Title: Analysis of the movement initiation problem in Parkinson's disease
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Title: Analysis of the movement initiation problem in Parkinson's disease
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Creator: Behrman, Andrea Louise, 1954-
Copyright Date: 1995
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ANALYSIS OF THE MOVEMENT INITIATION PROBLEM
IN PARKINSON'S DISEASE:
PRACTICE AS AN INTERVENTION













By


ANDREA LOUISE BEHRMAN


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


1995




























Dedicated to Jack and Louise Behrman













ACKNOWLEDGMENTS


I want to acknowledge and thank my dissertation committee members: Dr. James

Cauraugh, Dr. Robert Singer, Dr. Keith Tennant, and Dr. Carol Van Hartesveldt, who

provided valuable guidance and insight in this dissertation process. I want to specially

thank Dr. Cauraugh for his relentless enthusiasm and encouragement as a mentor and

advisor throughout my doctoral experience. I would like to recognize Dr. Philip

Teitelbaum for an introduction to studying movement in persons with Parkinson's disease

and to the skill of observation. My doctoral research was supported in part by the

Foundation for Physical Therapy Research and my doctoral education supported in part by

the Neurology Section of the American Physical Therapy Association, and I would like to

recognize and thank both organizations for their contributions. I would like to thank the

Parkinson's Support Groups of Ocala, Gainesville, and Sarasota and the American

Association for Retired Persons for their participation and contribution to this research. I

would like to gratefully thank the physical therapists who have encouraged and supported

me as peers and friends through these four years and more: Rebecca Craik. Pamela

Duncan. Robert Kellogg, Kathye Light, Deborah Nawoczenski. James Tomlinson, and

Susan Tomlinson. Special appreciation is also given to Frank and Darla Raines for their

sustaining friendship throughout this endeavor. I wish to acknowledge my sincere thanks

to my parents for their support, commitment to education, and for contributing to my desire

to learn, discover, share, and teach. Finally, I would like to thank the individuals with

movement difficulties with whom I have had the opportunity to work and to learn from and

who have continually provided the impetus for my doctoral education.














TABLE OF CONTENTS


ACKNOWLEDGMENTS....................................................................... iii

LIST O F T A B LES .............................................................................. ...vii

LIST O F FIG U R ES .......................................................................... .. viii

ABSTRACT ................ ........................................................................ x

CHAPTERS

1 INTRODUCTION....................................................................

Statement of Problem............................................................ 5
Research Hypotheses.............................................................. 5
Movement Complexity Hypotheses.............................................. 5
Practice Hypotheses........................................................... 6
Transfer of Skill Acquisition Hypotheses...................................... 7
Definition of Terms................................................................... 8
Assumptions...................................................................... 9
Lim stations ................................. ........ ............. .... .................. 9
Significance ................................................................. ........10

2 REVIEW OF THE LITERATURE ................................................ 12

Effects of Parkinson's Disease................................................... 12
Information-Processing Model of Motor Control................................ 13
Stages......................................................... .............. 13
Response Programming ........................................................ 16
Practice..................................... .................................. 19
Motor Performance............................................................... 19
Practice Effects on Motor Performance in Adults ......................... 20
Practice Effects on Motor Performance in Persons with Parkinson's
D disease ............................. .. .............................. .......... 21
Practice Effects and Response Complexity............................ ..22
Intervention Strategies for Rehabilitation in Parkinson's Disease...............23
Analysis of Movement Initiation in Parkinson's Disease: Contribution
to Motor Control Theory .......................................................24
S um m ary .............................. ...... .................... ...... ........... 27

3 METHODS .................................................................... ....28

Subjects .............................................. .............................. ..28
A apparatus ..................... ............... .... ...... ..................... .......... 29
Procedures .................................................. ....... ... ........... ... .. 30
Box and Block procedures......................................................30
Arm-reaching tasks...............................................................31









Experimental Design and Analysis............................................33


4 RESU LTS .................................... ...... ........ ... ...................... .. 40

Participant Descriptive Data Analyses..............................................40
Prelim inary Analyses.................................................................40
Movement Complexity and Practice................................................41
Reaction Tim e.....................................................................41
Premotor time ..............................................................42
Motor time ......... ................................. ........... .......... ....42
M ovem ent tim e ......................... ......................................43
Summary ......................... ................ .................. .... ...43
Transfer...............................................................................44
Resolution of Hypotheses ..... ...................................... ...... ...... 46
Movement Complexity Hypotheses.............. ...........................46
Practice Hypotheses..............................................................46
Transfer of Skill Acquisition...................................................47
Coefficient of Variation Scores as a Measure of Response Consistency........48
Reaction Time................................... .......... ............48
Premotor time ..................................................................48
Motor time ........................... .................. ................... 49
M ovem ent Tim e ....................................... ........................... 49
Summary ................................................ ............. ...... ... ..... 50

5 DISCUSSION, SUMMARY, CONCLUSIONS. AND
IMPLICATIONS FOR FUTURE RESEARCH ........................ ........61

Discussion ........................ .................................. .......... 61
Effects of PD on Response Programming and Movement Time.............63
Reaction Time .. ................................ ..... ....................63
Group similarity .........................................................64
Movement complexity effect: Reaction time.........................68
Movement complexity effect: Premotor time......................73
M otor tim e...................................... ..... ....... ..... ........ 75
Movement Time................. ........... ....... ................ 76
Sum m ary.............................. ........................................ 77
Effects of PD on Practice Effects for Response Programming and
M ovem ent Tim e ............ ............. ........................................77
Reaction Time ............. ............................................78
Practice Effects and PD ....................................................79
Fractionated reaction time: Premotor time ..........................83
Fractionated reaction time: Motor time ................................83
Effects of PD on Practice for Movement Time ............................84
Feedback and Goal-setting as a Practice Variable........................85
Sum m ary....................... ........ ............. ..................... 86
Transfer ........................... ...............................................86
Transfer Sum m ary................................. ........................ 89
Summary ..................................... ... .................. 89
Conclusions ............. .............. ................ ......... ........... 92
Implications for Future Research ............... ..................................93








APPENDICES ................................................. ..................................98


A PARTICIPANT QUESTIONNAIRE INCLUDING KATZ
ACTIVITIES OF DAILY LIVING AND GERIATRIC
DEPRESSION SCALE............................................ ............98

B MINI-MENTAL STATE EXAMINATION (FOLSTEIN ET AL.,
1975) ................................................................. ............. 10 2

C PARTICIPANT PHYSICAL AND NEUROLOGICAL SCREEN ...... 104

D HOEHN AND YAHR DISABILITY SCALE (1967)...................... 106

E LETTER OF APPROVAL FROM INSTITUTIONAL REVIEW
BOARD FOR THE RIGHTS OF HUMAN SUBJECTS ................. 108

F INFORMED CONSENT FORM .................................. ......... 110

G POWER ANALYSIS, METHODOLOGICAL
CONSIDERATIONS, AND PRELIMINARY STUDIES ................ 113

H DESCRIPTIVE DATA FOR COEFFICIENTS OF VARIATION
FOR REACTION TIME, PREMOTOR TIME, MOTOR TIME.
AND MOVEMENT TIME ................................................. .. 129

I COEFFICIENTS OF VARIATION FIGURES FOR REACTION
TIME, PREMOTOR TIME, MOTOR TIME, AND MOVEMENT
T IM E.......... ........ ...... ............ ........ .................. 134

REFEREN C ES .............................................................. ...................... 140

BIOGRAPHICAL SKETCH ............................................................... 153













LIST OF TABLES


Table


1 Descriptive Data for the Participant Groups: Parkinson's Disease and Control....... 35

2 Testing and Practice Schedule for the Box and Block Test (BBT) and Arm-
reaching Tasks (ART)................................. ................................... 36

3 Descriptive Data for Mean Reaction Time (ms) for Simple and Complex Arm-
reaching Tasks for Groups: Parkinson's Disease and Control ..................... 51

4 Descriptive Data for Mean Premotor Time (ms) for Simple and Complex Arm-
reaching Tasks for Groups: Parkinson's Disease and Control ....................... 52

5 Descriptive Data for Mean Motor Time (ms) for Simple and Complex Arm-
reaching Tasks for Groups: Parkinson's Disease and Control ....................... 53

6 Descriptive Data for Mean Movement Time (ms) for Simple and Complex Arm-
reaching Tasks for Groups: Parkinson's Disease and Control ..................... 54

7 Descriptive Data for the Box and Block Test (BBT) Scores for Day 1 and Day 2
by Group: Parkinson's Disease and Control. ............................................ 55

8 Comparison of Studies on Reaction Time in Parkinson's Disease.................. 97

9 Mean Premotor Times, Motor Times. Reaction Times (RT), Movement Times,
and Response Times (RespT) for Pretest and Posttest, Simple and Complex
M ovem ents ................................................................... ........ .......... .. 124

10 Pretest and Posttest scores (# blocks) on the Box and Block Test (BBT).......... 125

11 Descriptive Data for Reaction Time Mean Coefficients of Variation for Simple
and Complex Arm-reaching Tasks for Groups: Parkinson's Disease and
C ontro l ............................................... .................................. ... 130

12 Descriptive Data for Premotor Time Mean Coefficients of Variation for Simple
and Complex Arm-reaching Tasks for Groups: Parkinson's Disease and
Control .......................................................... .......................... 131

13 Descriptive Data for Motor Time Mean Coefficients of Variation for Simple and
Complex Arm-reaching Tasks for Groups: Parkinson's Disease and Control ....... 132

14 Descriptive Data for Movement Time Mean Coefficients of Variation for Simple
and Complex Arm-reaching Tasks for Groups: Parkinson's Disease and
Control ................................. ............ .. .............................. 133














LIST OF FIGURES


Figure pag


1. Information-processing model of motor control................................... 14

2. Experimental set-up including arm-reaching task, sequential timer, signal
converter, instrumentation recorder, EMG signal-amplification system,
and oscilloscope ............................. ......................................... 37

3. Box and Block Test apparatus..................................................... 38

4. Simple and complex arm-reaching movements.................................... 39

5. Reaction time means and standard deviations for complexity x test session
interaction .......... ..... ............................................. ....... ..... 56

6. Premotor time means and standard deviations for complexity x test
session interaction..................................... .......................... 57

7. Motor time means and standard deviations for group x test session
interaction .............. ...... ...... .. ........ .................. ........ ..... 58

8. Movement time means and standard deviations for group x test session
interaction....................................... .. . .......... ......... .... .... 59

9. Mean number of blocks and standard deviations for Box and Block Test
group effect ........................................................ ........ ... 60

10. Electromyographic activity and onsets for right anterior deltoid and biceps
muscles during performance of simple arm-reaching movement................ 126

11. Electromyographic activity and onsets for right anterior deltoid and biceps
muscles during performance of complex arm-reaching movement............. 126

12. Response movement component time intervals for the right biceps muscle
during performance of the simple arm-reaching movement during the
pretest (A) and posttest (B). .......................................................... 127

13. Response movement component time intervals for the right biceps muscle
during performance of the complex arm-reaching movement during the
pretest (A) and posttest (B). .......................................................... 128

14. Reaction time mean coefficients of variation and standard deviations for
test session effect....................................................................... 135









15. Premotor time mean coefficients of variation for group x complexity x test
session interaction........................................................... 136

16. Motor time mean coefficients of variation and standard deviations for
group effect .......................... .......................................... ... 137

17. Movement time mean coefficients of variation and standard deviation for
complexity x test session interaction.............................................. 138

18. Movement time mean coefficients of variation and standard deviations for
group x test session interaction........................................... ......... 139














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


ANALYSIS OF THE MOVEMENT INITIATION PROBLEM IN PARKINSON'S
DISEASE: PRACTICE AS AN INTERVENTION

By

Andrea Louise Behrman

August, 1995



Chairman: James H. Cauraugh, Ph.D.
Major Department: Exercise and Sport Sciences


The effects of Parkinson's disease (PD), movement complexity, and practice on

performance and learning of rapid, arm-reaching movements were studied. Persons with

and without PD practiced two, rapid arm-reaching tasks with movement complexity

manipulated by the number of steps in a movement sequence and the number of directional

changes in the movement. The tasks were practiced for 120 trials each across a 2 day

period. The response programming stage of information processing was studied by

analyzing the overall reaction time latency of each movement and its fractionated sub-

components, premotor and motor time. Movement execution speed was analyzed by

recording movement times for each task. A learning effect for practice was studied by

comparing the responses for a pretest to those for immediate (10 min rest interval) and

delayed retention tests (48 hour rest interval). The complexity by test session results of this

study demonstrated that, initially and following practice, persons with and without PD

demonstrated similar response programming as manipulated by movement complexity.

Reaction and premotor times supported a movement complexity effect. With practice of the









two arm-reaching tasks, both persons with and without PD exhibited a learning effect for

response programming and movement times and a diminished movement complexity effect

for each of the retention intervals. Transfer of practice for the rapid, arm-reaching skill to

performance of a manual dexterity skill, the Box and Block Test, was also studied.

Transfer of skill was analyzed by comparing the dexterity scores (the number of blocks

transported in 60 sec) performed prior to and after practice of the arm-reaching tasks.

Persons with PD demonstrated a deficit for timed manual dexterity. Following practice of

the arm-reaching tasks, persons with and without PD improved their manual dexterity

indicating a possible transfer or test-retest effect. This study demonstrated that participants

with PD performed response programming of rapid, arm-reaching tasks of varied

movement complexity as well as the control participants and that practice had a similar

learning effect for persons with and without PD.


1













CHAPTER 1
INTRODUCTION



Parkinson's disease (PD) is a central nervous system degenerative disorder that

affects older persons and causes movement dysfunction. One of the primary movement

disorders resulting from PD is difficulty initiating movement, a problem known as akinesia

(Delwaide & Gonce, 1993). In the motor behavior literature, slowness in movement

initiation in older adults, as measured by reaction time (RT), has been associated with

deficits in the information-processing stage of response programming (Light, 1991a; Light

& Spirduso, 1990).

Smith (1968), Stemberg (1969), Theios (1975), and Kerr (1978) have each proposed

theoretical models of information processing as a mechanism of study and analysis of

human motor behavior. Though the number and functions of each information-processing

stage differ across models, the stages most commonly identified among models are

stimulus identification, response selection, and response programming. Researchers

examining motor performance in normal aging have agreed that deterioration of RT to an

environmental stimulus is subsequent to central nervous system processes as described in

information-processing models (Light, 1991a). Independent manipulation of variables for

each stage of information processing has indicated that stimulus identification (Botwinick,

1972; Hines, Poon, Cerella, & Fozard, 1982), response selection (Baron. Menich, &

Perone, 1983; Jordan & Rabbitt, 1977), and response programming (Larish & Stelmach,

1982; Light & Spirduso, 1990) can account for the aging deficit in RT. To the contrary,

peripheral processes such as muscle contractile speed and nerve conduction have not

accounted for delays in RT.








The focus of this study is the response programming stage of information

processing. Response programming is the stage following stimulus identification and

response selection in which the actual movement response is structured and activated

(Schmidt, 1988). One factor which has been determined to influence the delay in RT

attributable to response programming in normal young and older adults is response

complexity (Christina, 1992; Henry & Rogers, 1960; Light & Spirduso, 1990; Light,

Reilly, Behrman, & Spirduso, in press). In the seminal work of Henry and Rogers

(1960), the researchers concluded that response complexity, defined as the difficulty of the

response to be performed after a stimulus, affected reaction time. More recently,

researchers have found that for healthy adults, increases in the complexity of the movement

response results in significant increases in RT, specifically response-programming time

(Christina, 1992). The response complexity effect, as defined by Christina (1992),

describes the increase in the time required to prepare to initiate (RT) a learned movement

response, to be performed as rapidly and accurately as possible, when the response

becomes more complex. Light and Spirduso (1990) referred to the significant increase in

RT, as a result of specifically increasing the complexity of a movement response, as a

movement complexity effect. Altering the difficulty of the actual movement to be executed

in response to a stimulus affects the response programming stage and subsequently affects

the RT.

The existence of response delays and the specific cause in persons with PD remains

controversial (Chan. 1986). Some researchers have observed significantly longer simple

reaction times (SRTs) for persons with PD than control subjects (Evarts, Teravainen. &

Calne, 1981; Stelmach, Teasdale, & Phillips, 1992), whereas earlier researchers have

reported no significant difference in SRTs between the two groups (King, 1959).

Furthermore. research findings do not indicate significant differences in the effects of

stimulus identification in persons with PD and control subjects. Evidence for a selective

impairment in the response selection stage in persons with PD compared to normal adults








continues to be debated in the literature as well ( Cooper, Sagar, Tidswell, & Jordan, 1994;

Evarts et al., 1981; Stelmach, Worringham, & Strand, 1986).

