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Negative BOLD and Aging: An fMRI Investigation

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PAGE 1

NEGATIVE BOLD AND AGING: AN fMRI STUDY By KEITH MATTHEW MCGREGOR A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2006

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Copyright 2006 by Keith Matthew McGregor

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This thesis is dedicated to Kristi Michelle Stahnke.

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iv ACKNOWLEDGMENTS This project could not have been complete d without the guidance and friendship of Dr. Keith White, to whom I am so very much grateful. I would also like to thank Dr. Bruce Crosson for his steadfast leadership and generosity and for providing the nurturing environment for this endeavor. Finally, I woul d like to acknowledge Dr. Ira Fischler, Dr. Keith Berg, Michelle Benjamin, Dr. Jason Cr aggs, Dr. Timothy Conway, my family and friends for their support and assistance thr oughout the completion of this project.

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v TABLE OF CONTENTS page ACKNOWLEDGMENTS.................................................................................................iv LIST OF TABLES............................................................................................................vii LIST OF FIGURES.........................................................................................................viii ABSTRACT.......................................................................................................................ix CHAPTER 1 INTRODUCTION........................................................................................................1 Functional Magnetic Resonance Imaging................................................................1 Negative BOLD and the Present Study...................................................................1 Role of Interhemispheric Connectivity....................................................................3 Hypotheses...............................................................................................................4 2 METHODS...................................................................................................................5 Participants...............................................................................................................5 Procedure.................................................................................................................6 Event-Related Block (ER-Block) Imaging Paradigm........................................6 Performance Evaluation.....................................................................................9 Apparatus.........................................................................................................10 Functional Imaging Data Analysis...................................................................11 Hemodynamic response function analysis.......................................................12 3 RESULTS...................................................................................................................13 Behavioral Performance.........................................................................................13 Imaging Analysis...................................................................................................13 Hemodynamic Response Function Analysis...................................................15 Multivariate ANOVA......................................................................................18 4 DISCUSSION.............................................................................................................19 Limitations.............................................................................................................21 Implications and Future Directions........................................................................22

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vi LIST OF REFERENCES...................................................................................................23 BIOGRAPHICAL SKETCH.............................................................................................29

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vii LIST OF TABLES Table page 1 Participant characteristics...........................................................................................5 2 Talairach coordinates and volumes of ac tive voxel clusters in the right M1 during learned response executions..........................................................................16

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viii LIST OF FIGURES Figure page 1 Sample stimuli for response conditions are shown for: (A) GO; (B) NO GO; and (C) NOVEL................................................................................................................8 2 Estimated hemodynamic response functi ons in a younger participant (s12)...........14 3 Estimated hemodynamic response functions in an older p0061rticipant (s01)........15 4 These four graphs show representations of the estimated hemodynamic response function averages......................................................................................................17 5 Group means overlayed on axial images..................................................................18

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ix Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science NEGATIVE BOLD AND AGING : AN fMRI INVESTIGATION By Keith Matthew McGregor May 2006 Chair: Keith D. White Major Department: Psychology The goal of this event-related fMRI study wa s to investigate age differences using a task previously reported to elicit nega tive BOLD signals. Six (to date) right-handed individuals from two age groups were traine d to perform a right hand, externally paced, 12 finger movements button press sequence. This task was performed during each of three response conditions: (a ) immediate execution of th e learned sequence (GO); (b) suppression of the learned sequence (NoGO) ; (c) initial suppression of the learned sequence followed by execution (DelayGO). Four regions of interest (ROI) were selected for analysis: both primary motor areas (LM 1, RM1), and both supplementary motor areas (LSMA, RSMA). Deconvolution analysis wa s used to estimate hemodynamic response profiles (HDRs) of maximally active voxels in each ROI for each response condition. Repeated measures analysis of variance of HDR profiles was performed across age groups, response conditions, and ROI. Younger subjects exhibited positive BOLD signals in LM1, LSMA and RSMA with negativ e BOLD signals in LM1 during GO and DelayGO conditions, as expected. Older ad ults, in contrast, s howed positive BOLD

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x signals in all four ROIs dur ing those conditions. Amplitudes and times to peak of the HDRs did not differ between age groups. These preliminary results indicate age differences in activation of R M1 cortex during execution of the right-hand learned button press sequence. These differences in BOLD signal across age could be related to the hemispheric asymmetr y reduction in older ad ults (HAROLD) model.

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1 CHAPTER 1 INTRODUCTION Functional Magnetic Resonance Imaging Functional magnetic resonance imagi ng (fMRI) has greatly enhanced our understanding of brain activation patterns during cognitive tasks. Blood oxygen leveldependent (BOLD) contrast has been the leading technique used by researchers to investigate neural correlates of cognitive activity using fMRI Synaptic activity, whether excitatory or inhibitory, causes an increas e in the local concentration of deoxygenated hemoglobin (deoxyhemoglobin) due to accelerated oxygen metabolism. Deoxyhemoglobin reduces the bulk magneti zation of nearby protons, reducing the measured MR signal through a dephasing eff ect. An overcompensation of oxygenated blood is then sent to the metabolically active area in a hemodynamic response (HDR) coupled to the increased oxygen demand. Lo cal deoxyhemoglobin is diluted, raising the MR signal above baseline. As the oxygen demand returns to baseline levels, so too will the MR signal gradually return to its baseline. The HDR resu lts in a roughly bell-shaped MR signal change, a positive BOLD response (PBR) over the course of 10 15 seconds for a relatively brief interval of synap tic activity. A measurement volume (voxel) exhibiting PBR signals during tasks is reporte d as being activated (Ogawa et al. 1990; Logothetis et al. 2001). Negative BOLD and the Present Study A negative BOLD response (NBR) appears like a mirror image of the typical PBR described above, that is a U-shaped ra ther than bell-shaped time course of MR

