role that BG has on movement and emotion. The basal ganglia are several groups of nuc lei in each cerebral hemisphere which include the striatum (caudate nucleus, putame n, and ventral striatum) and the pallidum or globus pallidus (see Figure 2-3; internal a nd external segment GPi, GPe, and ventral

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32 pallidum) (Greenberg, 2002). Clos ely related structures include the substantia nigra pars reticulate (SNr), the ventral tegmental area and the subthalamic nucleus (Haber, 2003). Figure 2-3. Motor circuit of the basal ganglia The indirect and direct pathways are presented along, with how the cortex co mmunicates with BG. GPi = internal segment of the globus pallidus; GPe = exte rnal segment of the globus pallidus STN, = subthalamic nucleus; SNr = substantia nigra pars reticularis The striatum is the main target of cortical thalamic, and brainstem input to the basal ganglia. In addition, the ventra l striatum receives input from the limbic regions, including the amygdala and hippocampus (Fudge et al ., 2002), and in addition the CMA/RCZ has been closely linked to the development of re ward-based learning (Hassani et al., 2001). The striatum projects to the GPi and GPe, a nd in turn the GPi projects to the thalamus. The internal section is one of two main output nuclei of th e basal ganglia, along with the SNr, which also outputs to the thalam us (Wichmann & DeLong, 1993). Outputs from these two structures are passed via the thalamus back to the cortex (primarily the SMA, and possibly also to the PM cortex; (B rotchie et al., 1991a, 1991b, 1991c), completing

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33 what is referred to as the “d irect” cortico-basal ganglia pathway. The GPe is connected to the STN, which in turn projects back to the GPi; this connectivity is the “indirect” cortico-basal ganglia pathway (Haber, 2003; Middleton & Strick, 2002). The motor circuit of the BG and its associated direct and indirect pathways are displayed in Figure 2-3. Information cycles from the cortex, to the basal ganglia and thalamus, and back to the cortex again, forming a functional loop that modulates movement. The collective summation of activation/inhibition of these pathways modulates movement. Stimulation of the direct pathway leads to increased inhibition of the GPi, which consequently reduces the inhibitory tone on the thalamus, in turn facilita ting excitation of the cortex and facilitating movement. In contrast, stimulation of the indirect pathway leads to increased inhibition of the GPe, which in tu rn leads to excitation of the STN; this activates the GPi and so increases the inhibiti on of the thalamus and reduces excitation of the motor cortex, inhibiting movement (Lewis et al., 2003). Appropriate balance between these two pathways is essential for typical ev eryday movements; PD, for example, results from a loss of the natural balance within th is motor loop. Specifically, a decrease in dopamine levels results in increased activity in GPi and SNr which prevents inhibition of the thalamus, resulting in under-a ctivation of motor cortical ar eas, as displayed overtly in hypokinesis (Chase et al ., 1998; Haber, 2003). From an input-output analysis, therefor e, the basal ganglia do not appear to generate motions directly; they take input from the cortical and subcortical regions, process this information and then pass it back to the cortex via the thalamus, for execution (Cummings, 1993). Nevertheless, the im portance of an intact BG system is substantiated by the arra y of symptoms that manifest fo llowing damage or disease in the

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34 BG: (1) hypokinesias: impairmen t of initiation, velocity, an d amplitude of movement, increase in muscle tension or hypertonia [e .g., ParkinsonÂ’s Disease; Haber, (2003)]: (2) hyperkinesia: disorganized or excessive movement (e.g., Hun tingtonÂ’s Disease) and, (3) dementias: cognitive and emotional dysfunctions. Varying cortical structures have been offered as key to movement preparation (see above; CMA, pre-SMA, PMCr). Ho wever, preparatory activity has been demonstrated at several other sites outside the cerebral hemi spheres, including the globus pallidus (Turner & Anderson, 1997), the stri atum (Alexander & Crutcher, 1990), and the pallidal-receiving areas of the thalamus (Ande rson et al., 1993). Motor preparation in much the same way as motor execution (S anes & Donoghue, 1997) should therefore be considered a distributed phenomenon not limited to the cerebral cortex (Prut et al., 2001). Given the range of motor dys functions that arise from or are related to BG malfunction (e.g., Parkinson Â’s & HuntingtonÂ’s disease), substantial efforts have sought to determine the exact role that BG play in motor function. Positron emission tomography (PET) studies have reported increased regi onal blood flow prior to voluntary movements not only in the SMA, M1, and ot her cortical areas, but also thalamus, and the BG (Deiber et al., 1996; Deiber et al., 1991; Jahanshahi et al., 1995; Wess el et al., 1997). BG appear to be activated similarly preceding voluntary movements that are internally generated and externally triggered (Cunningt on et al., 2002; Jahanshahi et al., 1995; Jenkins et al., 2000). Corroboration of BG involvement in motor preparation has been echoed by (Paradiso et al., 2004) who repor ted data from scalp and surgically implanted electrodes in the subthalamic nucleus of ParkinsonÂ’s pa tients while they completed wrist extension

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35 movements. Readiness potentials in the subthalamic nucleus were present before contralateral and ipsilateral hand movements. The authors thereby affirmed that in parallel with the cortex, BG circuitry was activated during movement preparation. A more detailed explanation of BG invol vement in movement preparation has been offered by (Nambu, Tokuno, & Takada, 2002) who have associated the initiation, execution, and termination pattern of movement with varyin g BG circuits. Immediately prior to cortically driven movement execution (planning = CMAr, pre-SMA, PMdr; execution = CMAc, SMA proper, PMdc) an acco mpanying signal is sent from SMA and Figure 2-4. The cortico-STN-pallidal “hyperd irect” pathway as proposed by (Nambu et al., 2002). STN = Subthalamic nucleus; GP i – external portio n of the globus pallidus. The additional pathway from the cortex to the STN is the cornerstone of the hyperdirect pathway. M1 to the GPi through a cortico-STN-pallidal “hyperdirect” pathway that comprehensively activates GPi neurons. Cons equently, large areas of the thalamus and cortex related to the selected and competi ng motor program are inhibited (see Figure 24). Next, a second signal is passed via the di rect pathway (see Fi gure 2-3 above) to the GPi to inhibit the specific set of pallidal neurons, dis-inhibiting the pathway between thalamus and cortex; leading to the execution of the selected movement. Finally, a third

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36 signal, passed via the “indirect” pathway (see Figure 2-3) br oadly activates GPi neurons, suppressing their targets and terminating the movement. As such, only the selected motor program is initiated, executed, and terminat ed at the appropriate time, whereas other competing programs in the surrounding area are quashed. Figure 2-5 outlines two BG related systems that account for the phenom ena that voluntary movements are always associated Figure 2-5. Volitional and automatic control of locomotor movements. GABAergic basal ganglia output to the thalamocortical neurons and the brainstem neurons integrate volitional and automatic control processes of movements (Takakusaki et al., 2004). with automatic control processes which ar e performed unconsciously (Grillner & Wallen, 2004). (Hikosaka, Takikawa, & Kawagoe, 2000) propose that BG have two ways to control movements using three output sy stems (direct, indirect, and hyperdirect thalamocortical) to amalgamate the voliti onal control of movement with automatic control processes (e.g. saccade: (Isa, 2002); locomotion: (Grillner & Wallen, 2004) which are controlled via networks in the brainstem and spinal cord (Takakusaki, Saitoh, Harada, & Kashiwayanagi, 2004). BG circ uits, therefore, appear to be essential: 1) during the

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37 preparatory state prio r to movement, suppressing all m ovements, 2) during the execution of movement, allowing only the desired m ovement to be executed, and 3) during movement termination when all movements ar e completed and a resting state is desired. Affective modulations of psychopysiological measures correspond with phases 1 and 2 of this progression and have lead to the form ulation of the defense cascade model. The Defense Cascade Emotions have the capacity to elicit a my riad of varying behavioral responses in human beings. Evolved from primitive circ uits in which a stimulus was typically followed by a response in a very standardized fashion, the human brain has developed the ability to use time That is, humans can permit, suppre ss, accentuate, or abolish overt behavioral responses to emotional cues (L ang et al., 1997). The complex interaction of the neural circuitry that process emotions is such that a si ngle response indicating activation of the appetitive or defensive motiv ational system is not necessarily reflected in a parallel way by all measures (i.e., HR SCR, ERP). Instead as activation levels associated with the eliciting stimulus increa se, a cascade of different response events occur (“defense cascade” see Figure 2-6; (La ng et al., 1997). Specific to activation of defensive circuitry, a three stage sequen ce has been proposed, based on the relative position of predator and pray (Bradley & Lang, 2000; Fanselow, 1994; Lang et al., 1997): pre-encounter, post-encounter, a nd circa-strike. Cir ca-strike refers to defensive actions when threat is proximal. An important issue therefore, is to determine how movements are altered at varying stages through the progression of the defense cascade. That is, will movement be facilitated/deb ilitated monotonically as arousal increases across time,

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38 or will movement be more affected by duration and proximity to valenced cues carrying different affective quality? As evident in Figure 2-6, overt action (i.e ., a defensive response) follows stimulus identification and then a freezing period. Follo wing initial perception, as threat and arousal simultaneously increase, SCR climbs startle potentiation increases reflecting defensive priming (via amygdala to PnC, to be discussed), and then immediately before movement, cardiac acceleration signal s a classic defensive response. Determining how the fundamental structures governing this sequence of events alter the resulting movement should be addressed in future res earch efforts. Once agai n, as is the case in the majority of affective research, little is known beyond the processes that precede “overt action” and consequently li ttle is known concerning how affect modulated movement increases an organis m’s chances of survival (LeDoux, 1998). Considerable advances may be made in move ment rehabilitation if emotional circuitry can serve as a movement facilitator. Figure 2-6. A schematic presentation of the defense response cascade underlying processing of increasingly arousing aversi ve stimuli. The arousal or intensity dimension is viewed here as analogous to a dimension of predator imminence that has been implemented in studies of animal fear. Reproduced from (Lang et al., 1997).

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39 Cross referencing the defense cascade with BG activity, it is possible that the progression from “freezing” to defensive ac tion maybe reflected in BG activation. As noted above, Nambu et al. (2002) suggest that BG control initial inhibition of movement (e.g., freezing) via the hyperdir ect pathway, while a decision is made concerning the most appropriate movement to make (CMA/RCZ), followed by mobilization of the chosen motor action (e.g., defensive response stimulated by an external motiv ationally relevant stimulus) via the direct pathway, followed by final movement termination once the threat has passed. In highly emotive situations the ability to control unnecessary movements, to then execute the most appr opriate movement at the most appropriate time are essential within all movement domains. Further support for converging emoti on and movement systems comes from reports concerning Parkinson’s disease. Give n the typical slowness of movement that often signals PD (Haber, 2003), emotionally ch arged situations have been reported to override bradykinesia and result in patients exhibiting “paradoxical kinesia”; a sudden transient remission of bradykinesia when conf ronted with a life threatening emergency (Zigmond, Stricker, & Berger, 1987 ). It is possible therefore, that intense emotions can result in the intense focusi ng of attention, and thus motiv ation towards completing the necessary movement(s) to ensure survival. The BG, therefore, maybe viewed as an attentional center that can alter the flow of information from sensory input to motor output, and in turn, simultaneously suppress and permit specific movements according to situations (Brown & Marsden, 1998). To re-iterate, it seems that without directly deciding, planning, or executing movement s, the BG has enormous influence on which movement, from a number of potentia l options, is amplified and executed,

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40 and which movement(s) are inhibited to al low the primary movement(s) to execute without interference. Such reports that intertwine the largely independent research lines of emotion and movement beautifully ex emplify the benefit of multi-disciplinary research, and serve as motivation to further investigate the complex relationship between emotion and movement. Focus will now turn to how emotionally rich information reaches the BG. Basal Ganglia and Emotion The nucleus acccumbens is a dominant part of the ventral striatum and is the leading sub-cortical candidate for the hub th at integrates emotion, motivation, and cognition with action (Greenberg, 2002) Divided into two principal parts, the nucleus accumbens is composed of a central core that is associated with the extrapyramidal motor system, and a peripheral she ll that links with the limbic system (Sturm et al., 2003). Receiving input from the hippocampus and the amygdala (Maclean, 1990) and projecting onto the ventral pallidum, substantia nigra, thalamus, and cingulate cortex, the nucleus accumbens is ideally located to serve as th e key limbic-motor interface (Sturm et al., 2003). (Graybiel, 1997) echoed th e importance of the such a hub, stating that the “…limbic basal ganglia system has a key func tion in translating action plans related to drive states and homeostatic contro l into action repertoires” (p. 460). It seems appropriate, therefore, to ask whether pro cesses within the NA translate fear into defensive action or positive af fect into approach behavior? Stimulation of different areas in the basa l forebrain can evoke different types of goal directed behaviors (Grillner, Geor gopoulos, & Jordan, 1997); see Biphasic Theory section). An important component of these mo tivated behaviors concerns the direction of

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41 the resulting movements; movements that wi ll transport an organism towards or away from a given situation/cue depending on the va lence of the stimuli (G rillner et al., 1997). Figure 2-7. Possible neuronal mechanisms of integration of voliti onal, emotional and automatic control of motor behaviors. One underlying issue concerns whether such movement patterns are executed with similar vigor; that is, are approach beh aviors executed with the same speed and force as defensive behaviors? Are attack be haviors executed as quickly, forcefully, and accurately as escape behaviors? If emotion primes movement, do movements vary according to valence, to arousal, or to a combination of each? The concept of emotions serving as action dispositions continues to gain support. de Gelder and colleagues (de Gelder, Snyde r, Greve, Gerard, & Hadjikhani, 2004), for example, exposed participants to affective images while simultaneously recording fMRI activity. Along with amygdala and visual cort ex activity, activity was also reported in the RCZ as well as the nucleus accumbens. The burning question therefore is: exactly what role, and to what extent do emotions alter the probability of specific action dispositions leading to the ex ecution of specific behaviors?