RT differences have been reported in persons with PD when response complexity

has been manipulated (Harrington & Haaland, 1991; Rogers & Chan, 1988; Stelmach,

Worringham, & Strand, 1987). In two of the studies, RTs of persons with PD were not

affected in duration for the more complex responses compared to the predicted increased

RTs of control subjects (Harrington & Haaland, 1991; Stelmach et al., 1987). Researchers

accounted for the lack of a complexity effect in persons with PD by proposing that these

individuals demonstrated a deficit in response programming. Thus, researchers suggested

that components of a movement were not programmed as a unit, but as sequential,

individual movements. In contrast, Rogers and Chan (1988) ascertained a complexity effect

in persons with PD, yet longer RTs for persons with PD compared to control subjects.

The nature of the tasks implemented by these three sets of researchers indicates a lack of

adherence to a strict definition of movement complexity (Christina, 1992; Fischman, 1984;

Henry & Rogers, 1960; Light & Spirduso, 1990) and may account for different findings and

conclusions.

Previous studies have not identified the exact nature of the Parkinson's-related

response-programming deficits. Moreover, limited research exists concerning the

difference between complexity effects for healthy elderly individuals and those with PD.

The effects of PD on behavior must be delineated from the effects of healthy aging as a

basis for understanding PD and for development of treatment interventions. Therefore, the

focus of this study was to investigate the response programming stage of information

processing in people with PD as well as the movement complexity effect To further

delineate the central processing effects from the peripheral component, total RT was

fractionated by surface electromyography (EMG) into premotor and motor RT (Lofthus &

Hanson, 1981; Stelmach et al., 1992). Fractionation provides another level of analysis








which may explain differences in the central and peripheral contributions to RT of persons

with PD and healthy elderly individuals.

Researchers have speculated that the basal ganglia functions in the initiation and

execution of automatic, learned movement sequences (Marsden, 1982, 1984; Marsden &

Obeso, 1994). Examination of motor behavior in persons with PD, specific to response

programming, serves as a contribution to the converging lines of evidence defining the role

of the basal ganglia in motor control and learning. Converging lines of evidence and

inference for basal ganglia function are founded in neuroanatomical, neurophysiological,

human disease, neural network model, and behavioral studies (Alamy, Trouche,

Nieoullon, & Legallet, 1994; Brotchie, lansek, & Homes, 1991a; Cheruel, Dormont,

Amalric. Schmied. & Farin, 1994: Contreras-Vidal & Stelmach. 1994; Evarts & Wise, 1984;

MacKinnon, Kapur, Verrier, Hoole, & Tatton, 1994; Marsden, 1984; Marsden & Obeso,

1994; Wing & Miller, 1984).

In this study, psychological and behavioral investigation perspectives were adopted

and PD was selected as the most appropriate human model for examining basal ganglia

dysfunction (Marsden. 1984: Wing & Miller, 1984). Thus, persons with PD and age- and

gender-matched control subjects were tested for response programming and movement

complexity effects. Two different movement responses based on levels of complexity were

combined in a simple RT paradigm. Movement complexity was varied by altering the

number of movement components (from one to four) and the number of directional changes

(from zero to three) (Anson. Wickens, Hyland, & Kotter, 1994: Christina. 1992; Henry &

Rogers, 1960; Light, Reilly, Behrman, & Spirduso, in press; Rosenbaum, 1980).

Furthermore, with extensive practice, the contribution of the response complexity

effect to RT is known to decrease in healthy subjects (Fischman & Lim, 1991; Hulstijn &

Van Galen, 1983: Norrie. 1967a, 1967b; Van Mier & Hulstijun, 1993). Practice is a critical

tool used for movement training (Ericsson, Krampe, & Tesch-Romer, 1993) and re-

training. The benefits of practice for motor learning in persons with PD have been limited








and task specific (Connor & Abbs. 1990: Gabrieli, 1995). The benefits of practice on

altering the complexity effect in clients with PD has not been established. Persons with PD

and the control subjects practiced the two different movement responses under simple RT

conditions on two separate days. The effect of this practice, PD, and its interaction with

the movement response complexity was examined to differentiate central processing effects

from peripheral changes.


Statement of the Problem


The general purposes of this study were to (1) determine the performance

differences between persons with and without PD for each component of speeded-

movement responses of varying complexity, (2) examine the differential effects of practice

on altering each of the movement-response components in persons with and without PD in

tasks of varying movement complexity, and (3) determine transfer of the practiced speeded-

movement responses to performance of another motor skill. Specifically, the effects of

PD, movement response complexity, and practice on simple RTs and speeded movement

responses were studied.


Research Hypotheses


The research hypotheses will be presented according to the following three

categories: movement complexity, practice, and transfer of skill acquisition.


Movement Complexity Hypotheses


When compared to the control participants, participants with PD will have

significantly slower: (1) overall SRTs, (2) premotor times, (3) motor times, and (4)

movement times. When comparing RTs for a simple to more complex movement, control

participants will demonstrate a significant increase in (1) overall SRTs and (2) premotor

times. When comparing RTs for a simple to more complex movement however,








participants with PD will demonstrate less change in (1) overall SRTs and (2) premotor

times than matched controls, thus demonstrating deficit behavior.

These hypotheses are consistent with the literature in that persons with PD

performing simple movements typically demonstrate slower movements throughout every

component of the movement response (Marsden, 1982; Rogers, 1991; Phillips, Muller, &

Stelmach, 1989). A movement complexity effect on RT is expected for control subjects as

supported by previous findings (Christina, 1992; Light & Spirduso, 1990). For the

complexity effect in persons with PD, less change in premotor time is hypothesized based

on the findings of Harrington and Haaland (1991), Stelmach et al. (1987), and Jones et al.,

(1994). Verification of a complexity effect in persons with PD remains controversial.

Unremarkable changes in RTs for persons with PD is inconsistent with changes expected

due to the movement complexity effect. Researchers have subsequently questioned the

ability of persons with PD to functionally program a series of movements into a sequential

unit Consequently, researchers have inferred that normal basal ganglia function is critical

to the preparation and initiation of sequential movements and to skill learning.

Slower motor times and movement times are projected for persons with PD

regardless of the level of movement complexity. Differentiation of premotor and motor

time effects is consistent with previous studies fractionating RT to infer central and

peripheral contributions to motor behavior (Christina & Rose. 1985; Stelmach et al., 1992).

Slowness of movement, termed bradykinesia, is also a typical movement disorder for

persons with PD (Rogers, 1991).


Practice Hypotheses


Participants with and without PD will benefit significantly from practice for (1)

premotor times, (2) overall RTs, and (3) movement times. Participants with PD will

benefit significantly less from practice than those subjects without PD for: (1) premotor








times, (2) overall RTs, and (3) movement times. The means for each of these variables

will decrease more for complex movements than for simple movements for both groups.

Practice has a beneficial effect on response programming and RT for normal,

healthy subjects with greater effects on complex tasks (Fischman, & Lim, 1991; Fischman

& Yao, in press; Norrie. 1967a, 1967b). Persons with PD have shown the capacity to

improve motor performance on varying motor tasks (Frith, Bloxham, & Carpenter, 1986;

Soliveri, Brown. Jahanshahi, & Marsden. 1992; Worringham & Stelmach, 1990), but have

not improved to the performance level of control subjects. Generally, the rate of

performance change has also been less in persons with PD. As the degree of performance

change has varied across studies, it may be task-dependent (Harrington. Haaland, Yeo. &

Marder. 1990: Hening, Rolleri, & Gordon, 1994). Reaction times for both PD and control

subjects are expected to improve with practice, yet control subjects may present greater

improvements (MacRae, Spirduso, & Wilcox, 1988). Persons with PD may require

extended practice, particularly for complex tasks (Fischman & Yao, in press), to decrease

the performance difference with control subjects (Soliveri et al., 1992).


Transfer of Skill Acquisition Hypotheses


(1) Participants with and without PD will improve on the transfer task scores from

pretest to posttest. (2) Participants with PD will score significantly lower on the BBT

compared to matched controls for both pretest and posttests. (3) Individuals who

demonstrate faster RTs and MTs on the two tasks of varying complexity will demonstrate

higher BBT scores. High scores on the BBT are a result of fast RTs and MTs. As persons

with PD exhibit slower RTs and MTs compared to control subjects (Marsden. 1982;

Rogers, 1991), lower scores on the BBT would be expected for persons with PD. (4)

Participants with decreased RT and MT scores from pretest to posttest will also display

significant improvements in BBT scores. The BBT is a validated test of timed manual

dexterity requiring fast, repetitive hand motions, including grasp and release of identical,








2.54 cm cubes (Desrosiers, Bravo, Hebert. Dutil. & Mercier, 1994). Persons with PD

have not been tested for transfer of motor performance from a practiced motor task to a new

motor task. Based on the similarity of the practice task and the transfer task requirements,

carry-over to BBT performance is speculated for persons demonstrating improved RT and

MT performance after practice of the two arm-reaching tasks.


Definition of Terms


Fractionated RT is RT divided into its two sub-components of premotor time and motor

time according to the onset of EMG activity.

Information processing model is a model of motor control based on a continuum of stages

of information processing from stimulus input to motor output.

Movement complexity is the difficulty of the movement to be executed explained by such

factors as sequence length, duration, and sides of the body controlled.

Movement complexity effect is a statistically significant increase in RT as a result of

specifically increasing the complexity of a movement response.

Movement time is the time interval between the onset of the movement response and the

completion of the movement.

Motor time is the time interval between the onset of EMG activity and the initiation of the

movement response.

Premotor time is the time interval between the onset of the movement initiation stimulus and

the onset of EMG activity.

Reaction time is the time interval between the onset of the movement initiation stimulus and

the onset of movement response.

Response complexity is the difficulty of a response manipulated by altering stimulus

identification, response selection, or response programming stages of information

processing








Response programming is the stage of information processing in which the actual

movement is structured and activated; the transformation of a selected, cognitive response

code to a motor response code as execution commands for the task.

Response selection is the stage of information processing after stimulus identification at

which a motor response is selected.

Response time is the time interval between the onset of the movement initiation stimulus

and completion of the movement response.

Stimulus identification is the stage of information processing at which the environmental

information or stimulus input is encoded and identified.

Transfer of skill is the influence that practice or experience of one type of task may have on

performance of another, different task.


Assumptions


This study enlisted the following three fundamental assumptions: (1) the movement

complexity effect on RT is robust and well-documented as an element of response

programming, (2) practice is one of the most influential variables in skill acquisition,

retention, and transfer, and (3) basal ganglia function may be inferred from examination of

motor behavior in persons with PD.


Limitations


Limitations of this study are imposed due to the population criteria, disease process,

task specificity, practice and feedback parameters, task validity, and testing validity. The

population studied included 15 persons with PD who are right-hand preferred, community-

dwellers, ambulatory (Level II and III Hoehn and Yahr scale), have normal cognitive

function, and have no history of other neuromuscular disorders and 15 age- and gender-

matched participants. Inferences from this study can thus be made only to persons with PD








matching these criteria. Inferences to basal ganglia function will be made cautiously

recognizing that PD also involves other areas of the central nervous system.

The tasks which participants will practice involve two fast, right arm-reaching

patterns at different levels of movement complexity. Thus, inferences will be limited to

performance of ballistic, upper extremity movements. Studies involving other motor tasks,

levels of movement complexity, or parameters of movement complexity may render

different findings.

Participants will complete a total of 20 pre-test trials and 120 practice trials for each

of the two arm-reaching movements across a two-day period prior to postttesting.

Summary feedback will be provided to the participants with the goal of improving response

times for each movement pattern. Each person completing the study will receive $50.00.

An additional monetary incentive will be provided for the fastest response time after

practice for one individual with PD and one individual without PD. Persons practicing

such tasks with a different practice schedule, number of trials, feedback, goal, and

incentives may perform differently than observed in this study.

This study will be conducted in a laboratory environment. The ecological validity

of the findings may be limited due to the testing environment, as well as the novelty of the

movement task. Inclusion of a transfer task of a validated task of manual dexterity will

contribute to the ecological validity of the study.


Significance of the Study


The review of the literature and findings from this study may advance knowledge of

the basal ganglia role relative to motor control and learning and may directly affect

intervention and rehabilitation strategies for persons who have PD. From this foundation,

four specific points for significance of the proposed study will be addressed.

First, this study will enhance our understanding of the specific motor problems

associated with PD. The slowness in movement behavior associated with aging in healthy








adults has been attributed to changes in every stage of information processing. However,

the slowness in movement behavior for persons with PD has yet to be clarified for

response programming. Identifying the contribution of the response-programming stage to

Parkinson's akinesia may appropriately redirect treatment efforts.

Second, comparing lines of evidence from behavioral science and

neurophysiological studies (motor behavior research in persons with PD and research of

basal ganglia function) may together provide a better understanding of motor control and its

organization specific to the acquisition and performance of automatic, learned movement

sequences. Examination of response programming, movement initiation, and execution in

persons with PD for complex, practiced, speeded responses will thus contribute to our

understanding of basal ganglia function, motor control, and motor learning.

A third point of significance is that examining the effect of practice for response

programming in persons with and without PD will aid in determining the efficacy of

extensive practice as a treatment intervention for persons with PD. Practice continues to be

a predominant tool of intervention for training and retraining motor skills, yet practice has

had limited, task-specific effects for persons with PD.

Lastly, transfer of skill acquisition has not been explored in persons with PD. This

study included a transfer task, the Box and Block test (BBT), to examine the effect of

practice of fast, arm-reaching movements on BBT performance. The BBT is a

standardized, validated test of manual dexterity. The notion of transfer remains a critical

principle of skill acquisition and is pertinent to an understanding of whether the benefits of

practice of response programming in persons with and without PD is task specific or may

be generalized to other tasks.













CHAPTER 2
REVIEW OF THE LITERATURE



The review of the literature is presented in six sections. First, an overview is

provided concerning the general effects of PD relative to motor function. Second, the

information-processing model of motor control is introduced as a mechanism for analysis

of motor dysfunction in persons with PD. For the purposes of the proposed study, the

response-programming stage of information processing is described, including the

response complexity effect. In addition, the effects of age and of PD on the response

complexity effect are reviewed. Third, practice is discussed relative to its influence on skill

acquisition. Specifically, the benefits of practice on motor performance by older adults and

by persons with PD, on the response complexity effect, and on transfer of motor skill are

addressed. Fourth, current intervention strategies in the rehabilitation of persons with PD

are reviewed relative to the proposed study. Fifth, analysis of the movement initiation

problem in PD is considered as one component of analysis which will contribute to an

integrated understanding of the role of the basal ganglia in motor control and learning. A

summary concludes this chapter.



Effects of Parkinson's Disease


Parkinson's disease is a progressive, degenerative disorder of the central nervous

system, primarily involving basal ganglia dysfunction. The disease predominantly affects

older individuals and results in a broad array of movement problems (Glendinning &

Enoka, 1994; Rogers, 1991). The major effect of PD is the diminishing of voluntary and

reflexive movements (hypokinesia). More specifically, persons with PD exhibit delay in








movement initiation akinesiaa), slowness of movement execution (bradykinesia), holding

of fixed postures for extended periods akinesiaa, rigidity), tremor at rest, decreased or

absent associated movements (e.g., arm swing during ambulation), and movement arrest as

observed in the freezing phenomenon (Brooks, 1986; Delwaide & Gonce, 1993; Marsden,

1982; Phillips, Bradshaw, lansek, & Chiu, 1993; Rogers, 1991; Stelmach & Phillips, 1991).

The focus of this study is an analysis of the movement initiation problem in PD, from an

information-processing model perspective, and an examination of practice as an

intervention.


Information-Processing Model of Motor Control





Motor behavior is viewed on an information-processing continuum from stimulus

input to motor output. One of the more accepted information-processing models is the

three-stage model which includes stimulus identification, response selection, and response

programming (Schmidt, 1988). (See Figure 1.) Previous researchers have validated the use

of the motor-control information-processing model to examine the basis of movement

disorders in PD (Brooks, 1986; Phillips & Stelmach, 1992; Phillips et al., 1989; Wing &

Miller, 1984). Although the information-processing model, using RT measurements, is

commonly reported in the literature on PD, the types and causes of information-processing

delays are controversial (Evarts et al., 1981; Flowers, 1976; Marsden & Obeso, 1994;

Montgomery, Gorman, & Neussen, 1991; Rogers & Chan, 1988).

Due to the relatively late age of onset of PD, the effects of aging on information

processing must be considered and delineated from the effects specific to PD. Numerous

age-related changes in the central nervous system lead to slowing of information processing

and execution (Birren, Woods, & Williams, 1980; Dustman, Emmerson, & Shearer, 1994).