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2 signal change. NBR indicates a decrease in metabolic/neuronal activity in the area in which it is found (Shmuel et al 2002; Stefanovic et al. 2004 ; Amedi, Malach, & PascualLeone, 2005). Specifically, Stefanovic et al. (2004) correlated NBR to decreases of regional metabolic rate of oxygen consumption (CMRO2). In some studies, voxels exhibiting NBR are included as being activated because they pass a statistical test for differing reliably from baseline. Older adults have higher pr evalence of NBR as compar ed to younger adults during both motor and visual tasks (Ai zenstein et al. 2005). Aizenst ein et al. (2004) contended that spatial averaging over a mixture of voxels having different direct ions of activations (i.e., NBR versus PBR) could possibly acc ount for previous findings of decreasing amplitude of BOLD response w ith increasing age in the visu al (Huettel et al. 2001; Ross et al. 1997; Buckner et al. 2000) and motor cort ices (D'Esposito et al. 1999; Hesselman et al. 2001; Buckner et al. 2000). Ol der adults have higher interindividual variability in BOLD contrast, consistent with individual variations in the mixture of NBR and PBR (see DEsposito et al. 2003 for review). Howe ver, we are unaware of any studies that were specifically designed to elicit NBR for the purpose of studying age effects. Many studies have found NBRs serendipitously ra ther than by design (Allison et al. 2000; Roether et al. 2002; Born et al. 2002; Aizenst ein et al. 2004; Amedi, Malach, & PascualLeone, 2005) while studies designed to elicit reliable NBRs have not included older adults (Shmuel et al. 2002; Hamzei et al 2002; Hamzei et al. 2005; Stefanovic et al. 2004; Hummel et al. 2004; Newton et al. 2005). We have adapted methods from the latter studies, making some modifications to accommodate older adults, for the present study.

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3 The NBRs are often elicited in a unima nual motor task wherein the contralateral (hand controlling) hemispheres primary motor cortex shows PBR, as expected, but at the same time and in the homologous location, th e ipsilateral M1 shows NBR (Hamzei et al. 2002; Stefanovic et al. 2004; Hamzei et al. in press; Gardner et al. 2005). The amplitude of the NBR has been shown to be reasona bly proportional to, although comparatively smaller than, than the other hemispheres PBR (Newton et al. 2005). Role of Interhemispheric Connectivity Interhemispheric connectivity is widely believed to be the source of the NBR (Allison et al. 2000; Shmuel et al. 2002; Stefan ovic, et al, 2004). It is well known that transcallosal synapses are mainly glutamater gic and exhibit excitatory effects on their target (Gerloff et al. 1998). Thus, cortical ce ll bodies resident in one hemisphere, which might extend actively firing axons transcallosa lly, generate increased metabolic activity at the target location due to the release of ex citatory neurotransmitter. At least one more level of connections must exist involving i nhibitory neurotransmission in order to reduce neural/metabolic activity. Because cortical inhibitory interneurons generally synapse locally (nearly all axons extend <200 micr ons), the accompanying increase in synaptic activity (due to both the transcallosal excita tory inputs and the local inhibitory outputs) will necessarily require a subsequent increase in blood flow resulting in PBR in the target vicinity. One possibility is that these inter-hemispheric ex citatory axons terminate on dendrites of inhibitory interneurons that in turn project to multiple pyramidal cells (Beaulieu and Colonnier, 1985) via axo-somatic or axo-axonal terminal branches (Koos and Tepper, 1999). Therefore, the downstream synaptic outputs of the pyramidal cells must be presumed to be disproportionately reduced in order to outweigh the PBR evoked by the synaptic activities bringing about the volume-averaged synap tic activity reduction.

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4 Negative BOLD could also be exhibite d one level downstream of inhibitory synapses distant from the target vicinity, for example in the thalamus, where reduced spike frequency would result in reduction of those thalamic a xons synaptic outputs at the cortex. This alternative means, possibly involving cortico-st riatal-thalamo-cortical loops (Alexander et al. 1990), woul d also reduce cortical meta bolic activity by reducing its synaptic inputs. If this alternative were to have merit then not only primary motor (M1) but also supplementary motor (SMA) cortices would be likely to ev idence activations in at least one but probably both he mispheres. Therefore, regions of interest for the present study will include both hemispheres M1 and SMA. Hypotheses Furthermore, it is well known that agi ng has a large influence on the striatum, specifically that dopamine uptake in caudate and putamen declines with age as indexed by levels of dopamine transporters (Kish et al 1992; van Dyck et al. 1995; van Dyck et al. 2002; Erixon-Lindroth et al. 2005). Reduc tion of dopaminergic input onto the D1 receptors in the direct path (striatum, globus pallidus internal, thalamus) would be expected to cause reduced net inhibition of the thalamus, and thus increased cortical input. This leads us to hypothesize that olde r adults will have a reduced magnitude of NBR.