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42 Traditionally the dopamine (DA) systems in the nucleus accumbens were thought to directly mediate the rewarding or prim ary motivational characteristics of natural stimuli such as food, water, and sex (S alamone, Correa, Mingote, & Weber, 2003; Salamone, Correa, Mingote, & Weber, 2005; Salamone, Wisniecki, Carlson, & Correa, 2001). In terms of the link between emotion and action, however, rath er than attenuating the primary motivation for natural reward s such as food, obstructing DA transmission within the NA disturbs the in clination of animals to enga ge in effortful responding to obtain food. That is, rats with accumbens DA depletions remain directed towards the acquisition and consumption of food. When not securing the food, however, the rats display a less vigorous, more cautious set of be haviors (Cardinal, Penn icott, Sugathapala, Robbins, & Everitt, 2001; Correa, Carlson, Wi sniecki, & Salamone, 2002; Salamone et al., 2003; Salamone et al., 2001). DA systems in the nucleus accumbens, therefore, appear to be critically involved in acti vational aspects of motivation, and a key modulator of response speed, vigor, and pers istence in directed behavior; functions that enable organisms to exert effort in reward-seeking behavior (Salamone et al., 2005). Analogous to a gate, filter, or amplifier, the NA can be promoted to the role previously given to the BG in general; that of altering emotion related information as it travels from various cortical or limbic areas on its way to motor areas of the brain (Everitt et al., 1999). An active NA, th erefore, is thought to encode information related to the predictive value of environmental stimuli and the specific behaviors required to respond to them (Nicola, Yun, Wakabayashi, & Fields, 2004). That is, accumbens DA is necessary for modulating the electrophysiolo gical and the behavioral responses to environmental cues (Yun, Wakabaya shi, Fields, & Nicola, 2004).

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43 In summary, although the role of the NA is becoming clearer in the rat brain, study of NA activity in the human brain has continued to follow psychopathologies, with the motor components taking a subsidiary ro le. If indeed the NA acts as a hub between the emotional limbic system and the motor system, it is of paramount importance to investigate how the NA may be us ed to facilitate movement. Brainstem Reticular Formation Extending into the spinal cord and diencephalons, the reticular formation refers to a region of neural tissue in the brainstem (medulla, pons, and midbrain) consisting of small areas of gray matter among fibers of white matter (Tortora & Grabowski, 2003). Traditionally the reticulospinal system (reticular formation, reticulospinal tract) has been charged with modulating automatic movements including the initiati on and regulation of locomotion (Matsuyama & Drew, 2000a, 2000b; Matsuyama et al., 2004), postural control, vestibular reactions (Bolton et al., 1992; Matsuyama & Drew, 2000a, 2000b), and head movements that permit gaze cont rol (Cowie & Robinson, 1994; Cowie, Smith, & Robinson, 1994). Without disputing the seve re impairment of postural control that results from lesioned reticulosp inal fibers, such lesions also manifest behaviorally in the impairment of gross limb movements (Lawrence & Kuypers, 1968). More recently, the reticular formation (m edial pontomedullary reticular formation (mPMRF)) has been associated with the preparation and performance of voluntary movements. Specifically, Buford & Davi dson (2004) published single neuron data collected from the mPMRF of monkeys while performing a two-dimensional reaching task that included an instructed delay interv al based on a color code d visuospatial cue. Monkeys were positioned in a primate chai r which limited postural movements, thus allowing cells involved in preparatory activity to be distinguished fr om those involved in

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44 movement-related activity. Give n that preparatory areas of the secondary and cingulated motor cortex (Pre-SMA, PMdr, CMAr) projec t to the reticulospinal system (Keizer & Kuypers, 1989) the authors sought to determine whether or not cells within the reticular formation may be sensitive to movement pr eparation. The authors reported that of the 176 neurons with movement-related activit y, 109 (62%) displayed pure-movement activity and 67 (38%) exhibited both prepar atory and movement activity. Although lower than ratios reported in SMA, PMd, and CM Ad (Alexander & Crutcher, 1990; Backus, Ye, Russo, & Crutcher, 2001), th ese data suggest that the reticular formation houses cells that are sensitive to the planning of upper limb reaching movements, and as such, the reticular formation may prove to be an alternative pathway for the voluntary control of gross movement. Given that subcortical regi ons maybe involved in moto r planning, applying this knowledge to situations where planning regions of the cortex have been damaged (i.e., stroke) holds considerable promise. However, consistently activating cells in the reticular formation that are sensitive to preparing movements with a view to strengthening their ability to compensate for damaged cortical regions, remains unknown. Further, activating cells in the reticular forma tion may be reliant on desce nding signals from the cortex. Furthermore, spatially cued, temporally spec ific planned movements originating in the reticular formation seem unlikely given the myriad of processes preceding movement preparation (e.g., stimulus per ception/interpretation, rule learning). Overt displays of planned movement in decerebreated primates would clarify whether activation of the reticular formation can compensate for damaged cortical regions.

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45 Summary: The Motor System The cortical and subcortical structures that elegantly interact to produce motor function are complex, flexible, and comprehens ively integrated. Rega rdless of its novelty and complexity, the planning, initiation, and ex ecution of a motor task appears to be a distributed process, requiring co rtical, subcortical and intact spinal tracts if appropriate motor actions are to be realized. Identifyi ng hubs within the motor system where emotion may potentially impact this complex network offers a tremendously fascinating task for movement scientists. The cingulated motor areas, and the nucleus accumbens have emerged as two potential candidates. With th is in mind, the following section offers a synopsis of the emotional system, with an empha sis placed on the structures that interact with motor areas. Emotion Emotion is a mental state that arises subjectively, via activation of primitive circuits that have been conserved throughout mammalian evolution (LeDoux, 2000) rather than through conscious effort. Emo tions are often accompanied by physiological changes. Emotions, therefore, are held to be functional products of Darwinian evolution, developed from primitive actions that facilitated the continued survival of living organisms. Echoing this basic premis e, hman, Hamm, & Hugdahl (p. 538, 2000) eloquently state: Evolution has primed organisms to be responsive to stimuli that more or less directly relate to the overall task of promoting ones genes to prosper in subsequent generationsÂ…. Stimuli of thes e types are embedded within emotional systems that help regulate behavior within critical functional domains Emotion-related behavioral and psychophysiolo gical data have been interpreted as reflecting approach/avoidance behaviors (Chen & Bargh, 1999; Duckworth, Bargh,

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46 Garcia, & Chaiken, 2002; Hillman et al., 2004). Interpretations of self-report data have resulted in the suggestion that many discre te emotions exist, ranging from sadness, happiness, loss, and guilt (Lazarus, 2000). Imag ing data continues to map the cortical and subcortical neural circuitry of the emotional system including these discrete states. Identifying the time course and physiological ma p of the startle reflex provides a fine example of the emotion-related successes ga rnered from animal research (Davis, Gendelman, Tischler, & Gendelman, 1982; Davi s, Parisi, Gendelman, Tischler, & Kehne, 1982, to be discussed). Suffice to say, the emoti on system is investigated with a divergent array of methodologies. Systems impacted via emotion are wide ranging, both in terms of when and how the system is altered. That is, following ons et of an emotional cue, demonstration of affective modulation occurs at varying tim es according to the measure being used; affective modulation of the startle blink response occurs 500msec following exposure; Skin conductance responses are altered according to arousal level, and can be illustrated physiologically 1-2 sec follo wing initial exposure (Coombe s, Janelle, & Duley, 2005); Affective modulation in heart rate response is visible 1500msec post emotional cue onset (Lang, Greenwald, Bradley, & Hamm, 1993). As such, depending on which branch of the sympathetic NS is being monitored, the time frame within which emotion driven changes will occur varies. In line with active lines of resear ch concerning the temporal characteristics of emotion modulated P3 responses, HR, and SCR (Schupp, Junghofer, Weike, & Hamm, 2003a; 2003b), quantifying the emotiona l modulation of overt voluntary motor function across time is a promising avenue for future research (Coombes et al., 2005). Further, the robustness and valid ity of the Biphasic theory of

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47 emotion lends itself well to the study of such phenomena (e.g., Coombes et al., 2005; Hillman et al., 2004). Biphasic Theory of Emotion Biphasic theory (Lang et al., 1990; Lang et al., 1997; Lang, Br adley, & Cuthbert, 1998a, 1998b) posits that the broad array of emotions experienced and displayed by human beings can be organized according to valence (i.e., appetitive or defensive) and intensity (i.e., arousal level). When engage d, each system (appetitive, defensive) impacts the functioning brain (including motor circ uits), priming specific representations, associations, and action programs that co rrespond to the immediate environmental context. Hence, while not actions in th emselves (Lang et al., 1997), emotions do influence action and typically emerge in circum stances where adaptive control is required (Ekman & Davidson, 1994). Thus, when conceptualizing affects as motivationally tuned states of readiness (Lang et al., 1998b), Schupp and colleagues propose that a key function of emotion is the preparation for action (Schupp et al., 2003a). In addition to valence and arousal, motor activati on has also been noted as a third factor particularly helpful in describing primar y emotions (Heilman & Gilmore, 1998). One commonly used measure that provides an inde x of the modulatory impact of emotion on involuntary motor function is the startle blink response. Emotional Circuitry The limbic system The limbic system concept, an anatomical abstraction for an arched shape group of structures, first emerged in the mid 1950Â’s (Maclean, 1949, 1952), and since its inception has been synonymous with efforts to explain and understand human emotion. The roots of a limbic system are grounded in an evolutionary explanation of mind and

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48 behavior (Isaacson, 1982; Maclea n, 1952, 1954, 1955a, 1955b, 1972). Sometimes referred to as the ancient, archicortex or pr imordial cortex (as opposed to the cerebral cortex that is referred to as the neocortex or new cortex) the limbic region is located on the medial border of th e cerebral hemispheres. The neocortex, found only in mammals, ha s been associated with thinking, reasoning, problem solving, and memory, leaving hunger, thirst, and other primitive internal urges to be attribut ed to the ancient cortex whic h is found in all vertebrates (LeDoux, 2000; Panksepp, 2003). As such, i ndependent anatomical regions were traditionally paired with corresponding inde pendent processes; emotion and cognition (Maclean, 1952, 1955a, 1955b). Scoville & Miln er (1957), however, reported that damage to a central structure in the limbic system -the hippocam pushad a debilitating effect on long-term memory rather than on emotional processes. In consequence, the polarization of separate systems for cogniti on and emotion began, which in turn brought into question components of, and hence, the existence of th e limbic system. Caution, therefore, should be exercise d when associating the limbic system exclusively with emotion. Indeed, with th e fear system often bypassing the hippocampus, LeDoux (2000) suggests that a “limbic system” grounded in tradition rather than data, is a flawed and inadequate account of the emo tional brain, and provides no more than an “…off-the-shelf explanation of how the br ain works” (p.159). Aside from issues concerning its authenticity, for those who s upport the limbic system account of emotion, widespread agreement has yet to be reached concerning exactly which nuclei compose the limbic system (Patterson & Schmidt, 2003). For example, given the abundant two-

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49 way connections between limbic structures and the hypothalamus and thalamus, some have included these later structures within the limbic system (Andreassi, 2000). Nevertheless, widespread use of the term “limbic system” has permitted the concept to remain prominent in contemporary discourse, with credible support for such a system continuing undiminished (Panksepp, 2003). Revisiting the vertebrate/mammal brain distinction, Panksepp (2003) retains and supports the notion that emotional responses, including their intrinsi c affective attributes, most likely emerge from "limbic" regions that are more evolutionarily conser ved in vertebrates than those that mediate cognitive capacities (Maclea n, 1990). Resolving the issue concerning whether or not a “limbic system” exists is not the focus of this discourse, and hence, whether considered to be, or not to be, components of the limbic system the following section outlines the amygdala and the periacqueductal central grey gi ven the integral role they play in the physiological and behavioral manifestations of emotion. Amygdala The amygdala is a nuclear complex in th e forebrain, positioned in the anterior medial section of the temporal lobe consis ting of about ten distinct nuclei that are grouped into four regions: baso lateral, lateral, central, and basomedial. The amygdala receives highly processed sensory input from the neocortex and hippocampus via the lateral and basolateral nuclei; in turn thes e nuclei project to the central nucleus which then project (via the stria terminalis) to a variety of hypothalamic sites, the nucleus accumbens (Graybiel, 1997; Maclean, 1990) and periaqueductal gray (Fendt & Fanselow, 1999), the cingulated motor areas (Morecr aft & Van Hoesen, 1998; Vogt & Pandya, 1987), as well as the PnC (Davis, Gendelman, Tischler, & Gendelma n, 1982; Lang et al.,

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50 1990). These functional links collectively mediate the manifestation of emotion modulated voluntary and involuntary movements. Potentiation of the startle blink reflex according to emotional context provides evidence of how emotion alters the execution of involuntary mo tor action; the rostral part of the medial subdivision of the central nuc leus of the amygdala contains cells that project to the PnC, a nucleus in the acousti c startle circuit [Rosen, Hitchcock, Sananes, Miserendino, & Davis, (1991); emotion and star tle to be discussed later]. In a similar fashion, the amygdala projects directly and indirectly to the nucleus accumbens and CMA respectively, altering volunt ary movements according to an organismÂ’s affective context and the consequences of varying acti ons within that affective context. The amygdala is involved in complex cognitive and behavioral functions, and serves to process somatic states that emerge from primary unconditional or learned inducers (Bechara, Damasio, & Damasio, 2003). LeDoux defines the amygdala as a cent er for emotional evaluation (LeDoux, 1994, 2003; LeDoux, Cicchetti, Xagoraris, & Roma nski, 1990), specifically involved in the detection and manifestation of fear. In addition to reports that continue to support the essential role of the amygdala in the f ear system, this association should not be considered unilateral. Indeed, when exposed to affective content, fMRI data have, in addition to coupling amygdala activation with fear, also associated the processing of positively valenced stimuli with sign ificant amygdala activity (e.g., Garavan, Pendergrass, Ross, Stein, & Risinger, 2001). Conflicting data exist, however, concerning the link between amygdala activation and pleas ant stimuli. For example, fMRI data reported by (de Gelder et al., 2004) indicat ed significant amygdala activation during