Variability of performance between and within individuals also increases as successive age





































MOVEMENT

OUTPUT


INSIDE HUMAN CENTRAL NERVOUS SYSTEM


Figure 1. Information-processing model of motor control (Schmidt, 1988).








groups are compared (Rabbitt, 1993). Older adults, though, typically demonstrate slower

movement response times than younger adults for both RT and MT components

(Salthouse, 1985). Increases in the information-processing requirements of a task result in

greater demands of mental processing and longer RTs for older individuals compared to

younger persons. Older adults appear to be more sensitive to changes in complexity of a

psychomotor task for all stages of information processing compared to younger adults

(Light, 1990).

Task complexity can be altered by manipulating variables for any of the

information-processing stages (Light, 1991b; Schmidt, 1988), resulting in RT changes.

Thus, increasing the intensity of an onset stimulus light affects the stimulus identification

stage and results in a faster RT. Increasing the number of response alternatives affects the

response selection stage and delays RT (Hick, 1952; Hyman, 1953). Manipulating the

difficulty of the actual movement to be performed affects the response programming stage

of information processing and will increase or decrease RT, accordingly (Light &

Spirduso. 199 a).

RT delays in persons with PD have been consistently reported in recent literature

(Sheridan. Flowers, & Hurrell, 1987; Stelmach et al., 1992). However, PD appears to have

differential effects on each of the information processing stages. Investigators report that

stimulus identification appears unimpaired in persons with PD (Bloxham, Mindel, & Frith,

1984; Stelmach & Phillips, 1991). However, existence of Parkinsonian-related deficits in

response selection and planning are controversial ( Brown, Jahanshahi. & Marsden, 1985;

Brown et al.. 1993; Cooper et al., 1994; Evarts et al., 1981; Marsden, 1982; Sheridan et al.,

1987, Stelmach et al., 1986). The selective impairment of response selection as

demonstrated by delays in choice RTs is debated (Cooper et al., 1994; Evarts et al., 1981).

Researchers generally agree that the last stage of information processing, response

programming, is the stage most disturbed by PD (Brooks, 1986; Delwaide & Gonce, 1993;

Sanes, 1985; Stelmach et al., 1986). However, the exact elements of the programming








problems have not been identified (Harrington & Haaland, 1991: Roy, Saint-Cyr, Taylor,

& Lang, 1993).


Response Programming


Response complexity effect. Response programming has been described as a

transformation of a selected, cognitive response code, i.e., an abstract idea of a response,

to a motor response code as execution commands for the task (Henry & Rogers, 1960;

Schmidt, 1988). Response complexity is one of the response-programming variables

studied extensively by previous investigators. Since Henry and Rogers' (1960) initial

work, in which they observed longer RTs in the performance of more complex

movements, investigators' findings have continuously supported this observation

(Christina, 1992).

The use of RT latency as a measure of programming time is based on the view that

greater central nervous system preparation time is required to coordinate and organize more

complex movements. This increased central nervous system preparation causes slower

movement initiation or slower RTs. Furthermore, fractionating RT into its subcomponents

allows for localization of the central processing time to premotor time, as opposed to the

peripheral contribution of motor time (Lofthus & Hanson, 1981). From these findings,

researchers have inferred that more complex movements require an increase in the amount

of time to program the movement, a phenomenon termed the response complexity effect

(Christina. 1992). The significant increase in RT as a result of specifically increasing the

complexity of a movement response has been more accurately described as the movement

complexity effect (Light & Spirduso, 1990).

Many factors have been studied as possible contributors to movement complexity,

including number of movement parts (Fischman, 1984; Henry & Rogers, 1960); number of

controlled sides of the body (Light & Spirduso, 1990; Rosenbaum, 1980), movement

duration (Klapp, 1975), and movement direction (Fischman, 1984). For this study,








movement complexity will be manipulated by the number of steps in a movement sequence

and number of directional changes in the movement (Anson, Wickens, Hyland, & Kotter,

1994; Christina. 1992; Christina, Fischman, Lambert, & Moore, 1985; Christina & Rose,

1985; Fischmann; 1984, Light, Reilly, Behrman, & Spirduso, in press).

Aging and the response complexity effect. As task complexity increases, the

difference between response speeds of younger versus older individuals becomes more

extreme (Birren & Botwinick, 1955; Cerella, Poon, & Williams, 1980; Jordan & Rabbitt,

1977; Light, 1991b; Tolin & Simon, 1968). Specific to response programming, as the

complexity of the movement response is increased, RTs increase significantly, also with

increasing disparity between RTs of older and younger subjects (Light & Spirduso, 1990;

Light, Reilly, Behrman, & Spirduso, in press).

Parkinson's disease and the response complexity effect. A movement complexity

effect has not appeared consistently when comparing healthy-old individuals and those with

PD. Complexity has been manipulated by altering the required type of movement response

(ballistic vs. tracking) (Rogers & Chan, 1988), control of simultaneous movements

(Benecke, Rothwell. Dick, Day, & Marsden, 1986; Benecke, Rothwell, Dick. Day, &

Marsden, 1987a; Stelmach & Worringham, 1988), repetitiveness or task homogeneity

(Harrington & Haaland, 1991), and sequence length (Benecke, Rothwell, Dick, Day, &

Marsden, 1987b; Harrington & Haaland, 1991; Jones et al., 1994; Rafal, Inhoff,

Friedman, & Bernstein, 1987; Stelmach et al., 1987).

The findings of Stelmach et al. (1987) indicated that differences in response

programming for persons with PD in comparison to control subjects by a lack of sequence

length effect for increased RT. The researchers also noted an increase in number of errors

in responses with increased sequence length. Harrington and Haaland (1991) similarly

observed no significant changes in RT for homogeneous responses and a lack of significant

increase in RT for increased sequence length of heterogeneous responses. Intratask

response times increased as sequence length increased for persons with PD, as well as








increased errors identifying the number of sequence changes even after precue. Thus,

persons with PD responded differently than persons without PD to changes in movement

complexity with regard to RT and intratask response time. As indicated by these

researchers, these observations may be attributed to an impairment of preprogramming of

entire movement sequences or deterioration of the execution plan for the movement

sequence.

Benecke et al. (1987) observed that persons with PD perform sequential movements

slower than normals and demonstrated delays in switching from one movement to the next.

The tasks involved a two-part sequence consisting of hand motions (isometric squeeze or

isotonic cutting) and/or elbow flexion (isotonic). These researchers suggested that PD

impairs the ability to organize an overall motor plan and subsequently the capacity to switch

from one program to another in a sequence. Benecke et al. further hypothesized that such

organization occurs under the direction of basal ganglia activity in association with the

supplementary motor area.

Jones et al. (1994) also did not find a complexity effect for persons in PD as

observed in the down time, the time taken to initiate movement from the button preceding a

sequence of three to five taps. Subjects performed a sequence of three, repetitive, finger

tap sequences. From their analysis, the researchers attributed deficits in sequential

movements to dysfunction in the initiation of submovements within the sequence of

sequences.

In contrast. Rafal et al. (1987) found no differences in the response programming

effects for sequential movements of one to three components for persons with and without

PD, as indicated by simple RTs and intra-response intervals. The researchers did find that

Parkinsonians were slower in movement initiation and execution of sequential finger

movements than control subjects.

Comparing across movement complexity studies, researchers have not adhered

strictly to definitions of complexity as described in the motor behavior literature (Christina,








1992; Henry & Rogers, 1960; Phillips et al., 1992). For example, the use of a ballistic

movement versus a tracking movement would be described more appropriately as a

comparison of open-loop to closed-loop movements than a manipulation of task complexity

(Rogers & Chan, 1988). Performance differences for persons with PD, though, were

accounted for by disturbances in central processing of complex tasks. The heterogeneity of

sequential movements may have allowed biomechanical limitations to affect performance

for persons with PD, not actualized under other conditions (Anson, 1982; Harrington &

Haaland, 1991). The level of complexity of some tasks (i.e., finger tap repetition) may not

be complex enough to generate differences in SRT conditions or in response programming

(Jones et al.. 1994: Rogers, 1991). Performance of tasks in which sequential movements

must be programmed on the basis of internal sensory cues may differ from performance of

tasks in which sensory cueing concerning the sequence is provided throughout movement

performance (Harrington & Haaland, 1987; Jones et al., 1994). Heterogeneity within the

population with PD may account for inconsistency in findings, especially when subjects

representing extreme levels of disability are included in the same experimental group

(Evarts et al., 1981; Zetusky, Jankovic, & Pirozzolo. 1985).


Practice



Motor Performance


Practice generally results in improved motor skill performance and is reported to be

the most powerful variable for motor skill acquisition (Ericsson & Charness, 1994; Lee,

Swanson, & Hall, 1991; Schmidt, 1988). As a learner practices and improves in the

performance of a motor skill, he or she progresses through a series of stages of motor

learning: Cognitive, associative, and autonomous (Fitts, 1964; Fitts & Posner, 1967).

These stages are characterized by a transition from performance dependent upon cognitive

learning of the task, high attentional demand to the task requirements, verbalization of the








steps, external cueing and feedback (Christina & Corcos, 1988); to performance focusing

on error-detection and a combination of self-feedback and external feedback; to

performance of the skill automatically requiring minimal attention to the task itself or a shift

in attentional resources, with remaining attentional capacity available for strategy or for dual

task performance (Ericsson et al., 1993; Logan, 1985; Marsden, 1984).

Practice-related improvement in motor performance can be measured in numerous

ways including changes in response times, number of errors, accuracy, consistency,

coordination patterns, retention, and transfer test performance (Schmidt, 1988). From an

information-processing model of motor control, performance improvements attributed to

changes in central-processing time may be measured by premotor RT, whereas changes in

the peripheral components may be measured by motor RT and movement time (Clarkson &

Kroll, 1978).


Practice Effects on Motor Performance in Adults


In the motor learning literature, movement practice is reported to be the most

influential factor for motor-skill acquisition among all age groups (Behrman, Vander

Linden, & Cauraugh. 1992; Fitts, 1964; Lee, Swanson, & Hall, 1991; Light, 1991;

Salthouse & Somberg, 1982: Salthouse, 1990: Schmidt, 1988; Spirduso & MacRae, 1990).

In particular, speed of movement responses is known to be extremely practice dependent

for the general healthy population. Older adults, however, may require extended practice

periods compared to younger adults to achieve motor performance improvements

(Carnahan. Vandervoort, & Swanson, 1993; MacRae, Spirduso, & Wilcox, 1988; Murrell,

1970; Murrell, Powell, & Forsaith, 1962; Salthouse, 1990).

Using an animal model of aging, MacRae et al. (1988) determined that age-related

impairments in RT can be reduced and eliminated with extensive practice. Such

impairments occur in conjunction with changes in the nigrostriatal dopamine system and are

found in the normal, aging population and in persons with PD. Furthermore, these


I








researchers observed high positive correlates for RT performance, age, and nigrostriatal

dopamine function. Extensive practice was suggested as a mechanism for improvement of

RT in both aging individuals with and without PD.


Practice Effects on Motor Performance in Persons with Parkinson's Disease


Researchers have determined that persons with PD can benefit from movement

practice for altering overall SRT (Worringham & Stelmach. 1990), overall response times

(Frith et al., 1986; Soliveri et al., 1992), and time-on-target (Harrington et al.,1990), yet

motor learning abnormalities persist with learning outcomes being reduced and task-

specific. Frith et al. (1986) concluded that persons with PD practicing semi-predictable and

novel tasks demonstrated learning and development of automaticity. Performance by

persons with PD, however, was worse than controls and lacked a reminiscence effect seen

in controls. These researchers proposed that persons with PD will have difficulty in the

sequencing of a novel task (demonstrating deficits in using prior knowledge or experience).

However, with extensive practice, it is suggested that automaticity can be achieved.

Soliveri et al. (1992) also observed improvements in performance of a buttoning

task by persons with PD, yet they required more practice than control subjects to achieve

similar buttoning speeds. Improvements in performance by persons with PD practicing

under dual task conditions provided further evidence for their capacity for skill

improvement. The researchers cautioned that limitations in improvement may be

attributable to an abnormal motor system as opposed to a deficit in learning.

From a review of the limited number of studies in which persons with PD practiced

motor skills of novel or familiar tasks (five studies between 1986 and 1993), practice does

appear to have beneficial effects. Practice time and schedules have varied including practice

to performance criterion (Roy et al., 1993), practice on one day (Frith et al.. 1986; Soliveri

et al., 1992), and practice across two to three days (Harrington et al., 1990; Worringham &

Stelmach, 1990). Continuous tasks were practiced in two studies and discrete tasks








practiced in three studies. The total number of practice trials for two studies using discrete

tasks was 20 and 192 (choice RT). The number of practice trials and the extent of practice

across days by persons with PD has been limited in these studies. Investigation of the

effects of relatively extensive practice in persons with PD is warranted.


Practice Effects and Response Complexity


Practice decreases the movement complexity effect in healthy-young adults (Brown

& Carr, 1989; Fischman & Lim, 1991; Fischman & Wan-Xiang Yao, (in press); Hulstijn &

Van Galen, 1983; Norrie, 1967a, 1967b; van Mier & Hulstijun, 1993) and between healthy-

young and old adults (Light et al., in press). Older adults practicing two arm-reaching

tasks of varying complexity reduced simple RTs more than did younger, adult subjects and

to the point of equivalence to the young practice group (Light et al., in press).

To date, practice has been determined to be beneficial to motor learning in persons

with PD, yet differences in motor learning and its effects relative to PD have been

marginally described (Worringham & Stelmach, 1990). Movement practice and its benefit

to response programming in persons with PD has not been sufficiently studied. The effect

of practice on altering RT, in particular the response complexity effect and the execution of

movement sequences, in persons with PD has yet to be determined (MacRae et al., 1988).

Performance of discrete, sequential tasks of varying complexity comprises a

significant component of normal, functional voluntary movement (Wing & Miller, 1984).

Marsden (1984) noted that the deficit in persons in PD in initiating and executing automatic

learned movement sequences may affect their capacity to learn a motor skill. The effects of

practice on learning such tasks by persons with PD has not been assessed. The relative

permanence of practice effects in persons with PD has also not been addressed in any

motor skill training or practice study to date. Furthermore, the transfer of skill acquisition

has not been examined in this population. Transfer of skill acquisition is defined as the

influence that practice or experience of one type of task may have on the performance of








another, different task (Schmidt & Young, 1987). Application of the principle of transfer

is important in designing efficient strategies for rehabilitation of persons with PD

(Winstein, 1991; Winstein, Gardner, Barto, & Nicholson, 1989). The specificity or

generalizability of training for performance of rapid, arm-reaching movement sequences

will be examined. Investigating these three aspects of motor learning: practice, retention,

and transfer in persons with PD performing sequential tasks of varying complexity will aid

in clarifying the motor learning potential of persons with PD, as well as address the

analysis of their movement initiation problem.


Intervention Strategies for Rehabilitation in Parkinson's Disease


Therapeutic interventions to improve motor function in persons with PD have

included general exercise, range of motion, relaxation techniques, stretching activities,

external cueing, and practice of movements (Schenkman et al.. 1989; Turnbull, 1992). The

efficacy of practice as an intervention for skill learning and transfer has not been determined

in patients with PD. Analysis of the effects of practice on speeded movement performance

with practice would provide insight into the nature of the movement disorder with PD, and

to the specific benefits of practice. Awareness of the impact of practice may aid in

treatment selection. Practice, as a direct intervention, may be beneficial to improve

function. Alternatively, compensatory strategies such as auditory or visual cues may

improve function (Morris. lansek, Matyas, & Summers, 1994a; 1994b).

Physical therapists are concerned with issues of complexity when attempting

movement retraining. The movement retraining progresses from simple to more complex

movements by adding limb movements, increasing the duration of tasks, and varying the

synchronicity of movements (Light, 1991b). This type of progressive task difficulty is

consistent with the definition of movement complexity and is thus used as a means of

treatment progression. Changes in the overall RT via the response programming stage of

information processing (Christina, 1992; Schmidt, 1988) would be expected to be congruent








with changes in the level of movement complexity. With extended practice of complex

movements, overall RT is expected to decrease indicating improvements in central

processing time and performance.


Analysis of Movement Initiation in PD: Contribution to Motor Control Theory


The study of motor behavior, how movements are controlled and learned, entails a

synthesis of several disciplines including neurophysiology, behavioral science, and

biomechanics. The study of movement disorders provides an additional mechanism to

examine brain function relative to motor behavior. In this manner, knowledge of the

structures which are dysfunctional due to disease or injury and awareness of the remaining

behavior of the organism are instructive (Phillips et al., 1989; Phillips & Stelmach, 1992;

Teitelbaum, 1986, 1994). Examination of a movement disorder often serves to define the

relationship of the involved brain structure and function. From this perspective,

researchers view the study of persons with PD, resulting from nigrostriatal path damage, as

a "window to basal ganglia function" (Contreras-Vidal & Stelmach, 1994) and to human

information processing relative to skill learning and memory (Gabrieli, 1995). The

behavior of the diseased or injured organism may further contribute to an understanding of

how behavior is organized and to the principles by which the remaining structures

contribute to function.