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5 CHAPTER 2 METHODS Participants Data from 12 right-handed participants we re used to estimate the presence of negative BOLD in two age gr oups (6 Young, mean age = 22 yr s, sd = 3.09 yrs; 6 Old, mean age = 71 yrs, sd = 6.49 yrs), see Table 1. All participants were prescreened by selfreport for claustrophobia, contraindicated me dications or metal implants, pregnancy (when applicable), and pre-exis ting neurological or psychiatric disorders. Participants with over two years of recent (within five years) piano pl aying experience were also excluded due to potential vari ation of signal dynamics (Ridding et al. 2000; Krampe, 2002). All participants were recruited and provi ded written consent after the experimental procedures were fully explained to them in accordance with the Internal Review Board of the University of Florida. Cognitive functioning in the older adults was assessed with the Mini Mental Status Exam (MMSE) with a mi nimum score of 26 needed for participation. All participants were asked to avoid caffeine for at least six hours prior to scanning (see Laurienti et al. 2003; see also Laurienti et al. 2004). Table 1: Participant characteristics. Younger Older N 6 (4 female) 6 (3 female) Age Range: 19-27 60-76 SD: 3.09 6.49 Mean: 24.0 71.0 MMSE mean (range) N/A 29.2 (28-30)

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6 Procedure Prior to scanning, participants were trai ned to overlearn a 12 movement button sequence with the fingers of their right ha nd. Task training outside the scanner room began with the participants learning the proper numerical re presentation for each finger of the right hand. The thumb was designated as 1 with integer increments for the subsequent digits (e .g inde x finger 2, middle finger -3, etc. ). The target sequence was as follows: 5-4-2-3-4-4-2-5-23-3-4. Sequenced button press training was performed on a five-button Model 300 PST Response Box (P sychology Software Tools, Pittsburgh, PA) and consisted of three phases. The first, a familiarity phase, required participants to self-pace sequence practice while viewing a display of the sequence on a laptop computer. This was followed by a memorization phase during which participants continued self-paced sequence presses, but now with the visual sequence display removed. Finally, in a cued phase, participan ts were asked to press button sequences in rhythm with the 1 Hz flashes of a star disp layed on a computer screen. After completing target sequence executions 10 times in a row w ithout error, participan ts advanced to the next progressive training stage. Scanning commenced after the su ccessful completion of the cued phase. All participants were able to train to criterion with in the allotted 1-hour training time. Event-Related Block (ER-Bl ock) Imaging Paradigm In the scanner, participants lay supine vi ewing a fixation cross in the center of the screen at which they are in structed to maintain fixati on throughout scanning. During each run, button press trials begin after a pseudo-randomly generated resting-state interval of 6, 7 or 8 TR (10.2, 11.9, OR 13.6 sec) Trials are consisted of four types: GO, NO GO, DELAY, and NOVEL. The GO, NO GO, and DELAY trials are together

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7 referred to as learned sequence trials, as they involve the execution or suppression of the target finger movements. The NOVEL tria l was added to mitigate boredom during scanning (see Hummel et al. 2004). Subjects are informed of the trial type through two different prepare cues. Participants are notified of an impending learned sequence trial by the presentation of a single green prepare st ar in the top center of the screen. After 1 TR (1.7 seconds), the prepar e star disappears and one of three trial types commences: GO, NO GO, or DELAY. Participants were cued of the NOVEL sequence in a similar manner except that a yellow star is used instead of a green star. An explanation of each trial type follows and sample images are presented in Figure 1. In a GO trial, a green go star begins to flash at 1 Hz in the center of the screen at the end of the prepare peri od. The participant was instru cted to press the learned button sequence by timing their button presses wi th 12 flashes of the green go star. Stars remain on the screen for 500 ms We instructed participan ts to continue through the sequence even if they believe d they made an error at a ny point during its execution. In a NO GO trial, a red, no go star is displayed in th e screens center cueing the participant to refrain from pressing the button press sequence. In a DELAY, as in a NO GO trial, a red no go star follows the aforementioned prepare cue. However, after a delay of either 1 or 2 TR (1.7 or 3.4 sec), the red star is replaced by 12 flashes (also at 1 Hz) of a green go star, in structing the participant to begin pressing the sequence in rhythm with the flashing star. We instructed participants to maintain attention to the red star as it may change to green at any point during its presentation. After the trials prep are period, the NOVEL response trial requires participants to press pseudora ndomly generated integers ranging from 2-5. The integers

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8 are individually flashed near the bottom of the screen, each remaining visible for 500 ms. 12 of these random integers are flashed during the trial at 1 Hz. The time of display for each integer is identical to the go star flashes in the learned response executions conditions. A B C Figure 1: Sample stimuli for response condi tions are shown for: (A) GO; (B) NO GO; and (C) NOVEL. In the scanner room, participants were re minded of the task procedures prior to entering the scanner apparatus and then ag ain immediately before commencement of functional imaging. After structural acqui sition but prior to EPI image acquisition, participants performed a pract ice run with representative stimuli. The scanner operator visually monitored participant performance on an LCD computer monitor in the control room which displayed the button responses. After successful completion of a full trial run (6 minutes 41 seconds), functional imaging proceeded. No participants required