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51 exposure to unpleasant/fearful im ages relative to neutral im ages, but not during exposure to pleasant as compared to neutral images. It is interesting to note though, that de Gelder et al. did not report a direct statistical comparison between activation patterns during exposure to unpleasant a nd pleasant stimuli. The amygdala has a dual sensory input system. Information is taken in via sensory channels and is streamed to the thalamus, at which point th e inputs diverge; one pathway leads directly to the amygdala (fast channel) while the other projects to the cortex (slow channel). Providing the amygdala with raw se nsory threat-related in formation via this specialized fast channel circuit may offer distin ct advantages in the interest of promoting survival. (LeDoux, 1995) has described this fast channel route as a “quick and dirty” subcortical pathway that allows for very ra pid, but crude, analysis of stimulus features from the incoming visual stream (LeDoux, 1995, 1996; Shi & Davis, 2001). This route, involves direct thalamo-amygdala pathways al lowing for a cursory but rapid analysis of visual objects passing from the retina into the fear centers of th e brain. The alternate ascending route to the cortex permits acute pro cessing of the sensory input to determine if the sensory input is real, perceived, danger ous, or harmless. Although delayed, the result of this more comprehensive cortical evaluation of sensory stimuli is projected back to the amaygdala, reinforcing or suppres sing initial amygda la activity. Although not actions themselves, emotions may be considered action dispositions, and while it is clear that th e amygdala are central in the in terpretation and evaluation of emotion, it is the efferent amygdala projecti ons that result in th e covert and overt consequences of an experienced em otion. Indeed, lesions of the central nucleus of the amygdala block all conditional fear responses including behavioral, autonomic,

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52 cardiovascular, and hormonal responses, whereas lesions of the pariacqueductal gray (PAG) block only the automated behavioral responses to fear (LeDoux, 1996). It is believed, therefore, that the central nucleus of the amygdala may be the final common pathway of conditional fear responses and that its effe rent targets, including the PAG, mediate specific automated responses (see BG and CMA section above for information concerning emotion and voluntary movement). Specifically, circastrike attack (overt defensive action) is not initiated by direct stimulation of the central nucleus of the amygdala (De Oca, DeCola, Maren, & Fanselow, 1998). In consequence, to understand the chain reaction that begins with activa tion of emotional circuitry and leads to involuntary overt movement, attention must turn to the periacqueductal gray. Periacqueductal central grey The periaqueductal grey (PAG) is a larg e structure in the midbrain (surrounding the aqueduct of silvus) thought to be involve d in two contrary patterns of defensive action, one related to freezing, in which ongoing behavior is halted leading to complete immobility except for that required for br eathing (De Oca et al., 1998), and another related to escape res ponses (Vianna, Graeff, Landeira -Fernandez, & Brandao, 2001). The PAG receives afferents from the amygdala, nuc leus stria terminalis, dorsal hypothalamus, midline thalamus, periventricular grey and the dorsolateral and ventrolateral midbrain tegmentum. In turn, the majority of effere nt fibers leaving the PAG terminate in the reticular formation, parabrachial nuclei, trigeminal motor nucleus, and nucleus ambiguous. With regard to defensive freezing, evidence suggests that such behaviors are modulated by afferent projections that the ventral PAG (vPAG) receives from forebrain structures, especially from the amygdala (Bandler & Shipley, 1994; Carrive, 1993;

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53 Fanselow, 1991; Fendt & Fanselow, 1999), whil e the dorsal portion of the PAG (dPAG) appears to mediate both active a nd inhibitory behavioral patter ns of defensive responses. Figure 2-8. Rats with lesions of the dPAG or the vPAG in comparison with shamlesioned rats showed enhanced or d ecreased levels of freezing, respectively, when presented with a cat. A dpated from (De Oca et al., 1998) In rats, lesions of the dPAG enhanced conditioned freezing (De Oca et al., 1998) and reduced escape reactions to electrical footshock (Fanselow, 1991). Alternatively, stimulating the dPAG by increasing current in a stepwise fashion elicits a freezing response followed by vigorous escape reac tions (Coimbra & Brandao, 1993; Schenberg, Costa, Borges, & Castro, 1990). Vigorous es cape reactions are not elicited by direct stimulation of the central nucleus of the amygdala. Indeed, stimulation of the lateral and central nucleus of the amygdala produces long-lasting, opioid-mediated inhibition of the affective defensive response elicited by dPAG stimul ation in the cat (Shaikh, Lu, & Siegel, 1991a, 1991b). Importantly, this in hibition is selective to defensive behavior; circling behavior (in cats) el icited by dPAG stimulation was unaffected by amygdala stimulation. Thus, it may be necessary for the amygdala to be inhibited in order to engage in active defensive behaviors.

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54 Figure 2-9. Linking the Amygdala, reticular fo rmation, and the Periacqueductal Central Grey in a functional circ uit that interact to m odulate the overt involuntary behavioral manifestation of emotion. Anatomical connections betw een the vPAG, dPAG, and the amygdala maybe key to the inhibition of a freezing response (see Fi gure 2-9). Specifically, activation of the dPAG may briefly inhibit the amygdala and vPAG to interfer e with the processing of incoming sensory information, while also permitti ng active defensive behaviors. Specifically, Walker & Davis (1997) suggest that an active dPAG inhibits presynaptic amygdalar inputs to the PnC, a critical component in the execution of reflexive and voluntary motor function (to be discussed), in dicating an involvement of the dPAG in the transition from freezing to defensive movements as threat levels increase. Concerning the interconnectivity of the vent ral and dorsal portions of the PAG, freezing and escape responses induced by dPAG stimulation do not depend on the integrity of the vPAG (Vianna et al., 2001), so whereas initial stim ulation of the dPAG leads to an initial freezing behavior, continued stimulation inhi bits amygdala and vPAG, leading to active

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55 defensive behaviors. The vPAG, alternatively, is specifically involve d in post encounter conditioned freezing response. The majority of efferent fibers leaving the PAG terminate in the PnC (in addition to the parabrachial nuclei, trigeminal motor nucleus, and nucleus ambiguous), likewise, coupled with amygdala afferents that also terminate in the PnC, the inhibition/activation triumvir ate pathway patterns between PAG, amygdala, and PnC all contribute to the execution of overt emotionally driven behaviors. (Ratner, 1967) proposed a description of defensive response topography that varied as a function of the distance between predator and pr ey. Defensive behaviors varied between freezing, flight, fight, and tonic immobility as the predatory distance decreased. Tonic immobility is a prone, immobile position elicited in wild prey animals thought to inhibit further attack by removing movement as an attack-eliciting cu e (Sargeant & Eberhard t, 1975). Drawing on the evolutionary stra ins of Biphasic theory and the de fense cascade (see above), when assessing the rate of approach of thre at, a freeze-attack/escape-freeze may be the appropriate dynamic sequalea for the con tinued survival of living organisms. Specifically, when faced with threat, forebrain activity mediating freezing leads to immobility as the animal freezes (activat ion of the sympathetic nervous system: decreased HR, increased SCR), then as the threat draws n earer and physical contact is made between predator and prey, the defensive needs of the animal may be best served by complete midbrain control and activation of circ astrike behaviors (inhibition of vPAG and amygdala, activation of dPAG ). Safe from the threat of direct physical attack, forebrain activity (reduction in ac tivation of dPAG with a s imultaneous activation of vPAG and amygdala) mediates the return to immobility and a second freezing response that continues until safety is restored (S argeant & Eberhardt, 1975). When the situation

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56 alters to become non-threatening, homeosta sis is realized via activation of the parasympathetic system. The parasympathetic system returns the body back to a relaxed state, culminating in the resumption of pr eferred activity within a safe environment (Fanselow, Lester, & Helmstetter, 1988). Acoustic Startle and Movement Startle Circuit The acoustic startle reflex is a shortlatency behavior elicited by a sudden and intense acoustic stimulus. Considered a primitive defensive reflex, the acoustic startle serves as an interrupt of ongoing behavior (Lang et al., 1990 ). The subcortical neural circuitry of the startle reflex has been mapped via techniques that focus on specific nuclei in an effort to either eliminate (electrolyti c lesion) or illicit (s ingle pulse electrical stimulation) a startle response. Given the temporal characteristics of the ac oustic startle (8ms in rats, from startle to EMG activity) Davis and colleagues (Davis et al., 1982a; Davis et al., 1982b) initially mapped what was then considered a simple pa thway through four synapses, three in the brainstem (ventral cochlear nucleus; an area me dial and ventral to th e ventral nucleus of the lateral lemniscus; nucleus reticularis pontis caudalis [PnC]) and one synapse onto motorneurons in the spinal cord. However in the intervening years since this 4-synapse route was evidenced, re-evaluation (e.g., Lee et al., 1996) has suggest ed that cochlear root neurons proceed directly too, and then te rminate in the PnC. Accordingly, given that cochlear root neurons terminate onto reflex crit ical PnC cells that in turn project to motor neurons in the spinal cord (Lingenhohl & Fr iauf, 1994) the previously identified synapse at the lemniscus is now bypassed (Lee et al., 1996). In summary, the chain of probable activation of the primary acoustic startle reflex is generally consider ed to consist of 3

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57 rather than 4 synapses: (1) cochlear root neurons; (2) PnC neurons; and (3) motor neurons in the spinal cord (Lang et al., 2000; Lee et al., 1996). Having established the central components of startle circuitry in animals (Davis et al., 1982a; Davis et al., 1982b), more recent effort s have sought to decipher the transient variables that contribute to, and the overt be havioral repercussions of, the human startle reflex (Lang et al., 1990). In human subjects, early research concerning startle elicited defensive movements identified a generalized bodily reflex following exposure to a gun shot (Landis & Hunt, 1939). Contemporary startl e research, however, typically centers on neuroelectric activity (ERP) a nd/or electromyographic (EMG) indices of eye blink, neck, shoulder, trunk, and/ or leg flexion. Figure 2-10. The primary acoustic startle reflex is generally consider ed to consist of 3 synapses: (1) cochlear ro ot neurons; (2) PnC neurons; and (3) motor neurons in the spinal cord Due to its sensitivity and slow habitu ation rate, the eye-blink has captured considerable attention. For example, guided by the biphasic theory of emotion, Hillman and colleagues (Hillman, Hsiao-Wecksler & Rosengren, 2005), reported a positive association between the eye-bl ink reflex and postural reactio ns to an acoustic startle. Likewise, in addition to home ostatic reflexive motor functions, a similar paradigm has

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58 been used in a number of laboratories worl dwide to study the impact of active startle circuitry on voluntary motor function (e.g., Ca rlsen, Chua, Inglis, Sanderson, & Franks, 2003; Carlsen et al., 2004a, 2004b; Carlse n, Hunt, Inglis, Sanderson, & Chua, 2003; Valls-Sol et al., 1999; Va lls-Sol et al., 1995). Acoustic Startle and Involuntary Movement Hillman and colleagues (Hillman et al ., 2005), reported evidence concerning the impact of an acoustic startle on blink magnitude and postural sway, permitting conclusions concerning the association between the magnitude and latency of the startle blink, with the magnitude and latency of whole body postural moveme nts. Specifically, Hillman et al. required participants to stand passively on a force platform. Postural adjustments (measured by changes in center of foot pressure) and the eye blink reflex were time-locked to the presentation of an acoustic startle (96dB). Relative to a baseline condition, beginning approximately 100 ms follo wing the acoustic star tle, participants displayed an initial anterior movement followed by a posterior movement. A positive association was reported between blink magn itude and the amount of movement in the posterior direction only. The authors postulate that the acous tic startle probe triggered a defensive reaction, and the resulting anterior -posterior response was an overt sign of postural flexion, an evolutionary reaction promoting survival (Hillman et al., 2005). The notion that an acoustic startle elic its involuntary movement is an often validated phenomena specifically in terms of the blink reflex. Startle and movement literature, however, has developed this rela tionship to include voluntary movement also. The following section will de tail the growing body of literature concerning acoustic startle initiated voluntary movements.