The basal ganglia are sub-cortical components of the human neural, motor system.

In a hierarchical model of motor control, the basal ganglia affect movement outcomes

indirectly by preparing for them and adjusting for them via multiple parallel circuit loops to

and from the cortex (Alexander, DeLong, & Strick, 1986; Brooks, 1986; Hoover & Strick,

1993). Two primary neural circuits of the basal ganglia involved in execution of learned

movement patterns are the putamen and the caudate circuits. The putamen circuit receives

inputs from premotor, supplemental motor, and somatic sensory areas of the cortex with

outputs, through the thalamic relay, primarily to the primary motor cortex. In contrast, the








caudate circuit receives inputs from the association areas of the cortex (areas integrating

motor and sensory information), and sends outputs to the premotor, supplemental motor,

and somatic sensory areas of the cortex. Thus, output from the caudate circuit is primarily

to accessory motor regions.

Researchers have speculated that the basal ganglia functions in motor sequencing,

motor learning, and automatic execution of learned motor plans (Brooks, 1986; Graybiel,

Aosaki, Flaherty, & Kimura, 1994; Marsden, 1982; Rogers, 1991; Seitz & Roland, 1992).

According to Marsden (1982), as a motor skill is practiced and learned, the basal ganglia

functions increasingly to automatically and accurately run the motor plan. Other

researchers agree with this perspective describing the role of the basal ganglia relative to a

continuum of automaticity in movement performance (Logan, 1985; Marsden. 1984;

Teitelbaum et al., in press). At one end of the continuum, the elite skilled athlete or

musician represents the height of automatic movement performance. Persons with PD

exhibit diminished automaticity (or none at all); the other extreme of the continuum. As the

capacity for automaticity in motor performance diminishes or is altered by PD, reliance on

cognitive control for motor behavior becomes necessary in individuals with PD (Fitts, 1964;

Teitelbaum et al., in press).

Based on animal studies, researchers have suggested that the basal ganglia generate

phasic neuronal activity, functioning as internal motor cues for movement components in a

sequence dependent upon the predictability, automaticity, or skill level of learned

movement sequences (Brotchie, Iansek, & Home, 1991b, 1991c). Thus, increases in

basal ganglia activity may be associated with performance of predictable movements after

prolonged practice or repetition to achieve automaticity. Furthermore, the internal motor

cue signals the cessation of one movement component in a sequence, allowing execution of

the next movement in the sequence. Seitz and Roland (1992), using regional cerebral blood

flow (rCBF) studies found the basal ganglia to be significantly involved in the advanced

stages of learning and establishment of a motor program for a complex, rapid finger








movement sequence in healthy individuals. Their findings were consistent with their earlier

work in which overtraining of performance of sequential movements was associated with

rCBF increases in the basal ganglia (Roland, Meyer, Shibasaki, Yamamoto, & Thompson,

1982). MacKinnon et al. (1994) have further identified differences in basal ganglia

pathways for repetitive finger opposition movements compared to the same movements

performed intermittently by humans.

From a behavioral perspective, researchers found that patients with PD demonstrate

both prolonged RTs and MTs of movement components in a learned movement sequence

compared to control subjects (Georgiou et al., 1993). These findings are consistent with

the view of hypokinesia as a deficit in the function of internal cues for performance of

learned movement sequences. Benecke et al. (1987) similarly observed delays in persons in

PD relative to normals in switching from one program to another in a sequence.

Researchers proposing a simulated model of neuroanatomical, neurophysiological,

and neurochemical function of the basal ganglia for simple and complex sequential

movements support the role of the basal ganglia in the initiation and execution of movement

(Contreras-Vidal & Stelmach, 1994). Dopamine depletion, as demonstrated through their

model, may account for various motor disorders, such as akinesia, associated with PD.

Other models of information processing in the basal ganglia also advance the basal ganglia

as critical in movement initiation (Graybiel & Kimura, 1995) and in skill learning (Gabrieli,

1995).

The works of Brotchie et al. (1991), Georgiou et al. (1993), and Benecke et al.

(1987), as described earlier, are examples of the complementary contributions of

neurophysiology and behavioral science to an understanding of the role of the basal ganglia

in motor control. From this perspective, this study will examine the response complexity

effect (Christina, 1992) relative to movement initiation delays and the motor behavior of

persons with PD. The function of the basal ganglia may be inferred from such an analysis

and combined with neurophysiological research serve to enhance our understanding of the








contribution of the basal ganglia to motor control. Movement behavior and the effects of

practice, as will be described by comparing persons with and without PD, can further

elucidate the importance of movement preparation, learning, and automaticity in the

performance of predictable, simple and complex movements.


Summary


Akinesia is a prominent movement problem contributing to the functional decline in

persons with PD. From a motor behavior perspective, the theoretical basis for this

phenomenon may lie in the movement complexity effect. The movement complexity effect

is age-dependent such that older persons are more sensitive to changes in response

complexity than younger individuals. A comparison of this effect in persons with and

without PD may enhance our understanding of motor function in persons with PD relative

to normal aging. Combining this behavioral perspective with previous research from a

neurophysiological analysis of basal ganglia function may together advance an

understanding of the contribution of the basal ganglia to motor control and learning.

Furthermore, a limited number of researchers have examined the effects of practice

on motor performance in persons with PD compared to their peers without PD. Practice is

known to be a critical variable in improving motor performance in individuals across the

life span. The benefits of practice, specifically of discrete, sequential arm-reaching tasks of

varying complexity on learning, retention, and transfer of a motor skill have not been

investigated in persons with PD. Investigation of the effects of such practice in persons

with PD is warranted to further identify the effects of akinesia and the efficacy of practice

as an intervention.













CHAPTER 3
METHODS


Subjects


Fifteen adults diagnosed with PD and 15 age- and gender-matched adults without

PD participated in this study. Each group consisted of 10 male and 5 female participants.

Table 1 presents a comparison of the descriptive data for the groups with and without PD.

Participants were community dwellers and right-hand preferred. With the assistance of

family members or caregivers, each participant completed a questionnaire concerning age,

onset of PD (if appropriate), educational level, occupation, medications, depression

(Geriatric Depression Scale; Yesavage, Brink, et al., 1983) and activities of daily living

(Katz Activities of Daily Living -ADL; Katz, Down, Cash, & Grotz, 1970) (Appendix A).

The experimenter evaluated all participants for cognitive state and memory with the Mini-

Mental State Examination (Folstein, Folstein, & McHugh, 1975; Bleeker, Bolla-Wilson,

Kawas, & Agnew. 1988) (Appendix B). Three participants with PD and scores below

standardized normal values for mental state were not included in the study. No participant

was on medication with the known side effect of central nervous system slowing. All

participants were without a history of other neurologic disease; mental disorder; severe

cardiovascular disorder; upper extremity musculoskeletal dysfunction or pain. Persons

were screened for normal neurological status cerebellarr function and spasticity of right

elbow; Goldberg, 1992) and adequate upper extremity range-of-motion to manuallly

perform the experimental arm-reaching tasks (Appendix C). No individuals included in the

study demonstrated abnormal neurologic status or proprioceptive or range-of-motion

deficits. The experimenter also screened participants for adequate visual acuity and contrast

discrimination with habitual correction devices (lenses) (by correct reading of switch-sized








printed letters placed on each switch), the ability to identify an auditory response-initiation

stimulus (buzzer); the ability to hear and follow instructions; and the ability to manually

perform the movements required by the task (Appendix C). All participants in the study

demonstrated adequate visual and hearing ability to perform the experimental tasks.

Individuals with PD were classified according to the Hoehn and Yahr (1967)

severity of disability rating (Appendix D). People with a disability rating of II or II on the

Hoehn and Yahr scale were accepted for participation in this study with 8 participants at

Stage II and 7 participants at Stage III. At these two levels, persons with PD exhibit mild

to moderate disability, demonstrate bilateral involvement, are still ambulatory, and may

exhibit difficulty with balance particularly while walking and turning. Tests and practice

sessions were conducted during medication on periods for individuals with PD as verified

by the participants. Six participants were being treated with sinemet for PD and 7

participants were medicated with a combination of sinemet and eldepryl.

All participants received $50.00 for completing the study. The two participants,

one with PD and one without PD, with the fastest mean response times after practice

received a monetary bonus of $50.00. The University of Florida Institutional Review

Board for the Rights of Human Subjects Approval provided approval to conduct this study

(Appendix E). All participants reviewed and signed appropriate informed consent forms

(Appendix F).


Apparatus


A response time (RT and MT) data collection system consisted of numerous

components including: a simple-RT auditory stimulus to indicate response initiation; a

metronome with earplug to set the warning-signal onset and the intertrial intervals; and five

microswitches to record the initial release time and subsequent parts in movement time

completion. The microswitches (Able-Net 100) required a minimum of 20-30 g of force

for closure and are 6.35 cm in diameter. These equipment components were connected to a








Lafayette Performance-Pack sequential-movement timer (Model 63520) which provided

immediate visual digital readouts for the RTs and response times. Activation of the

response onset signal simultaneously initiated the clock of the sequential timer to record

RTs, MTs, and response times. A signal converter assigned specific signal amplitudes to

the response stimulus and switch onset signals for identification during acquisition and

analysis. The RT, MT. and EMG signals were collected simultaneously on videotape via a

4-channel, Vetter Scientific Instrumentation Recorder. EMG signals were collected via

surface electrodes and an EMG signal-amplification system (Therapeutics Unlimited Inc.)

Pre-amplified, active surface electrodes with an amplification of 35x consisted of two

silver-silver chloride 1 cm diameter electrodes in an epoxy-mounted pre-amplifier with

centers 2 cm apart. During data acquisition, input of all timing and EMG signals was

monitored with a 2-channel digital storage oscilloscope (Hitachi-VC 6023). Response

component times and EMG activity onsets were identified with the Biopac/ AcqKnowledge

data acquisition and analysis software for the Macintosh computer. See Figure 2 for

experiment apparatus.

The apparatus for the Box and Block Test was a wooden box (53.34 cm x 25.4 cm)

partitioned into two, equal compartments, 100 (2.54 cm square) wood blocks, and stop-

watch (Mathiowetz,Volland, Kashman, & Weber. 1985). See Figure 3 for Box and Block

Test apparatus.


Procedures


Box and Block procedures. On Day 1, the experimenter pretested all participants for

manual dexterity using the Box and Block Test (Mathiowetz et al., 1985). Practice of the

task followed standardized instructions, including a 15 s practice period prior to the 60 s

test period. The testing box was placed at the edge of a standard-height table with

participants seated facing the box with their hands on each side of the box. Upon verbal








command, "Begin", one block at a time was grasped from the right-sided compartment

using the right hand, carried over the partition, and released into the opposite

compartment. A 60 s test period was timed with a stopwatch with a verbal "Stop"

indicating the period's end. The aim of the test was to move as many blocks as possible,

one by one, from the right to the left compartment of the testing box during a 60 s period.

The experimenter counted and recorded the number of blocks transported during the test.

Arm-reaching tasks. All participants were familiarized with the right arm-reaching

tasks. The experimenter demonstrated the tasks, manually guided the participant through

each movement pattern, and allowed two practice trials of each movement pattern. The

fast. arm-reaching test movements were (1) a simple lateral movement from right to left and

(2) a more complex, four-part movement consisting of the simple movement and three

additional movements requiring directional changes (Figure 4). The testing and practice

schedule consisted of protests for SRTs on the two movements on Day 1, followed by 2

days of practice (Day I and 2), and immediate and delayed retention tests (Day 2 and 3).

(See Table 2.) The three test sessions occurred in a Monday, Wednesday, Friday or a

Tuesday, Thursday, Saturday sequence. On-medication periods for persons with PD were

established prior to each test session according to self-report. No change in on-medication

periods for testing occurred in the three-day sequence. Each person was prepared and

positioned for testing and practice sessions. For the arm-reaching tasks, the right fingers

were positioned flat on the first switch, wrist supported by the table, and arm relaxed.

After skin preparation with alcohol wipes, surface electrodes with electrode gel were

applied to the right biceps brachii muscle, secured by a double-sided adhesive and

circumferential arm wrap. The electrodes recorded EMG activity prior to (baseline activity)

and during the movement response (Soderberg, 1992). A ground electrode was attached to

the opposite lateral tibia. The EMG signals were led to a high-impedance (15mQ at 100

Hz) differential amplifier (Therapeutics Unlimited Inc.). The resultant amplification

allowed a gain of 1,000 to 10,000 with a bandwidth of 20 Hz to 4 kHz. The common








mode rejection ratio was 87 dB at 60 Hz (Gerleman & Cook, 1992; Winter, 1980). EMG

activity was recorded on videotape by the Vetter Instrumentation Recorder during the

testing and practice sessions of Day 1, 2, and 3. Testing and practice were conducted in a

quiet room. Each participant sat in an adjustable-height chair such that their right arm was

supported on the standard-height table on which the testing apparatus was located.

For the simple movement, following presentation of a verbal, "Ready" signal and an

auditory, variable (1 3 s) response onset signal, manually activated by the experimenter,

the participant released the first switch and moved laterally to the left 12.7 cm to tap the

second switch (Figure 4). RT was the time between the onset of the response stimulus

(auditory) and the release of the first switch, whereas MT was the time interval from the

release of the first switch to the tap of the second switch. Premotor time was the interval of

time from the presentation of the response stimulus to onset time of EMG activity. Onset

time was defined as a three standard deviation change in EMG activity from baseline EMG

activity (Turker, 1993; Walter, 1984). Motor time was the time from onset of EMG to the

initiation of the movement response (release of the first switch). Response time was the

time between the onset of the response stimulus and the tap of the second switch

(completion of the simple movement).

The more complex movement was initiated in the same manner as the simple

movement, but three additional movements with directional changes were added (Figure 4).

RT measurements were identical to the simple movement condition. MT was the total time

required to complete the four-part movement sequence beginning with release of the first

switch. Premotor and motor times were measured as described for the simple movement.

Response time was the time between the onset of the response stimulus and the tap of the

fifth and final switch (completion of the complex movement. The matched-control

participants received the identical warning signal patterns and testing order as the

corresponding subject with PD. Pretests and posttests consisted of 40 SRT trials (20 trials

of each of the simple and complex movements), randomly assigned between participant,








without feedback. Catch trials were included to prevent anticipatory false starts (4 per 20

trials) during testing. During testing, trials indicative of false starts, anticipation of the start

button by the participant, inattentiveness, or errors in arm-reaching movements were

immediately recollected. Practice extended over a two-day period with 120 SRT trials (60

trials of each movement) provided on the first day and 120 SRT trials (60 trials of each

movement) occurring on Day 2. Trials were presented in blocks of 10 trials each with the

movement type changed after every block (Barth-Neander, Hynes, & Gentile, 1994).

During the practice trials, summary feedback concerning response times) for each

movement type was provided verbally to the subject for the 5, even-numbered trials just

completed in the block of 10 SRT trials. Feedback was used in performance evaluation and

goal setting by the subject. Trials were presented in 10 s intervals and subjects were

provided a 30 s rest between every trial block and a 1 min rest after every 6 trial blocks.

Upon completion of the practice session on Day 2, participants rested for 10 minutes.

During this time, participants responded to questions of the Mini-Mental State exam and

Hoehn and Yahr rating. Following the rest period, an immediate retention test of the arm-

reaching tasks and the Box and Block Test was conducted following the identical pretest

procedures of Day 1. On Day 3, a 48 hour delayed retention test was conducted and

followed the identical protesting procedure for the arm-reaching task. including recording

of EMG activity. Testing and practice schedules remained constant across the three days

for each participant (Table 1.) See Appendix G for a review of the power analysis used to

determine the sample size, methodological considerations, and preliminary studies

performed in preparation for the current study.


Experimental Design and Analysis


Descriptive data for the two subject groups included age, gender, educational level,

depression score, and ADL score. Hoehn and Yahr rating, years since onset of disease,

and current medications were reported for subjects with PD. The dependent variables for








this study were premotor RT, motor RT, total RT, and MT. Before analysis, the raw EMG

measures were fully rectified and smoothed and onsets indicated by an algorithm of three

standard deviations above the baseline mean (LeVeau & Anderson, 1992: Turker, 1993).

The baseline mean was measured across the .5 s time interval of EMG activity prior to the

visually-identified deflection of the EMG signal from the baseline. Descriptive data for

dependent measures were recorded including means, standard deviations, and ranges.

Separate 2 x 2 x 3 (Group x Complexity x Test Session) mixed design ANOVAs were

performed to analyze the dependent variables (total RT, premotor, motor time, and

movement time) and the effects of practice for RT. Appropriate post-hoc analyses

(Tukey's Honestly Significant Difference) were performed. All tests were conducted with

the alpha level set at the .05 traditional level.