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9 additional training or reported discomfort with the task as verified by verbal report immediately prior to EPI acquisition. Each of the 6 functional scanning runs (6 min 41 sec each ; 1368 total images) included 12 stimulus presentations in pseudo-ra ndomized order for a total of 72 trials in the imaging session. Of these presentations, 20 trials each were GO, NO GO, and DELAY. DELAY trials were further divided into 10 each of 1-TR and 2-TR delays. As they were mainly used in the paradigm to mitigate boredom, NOVEL trials were presented only 12 times (2 per run). Pse udo-randomization of the NOVEL button presses was done during paradigm design and, as su ch, all subjects recei ved the same NOVEL press sequences. Performance Evaluation Older and younger adults were not expect ed to vary on behavioral performance (accuracy and reaction time) due the training pr ocedures and the timed nature of the task (Janahashi et al. 1995; Rao et al. 1993). Button press performance during scanning was evaluated on an individual re sponse basis with each button press in the sequence taken as a response point (52 trials X 12 presses/trial = 624 total response point s per participant). Evaluation of accuracy of each response poi nt takes into consideration not only the specific button pressed, but also the reaction time. If a participant did not make a response within 500ms of the cue or made a re sponse within 300ms prior to the cue, then the button press is marked as incorrect regard less of key identity. Evaluation of errors was completed with E-Prime 1.1, Microsoft Excel and simple Perl 5.0 scripts written by the author. Error rates for tasks of the curren t studys types have been reported to be less than 10 percent (Liepert et al. 2001; Verst ynen et al. 2005; Gerlo ff et al. 1998; Hummel

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10 et al. 2004). Reaction times and error rate s were averaged across age groups for each condition and independent samples t-tests were used to compare these means. Apparatus All scanning was performed on a Siemens Allegra 3T MRI machine located at the McKnight Brain Institute of the University of Florida. After each participant was fitted with an MR-compatible headset (Resonan ce Technologies Inc.), their head was positioned within a standard quadrature RF h ead coil with padding to limit head motion. First surface mirrors at tached to the head coil were positioned above the participants eyes and rotated to allow viewing along the scanner bore axis. Afte r the participant had been moved into the bore, three single sli ce orthogonally oriented scout images were obtained to ensure that all pa rts of the head were within the homogeneous portion of the magnetic field. The scout images (TR = 18, TE = 4.28, FA = 25 degrees, 256x256, multiplane slice thickness = 3.0 mm, FOV = 280 mm) were also used to prescribe slice alignment parallel to the participants in terhemispheric longitudinal fissure. Next, a magnetic resonance time-of-flight angiogr am (MRA) was acquired using TR = 23, TE = 6.15, FA = 30 degrees, matrix = 256x256, axia l slice thickness = 5.0 mm, FOV = 240 mm. The MRA allowed slice prescriptions aligned parallel to the anterior commissure posterior commissure line as we ll as to the longitudinal fissure Slice prescriptions for all other image acquisitions were copied from the MRA. High resolution anatomic images were next obtained using a Siemens MPRAGE sequence with TR = 23 ms, TE = 6 ms, flip angle = 25 degrees, matrix = 256x192, 128 ax ial slices at 1.3 mm thickness (no gap), FOV = 240 mm. Lastly, the behavioral task was executed during multiple acquisitions of gradient echo echo-planar images (EPI) w ith the following parameters: TR = 1700 ms,

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11 TE = 50 ms, flip angle = 70 degrees, matrix = 64x64, 32 axial slices at 4 mm thickness, FOV = 240 mm. Participants viewed stimuli on an IFIS -SA presentation system (InVivo Systems, Gainesville, FL) using a Dell model 2100MP data projector, rear pr ojection screen, and first surface mirror display system. Stimuli were projected at 1024 x 768 pixel resolution, visible to the part icipant through two mirrors (one on the head coil, another outside the scanner bore). A MR-compatible button response pad, part of the IFIS-SA system, attached to the participants hand a nd wrist was used to record individual finger presses throughout the duration of scanning. Functional Imaging Data Analysis Imaging analysis was performed with AFNI software (Cox, 1996). The eight initial magnetization equilibration images (called di scarded acquisitions or disdaqs) from each functional run were omitted from subseque nt analysis. Using a 3-dimensional rigid body registration, functional images were ali gned to a base image from the functional volume acquired closest in time to structural im ages. Linear trends in the time series of each run were removed, and all imaging runs were then concatenated. Deconvolution, a multiple regression analysis procedure for estimation of hemodynamic response in each voxel, was performed using AFNIs 3dD econvolve program. As the GO and DELAY conditions were very much alike in their execution, the two conditions were combined into a learned response execution conditi on to enhance statis tical power (n = 40 response trials). (A previous analysis of activation patte rns both within and across age groups confirmed that GO and DELAY response conditions do not sign ificantly vary in correlates of functional activit y.) As negative BOLD is believed to be a mirror image of the positive BOLD signal, the non-directi onal F-statistic was chosen as the output

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12 statistical measure. Activation for a given voxel was determined if the F statistic from the deconvolution exceeded a value of 3.5 (p<.00001, uncorrected for multiple comparisons). Hemodynamic response function analysis We hypothesized that younger adults show a different NBR in R M1 than older adults during learned response execution. To te st this, we compared the time courses of the estimated hemodynamic response func tions as calculated by the 3dDeconvolve application (Ward, 2002) across older and younge r adults. These hemodynamic response function (HRF) estimates were created as fo llows. Four regions of interest were identified: left and right primary motor cortex (L/R M1), and left and right supplementary motor cortex (L/R SMA). For each participan t and each region of in terest, the voxel with the highest F-statistic was identified and the 16 numerical values from its estimated HRF time course were saved. An additional four active voxels (F > 3.5, p<.00001) in spatial contiguity with the maximally active voxel we re also identified and 16 numerical values from each voxels estimated HRF time course s were also saved. The five saved voxelwise estimates of the HRF were averaged for each of the 16 time points, for each participant and region of in terest, to represent the time course of the estimated hemodynamic response under those provisos. Th is HRF averaging procedure was carried out for all 4 regions of intere st in all 12 participants. A repeated measures ANOVA (2 X 4 X 16) compared age (young, old); region of interest (L M1, R M1, L SMA, R SMA), and time (16 HRF points).