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59 Acoustic Startle and Voluntary Movement Dependent on uniqueness and complexity, varying cortical an d subcortical areas of the brain have been charged with planning, executing, and controlling movement. Evidence indicates however, that once a move ment has been planned, movement maybe initiated and completed significantly faster when an unexpected acoustic startle (approx 124dB) replaces or accompanies a visual GO sign al (Valls-Sol et al., 1995). Valls-Sol and colleagues (1995) implemented a simple RT task requiring participants to respond to a visual GO signal. A visual warning signa l (5 seconds before the GO signal) readied participants to the imminent GO signal. Howe ver, during a portion of the experimental trials, an unexpected acoustic startle (est imated at 150dB) was delivered at fixed time intervals of 0, 25, 50, 75, 100 and 150 ms followi ng the visual GO signal. For interval durations between 0-75 ms post the GO signal, th e acoustic startle resulted in faster premotor and motor time, as well as faster task completion. Pre-motor, motor, and task completion time increased monotonically as the time between the GO signal and the startle increased. Acoustic startles were also presented preceding the GO signal, and although the net result was movement initiati on, the recorded RT was not as short as trials in which the startle stimulus unexpected ly accompanied the visual GO signal. These early reports suggest that pair ing or replacing the GO signal w ith an acoustic startle leads to faster PMT, MT, and overall task completion. Given that voluntary movement was the fo cus of the Valls-Sol (1995) paper and is the focus of this review, the factors that composed the speeded response deserve attention. To determine whet her the EMG signal underlying startle speeded RTs were similar to normal RTs, Valls-Sol et al. ( 1999) modified their 1995 protocol to include task related EMG activity and a second simple RT task. Two similar experiments were

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60 reported, the only difference between them bei ng the required behavioral response to the GO signal (wrist flexion/extens ion or stand on tiptoe). As in the 1995 paper, a warning signal preceded a 5 second silence, leading to a visual GO signal that was presented alone or accompanied by a 130dB acoustic startle. Results corroborated previous findings (Valls-Sol et al., 1995) indica ting that regardless of the response (wrist, tiptoe), the acoustic startle sped up the execution of the voluntary movement. However, the comparison made between EMG patterning of movement with and without the startle indicated that although a time shift was observed, as far as muscle activation was concerned, the patterning was near identical. Hence, the voluntary reaction was driven at the speed of a startle rea ction while maintaining the ch aracteristics of the motor program In light of identical EMG patterns be tween conditions, the authors concluded that faster reaction times were the conseque nce of a rapid initia tion of the movement pattern rather than an early startle refl ex coupled with a later voluntary response. Therefore, having established a similarity between the EMG patterning of startle and non-startle triggered movements, what and where is the mechanism driving the facilitation of the pre-EMG phase of st artle initiated prep lanned movements? When the subject is prepared to react, th e excitability of the motor pathway to the muscles involved in the planned reaction may be facilitated. As such Valls-Sol et al. (1999) suggested that because the startle and GO signals were in different modalities, the acoustic startle stimulus may not have been promoted into the thalamo-cortical sensory motor system, but rather, could have been in tegrated into the bulba r reticular formation. Coupled with a reduced threshold in the moto r system, the startle may have triggered the motor system at a level further downstream from where the visual GO would normally

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61 initiate the same movement. The reticu lar formation, where the startle response originates, logically becomes one potential candidate. Consequently, something akin to a motor program maybe stored in brainstem and spinal centers, allowing the program to be triggered (via startle) independently of the usual descending GO command from the motor cortex. The issue of subcortical initiated m ovement remains an interesting one, although to date, the mechanisms that p ermit an acoustic st artle to initiate subcortically stored voluntary movement have not been directly tested and are therefore unknown. In a series of related follow up studies Carlsen and colleagues (Carlsen et al., 2004a, 2004b; Carlsen, Nagelkerke Garry, Hodges, & Franks, 2000) have replicated and extended the findings of Valls-Sol et al. (Va lls-Sol et al., 1999; Va lls-Sol et al., 1995). Although the major premise of Valls-Sol et al.Â’ s work has not been significantly altered, a number of papers provide EMG, kinematic, si mple and choice RT evidence that further validate a startle elicited speeded RT. One potential explanation of the startle elicited speeded RT is that the startle may increase neural excitability, decrease motor system neural thresholds, summating to voluntary movement with shorter PMT. Accordingly, any movement that is elicited via an acous tic startle should be characterized by shorter PMTÂ’s. To address this issue (Carlsen et al., 2004a) modified the Valls-Sol protocol, adding two and four choice RT tasks to the simp le RT task. Participants heard a warning signal, followed by a short pause, and then at th e onset of a visual targ et were required to extend or flex the wrist to move a lever (rep resented by a cursor on a viewing screen) to reposition the cursor on the ta rget (also visible on view ing screen) as quickly and

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62 accurately as possible. On set of the target was randomly accompanied by a 127dB acoustic startle, with potential target locat ions varying between 1, 2, and 4 potential positions within each trial block, respectively. Again, if facilitated PMT were the result of neural excitability, then during each trial block, PMT for target plus startle trials should be faster than target alone trials. This, however, was not the case. As the number of potential targets increased (1, 2, 4) PMT increased, however, only simple PMTs were facilitated during startle compared to non st artle trials, with no differences emerging between control and startle conditions for either the 2 or 4 choice RT tasks (Carlsen et al., 2004b). The authors proposed that the cortical processes of response selection inherent in a choice reaction time task barred a preplann ed motor program from being formulated and stored, and subsequently in itiated subcortically. In conseq uence, Carlsen et al. argued that cortically initiated movements, relati ve to subcortical init iated movement, take considerably longer to materialize. However, these data simply suggest that a preplanned movement will be initiated faster if in itiation is accompanied by a startle. Speculating from these data, that a prepla nned movement cannot be initiated from the cortex so rapidly should be treated with considerable caution. Realistically, PMTÂ’s of a preplanned cortically stored motor program cannot be inferred from performance on a choice reaction time task because the PMT dur ing a CRT task involves response selection and movement execution rather than just movement execution. The second argument offered by the authors to support the subcortica l initiation of SRTÂ’s was that some PMTÂ’s < 60ms. Fixed amounts of time are require d for sensory transduction and neural conduction to the cortex, and for neural conduct ion from the cortex to the arm. The first volley of neural activity caused by acoustic s timuli takes 35 ms to reach the auditory

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63 cortex (Erwin & Buchwald, 1986). In turn, th e time it takes for the motor cortex to communicate with the arm is 20-25 ms (Jones, Calancie, Hall, & Bawa, 1996; Valls-Sol et al., 1999), suggesting a comb ined total of 60 ms. Given th at Carlsen et al. reported average times of 80ms for th e startle initiated SRT condition, they infer that the 20ms differential (80 – 35 – 25 = 20) is not adequate for the necessary cortical processing that is required for cortical initiated movement. Further, given that onl y three startle trials were included within each response category, va riability and inherent error must be taken into account. For example, when discussing issues on the scale of milliseconds across a small number of trials, one must be certa in that (among other technical issues) the acoustic stimulus is recorded in the physiologi cal trace at the exact po int the stimulus was actually presented. Erro r in the range of + 10ms per trial will have considerable consequences. Methodological issues are al so noted regarding the in clusion/exclusion criteria concerning participants; from the 20 particip ants tested, 2 did not display a startle response [as indexed by activity in the sterno cleidomastiod (SCM) mu scle, Carlsen et al., (2003a); Carlsen et al., (2003b)] and 4 failed to show decreased RTs during startle trials. All 6 participants were removed from analysis Although Carlsen et al were specifically interested in participants who showed fac ilitated RTs due to the presence of a startle response, it is perhaps no surprise that st artle and control initiated movements were statistically differentiated, gi ven that participants who did not display faster PMTs, although demonstrating a startl e response, were removed from the analysis. One must ask: Is it ethical to remove participants wh o did not show rapid startle initiated

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64 movements relative to a control tone, a nd then go onto conclude that startle initiation of a preplanned moveme nt results in speeded PMTs? A second point of interest concerns the us e of the SCM activity to infer a startle response. (Carlsen et al., 2003a) suggest that the blink reflex is not an accurate measure of the startle response (the SCM provides a more accurate representation) and as such, the reliance on a modulated blink reflex in affective research should potentially be discarded? Two important questions result: 1) Is the startle response an all or nothing phenomena simply reliant on a stimulus threshold to be realized? Indexing the behavioral impact of varyi ng stimulus intensities offers a protocol via which this issue can be evaluated. 2) Are the behavior al manifestations that occur in response to a 127dB startle probe considerably diffe rent from those observed following a 95105dB startle? Summary: Acoustic Startle and Movement Carlsen et al.Â’s efforts to build an ar gument for the subcortical storage of movement programs and the speed ed startle initiation of subc ortical movements (Carlsen et al., 2004a) is weakened by indirect assumpti ons, and the exclusion of data that does not support the hypothesized m echanism. Nevertheless, in the majority of participants, the fact remains that PMTs are speeded if an acoustic startle acts as or accompanies a GO signal. Further, evidence suggests that the sp eeded voluntary movement that is initiated via startle is similar in EMG burst duration and timing, kinematic pa tterning (Carlsen et al., 2004b; Valls-Sol et al., 1999) and accuracy (Carlsen et al., 2004b; Carlsen et al., 2000), as the same movement performed in the absence of the startling stimulus. In short the same voluntary movement occurs regar dless of the initia ting stimulus, the

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65 difference being that an acoustic startl e results in a voluntary movement being completed at the more rapid rate of a startle reflex (Carlsen et al., 2004a, 2004b; Valls-Sol et al., 1999; Va lls-Sol et al., 1995). Acoustic Startle, Emotion, and Movement Acoustic Startle, Emotion, and Involuntary Movement The influence of emotion on involuntary movements has attracted significant interest in recent years. Below, the potentia l mechanism for such a relationship will first be outlined, followed by data supporting the notion that emotions are capable of modulating the magnitude and latency of involuntary movements. Considerable data supports the notion that a direct pathway linking the amygdala and PnC mediates fear potentiated startle (s ee Figure 2-10; Rosen et al., 1991). However, the exact route(s) via which signals from th e amygdala reach the PnC (a crucial relay in the primary acoustic startle circuit: (Lee et al., 1996; Rosen et al ., 1991) are yet to be resolved. The issue has emerged because in addition to the PnC, the amygdala also projects to the rostral midbrain (Fendt, Ko ch, & Schnitzler, 1994b; Rosen et al., 1991) including deep layers of th e superior colliculus/deep mesencephalic nucleus (deep SC/DpMe), the periaqueductal gray (PAG), and the lateral mesencephalic reticular formation MRF), which all in turn project onto the PnC (Meloni & Davis, 1999). Lesions within rostral midbrain regions block fear-pot entiated startle (Fendt, Koch, & Schnitzler, 1994a; Yeomans & Frankland, 1996), suggestin g that these areas serve as a relay between the amygdala and the PnC. To determ ine the critical output relay between the amaygdala and the PnC, Zhao & Davis ( 2004) locally infused an equal dose of a glutamate non-NMDA receptor into the areas of interest within the rostral midbrain. In short fear-potentiated startle was blocked fo llowing infusion of the receptor into the deep

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66 SC/DpMe before testing but had no effect on baseline startle amplitude. The same dose infused into the dorsalolateral PAG, the lateral MRF, or the superficial layers of the SC did not affect fear-potentiat ed startle, although the trea tment did reduce contextual freezing when infused into the dorsal/lateral PAG. The authors concluded therefore, that of the three potential candidates that act as the critical output relay between the amaygdala and the PnC, the most likely mediatin g site for fear-potenti ated startle is the SC/DpMe, and furthermore, that glutamater gic transmission is required for this action (Zhao & Davis, 2004). Figure 2-11. Affective modulati on of startle circuitry: prim ing motor function. Reciprocal activation/inhibition between the peria queductal grey and amygdala modulate PnC activity which in turn modulates st artle potentiation and voluntary motor function. Animal literature has shown that startle reflex circuitry is directly influenced by amygdala projections (assuming an intact SC /DpMe, Zhao & Davis, 2004). Crossing into the human domain, evidence indicates that a loca lized lesion of the right amygdala results

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67 in an inhibited reflex contra lateral to the lesi on (Angrilli et al., 1996). Furthermore, the typical startle potentiation induced by an aversive emotive background does not manifest, furthering the belief that th e amygdala is involved with human startle and emotional responses (Angrilli et al., 1996). To determine whether the amygdala's role in affective processing extends beyond negative stimuli, Garavan and colleagues (Gar avan et al., 2001) collected fMRI data while exposing subjects to high and low ar ousing pleasant and unpleas ant pictures, in addition to neutral control pictures. Amygdala activation, relative to a neutral picture baseline, was significantly in creased for both affective s timuli and did not differ for pleasant and unpleasant categories. Furthermor e, whereas arousal level appeared to modulate the amygdala response for negative s timuli (increased arousal was associated with increase in activity), regardless of ar ousal level, pleasant pictures produced significant amygdala responses, s uggesting that the amygdala pl ays a significant role in the processing of affective s timuli indiscriminate of the motivational system activated (Garavan et al., 2001). Increased activati on of the amygdala, therefore, does not necessarily increase startle blink reflex ma gnitude; increased amygdala activity merely represents the modulatory impact the am ygdala has on response characteristics, potentially via its connections with the PAG. As such, Walker and Davis postulate that the role of the dPAG in potentiated startle is during the performance of fearmotivated behaviors and not during the acquisition and processing of fearful stimuli. The notion that affect, via activation of the amygdala, modulates startle has been extensively examined (e.g., Schupp, Junghofer, Weike, & Hamm, 2004). According to a

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68 motivational priming pattern of affective m odulation, associated startle reflexes are primed by the affective context well in adva nce of when a secondary probe is actually presented. The magnitude of the eye-blink re sponse (in addition to other physiological processes, e.g., ERP) is modulated according to the affective valence of the context, while the polarity of the res ponse is influenced by arousal. For example, the startle blink reflex is potentiated when humans are exposed to threat and violent death images, and is inhibited when humans are exposed to erotica scenes. This pattern of blink magnitude is robust across varying pleasant and unpleasant categories, with arousal levels controlling the polarization of the response (Bradley, Cuthbert, & Lang, 1999). Typical protocols present th e startle stimulus between 2-4 s after image onset, and indeed, the pattern of affec tive modulation is robust. However, blink magnitude is sensitive to the length of time an individual is exposed to the image before the startling stimulus occurs (Bradley et al., 1999). Speci fically; (1) strong inhibitory effects are obtained when blink reflexes ar e elicited immediately after pi cture onset, (2) at the point of maximum inhibition (300 msec after picture onset), reflex inhibi tion is significantly larger for arousing pictures, compared with neutral pictures, (3) 500 msec post picture onset, reflexes are significantly augmented for unpleasant versus pleasant foregrounds, suggesting affective modulation by this point. (4) inhibited re flexes characterize the first 3 s following picture onset, and following 3 s of exposure, the reflex magnitude appears to asymptote for all conditions.