Separate analyses were conducted for the Box and Block Test, a 2 x 2 (Group x

Test Session) mixed design ANOVA. Descriptive data recorded included the mean number

of blocks, standard deviations, and ranges. The relationship between the pretest and

posttest Box and Block Test performance and arm-reaching performance RT and MT.

were analyzed with Pearson Product Moment Correlations.






35




Table 1.


Descriptive Data for the Participant Groups: Parkinson's Disease and Control



Group


rnntrml


Variable M SD Range

Age 74 7 56-82

Duration of PD 7 4 1- 15

ADL 5.5 1 2-6

Depression 1.9 1.6 0 5

Mini-Mental State 28 1.6 25 30


M D Rane

73 7 57-83


0 6-6

.8 0-3

1.1 26-30


P nrk-incnn'P iepne- Cnntml


PntLinrnn'p nirPa~P










Table 2.

Testing and Practice Schedule for the Box and Block Test (BBT) and Arm-reaching Tasks
(ART).


Day


Procedure 1


BBT Pretest


ART Pretest

20 trials, simple

20 trials, complex


Practice

60 trials, simple

60 trials, complex


Delayed RetentionTest

20 trials, simple

20 trials, complex


Practice

60 trials, simple

60 trials, complex


Immediate Retention Test

20 trials, simple

20 trials, complex


Posttest


BBT













Response Switches


Stimulus and
Switch
Onset Signals


EMG Electrode
0 0


.325


0


EMG Signal Amplif
1 1


EMG Signal
IN-


Stimulus and Switch
Onset Signals


Oscilloscoi


, I I


Stimulus and Switch
Onset Signals


EMG Signal


Figure 2. Experiment apparatus including arm-reaching task, sequential timer, signal
converter, instrumentation recorder, EMG signal-amplification system, and oscilloscope.


Instrumentation Recorder


ler
-O 0


-0 1


....... !


Sequential Timer


Signal Converter






38












2. 54 cm
IH-


Figure 3. Box and Block Test apparatus.


2. 54


100 cubes


PIT





















SAble-Net switches
6.35 cms diameter

O Reaction time release switch
Able-Net switch


Figure 4. Simple and complex arm-reaching movements.


30.5 cms

15.2 cms


30.5 cms


Complex 10

Simple 4---
12.7 cms













CHAPTER 4
RESULTS


Participant Descriptive Data Analyses


Analysis of the age data for the PD and control groups by a one-way ANOVA

revealed no significant group differences. Separate Mann-Whitney U Tests were

performed to compare ADL, Depression, and Mini-Mental State scores between the

groups. A significant difference was found only for the depression score indicating that

PD group had higher scores for depression than the control group (p < .05). Further

review of the depression scores revealed that only 3 out of the 15 participants with PD were

categorized as depressed on the Geriatric Depression Scale, whereas no participant in the

control group attained a level of depression on the scale (Yesavage, et al., 1983).


Preliminary Analyses


Trial by trial, all tape recorded response onset and EMG signal data were

transferred to the Biopac/AcqKnowledge data acquisition and analysis software for

identification of response component times and EMG activity onsets. Prior to analysis,

each trial's raw EMG measure of biceps muscle activity was centered about a zero baseline,

fully rectified and smoothed (10 points), and EMG onsets indicated by an algorithm of

three standard deviations above the baseline mean. The baseline mean was measured

across a .5 s time interval of EMG activity prior to the visually-identified deflection of the

EMG signal from the baseline. The time intervals for premotor time, RT, and total

response time were identified and recorded from switch onset recordings. Motor time was

calculated by subtracting premotor time from RT, and movement time was calculated by

subtracting RT from the total response time.








Participant means for each dependent variable: RT. premotor, motor, movement,

and total response time were calculated for 20 trials of each condition. Values two standard

deviations above or below each subject's mean were removed from the data set (Ratcliff,

1993), then the means were re-calculated. One subject was eliminated from the group with

PD because of an insufficient number of adequate test trials. This individual's age- and

gender-matched control subject without PD was subsequently removed from the study as

well. The descriptive data are reported by group for each dependent variable: RT,

premotor, motor, movement, and total response time in Tables 3, 4, 5, and 6, respectively.


Movement Complexity and Practice


Separate 2 x 2 x 3 (Group x Complexity x Test Session) mixed design ANOVAs

were performed for the following variable means: premotor time, RT, motor time, and

movement time. Tukey's Honestly Significant Difference (HSD) post-hoc analysis further

differentiated the variable means for significant interactions.


Reaction Time


Analysis of the RT data revealed a significant Complexity x Test Session

interaction. F (2, 56) = 7.36, p < .05. Figure 5 illustrates the overall RT interaction. Post-

hoc analysis determined that the overall RT mean for the simple movements (305 ms) was

significantly different than for the complex movement (346 ms). The mean RTs for both

simple and complex movements for the immediate retention test decreased significantly

from the pretest values, but the difference between RT simple movement and complex

movements for the immediate retention test was not significant (simple, 137 ms and

complex. 142 ms). The delayed retention test RT means for both simple and complex

movements were not significantly different from the immediate retention values.

These findings indicate that both the PD and control groups exhibited a movement

complexity effect for RT, noting that the mean RT for the complex movement was








significantly greater than the mean RT for the simple movement. With practice of each

movement (120 trials each on Day 1 and Day 2), followed by a 10 minute rest period and

immediate retention test, both groups improved significantly in RTs for both the simple and

complex movements. The movement complexity effect for RT diminished with practice

across the two days, such that the RT for the complex movement became equal to that of

the simple movement. This relationship was sustained across a 48 hour rest interval as

indicated by the delayed retention test. These data demonstrate that participants with PD

and those without PD respond to practice in the same way.

Premotor time. A significant Complexity x Test Session interaction was also

revealed for premotor times. F (2, 56) = 6.65, p < .05. The interaction is displayed in

Figure 6. Similarly, for both the PD group and the group without PD, the difference

between mean premotor times for the simple and complex movements were significant only

for the pretest session (175 ms and 203 ms). These premotor values decreased

significantly at the immediate retention test (137 ms and 142 ms) and were maintained

across the delayed retention test (136 ms and 144 ms).

The premotor times mirror those of RT for the movement complexity effect. In the

pretest. the simple movement premotor values were significantly different than those for the

complex movement. With practice, however, this effect is eliminated and remains stable

for both immediate retention and delayed retention intervals.

Motor time. A third significant interaction was found in the motor time analysis, a

Group x Test Session interaction, F (2, 56) = 5.79, p < .05. The interaction is shown in

Figure 7. The post-hoc analysis of the Group x Test Session interaction ascertained that

for the pretest, the group with PD had significantly slower motor times than the control

group. From the pretest to the immediate retention test, motor times decreased by 33 ms

for the group with PD and no changes were found for the group without PD. The

improvement in motor times for the PD group was sustained across the delayed retention

test interval.








Movement Time


The 2 x 3 x 3 (Group x Complexity x Test Session) analysis of mean movement

times indicated a significant Complexity x Test Session interaction, F (2, 56) = 94.07, p <

.05. Figure 8 illustrates the interaction. Post-hoc comparisons demonstrated that overall

the movement time means for the complex task were greater than those for the simple task

(movement between two response switches). Across the practice training, significantly

faster movement times were identified only for the complex movement. The values for

complex movement times changed from the pretest to the immediate retention test (1.27 s to

901 ms). These faster movement times were sustained between the immediate and delayed

retention tests. These results indicate that individuals with PD. as well as those without

PD, became significantly faster in movement times for the complex task, but no significant

change was observed for the movement times in the simple task. Furthermore, both

groups maintained the improved movement time performance in the complex task when

tested for delayed retention 48 hours later.

A second movement time interaction, Group x Complexity interaction for

movement times approached significance, F (1, 28) = 3.79, p = .06. The group with PD

had longer movement times only for the complex movement than the group without PD

(1.11 s and 941 ms).


Summary


To summarize, for both groups with and without PD. differences between simple

and complex movement RT. premotor, motor, and movement times were found in the

pretest. The two groups responded similarly to two days of practice, demonstrating

significant improvements in the complex movement premotor, motor, and RTs from the

pretest to the immediate retention test. These improvements eliminated the significant

difference between the simple and complex movement for these variables and thus the

complexity effect. Practice improvements were maintained from the immediate to the








delayed retention test. indicating that the observed effects were a result of learning. For the

pretest, the motor times of the group with PD were significantly slower than the control

group, however they also decreased with practice, thus canceling the group differences in

the immediate and delayed retention tests. The improvements in motor times by the group

with PD remained stable at the delayed retention test.

For the PD group, the faster RTs observed after practice were a result of decreases

in both premotor and motor times. In contrast, the group without PD developed significant

faster RTs with practice only by significant decreases in premotor times.

Overall, the MTs for the complex task were greater than the MTs for the simple

task. With two days of practice, however, both groups improved their MTs for only the

complex task. These improvements remained across the 48 hour interval. Practice had a

uniformly greater effect on improving the MTs of the complex task than those of the simple

task.

With practice, both groups with and without PD improved RT, premotor, and MTs

from the pretest to the immediate retention test and maintained their level of performance

through delayed retention testing. Persons with PD also demonstrated the identical pattern

of improvement in motor times across the same practice and testing intervals. These results

indicated that both individuals with PD and those without PD demonstrated similar motor

learning effects for RT. premotor, and movement times. The PD group alone

demonstrated a learning effect for motor times.


Transfer


The initial BBT scores for two participants were not recorded. The descriptive data

for the BBT scores is presented in Table 7. Analyses were performed excluding BBT

scores for these two participants and their matched controls. A 2 x 2 (Group x Test

Session) mixed design ANOVA for the Box and Block Test scores (BBT) revealed a

significant Group effect, F (1, 24) = 5.73, p < .05. The mean BBT score for participants








with PD was significantly lower (56 blocks) than for participants without PD (66 blocks),

as seen in Figure 9. Thus, persons with PD were significantly slower than persons

without PD when performing a timed task requiring repetitive grasping of 2.54 cm cubes,

transporting it across a partition, and releasing into a box. A Test Session effect

approached significance, F (1, 24) = 4.25, p = .0503 with BBT scores increasing from 60

to 62 blocks.

Pearson product moment correlations comparing BBT scores for Day 1 with Day 2

for each of the groups determined significant, positive correlations (.98 and .88, p < .05).

Thus, after both groups practiced simple and complex, rapid arm-reaching movements

across two days, there was a significant association in BBT performance from Day 1 to

Day 2.

In addition, Pearson product moment correlations were conducted examining the

relationships between BBT Day 1 scores and pretest complex movement means for RT and

movement time between BBT Day 2 scores and the same dependent variables, and between

Day 1 and Day 2 scores. A significant correlation was determined only for the comparison

of BBT Day 1 and Day 2 scores (.94, p < .05). Thus, performance of the rapid, arm-

reaching movements required for the complex task were not associated with the BBT

scores.

Pearson product moment correlations were further performed separately for the

groups with and without PD. The results of this correlational analysis are interpreted

cautiously as less than 30 paired comparisons formed the data set (Morehouse & Stull,

1975). First, the relationships between BBT Day 1 scores and the pretest complex

movement means for RT and movement time were examined. Second, the associations

between BBT Day 2 scores and the immediate retention test, complex movement means for

RT and movement time were tested. Two significant correlations (O < .05) were found

only for the control group: (1) for Day 1, a correlation of -.54 for reaction time and BBT

scores and (2) for Day 2, a correlation of -.68 for movement time and BBT scores. These








findings indicate that on Day 1 persons without PD demonstrated faster RTs for complex

movements associated with higher BBT pretest scores. On Day 2, persons without PD

performed faster movements relative to higher BBT scores.


Resolution of Hypotheses



Movement Complexity Hypotheses


When compared to the control participants, the participants with PD will have

significantly slower: (1) overall simple RTs, (2) premotor times, (3) motor times, and (4)

movement times. From the findings of this study, participants with PD had significantly

slower motor times than the controls and otherwise demonstrated no significant differences

for RTs, premotor times, and movement times. A trend was observed in the data as

movement time differences approached significance for the two groups.

When comparing RTs for a simple to more complex movement, control participants

will demonstrate a significant increase in (1) overall RTs and (2) premotor times. The

analysis of this study indicated that both participants with and without PD demonstrated a

significant increase in (1) overall RTs and (2) premotor times.

For the RT changes for a simple to more complex movement, participants with PD

will demonstrate less change in (1) overall RTs and (2) premotor times than matched

controls, thus demonstrating deficit behavior. The results indicated that participants with

and without PD demonstrated equivalent performance change in (1) overall RTs and (2)

premotor times.


Practice Hypotheses


Participants with and without PD will benefit significantly from practice for: (1)

premotor times, (2) overall RTs. and (3) movement times. This hypothesis was upheld








with both groups demonstrating improvement in each of these variables with two days of

practice (120 trials for each task).

Participants with PD will benefit significantly less from practice than control

participants for: (1) premotor times, (2) overall RTs, and (3) movement times. The means

for each of these variables will decrease more for complex movements than for simple

movements for both groups. The first component of this hypothesis was not supported in

that both groups benefited equally from practice. The second component was supported

with the means of each variable decreasing more for complex movements than for simple

movements for both groups.


Transfer of Skill Acquisition Hypotheses


(1) Participants with and without PD will improve on the transfer task scores of the

BBT from pretest to posttest. The data did not support this hypothesis, though a trend

towards significance in the right direction was reported.

(2) Participants with PD will score significantly lower on the BBT compared to

matched controls for both pretest and posttests. This hypothesis was supported by the

findings.

(3) Participants who demonstrate faster RTs and MTs on the two tasks of varying

complexity will demonstrate higher BBT scores. Analysis of the combined groups did not

support the hypothesized association for arm-reaching RTs, MTs, and BBT scores.

Analysis of the groups separately supported an association for RT and MT for only the

group without PD.

(4) Significant improvements in BBT scores will be displayed by participants with

decreased RT and MT scores from pretest to posttest.. This hypothesis was not supported

as both groups overall demonstrated decreases in RT and MT scores, but neither improved

in the BBT from Day 1 to Day 2.








Coefficient of Variation Scores as a Measure of Response Consistency


Coefficients of variation were calculated from the adjusted data sets for each

dependent variable means. The CV was selected as a measure of response consistency

because it is a measure of relative variation. This measure accounts for differences in the

magnitude of the means by representing the standard deviation as a proportion of the mean

(Portney & Watkins, 1993). Mean CV are reported for each dependent variable in

Appendix H. Separate 2 x 2 x 3 (Group x Complexity x Test Session) mixed design

ANOVAs were performed for the coefficients of variation (CV) of RT, premotor time,

motor time, and movement time. Tukey's HSD post-hoc analysis was performed to further

assess significant interactions.


Reaction Time


Analysis of the RT mean CV indicated a significant Test Session effect, F (2, 56) =

12.01, p < .05 (Appendix I). Thus, both of the groups demonstrated a similar pattern of

change in RT variability. Post-hoc analysis determined that RT variability decreased

significantly from the pretest to immediate retention test and was maintained through the

delayed retention test. These findings complement the results of the mean RT analysis in

that both groups behaved similarly across test sessions. Both groups demonstrated

improved RTs and decreased variability of responses from pretest to immediate retention

and sustained those improvements at the delayed retention test.

Premotor time. A significant Group x Complexity x Test Session interaction was

revealed from analysis of the premotor time mean CV, F (2. 56) = 3.75, p < .05.

(Appendix I). Comparison of the means found that both the group with and without PD

decreased premotor time variability for the complex movement from the pretest to the

immediate retention test and held the decrease stable through the delayed retention test.

Initially, premotor time variability for the two groups did not differ, however, the








immediate retention test CVs were significantly less for the group without PD than the

control group. This difference was alleviated at the delayed retention test.

Regarding the simple movement task, only the group with PD demonstrated a

decrease in the CV from pretest to immediate retention test, but did not maintain the

decrease with delayed retention testing. The CV for premotor times of the group without

PD decreased significantly from the pretest to delayed retention testing. A significant

difference between the CV means of the two groups was found only for the delayed

retention test

Overall, the premotor time variability parallels the premotor time mean changes for

both groups across training noting improvements in both measures. Also, the initial

measures of variability were not significantly different for the two groups across

movements of varying complexity, yet the control group demonstrated the greatest decrease

in variability for both arm-reaching movements.

Motor time. A significant Group effect, E (1, 28) = 7.29, p > .05, identified

overall a more variable motor time for persons with PD than the group without PD (mean

CV, .22 and .16. respectively). See Appendix I. Though the mean motor times of

persons with PD decreased across test sessions, the variability in motor times for these

individuals remained greater than that of persons without PD across testing sessions.