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13 CHAPTER 3 RESULTS Behavioral Performance While learning the button-pr ess response sequence prio r to scanning, the older participants made more e rrors (older mean = 90.5; younge r mean = 32.5, t(10) = 2.38, p<.04) and required longer to train to criterion (older mean = 34.2 minutes, younger mean = 24.6 minutes; t(10) = 2.61, p<.03). Du ring scanning, however, there were no significant differences due to age in either number of errors or reaction times on GO, NO GO, and DELAY trials. Older participants had slightly longer reaction times on the NOVEL trials (older mean = 405 msec, younge r mean = 365 msec; t(10) = 4.66, p<.01). The generally comparable accuracies and speeds of executing the learned response sequence are noteworthy because behavioral performance does not require inclusion as a covariate in subsequent imaging analyses. Imaging Analysis During processing of the fMRI images for i ndividual participants, it became readily apparent that negative BOLD responses exis ted, as hypothesized, in th e right (ipsilateral) motor cortex (R M1) of the younger subjects (see an example in Figure 2) but positive BOLD response instead existed in the R M1 of the older participants (see an example in Figure 3). Figures 2 and 3 each present for i ndividual subjects (younger, s12; older, s01): (a) five examples of estimated hemodynamic response functions (HRFs) from voxels in R M1, and (b) sample fMRI axial slices incor porating the hand knob region of R M1. All brain images are in neurological convention (l eft = left on axial view). Voxels within R

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14 M1 were selected to form a contiguity group using the following criter ia: First, the voxel having the highest F-statistic associated w ith deconvolution relative to GO and DELAY (response execution) conditions combined was identified as the max-voxel. Next, four acquisition voxels touching max-voxel and havi ng F > 3.5 were identified. The five HRFs shown in Figure 2(B) a nd Figure 3(B) were obtained from the R M1 contiguity groups for s12 (younger) and s01 (older), respectively. A B Figure 2: Estimated hemodynamic response func tions in a younger participant (s12) (A). Five estimated hemodynamic response f unctions from four voxel contiguous to the most highly active voxel (bottom HRF in A) in R M1 of s12 (young adult) during learned response execution conditions. Voxel locations in cortex are represented in (B) with co lors coding probability associated with the F statistics (yellow: p<.0001; or ange: p<.001; red: p<.005) from deconvolution analysis.Contiguity group multivariate ANOVA

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15 A B Figure 3: Estimated hemodynamic response func tions in an older pa rticipant (s01) (A) Five estimated hemodynamic response f unctions from four voxel contiguous to the most highly active voxel (bottom HRF in A) in R M1 of s01 (older adult) during learned response execution conditions. Voxel locations in cortex are represented in (B) with co lors coding probability associated with the F statistics (yellow: <.0001; orange: p<.001; red: p<.005) from deconvolution analysis. Hemodynamic Response Function Analysis The example HRFs in Figure 2(B) each re semble negative BOLD responses, while the example HRFs in Figure 3(B) are typical (positive) BOLD responses. This striking age-related difference in the polarity of BOLD hemodynamic response in these individuals has been confirme d more generally by: (1) loca lizing the most statistically robust contiguity groups, as described above, within four hypothesis-driven regions of interest (specifically the left and right M1 and the left and right supplementary motor cortices (SMA), and (2) ex tracting HRFs from each voxel of these contiguity groups, calculating area-under-the-curve for each HR F and subjecting these to multi-factor ANOVA.

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16 Table 2 presents localizati ons and activation volumes of R M1 contiguity groups, as defined above, for all subjects for d econvolutions relative to response execution conditions. Localizations are gi ven in Talairach coordinate s. Activation volumes are based on 1.8 mm contiguity radius for 1 mm3 isotropic voxels cente red on max-voxel. All six younger adults evidenced negative BO LD in the R M1, while all but one older adult evidenced positive BOLD in the same area. Table 2: Talairach coordinates and volumes of active voxel clusters in the right M1 during learned response executions. Clusters were defined using an F-statistic threshold set at 3.5 (p<.00001, uncorrected ) with a contiguity radius of 1.8 mm3. and volume threshold of 50 L. Negative BOLD clusters are shown in BOLD typeface. Older Adults Talairach Coordinates Volume Younger Adults Talairach Coordinates Volume S01 (-46 -2, 53) 285 L s07 (-46 -2, 53) 64 L S02 (-35, 7, 56) 106 L s08 (-58, 2, 42) 83 L S03 (-30, 14, 52) 110 L s09 (-39, 19, 40) 74 L S04 (-28, 26,57) 454 L s10 (-43, 11,50) 109 L S05 (-23, 6, 58) 118 L s11 (-23, 6, 58) 92 L S06 (-32, 26, 52) 325 L s12 (-35, 36, 58) 193 L Four regions of interest (ROI), left an d right M1 and left and right SMA, were selected within each subject and five-voxel contiguity groups were identified for each ROI. HRFs were obtained from each of thes e 20 voxels per subject. Figure 4 shows the averages of these HRF time courses within each ROI and age group. The ordinates on Figure 4 show magnitude of HRFs from dec onvolution relative to response execution events. Each ordinate is plotted against imag e acquisition time (in TR s) relative to the response execution event, and compares younger and older age groups. This kind of plot is shown for each ROI. Starting from the top left panel, representing L M1, large positive BOLD HRFs were found as expected fo r both younger and older groups..