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69 Figure 2-12. The Evaluative Space Model (Cacioppo et al., 1994, 1999) is useful to illustrate how various local conditions may influence the dispositional attributes of an organism. Taking into account the temporal prop erties of the defense cascade (freeze response to circastrike) the temporal sensit ivity of emotion and attention processes appear to directly influence the magnitude and latency of an involuntary movement. Consequently, one can also predict th at a similar pattern maybe evidenced concerning the execution of voluntary movements Therefore, indexing the characteristics of a preplanned movement to an acoustic probe at va rying intervals during a fixed exposure period (in addition to or ra ther than just inde xing the blink reflex) appears to be one among many exciting future directions. Optimizing stimulus intensity and the lead interval of an initiating stimul us as well as identifying the most appropriate affective context for the execution of particular movements are critical manipulations that could drive the investigation of alternative unique mechanisms that may ultimately benefit movement rehabilitation domains (e.g., stroke, ParkinsonÂ’s). Notwithstanding the interacting impact of initiating stimulus, a growing body of literat ure has indexed the overt behavioral consequen ces of affective context.

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70 Cacioppo’s Evaluative Space Model Appropriately reacting to variable conditions in the environment is key to survival. Biphasic theory posits that an orga nism will initiate approach or avoidance behaviors when confronted with pleasant or unpleasant circumstances, respectively. Related to this biphasic notion, Cacio ppo and colleagues (Cacioppo, 1994; Cacioppo & Berntson, 1999; Cacioppo, Crites, Gardne r, & Bernston, 1994; Cacioppo & Gardner, 1999; Cacioppo, Uchino, & Berntson, 1994) predict that an organism’s affect system may be organized to achieve a dynamic ba lance between appetite and defense ( Evaluative Space Model, ESM; see Figure 2-12). Th e ESM suggests that positive and negative information initiates the activation of two functionally separate evaluative processors (i.e., positivity and negativity). Together, th e summation of these processors equate to a net predisposition to move toward or aw ay from a given stimulus. Because these processors are relatively dis tinct, each has the flexibility for the local environment to shape its activation function (Cacioppo & Bern tson, 1999). In the top-right corner of the figure, each function’s activation pattern is ch aracterized. At a net predisposition of zero, a small offset towards positivity can be notic ed. Additionally, as activation increases for either function, it can be seen that the slope for negativity increases faster than for positivity. Together, these functions express what has been called a positive offset and negativity bias According to Cacioppo & Bernston (1999), “t he process of natural selection may also have sculpted a propensity to react mo re strongly to negative than positive stimuli” (p.136). As the Evaluative Space model suggests, humans possess a fundamental orientation to rapidly shift into defense at lower levels of activation than for positivity. This predisposition, however, can be shaped by the local environment in the interest of

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71 survival. The net effect of this movement bi as has been investigated in a number of situations across a range of motor actions [posture, Hillman et al., (2004); pinch grip, Noteboom, Fleshner, & Enoka, (2001); lever pulling, Chen & Ba rgh, (1999); square tracing, Coombes, Janelle, & Duley, (2005)]. Emotion and Voluntary Movement Rapid conscious and non-conscious processi ng has been shown to influence overt movement speed and direction. Chen and Bar gh (1999) exposed participants to stimulus words and instructed one group of participants with incongruent instructions by requiring them to push a lever away from them (avoidanc e behavior) if the stimulus word presented was positive (activation of appetitive circui try), and to pull the lever toward them (approach behavior) if the stimulus word was negative (activation of defensive circuitry); the second group received opposite congruent instructions. Resu lts indicated that faster pulling of the lever coincided with positive in itiating cues, while negative initiating cues were associated with signifi cantly faster responses when pus hing the lever. In a second experiment, participants were exposed to positive and negative stimuli and were instructed to only pu ll (group 1) or push (group 2) th e lever to pleas ant and unpleasant initiating cues. Again, results confirmed that negative stimuli resulted in faster pushing movements, while positive stimuli led to signi ficantly quicker pulling movements. These valence effects are notable, given that nega tively valenced cues resulted in faster movement time, as compared to positively valenced cues, regardless of movement direction (i.e., push or pull). Interpreting these data within the Bi phasic theory (Lang, 2000), it can be argued that in the face of negative or threatening cues, activation of defensive circuitry primes the human organis m to move with greater haste. That is, when

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72 exposed to negative cues, speeded movement may increase survival rate, permitting notions that this functional re lationship has, and may continue to provide an evolutionary advantage to the human organism. Replica tion of movement speed findings have been reported with stimuli being novel words rath er than familiar words, corroborating the notion that emotions can and will differenti ally impact movement speed and direction (Duckworth et al., 2002). This sequence of studies draws attention to a number of important issues: Is there different motor circuitry underlying defensive and appetitive motivated behavior? Perhaps, alternatively, neural thresholds are decreased throughout the motor system, or the basal ganglia amplifies movements in unpleasant or threatening contexts? Alterations in center of pressure (i.e ., postural adjustments) resulting from exposure to affective pictures were record ed by Hillman, Rosengren, & Smith (2004) in an effort to determine whether activation of motivational systems alter the magnitude and direction of postural movements. The author s reported gender-differences for postural responses to unpleasant pictures; an effect not found for pleasa nt and neutral pictures. In line with approach-avoidan ce predictions, females exhi bited increased postural movement away from the unpleasant cue, but contrary to prediction males exhibited increased movement towards unpleasant pi ctures. Although gender differences in postural sway corroborated the findings of Br adley and Colleagues (Bradley, Codispoti, Sabatinelli, & Lang, 2001) who suggested that females have a broad disposition to react with a greater defensive set during unpleasant, highly arousing pictures, testing broad predictions of avoidance behaviors whenev er an organism is faced with unpleasant, threatening, or dangerous situations appear s problematic. Revisiting the fight or

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73 flight response, it is reasonable to assume that when coupling certain threatening or dangerous situations (i.e., no escape route) with certain temperaments (i.e., aggression) whereas one individual may flee another may fight. Consequently, although in each case safety may ultimately be reached, the means by which safety is achieved contrasts significantly. The questio n therefore remains: do fight and flight responses differ in terms of movement di rection but remain identical in terms of neural circuitry and movement force, speed, and accuracy? With regard to stable sustained muscle activation, Noteboom and colleagues (e.g., Noteboom, Barnholt, & Enoka, 2001) required part icipants to perform a pinch grip task across a 10 min period, asking only that their pinch remain constant; while error was recorded and reported, time was not an issue within the protocol. The authors reported associations between increased impairment of steadiness on a pinch grip task with increases in arousal, trait a nxiety, and intensity of a noxious stimulus (electric shock to the hand). Conversely, protocols that include th e lever pulling task mentioned previously (Chen & Bargh, 1999) have not incorporated movement accuracy, but rather have recorded speed of pulling or pushing the leve r, with movement direction and time being the dependent measures of interest. As such, there is considerable data suggesting that the temporal and spatial characteristics of voluntary movement are influenced by the affective state of the individual, and that the speed and magnitude of startle elicited reflexive movements (e.g., blink reflex) vary according to affective states. Furthermore evidence suggests that voluntary movements can be achieved at the pace of a reflexive movement if the voluntary movement is initiated via an acousti c startle. To date however, startle initiated

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74 voluntary movement and manipulated affectiv e states have never been collectively examined in a systematic fashion. Linking emo tion driven behavioral alterations with an underlying neural mechanism remains a formid able but exciting challenge for movement scientists. Acoustic Startle, Emotion, and Voluntary Movements Overt behavioral movements that accompany the startle reaction are considered reflexive (homeostatic) and are therefore t ypically considered to be exempt from voluntary control (Valls-Sol et al., 1995). Startle reflex pathways, however, require neural structures that are also intricat ely involved in volunt ary motor action (e.g., reticulospinal system). Evidence for th e facilitation of voluntary movement via manipulation of affective contex t and initiating stimulus has been reported. For example, Bradley, Drobes, & Lang (1996) exposed partic ipants to pleasant, unpleasant, and neutral images; at varying intervals during the expos ure period participants were required to make a simple button press following the pr esentation of an acoustic startle or tone. Faster reaction times coincided with startle probes and RT were accelerated later in the viewing period (i.e., at longer startle lead intervals). Specifically, longer RTs emerged early in the viewing period (maximal at 300m sec) and decreased as the exposure period progressed. Similar to eye-blink magnitude (see above), RTs leveled off following 2-3 s of exposure and remained relatively constant for the duration of the 6 s exposure period. These findings (coupled with st artle blink modification data presented above) represent varying attentional and emoti onal processes in picture per ception (Bradley et al., 1999). In discussing the Bradley et al. (1996) ab stract, Bradley et al. (1999) suggest that following picture onset, processi ng resources were automatically allocated to stimuli that

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75 engaged appetitive or defensive motivational systems, resulting in inhibited blink magnitude and lengthy RTÂ’s, relative to neutral pictures. As such, an initial orientating response may inhibit overt behavior, a phenomen a magnified with activation of defensive circuitry (i.e., freezing). During the continui ng exposure period, once initial processing has occurred attentional resources maybe freed up resulting in great er blink potentiation and faster RT. Figure 2-13. Priming motor function: Amygdala activity projects to the PnC and nucleus accumbens (NA) which in turn modulate reflexive and voluntary motor function. CMA = cingulated motor ar ea, NA = nucleus accumbens, M1 primary motor area, SMA = supplementa ry motor area, PMd dorsal premotor cortex. Conclusion Aside from one abstract (Bra dley et al., 1996) and a brief synopsis of that abstract (Bradley et al., 1999), startl e elicited movements have not been systematically investigated within varying affective contexts. The above review, however, amalgamates

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76 largely independent but complementary bodies of literature that summate to provide strong inference concerning the means by which the emotional system primes motor actions, and the varying impact initiating cu es have on overt movements (See Figure 213). In closing, the above revi ew justifies the necessity a nd importance of developing a research line that can successfully deli neate the mechanisms underlying how and if affective states coupled with initiating cues impact the characteristics of voluntary motor function.

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77 CHAPTER 3 METHODS Participants Thirty five (females = 17; males = 18) unde rgraduate students from the University of Florida were recruited to participate in this study, and received extra credit as compensation. Participants reported no heari ng loss or central nervous system disorders that could affect movement. Written informed consent was obtained from all participants prior to beginning the study. All ParticipantsÂ’ self-reported domi nant hand use. All left handed participants (3, male) were excluded from the analyses to prevent confound due to handedness. In addition, data points 3 SDs from the mean were considered extreme scores and were removed prior to analysis. The repeated measures analyses were such that participants missing one (or more) score(s) were completely removed from each separate analysis. Consequently, 29 participan ts were included in the PRT, EMG peak, EMG risetime, and peak force analyses; 28 part icipants were included in the EMG slope and force risetime analyses; and 25 participants were included in the force slope analysis. With regard to analyses of the startle blink reflex, 26 participants were included in each analysis. Instrumentation Affective Stimuli Participants viewed a total of 64 digitized photog raphs selected from the International Affective Picture System (IAPS; NIMH Center for the Study of Emotion and Attention, 2005) representing three affective categories ( 16 erotic couples, 16 attack,

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78 16 household objects1). Sixteen blank black images were also presented. All pictures were visible for 6 seconds. Images were sele cted according to affective normative ratings (CSEA) to ensure that erotic and attack im ages were similarly arousing, and that each were significantly more arousing than neutra l images (P = 6.57; U = 6.64; N = 2.56). For valence, each category significantly differe d from each other (P = 6.75; U = 2.4; N = 4.97). Each participant viewed each picture only once. Stimulus presentation order was randomized and counterbalanced. Task While viewing each picture, participants were required to respond as quickly as possible to any acoustic stimulus by initiati ng an isometric bimanual contraction of the wrist and finger extensor muscles against two independent load cells (left/right limb). Acoustic Stimuli Created with custom built Labview softwa re (7.1; National Instruments, Austin, TX), the tone cue consisted of a 50 ms tone de livered at 80 dB. In contrast, the startle cue stimulus was a 50 ms burst of white noise de livered at 107 dB with near instantaneous rise time. Acoustic stimuli were presente d binaurally through a set of calibrated headphones (Radio Shack digital sound level meter: 33-2055, Fort Worth, TX). Acoustic stimuli were presented at set interval s of 500, 1500, and between 3000-5000 msec post picture onset ( M = 4011.88, SD = 153.11, range = 3645.50-4345.25). Tone and startle cues were equally represented within each picture category at each time period (2 startle/tones per categor y per time period). As such, each valence by acoustic cue by time 1 IAPS images: erotic couples: ,4647, 4607, 4652, 4656, 4658, 4659, 4660, 4664, 4670, 4681, 4687, 4689, 4694, 4695, 4800, 4810; attack: 3530, 3500, 6260, 6540, 6313, 6550, 6243, 6370, 6510, 6200, 6560, 6360,6230, 6250, 6300, 6244; household objects: 7002, 7004, 7006, 7009, 7010, 7025, 7035, 7041, 7050, 7052, 7055, 7059, 7080, 7090, 7150, 7175.