Movement Time


A significant Complexity x Test Session interaction was found for movement time

CV, F (2, 56) = 3.86, 2 > .05, Appendix I. Post-hoc comparisons revealed that across

test sessions, movement time variability for the simple arm-reaching task was greater than

that for the complex arm-reaching task. In addition, movement time variability decreased

for the complex movement from pretest to immediate retention relative to minor increases in

variability of simple movement. Second, a significant Group x Test Session interaction

was revealed for movement time CV, F (2, 56) = 5.19, p > .05, (Appendix I). Tukey's









post-hoc analysis demonstrated that pretest movement time variability was greater for the

group with PD and decreased to a level comparable to the group without PD.


Summary


Both the group with and without PD demonstrated similar values for response

variability across the testing sessions for RT and premotor times. Both groups also

demonstrated equivalent decreases in response variability across the test sessions for RT

and premotor times. At the pretest, persons with PD demonstrated significantly greater

variability for motor and movement times. Motor time variability for persons with PD

decreased across test sessions but remained greater than the variability for the control

group. In contrast, movement time variability for persons with PD decreased to a level

comparable to the control group. For both PD and control groups, movement time

variability was greater for the simple arm-reaching task than the complex arm-reaching

task.


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Table 7.

Descriptive Data for the Box and Block Test (BBT) scores for Day 1 and Day 2 by Group:
Parkinson's Disease and Control.


Group


Parkin n's Di s


( ntrnl


# Blocks Mean


SD Range


Day I

Day 2


38 74

41 74


Mean


Range


40- 80

45 84


a os %214 12 h g m m















420-

400-

380-
360-

340-
320-

300-

280-

260-
240-

220-

200-


Pretest


--- Simple

............... Com plex


I I
Imme Retention Del Retention

Test Session


Figure 5. Reaction time means and standard deviations for complexity x test session
interaction. Imme = immediate. Del = delayed.















280-

260

240-

220-

200-

180-

160-

140-

120-

100-


Preest
Pretest


----- Simple

- ........ ...... Complex


Imme Retention Del Retention

Test Session


Figure 6. Premotor time means and standard deviations for complexity x test session
interaction. Imme = immediate. Del = delayed.























-a-- PD

-...-... .. Control


SI
Pretest Imme Retention


Del Retention


Test Session












Figure 7. Motor time means and standard deviations for group x test session interaction.
Imme = immediate. Del = delayed.


190


170


150


130-


110-


90-














-0--- Simple
-........ . Complex



,. T


1800-

1600-

1400-
1200-

1000-

800-

600-

400-

200-

0-


Del Retention


Figure 8. Movement time means and standard deviations for complexity x test session
interaction. Imme = immediate. Del = delayed.


I
Imme Retention
Test Session


Pretest


~---
i ~-----~






60







80- PD
80
7- Control
70

2G 60

50-

40

E 30

20-

10




Group












Figure 9. Mean number of blocks and standard deviations for Box and Block Test group
effect.













CHAPTER 5
DISCUSSION, SUMMARY, CONCLUSIONS, AND IMPLICATIONS FOR
FUTURE RESEARCH



This study was designed to (1) examine the effects of PD and movement

complexity on response programming, (2) determine the differential effects of practice on

altering response programming in persons with and without PD, and (3) examine transfer

of the practice effect for fast arm-reaching movements to another upper limb motor skill.

The discussion of the results follows the same order to address the three investigated areas.


Discussion


Parkinson's disease results in a spectrum of movement difficulties including slowed

initiation and execution of movements, movement arrest, resting tremor, postural changes,

and an absence of associated, automatic movements. Delay in initiating movements,

termed akinesia, is one of the distinct movement problems associated with PD.

Controversy prevails in the literature concerning the occurrence and cause of akinesia

(Evarts, 1980; Montgomery, Gorman, & Nuessen, 1991; Zappia, Montesanti, Colao, &

Quattrone, 1994). Several researchers have reported deficits in the response programming

stage of information processing by persons with PD and have associated this deficit with

movement or response initiation delays (Harrington and Haaland, 1991; Stelmach et al.,

1987).

Response programming is the transformation of a selected, cognitive response code

to a motor response code as execution commands for the task. RT latency has been used as

a measure of programming time with the perspective that greater central nervous system

preparation time is required to coordinate and organize more complex movements. The

movement complexity effect is a statistically significant increase in RT as a result of








specifically increasing the complexity of a movement (Light & Spirduso, 1990). Older

adults are particularly sensitive to task complexity resulting in age-related slowing for RTs

(Fozard, Vercruyssen. Reynolds, Hancock, & Quilter, 1994). The effects of PD on

response programming and RTs must be differentiated from the effects of healthy aging on

RTs. For this study, two levels of movement complexity were manipulated by the number

of steps in a movement sequence (one to four) and number of directional changes in the

movement (zero to three) (Christina, 1992; Light, Reilly, Behrman, & Spirduso, in press).

RT latency can be fractionated by the demarcation of EMG activity onset into its

subcomponents of premotor time and motor time. From this division, the contribution of

central neural processing time (premotor time) can be distinguished from that of peripheral

processing time (motor time). In examining the basis for RT delays in persons with PD,

the delineation of premotor time from motor time provides a more sensitive and descriptive

means of RT analysis.

In this study, initial RT latencies of the PD group were not significantly different

from those of the control group. However, both groups demonstrated a movement

complexity effect for RT responses for the arm-reaching tasks of varying complexity.

Thus, the more complex movement took a greater time to prepare than the simple

movement. The significant difference in RTs between the two tasks verified that the tasks

represented two distinct levels of movement complexity. Examination of the fractionated

components of RT between the two tasks revealed that RT differences were specifically due

to longer premotor times for the more complex movement compared to the premotor times

for the simple movement. Because no differences were found for motor times between the

simple and complex task, the movement complexity effect on RT latencies can be

conclusively attributed to the premotor time component. Longer premotor times signify

that greater central neural processing time was required to prepare the complex movement

in comparison to the simple movement.








Effect of PD on Response Programming and Movement Time



Reaction Time


In the present study, the lack of a significant difference between RTs of the PD and

control groups, as well as similar group responses to complexity was unexpected and adds

to the controversy surrounding RT, akinesia, and PD. The contradictions and

inconsistencies concerning the relationship between RT and PD have stimulated research

aimed at discerning their causess. Inconsistent findings have been attributed to differences

among study samples, the true variability in the PD population, duration of PD, age of

onset of PD, severity of PD, medications, extremity affected, and types of experimental

tasks (Evarts, 1980: Montgomery et al., 1991; Rogers & Chan, 1988; Ruberg, Scherman,

Jovoy-Agid, & Agid, 1995).

In Table 8 the type of experimental task, mean age of participants, and mean RT for

persons in the present study are compared to those found in the literature on PD, simple

RTs, and response programming. As can be seen in Table 8, the PD group RTs for the

current study appear to be somewhat faster than those reported in the literature and that the

results of the present study are most similar to those of Rogers and Chan (1988).

Significant differences were not found in either study for mean simple RTs between groups

with and without PD. The experimental tasks and test conditions for these two studies are

alike in that both tested rapid flexion responses to a predictable environmental cue, though

Rogers and Chan (1988) tested the lower extremity and the current researcher tested the

upper extremity. These experimental similarities may account for the comparable findings

for these two studies. However, researchers testing other types of tasks have observed

group differences for mean RTs between persons with and without PD.

In the current study, the equivalent RT performances for the PD and control group

was an exceptional finding relative to the quantity of literature supporting group

differences. In the next section, the validity of this finding and possible explanations for








this outcome will be addressed. Following this discussion, the significance of the similar

findings for response programming between the PD and control groups will be considered.

Group similarity. The lack of significant RT differences between the participants

with and without PD could be accounted for in a variety of ways. Possibly the current

experimental design failed to have adequate power and therefore resulted in a beta error. A

lack of power may result from too few participants relative to the standard deviation of the

response variable, the size of the value designated as meaningful and significant, and the

significance level set for the study (Marks, 1982; Portney & Watkins, 1993). Recalculation

of the power analysis to determine the appropriate number of participants needed for this

study indicated that the 15 participant sample size per group was adequate. Specifically,

the RT standard deviation determined from this study's results did not exceed the standard

deviation used for the initial power analysis. The recalculation of power for this study

demonstrates that the RT data are representative of the true population mean. Other factors

which may have influenced the RT data outcome will be considered next.

Researchers have recognized that variability in the PD population may account for

discrepancies among RT studies. In this study, RT variability in persons with PD is a

possible explanation for the equivocal performance by the PD and control groups. For the

current study, the coefficient of variation (CV) was selected as a measure of response

variability. The CV accounts for variations in the magnitude of the mean by representing

the standard deviation as a proportion of the mean (Portney & Watkins, 1993). The CV for

persons with PD has varied in the literature from a value of .33 (Stelmach et al.; 1992) to a

value of .09 (Rogers & Chan, 1988). The sample size for each of these studies was limited

to seven individuals with PD. In comparison, the CV for the PD group in the current study

of .19 for the complex task and .17 for the simple task (Table 11) appears to be in the

middle of the range of variability. Only Stelmach et al. (1992) reported significant group

differences for the CV. However, in the current study, overall variability decreased

significantly from the pretest to the immediate retention test and was maintained through








the delayed retention test. Variability of performance, as measured by CV, does not

provide a plausible explanation for the RT outcome in this study as compared to other

studies (Evarts et al., 1981). The relatively greater amount of response consistency found

in the current study, however, warrants further consideration in future investigations.

Other potential explanations for equivalent RTs for the PD and control groups

include the participant's degree of motivation and the influence of depression on

motivation. No objective measurement of motivation was not attempted in the current

study. However, the offering of a financial incentive may have affected subject motivation.

Other reports in the literature concerning PD and RT did not report such incentives.

Motivation and performance may be influenced by both intrinsic and extrinsic factors and

achievement goals (Duda. 1993: Roberts, 1993). Each participant knew that they would

receive monetary compensation ($50.00) for completing the study, as well as a report of

their individual performance compared to the outcomes for both the PD and control group.

An additional bonus of $50.00 was awarded to the participant demonstrating the fastest

average response time on Day 3 for each PD and control group. The effects of the

monetary compensation, bonus, and performance information on participant motivation and

performance may have varied according to individual perceptions of rewards, incentives,

and achievement goals. Several participants with PD subjectively commented that at their

age money was not a strong incentive and that their particular interest in participating was to

see how they performed and how they compared to individuals without PD. These

subjective comments by the participants concerning the effect of monetary reward on

performance are supported in the literature (Grant. Storandt, & Botwinick, 1978). As

motivation was not directly assessed in this study, its effect on the findings can only be

speculated from experimenter casual observation and participants' comments.

An indirect measure of motivation is persistence in task performance (Duda, 1993).

Both groups attended all three practice and testing sessions and thus persisted in

performance across the three days achieving a 100 per cent attendance. Another indirect








index of participant motivation or potential for motivation is an objective evaluation for

depression. Individuals with depression may not attend, concentrate, or persist in learning

a new task as well as individuals who are not depressed. These differences in participation

and motivation may be reflected in lower performance scores for individuals who are

depressed. The RT results of studies reporting differences in depression scores between

the groups may have been influenced by the effect of depression on motivation and

performance (Harrington & Haaland, 1991). In the current study, a significant difference

for the mean depression score was observed between the two groups. If depression had

influenced performance outcome, slower RTs would be expected, as opposed to faster

RTs. The arm-reaching response scores for the three individuals with PD and depression

are in the similar range as the timed responses of the other PD participants. Depressive

states did not appear to influence the scores negatively and is thus ruled out as associated

with the lack of RT differences between the PD and control groups.

A third possible factor that could have influenced the RT results in this study were

the levels of medication in persons with and without PD. A review of the medication list

reported by each participant found no medications listed affecting RT (Barnhart, 1988).

Participants with PD were tested during an on-medication period for treatment of PD and at

the same time during the medication cycle for each of the test sessions. In this study, 13

participants were being treated with sinemet for PD and 7 participants were treated with

eldepryl in combination with sinemet. No subject reported a change in their medication

schedule or a change in their physical status from one test session to the next.

Pharmacological intervention for PD has been successful in treating bradykinesia,

rigidity, and tremor. Beneficial RT effects of medication, in particular L-dopa, have not

been confirmed to the same degree in the literature (Cutson. Laub, & Schenkman, 1995).

An exception is a study by Pullman et al. (1988) in which the researchers reported a lack of

dosage concentration effect on simple RT, yet an increase in choice-RT as plasma L-dopa

levels decreased. These researchers proposed that the differential effect of dosage on








simple and choice-RT was due to different neural circuitry involved in the two tasks.

Simple RT may be partially dependent on nondopaminergic paths, such as arousal systems.

Choice RT, however, may be highly dependent on higher level cortical processing

necessary for cognitive and complex motor behavior. A parallel may be suggested for the

effects of L-dopa comparing Pullman et al.'s study and this study examining simple RT for

simple and complex tasks. All movements in the current study were examined for simple

RTs with no significant differences found between the PD and control groups. Response

complexity can be altered by manipulating any stage of information processing. One

method could be varying the number of response choices (simple vs. choice-RT) and

another varying the degree of movement complexity. Both manipulations affect response

complexity by affecting separate and distinct stages of information processing: response

selection and response programming, respectively. The effects of medication on choice-RT

and movement complexity should thus not be equated.

According to Montgomery et al. (1991), the finding of high RT variability, yet high

MT consistency across studies with different samples of individuals with PD may be

attributed to a division of labor for motor initiation and motor execution. This division of

labor is delineated both anatomically and physiologically between the caudate nucleus for

motor initiation and putamen circuits for execution, respectively. Montgomery et al. (1991)

cited greater variability in dopamine loss in the caudate compared to the putamen as a

rationale for the variability in RT performance in persons with PD across studies. Such

variability across studies may account for overall RT differences observed in this sample of

persons with PD when compared to previous studies.

If variability in the loss of dopaminergic innervation (Kish, Shannak, &

Hornykiewicz. 1988) accounts for the variability in RT performance, are such differences

associated with age at PD onset or with duration of the disease? Ruberg et al. (1995) found

that the loss of dopaminergic innervation in the striatum of patients with PD was not

affected by age of onset but only by disease duration. According to Ruberg et al., an








individual with a 1 year duration of PD is less likely to have the same amount of

dopaminergic loss as an individual with a 15 year duration of PD. In the current study, the

individuals with PD varied in disease duration from 1 to 15 years. These duration

differences may have contributed to the lack of differences in RT between PD and control

groups. To test this possibility, the responses for the participant with a 1 year history of

PD were compared to the overall group mean. The RT values for the individual with a 1

year duration were within 2 standard deviations of the group mean, therefore duration of

PD did not appear to be an influential factor in the RT data.

Lastly, Evarts (1981) and Rafal, Friedman, and Clannon (1989) documented faster

RTs for the lesser involved limb in persons with PD compared to the more involved limb.

In the current study, 4 of the 15 participants with PD reported that their left arm was more

involved than their right arm. As all participants performed the arm-reaching tasks with

their right arm, the RTs for the 4 individuals with greater left side impairment may have

been slower if testing had been performed with this limb. Comparison of the RT values for

these 4 individuals with the group mean confirmed that their scores were within 2 standard

deviations of the mean and thus did not seem to affect the data as outliers.

From this examination of the RT data in comparison to previous studies and for

potential influential variables, no definitive conclusion can be made to justify the lack of RT

differences between the PD and control groups. Researchers have reported both RT

differences and no differences between persons with and without PD (Pullman ct al., 1988,

Rogers & Chan. 1988). Task differences and practice conditions among studies could

explain the discrepancies between the current study's findings and the literature. In the

current study, similar group responses were observed for RTs. as well as similar group

effects to movement complexity.

Movement complexity effect: Reaction time. For the pretest, a movement

complexity effect for RTs of the control group was expected and consistent with the

previous literature (Light & Spirduso, 1990; Light et al., in press). As the complexity of








the movement increased. RTs increased significantly. Observing a similar movement

complexity effect for the RTs of the PD group was not expected. In the following

discussion, this finding will be compared with the results and conditions for previous

response programming studies of persons with PD. The elements) of movement

complexity manipulated and the type of response task examined in these studies may be the

discriminating factors for identifying the response programming deficits in persons with

PD from the responses of healthy, age-matched persons.

In contrast to the results of the present study, Stelmach et al. (1987) determined that

the RTs for only the control group performing a repetitive, rapid index finger-tapping task

(1 to 5 taps) demonstrated a linear increase of RT with respect to increases in sequence

length. Evidence for a programming deficit in persons with PD was further supported by

an overall prolonged first intertap interval compared to the control group. According to

Stelmach et al. (1987), this finding indicated that persons with PD responded to the first tap

with similar RTs regardless of sequence length, followed by ongoing monitoring to

produce the correct number of subsequent taps. A comparative analysis of the simple task

MT and the first interswitch interval MT for the complex task was not conducted for this

study, however, such an analysis may be a means to examine differences in programming

execution between the groups. This analysis will be performed in the future to examine

movement execution differences between persons with and without PD.