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17 Figure 4: These four graphs show repr esentations of the estimated hemodynamic response function averages of the most highly active voxel and four of its suprathreshold contiguous neighbors for older and younger adults during learned response execution. Each of the four graphs shows a different region of interest (clockwise from top left: L M1, LSMA, RSMA, RM1). The ordinate values are the magnitude of the hemodynamic response function (HRF) shown against time (i n TR units) relative to the response event. Large positive BOLD responses can be seen fo r older and younger adults in L M1. Moderate positive BOLD responses are shown for each age group for SMA bilaterally. However, in R M1, younge r adults show a moderate negative BOLD response while the older adults show a large positive BOLD response. Proceeding clockwise, L SMA and R SMA each showed moderate positive BOLD HRFs for both age groups. For R M1, however, younger adults had a moderately negative HRF

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18 while older adults had a large positive HRF. Figure 4 confirms in group averages the observations illustrated for individual subjects by Figures 2 and 3. Figure 5 compares averaged Talairached younger and older gr oups brains, showing HRF magnitude colorcoded across brain locations in a glass brain view Multivariate ANOVA Results from a contiguity group repeat ed measures, multivariate ANOVA indicated an interaction between age groups and area across the hemodynamic response function (Hotellings F(3, 10) = 8.345, p = .003). As this finding was consistent with our hypothesis of differences in HRF across age gr oups and regions, we did not interpret higher-order interactions. A B Figure 5: Group means overlayed on axial im ages for A) older adults and B) younger adults during learned response executi on after area-under-the-curve analysis of estimated HRF. (Yellow indicates large positive area, orange indicates moderate positive area, and blue indicates negative (below baseline) area.

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19 CHAPTER 4 DISCUSSION The primary goal of this investigation wa s to compare negative BOLD responses (NBR) in older and younger adults on a task pr eviously shown to exhibit NBR. The main findings are as follows. Indi vidual subject analysis of maximally active voxels in the primary (M1) and supplementary motor (SMA) co rtices showed different results for older and younger adults during execution of learne d button press sequences. All individuals in each group evidenced typical positive BOLD responses (PBR) in M1 contralateral to the response hand as well as in bilate ral SMAs during res ponse executions. Younger participants showed the expected NBR in ips ilateral M1 while, surprisingly, all but one older adult showed positive BOLD in this re gion. This difference in BOLD contrast directions (NBR vs PBR) cannot be explained by performa nce differences, because the age groups were nearly identical on measures of accuracy and reaction time for execution of the learned button press sequence. These results indicate that he althy aging is linked to changes in interhemispheric comm unication (see Peinnemann et al. 2002). The present results are consistent with recent fMRI findings by Newton et al. (2005). They studied 6 young adult participants (mean age 28) who were instructed to execute or withhold a 4 Hertz thumb button pr ess after a prepare cue while being scanned in a block paradigm at 3T. Response execu tion versus passive fixation point viewing elicited ipsilateral (to the response hand) M1 NBR with concomitant PBR in the contralateral M1. Newton et al. (2005) suggested that negative BOLD might signify preparation of the ipsilateral M1 for potential cooperation with contralateral M1 if motor

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20 processing became complex enough to require bila teral recruitment. Reduced activity in ipsilateral M1 could serve to suppress its recruitment by other connections into this area. The present results are also generally consistent with the model of hemispheric asymmetry reduction in older adults, or HAROLD (Cabeza, 2002). The HAROLD model evolved to explain an accumulation of neuroimaging studies comparing BOLD activations of older and younger adults perfor ming the same tasks, which showed with some consistency that older adults have le ss lateralized activation than that seen in younger adults (Rueter-Lorenz et al. 2000; Garavan et al. 1999; Dixon et al. 2004; Cabeza et al. 2004). The HAROLD model has been used to describe aging related activation patterns for a number of specific ta sks involving the prefront al cortex including verbal working memory, visuo-spatial working memory and pre-potent response inhibition. Support for the model has also ac crued from investigations of hippocampus (Maguire & Frith, 2003) and motor cortex (Nac carato et al. 2004; James, 2005; Baliz et al. 2005). One explanation for the HAROLD phenomenon is compensation for declining functionality in the aging brain by recru itment of cortical homologues (Cabeza, 2002; Cabeza et al. 2004; Baliz et al. 2005; see also Salthouse & Babcock, 1991). The Newton et al. (2005) suggestion th at NBR in young adults might signify preparation of R M1 for potential coopera tion with L M1 should motor processing became complex enough, combined with normally declining functionality in the aging brain and HAROLD, would lead one to e xpect the BOLD signal direction change (younger RM1 NBR to older RM1 PBR) observed in the present study. Our findings thus add further support to the notion of neural compensation by recruitment of cortical homologues in normal aging.

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21 There are many plausible candidates to se rve as the neurophysiological basis for age-related decline in brain functionality. Age-related vascular changes are common (Fang, 1976). Structural magnetic resonance imaging has shown that normal aging is associated with a decrease in the thickness of the neocortex (Salat et al. 2005). Diffusion tensor imaging has shown that aging is asso ciated with significant increases of water diffusion, probably resulting from decreases in the diffusion-limiting myelinated fibers connecting cortical and/or subcortical areas (Pfefferbaum et al. 2005; Salat et al. 2005; see also Madden et al. 2004). Dopamine upt ake in caudate and putamen declines with age as indexed by levels of stri atal dopamine transporters (K ish et al. 1992; van Dyck et al. 1995; van Dyck et al. 2002; Erixon-Lindr oth et al. 2005). Evidence exists that interhemispheric signaling could make use of cortico-striato-thalamo-cortical loops (Gerloff et al. 1998; Kuhn et al. 2004; but see al so Chen et al. 2004). As an example, a recent case study reported that a patient la cking the corpus callosum showed TMSevoked reduction in ipsilateral motor evoke d potentials, thus imp licating subcortical pathways in interhemispheric communicati on (McNair, 2004; though see Reddy et al. 2000). Limitations The present study has two key limitations. First, locations of the NBRs in younger adults were rather variable (see Table 2), but such va riability is common for NBRs (Allison et al. 2000; Nirkko et al. 2001; Born et al. 2002; Shmuel et al. 2002; Hamzei et al. 2002; Aizenstein et al. 2004; Stefanovic et al. 2004; Stefan ovic et al.. 2005; Newton et al. 2005). Second, age group comparisons with su ch a small sample size (n=6 per group) have questionable generality to the older population. Both Cabeza (2002) and ReuterLorenz & Lustig (2005) emphasize inter-indi vidual variability of functional imaging