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79 period combination was experienced twice. To prevent habituation and anticipation, catch trials (no sound) occurred four times within each valence category. Intertrial intervals varied from 10-14 s. Voluntary Movement Participants were prepared for measurement in accordance with the Society for Psychophysiological Research guidelines (Putnam, Johnson, & Roth, 1992). EMG surface electrodes (silver–silver ch loride electrodes, 1 cm in diameter and 2 cm apart with an epoxy-mounted preamplifier) were placed over the extensor co mmunis digitorum and extensor carpi ulnaris muscles of left and right arms. To index force generation during each isometric wrist/finger extension, tw o 34.1 kg load cells embedded in cushioned platforms were altered in height to accomm odate individual hand si zes (see Figure 3-1). Upper limb EMG (bandpass filter 1-500 Hz) a nd force data were amplified by 5 K and collected at 1000 Hz via Biopac software ( 3.8.1, Biopac Systems Inc, Goleta, CA, USA). Blink reflex The eye-blink response to th e acoustic startle probe wa s recorded by placing two Biopac shielded 4 mm Ag/AgCl electrodes (ELS 204S) over the orbicularis oculi muscle beneath the left eye. The raw EMG signa ls were amplified by 5,000 using a Biopac bioamplifier (EMG100B) and bandpass filtered from 90 to 250 Hz. Trial onset and offset, and visual a nd auditory stimulus presentation were controlled via a custom Labview program. The custom-written program simultaneously sent a 5-volt digital marker into the physiological trace to indicate picture onset and acoustic stimulus onset. Each separate 10 s trial (2 s baseline; 6 s pict ure presentation; 2 s buffer) was streamed to disk for offline analyses.

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80 Procedure After all questions had been answered a nd informed consent had been obtained, participants were seated in a comforta ble chair positioned 1.0 m from a 19” LCD presentation screen. Next, height of the force platforms was adjusted, load cells were calibrated, and EMG sensors were attached to the forearms and beneath the left eye (see Figure 3-1). Following calibration, participants were familiarized with the protocol via a 4 trial practice session (all blank images, 1 star tle, 2 tone, and 1 catch trial). Participants were instructed to (1) “look at each picture fo r the entire time it is on the screen”, (2) “consider picture onset as a cue to prep are to make the required wrist and finger extension”, and (3) “respond as quickly as possi ble to an acoustic s timuli by initiating a short duration bimanual isom etric contraction of the wrist and finger extensor muscles.” Following picture offset, participants were instructed to continue viewing the blank screen as the next image would appear after a short break. At the conclusion of all trials, hands were removed from the customized force platform, EMG sensors were removed, and the participants were debriefed. From par ticipant arrival to departure, the experiment lasted approximately 30 minutes. Data Reduction Voluntary movement EMG and force data were analyzed o ffline via a custom LabVIEW program. EMG signals were rectified and filtered with a 25-Hz lowpass elliptic filter (Carlsen et al., 2004b). Baseline EMG and force scores were calculated for each trial (mean score during 150 ms preceding acoustic stimulus ons et). Eight dependent measures were calculated for each trial: (1) premotor reaction time: PRT, (2) force onset: Fonset, (3) EMG amplitude: EMGamp, (4) force amplitude: Famp, (5) force risetime: Frisetime, (6) EMG

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81 Figure 3-1 Experimental setup. Top : postures of arms, forearms, and shoulders before and during the bimanual task. Bottom left: posture of hands relative to load cells during movement preparation and ITI. Bottom right: posture of hands relative to load cel ls during ballistic movement execution. risetime: EMGrisetime, (7) force slope: Fslope, and (8) EMG slope: EMGslope, (see Figure 3 for specific details and calculations). For each trial for each limb, the semi-automated analysis program superimposed force and filtered EMG data over the digital trigger signal. Visible on a computer monitor, the program automatically identified and then inserted cursors at Famp and EMGamp locations within specif ied windows after acoustic stimulus onset (EMG: 40-500 msec; Force: 40-800 msec). Baseline corrected normalized Famp and EMGamp T-scores were calculated for each tr ial within each participantÂ’s data prior to statistical analysis. Onset of muscle action was identified by locating the first time point where EMG signal amplitude was greater than double the baseline value (Wong & Ng, 2005). Likewise, onset of force pr oduction was identified as the first time point where force data exceeded double the for ce baseline value (see Figure 3). Given the

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82 strictness of the detection al gorithm, coupled with intermittent intermediary EMG and/or force noise between stimulus onset and move ment onset, the locati on of each of these threshold locations was visually verified a nd manually adjusted if necessary. Because of excessive noise and/or no visible peak in EMG or Force within the specified windows, a total of 19 trials were removed from 9 participantsÂ’ data sets (range 1-4 trials per subject; 97.8% of the trials were include d in the analysis). For each pa rticipant, no more than 1 trial was removed from each acoustic stimul us by valence condition. Summary statistics were created by averaging left and right lim b data for each dependent variable. Blink reflex The raw EMG signals were rectified and low pass filtered (25Hz) offline via a custom built LabVIEW program. The semi-aut omated program identified and inserted a cursor at peak EMG amplitude within a 20-150 ms window after startle stimulus onset. Onset of muscle contraction was identified by locating the time point where EMG signal amplitude first equaled and then surpasse d double the baseline value (Wong & Ng, 2005) 2005). A cursor was displayed at this location. Baseline corrected peak t-scores were then calculated for each trial within each participantÂ’s data prior to statistical analysis. Four

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83 Figure 3-2. Calculation of dependent variables, voluntary movement. PRT: Delay between acoustic stimulus onset and EMG threshold. Fonset: Delay between acoustic stimulus onset and Force onset. EMGamp: Peak amplitude within a 40-500ms window following acoustic stimulus onset. Famp: Peak amplitude within a 40-800ms window following acoustic stimulus onset. EMGrisetime: Latency between EMG onset and peak. Frisetime: Latency between Force onset and peak. EMGslope: EMG amplitude change from threshold to peak, divided by time from threshold to peak. Fslope: Force amplitude change from threshold to peak, divided by time from threshold to peak. dependent variable scores were calculated for each startle trial: premotor time, peak force latency, peak amplitude, EMG slope (see figure 3-3). For each participant, data from accepted trials were averaged for each level of valence for each level of probe interval. Statistical Analyses To establish whether startle initiated movements and activation of appetitive and/or defensive circuitry alter voluntary a nd involuntary motor function, each dependent variable was analyzed in 2 (ACOUSTIC STIMULUS: startle, tone) 4 (VALENCE: erotica, attack, household objects, bla nk) 3 (PROBE INTERVAL: 500ms, 1500ms, 3000-5000ms) analysis of variance (ANOVA), with repeated measures on all three factors.

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84 Figure 3-3. Calculation of depe ndent variables, blink reflex Threshold refers to the location and amplitude in the EMG trace where values are greater than double the corresponding baseline value. PMT: Delay between acoustic stimulus onset and EMG threshold. Peak amplitude : Peak amplitude within a 20150ms window following acoustic stimulus onset. Peak latency : acoustic stimulus onset to peak EMG amplitude. Slope : EMG amplitude change from threshold to peak, divided by time from threshold to peak. For F ratio interactions with valence a nd probe interval, if the sphericity assumption was violated, then Geisser-Greenhou se corrections were used to obtain the critical p -value. Follow-up analyses were conducte d using simple effects tests and the Tukey HSD procedure for significant interact ions and main effects, respectively. To illustrate the relationship between vol untary and involuntary startle triggered movements, Pearson correlation coefficien ts were computed between corresponding variables (voluntary and invol untary: PMT, EMG peak, peak EMG latency, EMG slope) matched for valence, probe interval, and limb. For all analyses, the probability value was set at p < .05.

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85 CHAPTER 4 RESULTS Voluntary Movement Premotor Reaction Time (PRT) A significant main effect of time ( F (2, 56) = 28.82, p < .001) evidenced that PRTs were faster following longer probe intervals (1500 and 3000-5000 msec) relative to shorter probe intervals (500 msec). A significant main effect of acoustic stimulus indicated that when movements were initiate d following startle relative to tone cues, premotor times were accelerated ( F (1, 28) = 44.67, p < .001). Additionally, a significant main effect of valence indicated that relati ve to erotic images, exposure to attack and household object images resulted in faster PRT, F (3, 84) = 9.98, p < .001. Further, PRT during exposure to scenes of household objects was faster as compared to attack and blank conditions. These significant main effects, however were superseded by a Time x Valence interaction ( F (6, 168) = 3.55, p = .002). Follow-up analyses indicated that PRTs initiated to cues 500 msec following erotic image onset we re slower than all other Valence x Time conditions aside from attack and blank condi tions at 500 msec. In addition, exposure to attack images at 500 msec resulted in slow er PRT relative to blank conditions at 1500 and 3000-5000 msec intervals. Finally, PRTs to cues at 500 msec during blank exposure periods were greater than during household obj ect exposure periods wi th probe intervals of 1500 and 3000-5000 msec. (see Figure 4-1). Re maining interactions did not reach significance ( pÂ’s > .05).

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86 Figure 4-1. PRT (+ 1SE) for startle and tone cues for each valence category for each probe interval. E = erotica, A = at tack, N = household objects, B = blank EMG Risetime (EMGrisetime) EMG onset to peak was significantly altered by initiating stimulus ( F (1, 28) = 7.50, p = .012) with inspection of the means indi cating that rise times were shorter to startle relative to tone cues ([msec] Startle: M = 69.86, SE = 5.32; Tone: M = 80.60, SE = 8.90). Main effects of time, valence and remain ing interactions did not reach significance ( pÂ’s > .05). EMG Peak Normalized T-scores (EMGamp) A significant main effect of acoustic s timulus was evidenced, indicating that EMGamp was greater to startle relative to tone cues, F (1, 28) = 66.08, p < .001. This main effect, however, was superseded by a significan t Time x Acoustic Stimulus interaction ( F (2, 56) = 3.79, p = .029), and Time x Valence interaction ( F (6, 168) = 3.55, p = .002)

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87 (see Figure 4-2). Follow-up tests for the Time x Acoustic Stimulus interactions revealed that peaks to startle cues at 1500 and 3000-5000 msec were gr eater than tone conditions at the same intervals. In addition, peaks to startle cues at the 1500 msec interval were greater than all tone conditi ons. Post-hoc tests to iden tify specific Time x Valence differences were not significant. Main effects of time and valence did not reach significance ( pÂ’s > .05). Figure 4-2. EMGamp (normalized T-scores, + 1SE) for startle and tone cues for each valence category for each probe interv al. E = erotica, A = attack, N = household objects, B = blank EMG Slope (EMGslope) Analyses revealed that EMGslope was significantly altered by acoustic stimulus, such that slopes were of a steeper gradient when movements were initiated to startle relative to tone cues ( F (1, 27) = 7.28, p = .012) ([msec] Startle: M = .93, SE = .05; Tone:

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88 M = .76, SE = .05). Main effects of time and valen ce and all higher order interactions did not reach significance ( pÂ’s > .05). Force Risetime (Frisetime) Analyses revealed a significant effect of acoustic stimulus on the latency between force onset and peak force ( F (2, 56) = 3.97, p = .024), indicating that risetimes were more rapid to startle relative to tone cues ([msec] Startle: M = 147.78, SE = 12.49; Tone: M = 155.34, SE = 13.35). Peak Force Normalized T-scores (Famp) Analysis of normalized Famp scores evidenced a significan t main effect of acoustic stimulus ( F (1, 28) = 97.19, p < .001), indicating that peaks were greater following startle relative to tone cues. Analysis of Famp also revealed a sign ificant Time x Acoustic Stimulus interaction ( F (2, 56) = 4.86, p = .011) with follow-up te sts revealing greater peaks following startle cues at 1500 and 30005000 msec probe interval s relative to tone cues at the same intervals. In addition, p eaks to startle cues at 1500 msec were greater than tone conditions at 500 msec. (see Fi gure 4-3). Finally, a si gnificant interaction between time and valence was evidenced ( F (6, 168) = 2.50, p = .025), although followup tests including planned comparisons for a ttack images were not significant. Main effects of time and valence and remaini ng interactions were not significant ( pÂ’s > .05). Force Slope (Fslope) Gradient of slope between Fonset and Famp was significantly affected by Acoustic Stimulus ( F (1, 24) = 33.75, p < .001). Follow-up analyses in dicated that steeper slopes coincided with all startle conditions ( M = .42, SE = .04) relative to tone conditions ( M = .36, SE = .03). Neither main effects for time, va lence, nor the rema ining interactions reached significance ( pÂ’s > .05).

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89 Figure 4-3. Forceamp (normalized T-scores, + 1SE) collapsed across initiating stimulus (startle, tone) for each valence ca tegory for each probe interval. Involuntary Movement (Blink Reflex) Premotor Reaction Time (PRT) Significant main effects of time ( F (2, 42) = 12.73, p < .001) and valence ( F (3, 63) = 7.26, p < .001) evidenced that PRT was longer at probe intervals of 500 msec relative to all later probe intervals, and longer during exposure to pl easant stimuli relative to all other categories. The time by valence interaction was not significant ( F (6, 126) = .39, p = .88). Peak EMG T score Analyses revealed that peak EMG of th e startle blink reflex was significantly altered by affective context ( F (3, 63) = 5.86, p = .001), with follow-up analyses evidencing smaller peaks during exposure to pleasant images relative to all other

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90 categories. In addition, a si gnificant main effect of time was also evidenced ( F (2, 42) = 23.15, p < .001), with follow up analyses confirmi ng that smaller peak scores at 500 msec relative to peaks at 1500 msec and 3000-5000 msec. The time by valence interaction was not significant ( F (6, 126) = .93, p = .47). Figure 4-4. Blink reflex premot or reaction time for each prob e interval for each valence category. PRTÂ’s were longer at probe inte rvals of 500 msec re lative to all later probe intervals, and longer during exposure to pleasant relative to all other stimuli. Peak latency Peak EMG latency of the startle b link reflex was not altered by time ( F (2, 42) = 2.97, p = .062), valence ( F (3, 63) = .30, p = .83), or from an interaction between these two factors ( F (6, 126) = .93, p = .47).