Harrington and Haaland's outcomes (1991) were similar to those of Stelmach et al.

(1987). Their findings supported the view that persons with PD have a deficit in response

programming influenced by response complexity and sequence length. These researchers

found significant RT differences between persons with PD and a control group performing

repetitions of different, functional hand postures varied by sequence length (1 to 5). The

PD group was less influenced by sequence length for the different hand postures than the

control group. In contrast, both groups demonstrated a movement complexity effect for








sequences of identical hand postures. The hand postures included pressing a button,

hitting a lever, and grasping a handle.

Comparing the results of studies on PD and response programming provides an

interesting background for the results of the current study. Harrington and Haaland (1991)

determined a complexity effect for identical repetitive hand postures in persons with PD,

whereas Stelmach et al. (1987) did not find a complexity effect for identical, repetitive

finger-tapping in the PD group. Response programming deficits in the PD population were

apparent to Stelmach et al. (1987) for all levels of the task studied. Harrington and Haaland

(1991) did not observe programming deficits until the sequence of the task response was

varied by changing the functional hand postures as opposed to requiring the same hand

postures in repetition. From a theoretical perspective, discrepancies such as these in the

literature are difficult to explain. If persons with PD are as sensitive to complexity changes

manipulated by sequence length as demonstrated by Stelmach et. al. (1987), one would

anticipate similar findings for the repetitions involving identical, hand postures. Based on

the number of digits and proximal stabilization required to perform the two tasks, repetitive

finger movements appear less complex than repetitive identical hand postures. However, a

response programming deficit was found for persons with PD dependent on sequence

length for a simple finger-tapping task but not for the more complex task of repetitive

identical hand postures. Harrington and Haaland (1991) found further that a difference in

response programming performance between persons with and without PD dependent not

only on response sequence length, but also on the movement complexity issue of different

versus same hand posture in sequence.

The findings by Jones et al. (1994) also demonstrated programming deficits in

persons with PD compared to a control group for the advanced preparation of button-

pressing sequences. The control group demonstrated greater response preparation time for

sequences of three or more presses, whereas the PD group RTs were not affected by

change in sequence length. In the Jones et al. study, persons with PD did not exhibit a








movement complexity effect for sequence length, whereas the findings for the current study

demonstrated similar group responses to movement complexity defined by sequence length

and the number of directional changes. In addition to task differences, the combination of

directional change and sequence length may have had a different effect on response

programming in the current study than sequence length alone.

Similar to the findings of the current study, Rafal et al. (1987) found no differences

in the response programming effects on simple RTs for persons with PD performing finger

press sequences of 1 to 3 parts compared to control groups. Thus, similar movement

complexity effects on RT were determined for the PD and control groups. A

methodological discrepancy between the Rafal et al.(1987) study and the present study is

that Rafal et al. averaged the RTs for the right and left limbs. Averaging limb RTs may

have masked differences between the PD and control groups due to variations between limb

RTs for persons with PD (Evarts, 1980). Furthermore, Rafal et al. (1987) did not

specifically age- and gender- match the control group to the PD group. For example, an

age pairing was included with an age discrepancy of 8 years. In addition, the gender ratio

was 5 males and 3 females for the PD group, whereas the paired controls included 2 males

and 6 females. Since RTs are slower with increasing age and males have faster RTs than

females (Spirduso, 1995), the group differences for age and gender may have affected the

RTs in the Rafal et al. study In comparison, typical age pairings in the current study were

2 years or less with identical and complete gender-matching of control participants to

participants with PD.

The evidence for response programming deficits in persons with PD. as measured

by RT latency, is inconsistent based on a comparison of the four studies just reviewed and

the current study. Findings for a movement complexity effect in persons with PD are

inconclusive and contradictory relative to the sequence length effect across studies and

response tasks. Those studies in which RT did not differ between the PD and control

groups may have reflected the amount of movement complexity in the tasks. If the extent








or type of movement complexity was not adequate to generate response programming

differences, similar RTs for persons with and without PD may have resulted (Jones et al.,

1994; Rogers, 1991).

Though a movement complexity effect was found in the current study, the amount

or type of complexity in the two arm-reaching tasks in this study may not have been

adequate to differentiate the response programming problem of persons with PD from the

control group. The types of complexity manipulated in the various studies reviewed may

also be relevant to the response programming performance. The complex arm-reaching

task in the current study can be described as an aiming task with four targets of identical

size and force production requirement. The more complex movement entailed a movement

sequence with three different amplitudes, three directional changes, and two different

angles of directional change. Describing task differences based on amount and type of

complexity may be pertinent to identifying the response programming deficits in persons

with PD, especially when comparing studies and tasks.

Studies which demonstrated deficits in RTs between PD and control groups

manipulated the type of complexity by varying sequence length for rapid index finger-

tapping (Stelmach et al., 1987), repetitions of identical versus different hand postures

(Harrington & Haaland. 1991), and button-pressing sequences in a series (Jones et al.,

1994). Another type of movement complexity manipulation may be based on the task

demands for the anatomy and musculature. For instance, complexity may vary according

to the number of body sides, the number of joints, or perhaps the degree and sequencing of

proximal to distal musculature required to perform the task (Light & Spirduso, 1990; Van

Galen, Van Doom, & Schomaker, 1990). The three studies noted here all entailed a distal

limb requirement for finger manipulation. In the current study, relatively more proximal

muscle control was required with a more gross movement of the hand and fingers to press

the target switches. Programming demands may possibly be greater for motor tasks

requiring finger manipulation compared to those that do not (Van Galen et al., 1990; van








der Plaats & van Galen, 1990). If programming demands are greater for tasks involving

finger manipulation, then differences in RTs between PD and control groups could be

dependent upon the degree of finger control required. Examining this hypothesis is beyond

the scope of the current study but it affords implications for future investigations.

Movement complexity effect: Premotor time. A complexity effect for premotor

times has been reported previously for healthy individuals (Sheridan, 1984) and supports

the concept of the movement complexity effect for RTs. The pattern of premotor findings

for simple and complex movements in the current study was analogous to that for RTs for

both PD and control groups. The longer premotor times observed for the more complex

movement indicated the movement complexity effect for RTs for both groups. More

central nervous preparation time was required to organize the complex movement compared

to the simple movement. As with RT expectations, the investigator anticipated longer

premotor times for the PD group than the control group. Though RTs have been reported

to be longer in persons with PD, fractionation of RTs for tasks of varying complexity has

been reported only once prior to the current study (Sheridan et al., 1987).

Sheridan et al. (1987), similar to the current researcher, examined response

programming for persons with PD by manipulating movement complexity. Fractionated

RT and MTs were dependent variables common to both studies. The two studies differed

in that Sheridan et al.. first, used an adaptation of the Fitts paradigm (1954) to manipulate

target aiming complexity and second, compared choice-RTs to simple RTs. The present

researcher examined only simple RTs. From this perspective, a comparison of the results

of these two studies is pertinent and beneficial.

First. Sheridan et al. (1987) found that persons with PD had significantly longer

premotor times than the control group for the simple RT condition, but that premotor times

were not significantly different under the choice-RT condition. In contrast to Sheridan et

al., the findings for the current study demonstrated that both PD and control groups had

similar premotor times relative to variations of movement complexity under a simple RT








condition. Sheridan et al. concluded that persons with PD had an impaired ability to use

the advanced information provided in the simple RT condition to reduce the movement

preparation time. Based on the current study, an alternative conclusion is made supporting

similar response programming capabilities for persons with and without PD relative to the

use of advanced information in a simple RT condition.

Stelmach and Worringham (1990) suggested that Sheridan et al.'s finding of longer

premotor times for persons with PD may have been influenced by on-going learning of the

psychomotor aspects of the task dynamics. As target aiming required a successful

interaction between the participant, a lever, and a computer cursor, Stelmach and

Worringham (1990) speculated that greater reliance on closed-loop feedback may have

precluded the programming of this task in an open-loop manner. Target aiming in the

current study was accomplished by the participant's own limb and did not require use of an

intermediate instrument, such as a lever, for control. From this comparison,

preprogramming may have occurred more easily for the direct limb aiming task.

Second, Sheridan et al. (1987) also observed no significant group differences for

premotor times based on the manipulation of the index of difficulty for target aiming. From

these findings, they suggested that the ability to construct a motor program is not impaired

in persons with PD. Similarly, the current study determined that both PD and control

groups demonstrated similar premotor times relative to variations of movement complexity.

Sheridan et al.'s premotor findings for movement complexity in aiming tasks are similar to

the movement complexity findings for the arm-reaching tasks of the current study.

Sheridan et al.'s study and the current study indicated similar response programming

capacities by persons with and without PD for rapid, aiming tasks of varying movement

complexity or difficulty. Sheridan concluded further that the details of the motor program

are preserved in PD.

Discrepancies among the findings of studies of persons with PD for fractionated

RTs may be attributed to differences in the processing of EMG data and the procedure used








to designate EMG onsets. Researchers have not clearly reported their procedures such that

exact replication is possible (Stelmach et al., 1992; Sheridan et al. 1987). Furthermore, the

procedures for EMG onset designation have differed in the literature on EMG analysis from

the use of visual observation to the use of a standardized algorithm (Turker, 1993, Walter,

1984). Moreover, researchers have reported that the surface EMG signal of persons with

PD has a lower amplitude with inconsistent discharge rates (Glendinning & Enoka, 1994).

Standardization of EMG onset designation procedures would minimize discrepancies due to

such variations in the signal.

Motor time. Motor times reflect peripheral neuromuscular and physiological

processes required to initiate and develop muscle activity. The significantly longer pretest

motor time (148 ms) for persons with PD compared to the control group (119 ms) found in

the current study was inconsistent with previous studies. Motor times have been found to

be constant across experimental conditions with no differences between persons with and

without PD (Pullman, et al., 1988; Sheridan et al., 1987; Stelmach et al.. 1992).

In the present study, the lack of significant differences in motor times between the

PD and control groups, was consistent with previous studies. The overall mean motor

times were 126 ms for persons with PD and 108 ms for persons without PD in the current

study. These values are comparable to the overall mean motor times of 103 ms and 119 ms

for the PD and control groups found by Sheridan et al. (1987).

In contrast, Montgomery (1995) reported that motor times are often more abnormal

for persons with PD than premotor times. He noted that in circumstances when movement

begins against a background of antagonist activity, prolonged motor times in persons with

PD may be due to abnormal agonist motor unit recruitment and synchronization, as well as

abnormal antagonist derecruitment (Montgomery et al., 1991). In the present study,

participants initiated their arm movement against a background of resting or silent agonist

electromyographic activity as monitored on the oscilloscope. The antagonist triceps muscle








was not monitored for resting levels. Antagonist muscle activity cannot be ruled out as

influential on motor times in persons with PD in the current study.

Glendinning and Enoka (1994) also reported that motor unit activity differs in

persons with PD compared to healthy, aging individuals and may contribute to akinesia and

bradykinesia. Though Glendinning and Enoka (1994) did not specifically address motor

times, they characterized motor unit behavior in persons with PD as having inconsistent

discharge rates, increased number of motor units activated at low forces of contraction, and

increased muscle coactivation. Such changes could account for longer motor times in

persons with PD as observed in the present study.

Secondary disuse and weakness may also alter motor unit activity in persons with

PD resulting from a slowing of movements, rigidity, and less active lives (Glendinning &

Enoka, 1994; McGoon, 1993). Differences in fitness and lifestyle activity levels between

the PD and control groups in this study may have contributed further to the differences in

initial motor times (Spirduso; 1995).


Movement Time


Slowed MT is one of the most pervasive and debilitating characteristics of PD

(Delwaide & Gonce, 1993: Isenberg & Conrad, 1994; Montgomery, 1995; Zappia et al.,

1994). Slowing of movement is also characteristic of normal aging (Haaland, Harrington,

& Grice, 1993), though controversy exists concerning the extent and nature of age-related

differences (Pratt, Chasteen, & Abrams, 1994). As only a trend towards significant group

differences for the MTs of the complex task was found for the current study, additional MT

analysis was warranted. The coefficient of variation (CV) for MT was subsequently

analyzed to examine the possible effects of performance variability on mean MT data. For

the pretest, the MT CV was significantly greater for the PD group than the control group.

A greater degree of response variability for the PD group may have influenced their mean

MT score resulting in a lack of MT differences between the groups.











Persons with PD demonstrated similar RTs, premotor times, and MTs for the

performance of rapid arm-reaching movements. Though this finding was unexpected, it

demonstrates the specificity with which PD affects movement complexity, response

programming, and execution. Persons with and without PD responded to manipulations of

movement complexity in the same manner as healthy elderly individuals with increased

processing time for more complex or difficult movements. Differences in motor times may

be secondary to the disease or disuse effects. Similar MTs for the complex task for both

groups may have been a factor of greater MT variability for persons with PD.


Effects of PD on Practice Effects for Response Programming and Movement Time


Practice is viewed as the most influential variable affecting response speed and skill

acquisition (Ericsson & Charness, 1994, Lee, Swanson, & Hall. 1991; Schmidt, 1988;

Spirduso, 1995). For the healthy older population, extended practice can decrease

information processing time and subsequently improve the speed of movement responses

to environmental stimuli and the speed of skilled performance (Murrell, 1970; Spirduso,

1995). A slowing of the physical speed with which older adults react and move is

characteristic of the normal, aging process (Spirduso, 1995). This decline in speed impacts

on every aspect of the aging individual's life including activities of daily living,

employment, and recreational and social pursuits. Individuals with PD are particularly

slower initiating and executing movements compared to healthy age-matched individuals

(Montgomery, 1995). Consequently, the impact of slowed behavior on daily activities is

compounded for persons with PD. Researchers to date have reported deficits in initial

levels of motor performance for persons with PD and with practice, limited improvement in

motor performance for persons with PD compared to the control groups (Frith et al., 1986;

Harrington et al., 1990; Soliveri et al., 1992; Worringham & Stelmach. 1990). The benefits








of practice on response and movement speed for persons with PD is critical to an

understanding of the disease, motor behavior, and effective interventions for PD.

One of the major purposes of the current study was to explore and compare the

benefits of practice on fast movement responses for persons with PD compared to the

healthy, aging population. The effects of practice on the response programming of rapid

arm-reaching tasks for persons with PD compared to age- and gender-matched controls will

be discussed in the following section. Practice effects for response programming will be

addressed relative to the dependent variables of reaction time and fractionated RT. To date,

the effect of practice on fractionated RT has not been examined with the PD population.

The effect of practice on the speed of execution or movement times will also be addressed.


Reaction Time


Practice decreases the movement complexity effect in healthy-young adults

(Fischman & Lim, 1991; Fischman & Yao, in press; Hulstijn & Van Galen, 1983, Norrie,

1967a, 1967b; van Mier & Hulstijun, 1993) and between healthy-young and old adults

(Light et al., in press). With practice or extended practice, mean RTs for the performance

of complex tasks decreased to similar mean RT values for simple tasks. The time required

for response programming or cognitive preparation of a movement response, in particular

for complex tasks, is sensitive to practice.

In the present study, both participants with and without PD benefited from practice

for response programming of the complex arm-reaching task. The significantly decreased

RTs at the immediate retention test for both groups demonstrated the relatively immediate

benefits of practice. More importantly, the effect of practice on RTs for both groups was

sustained across a 48 hour rest interval. Sustaining the performance level across a retention

period indicated a learning effect as compared to a temporary effect of practice.








Practice Effects and PD


The current study's finding that persons with PD benefited similarly from practice

for response programming when compared to persons without PD is striking and a very

significant finding. The previous literature has characterized the benefits of motor skill

practice for persons with PD as limited with a slower rate of improvement and significantly

less improvement compared to the outcomes for persons without PD (Frith et al., 1986;

Harrington et al., 1990; Soliveri et al., 1992; Worringham & Stelmach, 1990). In the

present study, the effect of a 2 day period of practice (120 trials each task) for response

programming rapid, arm-reaching tasks was examined. Motor tasks in the practice

literature for persons with PD have varied including target tracking with a semi-predictable

target, target tracking with a novel control system, pursuit rotor time-on-target, timed

sweater buttoning, and discrete aiming (Frith et al., 1986; Harrington et al., 1990; Soliveri et

al., 1992; Worringham & Stelmach, 1990). Target tracking or pursuit tasks can be

classified as closed-loop tasks requiring continuous feedback and on-line monitoring for

successful performance. In comparison, the timed buttoning and discrete aiming tasks can

be described as open-loop tasks which are preprogrammed when performed rapidly

without the availability of feedback (Schmdit, 1988). The rapid, arm-reaching task in the

current study is also an open-loop task and compares best to the timed buttoning and

discrete aiming tasks. This distinction between closed- and open-loop tasks may be critical

in distinguishing the deficits in motor behavior for persons with PD and the effects of

practice as an intervention. A comparison of these studies to the current study is discussed

next.