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22 results across older adults. This was apparent in the present study because one older adult (s05, age 68, a champion marathon runner) showed NBR, not PBR, in R M1 during response execution, a finding which was similar to the NBRs of younger adults. It is quite likely that variations in social activity, exer cise patterns, mental engagement, and other factors, all contribute to the effects of normal aging on brain activations (Peinnemann et al. 2002; Dixon et al. 2004). Both of thes e limitations could be mitigated by expanding the sample size. Implications and Future Directions The current findings may have important im plications for the focused development of motor rehabilitation treatme nts because the age of the individual has an important influence on how their primary motor cortical homologues interact. Both practitioners and researchers are beginning to better grasp the manner in which the brain reorganizes after stroke or other damage. A primary c onsideration for the deve lopment of treatment regimens is the ability to identify substrat es in the remaining viable tissue to which functions formerly resident in the damage d tissue can migrate. The use of fMRI to monitor brain plasticity during recovery of function provides a new t ool for the continued development of customized rehabilitation progr ams. The present evidence implies that brain rehabilitation programs may need to be different for people of different age ranges.

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26 Liepert J., Dettmers C., Terborg C., Weille r C., 2001. Inhibition of ipsilateral motor cortex during phasic generation of lo w force. Clinical Neurophysiology 112, 11421. Logothetis, N.K., Pauls, J., Augat h, M., Trinath, T., Oeltermann, A., 2001. Neurophysiological investigation of the ba sis of the fMRI signal. Nature 412, 150157. Madden D.J., Whiting W.L., Provenzale J.M., Huettel, S.A., 2004. Age-related changes in neural activity during vi sual target detection measur ed by fMRI. Cerebral Cortex 14, 143-55. Maguire, E.A., Frith, C.D., 2003. Aging aff ects the engagement of the hippocampus during autobiographical memory retrieval. Brain 126, 1509-10. McConnell K.A., Bohning D.E., Nahas Z., Shas tri A., Teneback C., Lorberbaum J.P., Lomarev M.P., Vincent D.J., George M. S., 2003. BOLD fMRI response to direct stimulation, transcranial magnetic stimulati on of the motor cortex shows no decline with age. Journal of Neural Transmission 110, 495-507. McNair, N.A., 2004. Hemispheric interaction as sociated with motor-task complexity may be mediated by subcortical pathways in acallosal individuals. Po ster presented at the Annual Meeting of the Cognitive Ne uroscience Society 2004, San Francisco. Naccarato, M., Calautti, C., Day, D.J., Fletch er, P.C., Jones, P.S., Carpenter, A.T., Bullmore, E.T., Baron, J., 2004. Does age a ffect hemispheric ba lance during finger tapping? An fMRI study. Poster pres ented at Human Brain Mapping 2004, Toronto, Ontario. Newton J.M., Sunderland A., Gowland P.A., 200 5. fMRI signal decreases in ipsilateral primary motor cortex during unilateral ha nd movements are related to duration and side of movement. NeuroImage 24, 1080-7. Nirkko, A.C., Ozdoba, C., Redmond, S.M.,Buerk i, M., Schroth, G., Hess, C.W. and Wiesendanger, W., 2001. Different Ipsila teral Representations for Distal and Proximal Movements in the Sensorimotor Cortex, Activation and Deactivation Patterns, NeuroImage 13, 825-835. Ogawa S., Lee T.M., Kay A.R., Tank D.W ., 1990. Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proceedings of the National Academy Sciences U.S.A. 87, 9868-72. Peinemann A., Lehner C., Conrad B., Siebner H.R., 2001. Age-related decrease in pairedpulse intracortical inhibition in the hu man primary motor cortex. Neuroscience Letters 313, 33-6.