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91 EMG slope EMG slope of the startle blink re flex was not altered by time ( F (2, 42) = 2.10, p = .136), valence ( F (3, 63) = .28, p = .84), or from an interac tion between thes e two factors ( F (6, 126) = .76, p = .61). Figure 4-5. Mean blink peak T score for each probe interval for each valence category. Attenuated peaks coincided w ith exposure to erotic images relative to all other categories, and smaller peak scores were evidenced at 500 msec relative to peaks at later probe intervals. Correlations: Voluntary and Involuntary Movement To investigate the relationship between voluntary and involuntary startle triggered movements, Pearson correlation coefficien ts were computed between corresponding voluntary and involuntary va riables matched for vale nce and probe interval.

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92 Premotor Reaction Time (PRT) No significant correlations were evid enced between voluntary and involuntary PRTs ( pÂ’s > .05). Peak EMG T score Significant positive correlations were obt ained between peak EMG of voluntary movement and peak EMG of the startle blink reflex during exposure to attack and during exposure to household object images with probe intervals of 500 msec (attack: N = 26, r = .420, p = .037; household objects: N = 26, r = .401, p = .042). Figure 4-6. Peak EMG latency of the blink refl ex for each probe interval for each valence category. No main effects or interactions were evidenced.

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93 EMG slope Analyses revealed a significant pos itive correlation be tween voluntary and involuntary movements for EMG slope. Specifically, the varia tions in EMG slope of the blink reflex positively correlated with co rresponding voluntary movements at probe intervals of 500 msec during e xposure to erotic images ( N = 26, r = .440, p = .028). Figure 4-7. EMG slope of the startle blink refl ex for each probe interval for each valence category. No main effects or interactions were evidenced.

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94 CHAPTER 5 DISCUSSION The present experiment extended a prev ious protocol (Coombes, Cauraugh, & Janelle, in review) to determine the impact of probe interval (500-5000 msec), initiating cue (80dB tone, 107dB startle), and affective context (ero tic, attack, household object, blank images) on preplanned vol untary ballistic movement a nd the involuntary startle blink reflex. The aim of the present study wa s three-fold: (1) to index the impact of arousal and valence on voluntar y and involuntary movement at various intervals during a 6 second viewing period, (2) to corroborate pr evious evidence that faster and stronger voluntary movements are initiated to startle, relative to tone cues, and (3) to determine whether or not startle triggered voluntary and involuntary movements are positively correlated. To address these aims, particip ants were required to execute voluntary movements to the onset of ac oustic stimuli while viewing a range of scenes. In the discussion that follows I will argue that (1) central and peripheral motor processes of voluntary and involuntary moveme nts are differentially altere d by varying combinations of time, acoustic stimulus, and valence; (2 ) that voluntary and i nvoluntary movements are sensitive to short lead interv al prepulse effects, and (3 ) faster and stronger voluntary movements occur approximately 1500 msec post image onset when initiated to startle cues, with a trend that this combination is accentuated during exposure to attack images. Having addressed my findings, limitations of the present study will be outlined, and recommendations for future research will be offered.

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95 Voluntary Movement Premotor Reaction Time Hypotheses 1a and 1b posited potential di fferences in the temporally sensitive impact of emotional valence and emotiona l arousal on central (a nd peripheral) motor processes. Corroborating previous evidence, voluntary premotor RTs were altered by emotional valence such that relative to erotic images, faster premotor RTs coincided with exposure to attack (Chen & Bargh, 1999; Coombes et al., 2005) and household object images (Coombes et al., in review; Coombes et al., 2005). These data support the notion that faster overall movement times during or following exposure to attack/unpleasant and household object/neutral images partially re sult from expedited centrally driven motor processes (Coombes et al., in review). Additionally, central pr ocessing times during exposure to household images were faster th an attack and blank conditions. Neutral conditions have rarely been employed in emotion-movement protocols (Chen & Bargh, 1999; Marsh, Ambady, & Kleck, 2005), however, when they have been included, their impact on motor related pro cesses have been difficult to interpret (Schimmack, 2005). This issue will be addressed in detail later. Time periods also modulated premotor RT ; with speeded premotor RTs evidenced following longer probe intervals (1500 a nd 3000-5000 msec) relative to shorter probe intervals (500 msec). These data exemplify a pr epulse effect, such that attentional capture to visual stimuli (regardless of the arousal/v alence properties of the foreground image) inhibited premotor RT at 500 ms ec intervals (see Figure 4-1). Superseding independent effects of valence and time, follow-up analyses demarcating the interactive effect of time and valence on premotor RT indicated that movements initiated to cues presented 500 msec following erotic image onset were

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96 slower than all other conditions aside from attack and blank conditi ons at the same time interval. In addition, exposure to attack images at 500 msec resulted in slower premotor RTs relative to blank conditions at 1500 a nd 3000-5000 msec intervals. Finally, Premotor RTs to cues at 500 msec during blank exposure periods were greater than during neutral exposure periods with probe in tervals of 1500 and 3000-5000 msec. These data corroborate previous emotion-st artle blink evidence (Bradley et al., 1993) but in the voluntary movement domain demonstrating that more arousing foregrounds (erotic, attack) inhi bit the speed of m ovement execution at early relative to late probe intervals. As these arousing stimuli also draw attention to them, an attentional explanation likely accounts for inhibition in 2 of the 3 short lead interval findings (Bradley et al., 1993; Fili on, Dawson, & Schell, 1998). However, blank foregrounds resulted in inhibition of premotor RT, which cannot be directly attr ibuted to arousal or valence. One potential explanation is that du ring exposure to blank images, participants were expecting the blank picture to be replaced by an IAPS scene; as such, anticipation resulted in maintenance of attention on the blank screen, resulting in a relative delay in premotor RT. The notion that expectati on may alter response times can be easily controlled in future studies by varying pictures that are included within each image sequence, a suggestion that will be further addressed in the limita tions/future research sections later. Premotor RTs elicited later in the viewi ng period were not significantly altered by valence. Consequently, the motivational priming hypothesis, which accounts for valence effects following long lead intervals was not supported (Bradley et al., 1993). Previous evidence indicates that exposure to unpleas ant and neutral imag es speeds central

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97 processing when movements are initiated between 2-4 s post picture onset (Coombes et al., in review). I predicted th at faster and stronger moveme nts would manifest later (1500, 3000-5000) in the viewing period during exposure to attack images relative to other affective contexts at the same time interv al. The expected progression from freezing to a fight/flight pattern was not demonstrated in the temporal modulation of voluntary movement. A number of potential explanat ions may account for this unexpected finding. First, psychophysiological indices that ac t as the foundation for the defense cascade model (Lang et al., 1997) were garnered from participants while they passively viewed images. The anticipated pattern of behavior, therefore, doe s not take into account the planning or execution of overt motor action; pr ocesses that alter the pattern of a typical psychophysiological response (e .g., HR, Coombes et al., 2005). In the present case, planning, anticipation, and executi on processes directly rela ted to the motor task may have suppressed or masked activation of the emotion circuits; thereby preventing emotion from maximally impacting movement. A s econd and more plau sible (and testable) explanation concerns the nature of the m ovement. Specifically, research on the monkey brain has demonstrated that the CMA areas are essential in decision making, planning, execution, and the control of motor action on ly when rewards are offered for specific movements (Shima & Tanji, 1998). In the pr esent case, the movement was not linked to any functional consequence associated with the affective foreground, and likewise, no accuracy component was incorporated permittin g a feedback loop (i.e., success/failure). As such, the impact of emotion may be accentuated when movement accuracy (rather than just movement speed) is a core component of the task. Hence, it is plausible that the emotion network and the movement networks were not maximally integrated in the

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98 current protocol. For example, it has been demonstrated that offering choices for the treatment activities and incorporating functi onal goals to therapeutic tasks can enhance response rate and movement efficiency in stroke patients (Wu, Wong, Lin, & Chen, 2001). Likewise, Volman and colleagues (Vol man, Wijnroks, & Vermeer, 2002) reported that providing a functional context to perform a task (i.e., turning a light switch off versus reaching to a marker) enhances the qualit y of reaching movements (speed, smoothness, control) of the affected arm in children with spastic hemiparesis. Further discussion of these potential explanations along with future solutions are offered in the limitations and future research sections below. In line with the second hypothesis, an effect of initiating cue emerged for premotor RT. Specifically, relative to the 80dB tone cue, the 107dB startle initiating cue resulted in speeded premotor RTs, corrobor ating prior startle triggered premotor RT findings (Carlsen et al., 2004a, 2004b; Rothwe ll, 2006; Valls-Sol et al., 1999; Valls-Sol et al., 1995), and further valida ting the notion that startle init aiting cues expidite central motor processes. Additionally, the nature of the initiating cue impacted all peripheral voluntary movement indices. That is, the in tensity of the 107dB startle initiating cue resulted in speeded EMG risetimes, force risetimes, greater peak EMG and force amplitudes, and steeper EMG a nd force slope gradients. Two complementary explanations are o ffered to account for the impact of acoustic stimulus on movement: (1) subcortical triggering and (2) stim ulus intensity. The reticular formation has been implicated as a central structure within the startle circuit (Grillon & Baas, 2003), ensuring rapid overt be havioral responses to abrupt startling stimuli (i.e., startle blink respons e). In addition to the role of the reticular formation in the

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99 manifestation of involuntary movements, emerging evidence indicates that neurons within the reticular system are sensitive to voluntary motor planning and initiation (Buford & Davidson, 2004). As such, although our premotor RTÂ’s were not fast enough to rule out cortical processing (cf., Carl sen et al., 2004a; VallsSol et al., 1999), the possibility that movements were subcor tically initiated ca nnot be discarded. To bridge the affective and motor literatu re, the protocol used herein presented startle cues at a volume of 107dB through h eadphones (within the common range of that used in the emotion-startle blink literatu re, (e.g., Lang et al., 1990; Stanley & Knight, 2004) rather than the 124 dB presented th rough speakers behind the subjects head (as used by Carlsen et al., 2004a; Valls-Sol et al., 1999). The disparity between startle stimulus volume potentially slowed response tim es in the present data set, while also leading to questions concerning the volume at which a stimulus intensity effect gives way to activation of startle circuitry. For exampl e, can the startle circuit be activated at varying stimulus intensities? is the startle response an all or nothing response? if the startle circuit is not activated, what are th e pathways that permit a stimulus intensity effect on voluntary movement? what are the c onditions necessary for a startle response to occur? These questions aside, results s howed strong effects of acoustic stimulus, supporting previous evidence that voluntary reaction times to auditory stimuli are inversely correlated with stimulus in tensity (Pascual-Leone et al., 1992). The majority of the startle-voluntary movement literature to date has contrasted premotor RTs following cues at 80dB and 124dB without the presence of a concurrent visual stimulus. A promising future research direction, therefore, is to gauge the impact of a concurrent visual emotional stimulus while also identifying the parameters that

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100 separate a stimulus intensity effect from activ ation of the startle ci rcuit (e.g., stimulus volume, environmental context), and ultimately, how these factors alter overt voluntary movement. Although blink reflex data were coll ected in this experiment via activity of the left orbicularis oculi muscle, activity of the sternocleidomastoid (SCM) muscle was not recorded (viewed as an index of the pres ence of a startle respons e; (Valls-Sol et al., 1999) preventing strong inferences that modulation of central and peripheral indices were driven by an active startle circ uit rather than a stimulus inte nsity effect. Activation of the startle circuit aside, these data confirm th e finding that increasing the intensity of an auditory stimulus expedites m ovement initiation and executi on. Furthermor e, stimulus volume and the concurrent viewing task used in the present study are the most likely explanations to account for the slowing of premotor RTs rela tive to other stimuli used (124dB startle; Carlsen et al., 2004a). Peak EMG and Peak Force Amplitude With regard to peak peripheral motor pro cesses, we observed a similar interacting effect of time and acoustic stimulus for bot h EMG and force, such that EMG and force peaks to startle cues at 1500 and 3000-5000 ms ec intervals were greater than tone conditions at the same intervals. Interpreti ng these results while viewing Figure 4-2 (peak EMG), it is clear that whereas peak responses to tone cues remained relatively constant across varying time intervals, significant fi ndings were predominantly the result of greater peripheral activity to startle cues later in the viewing period, with maximal activation occurring at 1500 msec to startle cues. Simila r to the interpretation offered above to account for the modulati on of premotor RTs, it is con ceivable that in addition to slowing central motor processes, a prepulse e ffect also inhibited peripheral motor activity at the 500 msec time interval (Bradley et al., 1993) relative to the later probe intervals.

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101 With regard to probe interval and initiati ng cue, faster and stronger movements were executed 1500 msec post visual stim ulus onset and to a startle ra ther than a tone cue. This finding is important for those who seek to faci litate the speed and st rength of movement, and likewise, for those who seek to control or attenuate movement speed and force. Although initial analyses offered support to the notion that the affective foreground and the exposure length preceding movement initiation impact movement execution, further analyses did not reveal specific differences between pairings of affective context and time period for peak EMG or peak force. Viewing Figure 4-3 this finding (at least for peak force) is surprising give n the sharp contrast between scores at 1500 msec relative to early and late time periods during exposure to attack images. Ad-hoc tests implemented to delineate the effect of time and activate de fensive circuitry failed to reach significance. Summary To summarize, central and peripheral mo tor processes of voluntary and involuntary movements are differentially altered by varyi ng combinations of time, acoustic stimulus, and valence. Specifically, (1) voluntary movements are sensit ive to short lead interval prepulse effects (i.e., attentio n; Bradley et al., 1993), (2) the intensity of an acoustic startle stimulus accelerates temporal com ponents and strengthens magnitude components of voluntary movement, (3) Brid ging the prepulse effect, s timulus intensity effect, and the motivational priming hypothesis, faster and stronger voluntary movements occurred 1500 msec post image onset, when initiated to st artle cues with a st rong trend indicating that this pattern was accentuated during exposure to attack images.