Overall, Frith et al. (1986) determined that persons with PD increased the time-on-

target with practice of target tracking using a semi-predictable and novel control system.

However, the control group improved better and faster than the PD group, especially for

target tracking with a novel control system. Frith et al. (1986) categorized their target-

tracking tasks within the scope of open-loop tasks. As a rationale for this categorization,








these researchers noted that to perform this variation of a continuous tracking task, the

learner must make temporary stimulus-response attachments or associations much like

those required in a choice-RT condition for a discrete task. From their perspective, practice

of these attachments led to program and skill development for continuous target-tracking.

Improvements in arm-reaching programming for persons with PD comparable to

persons without PD in the current study and limited improvement in time-on-target (Frith et

al., 1986) for persons with PD, regardless of the task, may have been due to differences in

the number of environmental stimuli and their associated responses. The time-on-target

task required continual monitoring for changes in the stimulus and then selection of an

appropriate motoric response, whereas the arm-reaching study had a one-to-one, stimulus

response relationship. Thus. a slower rate of improvement in the target tracking study may

have been associated with the number of response choices. Frith et al. (1986) also

attributed the slower rate for skill acquisition by persons with PD to a difficulty in the use

of previously developed programs or skills in a novel circumstance or to a novel stimulus

and a greater reliance on feedback early in learning. The rate of skill acquisition was not

examined in the current study with only performance outcomes being examined on Day 2

and Day 3 following completion of practice.

Harrington et al. (1992) also studied continuous tracking performance in persons

with PD on a pursuit rotor task. Their purpose was to examine procedural memory and

skill learning relative to basal ganglia function by comparing the pursuit rotor, motor task,

to a visuoperceptual task, mirror reading. To summarize the tracking performance, persons

with PD (Harrington et al., 1990) demonstrated similar initial performance levels; improved

with practice across three days, however, less so compared to the control group; and

responded to increases in task difficulty similar to the control group. This pattern of

findings parallels that for the current study with one major exception. Persons with PD

practicing the two, arm-reaching tasks improved to the same degree for the control group.

Thus, the rates of improvement differed in the pursuit rotor task with the PD group never








achieving the level of performance of the control group. In contrast, Harrington and

Haaland (1992) found that the PD and control groups demonstrated similar initial

performance levels for mirror reading, as well as similar benefits to practice. In the current

study, similar performance improvements were achieved by Day 2 of practice for the

complex, arm-reaching task though the intermediate rate of performance change was not

analyzed.

Two other practice studies involving persons with PD are more closely aligned with

the current response programming study for arm-reaching tasks (Worringham & Stelmach,

1990: Soliveri et al., 1992). First. Worringham & Stelmach (1990) examined the effects of

practice on the preprogramming for a discrete aiming task under simple and choice-RT

conditions. Stelmach and Worringham (1990) found that persons with PD significantly

decreased RTs only for the simple condition while the control group significantly improved

RTs for the 4- and 8-choice conditions. These researchers concluded that persons with PD

can preprogram movements given adequate practice and familiarity with a task. The

equivalent benefits of practice for persons with and without PD determined in the current

study further support Stelmach and Worringham's conclusion.

Stelmach and Worringham (1990) also observed initial similar simple and choice-RT

responses for the PD and control groups though improvements for simple RT occurred at a

slower rate for the PD group. Rates of skill acquisition are not comparable for the current

study to the discrete-aiming study, however, they would be of interest due to the similarity

in tasks and amount of practice. Stelmach and Worringham (1990) accounted for the

slowed rate of change by speculating that the PD group began with a single strategy of

response planning to the onset signal whether the condition was simple or choice-RT, then

progressed with practice to differentiating strategies for the simple and choice-RT

condition. Furthermore, persons with PD did improve somewhat in the 2-choice RT

condition. Stelmach and Worringham judged that improvements were based on the

potential to partially preprogram 2-choice RT conditions. Such improvements may be








indicative of response-response compatibility effects on response programming (Light &

Spirduso, in press). The additional distinction in practice effects for simple and choice-RT

conditions in persons with PD extends the support for the view that the neural path for

response selection may be dopaminergic whereas the path for response programming may

not (Pullman et al., 1988).

Second. Soliveri et al. (1992) approached the study of practice in persons with PD

from a more functional, ecological perspective by using the familiar task of cardigan

buttoning. Their intent was to test the capacity in persons with PD for improvement of

motor performance and the extent to which learning demands attention. Soliveri et al.

(1992) found, as expected, that persons with PD button slower than the control group.

Both groups improved with practice, but the control group reached a plateau, perhaps

experiencing a ceiling effect. The rate of improvement with practice of buttoning alone was

similar between the groups. With the introduction of a secondary simultaneous task, foot-

tapping, both groups experienced detriments to performance though it had a greater effect

on slowing the buttoning speed of the PD group. Continued practice by the control group

of buttoning and foot-tapping eliminated the effect of interference from the tapping task on

buttoning speed. However, dual-task practice by the PD group did not have equivalent

performance benefits. Soliveri et al. (1992) concluded that persons with PD improved in

performance with practice, however at a slower rate than controls. They posed that the

rate-limiting factor for improvement may be the primary motor system dysfunction in PD as

opposed to a motor learning deficit. For this reason, they suggested that persons with PD,

even with extended practice, would never achieve the performance of persons without PD

on speeded skilled tasks.

In contrast to Soliveri et al.'s findings (1992), in the current study equivalent RTs

were determined both initially and following practice for initiation of rapid, arm-reaching

tasks of varying complexity for persons with and without PD. From a theoretical

perspective, persons with PD in the current, arm-reaching study demonstrated effective








response programming and equal benefits of practice on motor learning. As commented by

Soliveri et al.(1992), laboratory tasks often do not represent the complexity of daily,

functional activities. The remarks of Soliveri et al.(1992) are critical when the implications

for laboratory findings are extended to the real world for persons with PD. Certainly

differences exist between the buttoning task and the arm-reaching tasks relative to

movement complexity. The buttoning task requires repetitive, bimanual coordination of the

upper extremities, particularly the fingers and thumbs for fine motor manipulation, and can

be performed with relative ease without visual feedback. The arm-reaching task was a

novel task for the participants requiring sequencing of arm reaches based on directional

change and aiming for targets. The fine-motor manipulation and coordination was absent

in the arm-reaching task and may be the defining factor for differences in improvement

capacity for persons with PD.

Fractionated reaction time: Premotor time. In this study, the parallel decrease in

premotor and RTs for both the PD and control groups due to practice was consistent with

the practice literature for healthy individuals (Clarkson & Kroll, 1978; Lofthus & Hanson,

1981). However, the similar effect for persons with PD has not been previously reported in

the literature. The effect of practice on motor learning and response programming relative

to fractionated RTs in persons with PD is a new contribution to the literature. With

practice, persons with PD improved the cognitive processing component of reaction time in

preparing the more complex movement and demonstrated relatively lasting effects on

premotor time. Such sustained improvements have significant implications concerning the

use of practice for re-training motor behavior in Parkinsonian patients.

Fractionated reaction time: Motor time. Motor times typically remain constant

across practice sessions for healthy individuals though exceptions have been noted

(Lofthus & Hanson, 1981). In this study, overall mean motor times decreased from the

pretest to immediate retention test only for persons with PD, while motor time remained

consistent for the control group. The improvement in motor times for the PD group








persisted without further significant change at the delayed retention test. Variability in

motor times may account for the distinct findings for persons with PD, yet the mean CV for

motor times was significantly greater for persons with PD than the control group across all

conditions.

A change in neuromuscular coordination or adaptation may also account for the

change in motor times in persons with PD from the pretest to the immediate retention test.

Glendinning and Enoka (1994) proposed that, due to changes in motor unit behavior with

PD, strength training may improve performance and function in persons with PD. Though

participants in the current study did not participate in strengthening exercises, with practice

participants with PD may have benefited from increased familiarity with the task and

heightened neuromuscular activity. Possible decreases in motor times for persons with PD

occurred with improved consistency of motor unit discharge rates or decreases in muscle

coactivation


Effects of PD on Practice for Movement Time.


Across age groups for healthy individuals, practice is a critical variable for

improving the speed of a response (Camahan, Vandervoort. & Swanson, 1993; Lee,

Swanson. & Hall. 1991; Light et al., in press; Salthouse & Somberg, 1982). Fast

responses are dependent upon both RT and MT components (Spirduso, 1995).

Behaviorally, MT is the speed with which individual can move their limbs and is related to

the peripheral contractile processes of the muscle. Slowness in the execution of

movements has a significant impact on the performance of everyday activities whether such

slowness is due to healthy aging or disease processes such as Parkinson's. Intervention to

maintain speed of performance is thus advantageous and important for both populations.

With practice, persons with PD improved the speed of buttoning under both single

and dual-task interference conditions (Soliveri et al., 1992), though group differences

persisted. For the present study, the decrease in movement times for both PD and control








groups practicing the complex movement was consistent with the literature (Light et al., in

press). The fact that improved MT was maintained for both subject groups upon delayed

retention is one of the most important findings in this study. Practice may be particularly

beneficial for increasing the performance speed of persons with PD. For the PD group,

practice also improved within-participant MT consistency as seen by the significant

decrease in CV from pretest to immediate retention and the maintained improvement

through the delayed retention test (See Appendix J). In addition to improved movement

execution speed, improved consistency of performance is an extremely important benefit of

practice.

Furthermore, Soliveri et al. (1992) demonstrated that with practice the interference

effects of a secondary task on buttoning speed diminished. This paradigm was used to test

the degree of automaticity achieved with practice. Although the dual task paradigm was not

used in this study, sustained performance at the delayed retention test is a powerful test and

indicator of motor learning effects.


Feedback and Goal-setting as a Practice Variable


The use of summary feedback throughout the practice sessions may have served as

an additional motivating factor for task persistence and performance improvement by the

participants (Salmoni, Schmidt, & Walter, 1984). The use of feedback has not been

reported previously in the literature relative to persons with PD. In the current study,

participants received summary feedback for total response time for every other trial and

immediately following completion of a set of 10 trials. Participants were encouraged to use

this information to monitor their progression and to set goals for improvement of speed of

performance. On Day 2, the experimenter also compared the participant's response time

scores for the first set of trials on Day 2 with the final response times for the last set of

trials on Day 1.








Summary


Persons with PD benefited similarly to practice of the two, fast arm-reaching tasks

for RT, premotor time, and MTs when compared to persons without PD. In particular,

response programming and movement execution speed of the more complex task improved

with practice. The movement complexity effect was sensitive to practice for both PD and

control groups with the effect diminished by practice. These findings are significant and

important. Though performance improvements have not been consistent across practice

studies in the PD population, this study demonstrated the benefit of practice and the

capacity to learn in the performance of fast, predictable arm-reaching responses. Persons

with PD were able to use a predictable, environmental stimulus as a cue for programmed

responses of rapid aiming with arm-reaching. In addition, a learning effect for these

improvements was sustained across a 10 minute and 48 hour rest interval. Determining

this learning effect for persons with PD is important in justifying practice as an effective

rehabilitation intervention to improve motor performance in persons with PD.


Transfer

In motor learning, the issue of transfer concerns how learning one task affects the

performance or learning of another task. Motor skill transfer is valuable when teaching

similar skills or developing rehabilitation strategies to maximize learning time and

intervention (Schmidt & Young, 1987; Winstein, 1991). Transfer capabilities have been

demonstrated for older adults. Older adults, practicing novel video games, not only

improved their video scores but also demonstrated generalization of the skill to performance

of a 2-choice RT task (Clark, Lanphear. & Riddick, 1987: Dustman, Emmerson, Steinhaus,

Shearer. & Dustman. 1992).

The Box and Block Test, a timed test of manual dexterity, was used in the present

study as the transfer test for the practice of the rapid, complex arm-reaching task. The

overall mean BBT scores for the control group (66 blocks) was consistent with the








normative data for 360, healthy participants, mean age of 72 (68 blocks) (Desrosiers et al.,

1994). The PD overall mean BBT score of 56 blocks was significantly less than the

control group, although it was higher than the average score for a group of 34 subjects with

varying upper limb, neurological impairments (Desrosiers et al., 1994); (42 blocks). To

date, researchers have not specifically examined the relationship between Box and Block

Test scores for persons with and without PD.

Scores on the BBT increased by 2 blocks from Day 1 to Day 2 for both groups with

this increase approaching significance. A direct conclusion for transfer of arm-reaching

practice to Day 2 Box and Block Test scores cannot be made without additional PD and

control groups which did not practice the arm-reaching tasks. However, Desrosiers et al.

(1994) noted that the Box and Block test-retest reliability for healthy individuals (M = 72

years) performed across an average interval of eight days was an intraclass correlation

coefficient (ICC) of .90. For individuals with disabilities affecting the upper extremity (M

= 75 years), the test-retest reliability across the eight day period was ICC .97. The test-

retest for the BBT in the current study using Pearson's correlation coefficient was .86 for

the control group and .98 for the PD group. The test-retest scores were thus significantly

correlated for both groups and both groups demonstrated an improvement in Box and

Block Test scores from Day 1 to Day 2.

In a study of 15 older adults with cerebral vascular accidents and matched-controls,

Box and Block Test scores significantly improved by 1 block from pretest to posttest

within a 1 week interval, regardless of whether or not the groups participated in brief,

upper extremity exercise (Pearson, Smyth, Pendergrass. Longway, & Freund; manuscript

in preparation). In the current study, participants with and without PD improved by 2

blocks across a 2 day interval, though both groups had practiced the arm-reaching tasks for

120 trials each prior to the BBT on Day 2. The improvement differences between the

current study and the Pearson et al. study may indicate transfer effects for the current study

and warrants further investigation.








The Pearson product moment correlation was performed as a test of association

between the BBT scores and the complex task for Day 1 and then Day 2. The variables of

RT and MT were correlated separately with the Box and Block Test. Of particular interest

when comparing the Box and Block Test scores and the arm-reaching task is a lack of

association for performance of the two tasks, particularly by persons with PD. If

practicing the arm-reaching task provided and element of transfer to the Box and Block

Test, then RT or MT would be expected to be negatively correlated with Box and Block

Test scores. No association was found between the complex arm-reaching task RTs and

MTs and the BBT scores for the PD group. Significant, negative associations were found

for the control group with BBT scores relative to RT on Day 1 and with MT relative to Day

2. Though the associations for the control group were inconsistent across Day 1 and Day

2, the correlations did indicate a potential performance association between the two tasks

for the control group.

Box and Block Test scores were significantly different between the groups with and

without PD. As discussed previously, finding the BBT scores to be different but no group

differences in the RTs for the arm-reaching tasks is important to the understanding of the

motor problems in PD. The BBT score, a timed, validated task for manual dexterity, more

closely represents the problem of bradykinesia associated with PD. The predominant

component of the BBT is movement execution as compared to movement preparation or

initiation. Bradykinesia is defined as a slowing of movement execution. Timed functional

tasks, similar to the BBT, may be pertinent in the evaluation of motor dysfunction in PD,

as well as in reassessment following intervention (Soliveri et al.. 1992; Podsiadlo &

Richardson, 1991). An important, desirable outcome of rehabilitation intervention for

persons with PD is the successful performance of daily activities in a safe and efficient

manner. The significant difference in Box and Block Test scores for persons with and

without PD, as determined in this study, points to the potential application of timed

functional movements in both rehabilitation and research efforts with persons with PD.








Transfer Summary


A definitive conclusion cannot be made concerning the transfer of practice and

learning of the arm-reaching tasks to the performance of the BBT of manual dexterity.

Though both PD and control groups improved BBT scores from Day 1 to Day 2, the

improvement only approached significance. Comparison to PD and control groups who

did not practice the arm-reaching tasks would be necessary to differentiate a transfer effect

from a test-restest effect. Correlational analyses did not further support an association

between arm-reaching task speed of performance and BBT scores, in particular for persons

with PD. Significant differences in BBT scores between the PD and control groups

provided definite evidence for a deficit in motor performance in persons with PD.


Summary


The purposes of this study were to: (1) determine the performance differences

between persons with and without PD for each component of rapid movement responses of

varying complexity, (2) examine the differential effects of practice on altering each of the

movement response components in tasks of varying complexity for persons with and

without PD. and (3) determine transfer of the practiced rapid movement responses on

performance of an upper limb motor skill. Specifically, the effects of PD. movement

complexity, and practice were studied.

Persons with PD and age- and gender-matched controls practiced two, rapid arm-

reaching tasks of different movement complexity. Movement complexity varied between

the two tasks by the number of steps in the movement sequence and the number of

directional changes in the movement. Participants practiced each task for 120 trials across a

2 day period. Response programming was studied by analyzing the overall RT latency of

each movement and the fractionated subcomponents for RT: premotor and motor time.

Premotor time represents the contribution of central nervous system processing to RT,

whereas motor time is the peripheral component. A learning effect for practice was




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