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102 Involuntary Movement Human startle modification research is di vided into two primary areas: short and long lead interval effects. Short lead interval effects refer to star tle modification by lead stimuli occurring between 0 and 500 to 800 ms and long lead interval effects of approximately greater than 800 ms (Filion et al., 1998). However, it is has been demonstrated that when viewing pictures of their own feared object phobics show startle potentiation as early as 300 ms relative to c ontrol pictures, while controls do not display valence driven differences until around 800 ms (Globisch et al., 1999) In the involuntary domain (startle blink potentia tion/inhibition) the work of Stanley and Knight suggests otherwise (Stanley & Knight, 2004), however, with startle blink potentiation noted at early lead intervals (300 msec) but only to specific threat related cues, as opposed to a broad range of unpleasant stimuli. Predictions for modulation of involuntary movement were similar to those concerning voluntary movement, a nd were driven by previous evidence of startle blink potentiation during exposure to unpleasant foregrounds (e.g., Lang et al., 1990; Stanley & Knight, 2004). Main effects of valence on pr emotor RT and peak EMG indicated that time to movement initiation was shorter, and EMG peaks larger during exposure to attack, household object, and blank images rela tive to erotic images and at each of the late intervals relative to the 500 msec time interval. As such, hypotheses concerning latency and amplitude were corroborated in terms of the comparison between appetitive and defensive circuitry (Stanl ey and Knight, 2004). However, analogous to premotor RTs of voluntary movement, responses during expos ure to attack, house hold object and blank images were indistinguishable. The salient is sue therefore, is whether erotic images

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103 inhibit the latency and amplitude of the st artle blink, whether a ttack, household object and blank images potentiate the startle bli nk, or a combination of both. Either way the similar scores during exposure to attack, hous ehold object and blank images are difficult to interpret given the valence and arousal disparity between the stimuli. Potential explanations, however, are offered next. Unpleasant and Neutral Stimu li Similarly Modulate Movement? Similarity in the blink reflex responses between neutral and unpleasant images at late intervals has not been reported to date. However, similar movements following unpleasant and neutral images have been repo rted in the emotion-voluntary movement literature (e.g., Coombes et al., in review; Schimmack, 2005). The requirement, therefore, to execute an overt motor response is one explanation to account for the similarity between unpleasant and neutra l images demonstrated in the present study. Schimmack (2005) for example, elegantly pitted arousal, general negativity, and evolutionary threat hypotheses against each other with in an interference protocol. Participants were required to solve a math problem (study 1) and to detect the location of a line (study 2) during the simultaneous presentation of varying emotiona l images. Findings indicated that although arousal was a significant predictor of res ponse latency, no significant differences in response latencies between neutral and snake pictures were eviden ced in either study. Schimmack suggested that a threat detec tion system (in our case, reflected as a component of the voluntary movement), may not be hardwired, but may be under voluntary control and open to the influence of learning experiences. A flexible system that is open to learning would certainly be consistent with functional theories of emotion (Nelson, Shelton, & Kalin, 2003), and functionally adaptive.

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104 Given that explanations are lacking, a nd the majority of previous protocols addressing emotion and movement have not yi elded data from neutral conditions (Chen & Bargh, 1999; Duckworth et al., 2002), th is issue remains key to the continued progression of emotion and movement research and demands further attention. To this point, however, predictions driven by emo tional valence or emotional arousal cannot alone offer an adequate and comprehensive interpretation of the relationship between emotion and overt motor behavior. Voluntary and Involuntary Moveme nts: Is there a relationship? Premotor RT Premotor time findings for voluntary and involuntary movements were each modulated by valence and by time, such that times were longer during exposure to erotic images and longer at the 500 msec interval. Co rrelation analyses, however, did not yield significant relationships betw een voluntary and involuntary movement, suggesting that although similar patterns emerged, these patte rns did not present in a linear fashion within each subject. In cons equence, it is unlikely that startle cues of 107dB trigger voluntary and involuntary movements via similar subcortical pathways. Peak EMG Significant positive correlations were obt ained between peak EMG of voluntary and involuntary movement during exposure to attack and household object images with probe intervals of 500 msec, respectively. Toge ther these data provide some evidence for a link between voluntary and involuntary moveme nts, but only within specific conditions. The few correlations that were significant, how ever, and the arbitrariness with which they emerged prevent firm conclusions from bei ng drawn regarding a relationship between reflexive and voluntary movements (i.e., w hy would peak EMG between the limb and

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105 eye only be related at 500 msec to unpleasant and neutral imag es, and not other intervals, or valence conditions?) EMG Slope Similar in nature to peak EMG findings only a single positive correlation was evidenced between the slopes of voluntary a nd involuntary movement at probe intervals of 500 msec during exposure to erotic im ages, suggesting again that voluntary and involuntary movements are not significantly corr elated, and likely therefore, do not share similar pathways. The hypothesis that vol untary and involuntary movements share similar pathways cannot be completely di scarded, however, given that variations downstream of the subcortex contribute to movement execution (e.g., spinal thresholds, motor unit size, recruitment, and firing frequency) Summary If voluntary and involuntary movements do indeed share similar pathways within the subcortex, one would assume that volun tary and involuntary movements would be positively correlated, which was not demonstrated within the present experiment. Although there are mechanisms downstream of the subcortex that by default must be unique to eye blinks and limb movements and that these factors could potentially alter movements in varying fashions, the conclusion drawn from these correlation data is that voluntary and involuntary movements to 107dB star tle cues share few if any neurological pathways. Limitations Previous evidence indicates that emotions alter voluntary (Coombes et al., in review) and involuntary (Stanley and Kn ight, 2005) movement. In addition it has previously been established th at the intensity of an initia ting cue alters the speed and

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106 force with which voluntary movements are in itiated and executed. Furthermore, within the emotion-blink reflex literature, the time course of emotion m odulation suggests that the blink reflex is differentially modulate d by a two-way interaction between time and valence (Stanley and Knight, 2004). The expe rimental parameters manipulated in the present study involved replication of a prev ious voluntary movement study that evaluated the impact of variations in valence and ac oustic stimulus (Coombes et al., in review). However, three notable changes were made to the present protocol. First, valence categories were restricted to attack, erotic and household object images (as opposed to a broad array of unpleasant, plea sant, and neutral images). Second, acoustic stimuli were randomly presented at varying time inte rvals (500 msec, 1500 msec, 3000-5000 msec) during the 6 second viewing period (rather than between 2000-4000 msec). Finally, the magnitude and latency of the startle blink reflex response was added as a dependent variable to chart involuntary movement characteristics. De spite encouragi ng results, two limitations potentially hindered firmer conclu sions from being drawn. Specifically, it is plausible that by adding the Time factor (with 3 levels), fewer indi vidual trials were averaged into each condition. Furthermore, to accommodate the Time factor, the number of total trials was more than doubled (30 to 70), which may ha ve potentially resulted in extraneous factors conf ounding results (i.e., boredom, fatigue, habituation) The endeavor to replicate previous emo tion and movement pr otocols was coupled with an effort to imitate the typical emoti on-startle blink protocol. Accordingly, acoustic cues were delivered at a volume of 80dB (tone) and 107dB (startle ) as opposed to the 124dB used within the startle-movement lite rature (Rothwell, 2006; Valls-Sol et al., 1999). Coupled with this attenu ation of startle stimulus intensity, EMG activity was not

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107 collected from the SCM, preventing a dichotom y of the data into trials where startle responses were and were not present. Nevert heless, strong effects of stimulus intensity did emerge within central and peripheral m easures. Although attenuation of stimulus volume and not collecting data from the SCM prevented inferences concerning the subcortical triggering hypothesis, in no way did this diminish the efficacy and salience of our stimulus intensity findings. A second methodological issue concerns the affective images used. Although a range of valenced images have traditionall y been used in emotion and startle blink paradigms, recent reports have narrowed the specific categories of images (e.g., threat, Stanley& Knight, 2004). Likewise, in the em otion and movement literature, researchers have typically only used pleas ant and unpleasant stimuli. In doing so, the relative effects of pleasant and unpleasant states have not been compared to neutra l and blank conditions. Indeed, Marsh et al. (2005) recently reporte d motor responses to fear and anger cues only, and drew inferences from differences between them (outlined previously). In consequence, comparing two arousal matched emotions similar in valence (e.g., threat, anger) or polarized by valence (fear/erotic) would limit the number of trials (i.e., not including neutral and blank condition) within the protocol, resulting in a cleaner design which may permit firmer conclusions, albeit at the expense of being unable to control for the impact of affective arousal. One final issue that may have limited the impact of emotion on movement, is that the movement required by participants had no functional significance Further, their was neither an accuracy component or a reward manipulation included in the protocol, which may have attenuated the impact of emotional context on movement.

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108 Future Research Upon considering future adjustments to the present protocol, limiting the number of conditions by comparing specific appetitive a nd/or defensive systems, (i.e., fear versus anger) will ensure that results are more easily interpreted. Doing so will also provide a stronger indication that the e ffects reported to date are not the consequence of multivalenced image sequences. In addition, rem oving either the startle or tone condition (given the robust stimulus intensity effect already demonstrated) w ould permit fewer over all trials, and greater emphasis on emotion mo dulation. Further, within a picture viewing paradigm, increasing the startle stimulus intensity and recording EMG from the SCM would be a logical progression to permit conclusions concerning the subcortical triggering hypothesis and the impact that aff ective context has on s ubcortically triggered movements. In addition, a simple movement-sta rtle protocol in which startle cues are presented at varying intensities (80dB124dB) while simultaneously collecting EMG activity from multiple locations would offer insight into the parameters that separate stimulus intensity from activation of the startle circuit. A simple modification to the protocol used herein, would be to alter instructions to require participants to move as hard as possible, rather than as quickly as possi ble. The goal oriented emphasis of the task may alter the interaction effect between emotion and central and peripheral motor processes. The present protocol may benefit from the introduction of goal oriented movements, the result of which would di ctate a subsequent administration of reward/punishment. By overlaying greater f unctional meaning to the task, and relevant consequences to its execution, the cingulat e areas may be prefer entially involved, and would by default potentially magnify the in teraction of the emotion and movement

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109 systems. In addition, altering the task and o ffering post-hoc or real time feedback would add to the ecological valid ity of understanding how em otions alter movement. Developing the notion that real worl d functional movements are executed differently from more abstract movements, response rate and movement efficiency are facilitated following stroke when patients are offered choices in terms of which treatment activities to participate in and by incorporat ing functional goals into the rehabilitation protocol (Wu et al., 2001). Furthermore, th e functional consequence of performing a task has been shown to alter the speed, control, a nd quality of movement in the affected arm of children with spastic hemiparesis (Vol man et al., 2002). Specifically, subjects made fast reaching movements with the affected ar m in three context c onditions: (a) reach to press a light switch to turn on a red light (func tional), (b) reach to press the light switch; no light (semi-functional), and (c) reach to a marker (nonfunctional). The authors concluded that the functional condition (i .e., condition “a”) elic ited better quality movements of the affected arm. As such, the interaction of em otion and movement systems is receiving greater attention across a broad range of disciplin es. Future research is clearly required to identify the pathways that result in emotion modulating movement. In addition to protocol changes, underst anding the impact of emotion on ballistic movement will benefit greatly from layeri ng other methodologies onto protocols similar to the one used herein. For example, a more precise understanding of how emotions alter central and peripheral control systems would be achieved by including measures derived from single motor unit technique s (peripheral), spectral analys es of SEMG (peripheral), as well as brain imaging (central) technique s. For example, mapping the central neural pathways preceding, and charting the periphe ral activity during movement under varying

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110 emotional states would offer considerable in sight into how and w hy attack and household object central processing times are similar. In addition, the use of transcranial magnetic stimulation during movement preparation/pl anning (i.e., following picture onset but preceding the initiating cue) would permit conclusions concerning whether or not emotions alter the excitability of cortical motor areas. The use of converging methodologies and complimentary instrumentation will permit a number of important questions to be answered: Do emotions alter the size, number, and/or frequency of firing motor units? Do emotions alter the “size principle” or “rate coding” mechanisms? Do startle cues tr igger movements stored in the subcortex? Do amygdala-reticular formation connections o ffer a “fast-track” pathway to ensure rapid voluntary movement initiation in aversive co ntexts? Are the basal ganglia/CMA essential to the expression of emotion modulated movement? Conclusion Levels of overt aggression have declined with the advancement of civilization such that on a daily basis one rarely has to move forcefully and/or quickly to survive. As such, the evolutionary notion that em otions are essential for survival, at first glimpse, appears outdated within the relatively safe contemporary society. However, for those suffering motor deficits (e.g., bradykinesia: stroke, Pa rkinson’s disease, a ffective disorders), supplementing existing or developing new reha bilitation protocols to take advantage of primitive brain circuits appears to be a promising noninvasive avenue for future research. In addition, for those striving to regulate th e impact of emotion (e.g., police officers, military personnel) the present findings highlight the innate disposition of the human to move more rapidly in aversi ve contexts, strengthening the notion that innate movement dispositions may not always be congruent w ith intended movement plans. With continued

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111 empirical effort, researchers will be able to provide recommendations to harness the benefits and alleviate the costs associ ated with emotion modulated movement.

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133 BIOGRAPHICAL SKETCH Stephen Coombes was born in Bristol, England, on April 7th, 1977. After receiving his Bachelor of Science Degree in applied ps ychology and sports science from Liverpool John Moores University, he relocated to Gainesville (Florida) in 2000 and in 2002 received a Master of Science degree in a pplied physiology and kine siology (APK) with a concentration in motor learni ng and control from the Univer sity of Florida. Stephen continued in the APK doctora l program with a concentration in motor learning and control, and under the guidance of Dr. Christopher Janelle, received his PhD in August 2006.