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27 Pfefferbaum A., Adalsteinsson E., Sullivan E.V., 2005. Frontal circuitry degradation marks healthy adult aging: Evidence fr om diffusion tensor imaging. NeuroImage 26, 891-9. Rao S.M., Harrington, Haaland K., Bobhol z J.A., Cox R.W. and Binder J.R., 1997. Distributed neural system s underlying the timing of movements. Journal of Neuroscience 15, 5528-35. Reuter-Lorenz, P. A., Jonides, J., Smith, E. S., Hartley, A., Mill er, A., Marshuetz, C., 2000. Age differences in the frontal latera lization of verbal and spatial working memory revealed by PET. Journal of Cognitive Neuroscience 12, 174-187. Reddy H., Lassonde M., Bemasconi A., Bemasc oni N., Matthews P.M., Andermann F., Amold D.L., 2000. An fMRI study of the late ralization of motor cortex activation in acallosal patients. Neuroreport 11, 2409-13. Reuter-Lorenz, P. A., and Lustig, C., 2005. Br ain aging: reorganizi ng discoveries about the aging mind. Current Opin ion in Neurobiology 15, 245-251. Ridding M.C., Brouwer B., and Nordstrom M.A., 2000. Reduced interhemispheric inhibition in musicians. Experime ntal Brain Research 133, 249-253. Roether J., Knab R., Hamzei F., Fiehler J ., Reichenbach J.R., Buchel C., Weiller C., 2002. Negative dip in BOLD fMRI is caused by blood flow--oxygen consumption uncoupling in humans. NeuroImage 15, 98-102. Ross M.H., Yurgelun-Todd D.A., Renshaw P.F., Maas L.C., Mendelson J.H., Mello N.K., Cohen B.M., Levin J.M., 1997. Age -related reduction in functional MRI response to photic stimulation. Neurology 48, 173-6. Salat D.H., Tuch D.S., Greve D.N., van der Kouwe A.J., Hevelone N.D., Zaleta A.K., Rosen B.R., Fischl B., Corkin S., Ro sas H.D., Dale A.M., 2005. Age-related alterations in white matter microstructu re measured by diffusion tensor imaging. Neurobiol Aging 26, 1215-27. Salthouse, T.A., Babcock, R.L., 1991. Decomp osing adult age differences in working memory. Developmental Psychology 27, 763-776. Shmuel A., Yacoub E., Pfeuffer J., Van de M oortele P.F., Adriany G., Hu X., Ugurbil K., 2002. Sustained negative BOLD, blood flow and oxygen consumption response and its coupling to the positive response in the human brain. Neuron 19, 1195-210. Stefanovic, B., Warnking, J. M., and Pi ke, G. B., 2004. Hemodynamic and metabolic responses to neuronal inhi bition. NeuroImage 22, 771-778. Stefanovic, B., Warnking, J. M., Kobayashi, E ., Bagshaw, A. P., Hawco, C., Dubeau, F., Gotman, J., and Pike, G. B., 2005. Hemodynamic and metabolic responses to activation, deactivation and epileptic discharges. NeuroImage 28, 205-215.

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28 van Dyck C.H., Seibyl J.P., Malison R.T., Laruelle M., Wallace E., Zoghbi S.S., ZeaPonce Y., Baldwin RM., Charney D.S., Ho ffer P.B., 1995. Age-re lated decline in striatal dopamine transporter binding w ith iodine-123-beta-CITSPECT. Journal of Nuclear Medicine 36, 1175-81. van Dyck C.H., Seibyl J.P., Malison R.T., Laru elle M., Zoghbi S.S., Baldwin R.M., Innis R.B., 2002. Age-related decline in dopamine transporters, analysis of striatal subregions, nonlinear effects, and hemisphe ric asymmetries. American Journal of Geriatric Psychiatry 10, 36-43. Verstynen T., Diedrichsen J., Albert N., Apar icio P., Ivry R.B., 2005. Ipsilateral motor cortex activity during unimanual hand m ovements relates to task complexity. Journal of Neurophysiology 93, 1209-22. Ward, B.D., 2002. 3dDeconvolve. Retrieved Ma rch 21, 2006, from Nationa l Institute of Health Web site: http://afni.nim h.nih.gov/pub/dist/doc/manual/Deconvolvem.pdf

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29 BIOGRAPHICAL SKETCH Keith Matthew McGregor was born in Norwood, MA. After his 1997 graduation from the College of the Holy Cross in Wo rcester, MA, with a B.A. in psychology, he began a career in informati on technology. After working in the technology industry for a number of years, Mr. McGregor returned to graduate school in 2003 at the University of Florida entering a PhD program in cognitive psychology. He is married and currently resides in Gainesville, FL.


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Title: Negative BOLD and Aging: An fMRI Investigation
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Copyright Date: 2008

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Holding Location: University of Florida
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NEGATIVE BOLD AND AGING: AN fMRI STUDY


By

KEITH MATTHEW MCGREGOR




















A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE

UNIVERSITY OF FLORIDA


2006


































Copyright 2006

by

Keith Matthew McGregor

































This thesis is dedicated to Kristi Michelle Stahnke.















ACKNOWLEDGMENTS

This project could not have been completed without the guidance and friendship of

Dr. Keith White, to whom I am so very much grateful. I would also like to thank Dr.

Bruce Crosson for his steadfast leadership and generosity and for providing the nurturing

environment for this endeavor. Finally, I would like to acknowledge Dr. Ira Fischler, Dr.

Keith Berg, Michelle Benjamin, Dr. Jason Craggs, Dr. Timothy Conway, my family and

friends for their support and assistance throughout the completion of this project.
















TABLE OF CONTENTS

page

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

LIST OF TABLES .............. .................. ............ .......... ................. vii

L IST O F FIG U R E S .............. ............................ ............. ........... ... ........ viii

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

CHAPTER

1 IN T R O D U C T IO N ............................................................................. .....................

Functional M agnetic Resonance Im aging..................................... ...............
Negative BOLD and the Present Study ....................................... ............... 1
R ole of Interhem ispheric Connectivity ................................................. ...............3
H y p oth eses .................................................................................. . 4

2 M E TH O D S .................................................................5

P articip ants .................................................................................. . 5
Procedure ........................................ .. ....... ......... 6
Event-Related Block (ER-Block) Imaging Paradigm ......................................6
Performance Evaluation............................................................9
A pparatus ...................... ...................................................................... ........ 10
Functional Imaging Data Analysis ............................................11
Hemodynamic response function analysis........................... ............... 12

3 R E SU L T S ...........................................................................................................13

B ehavioral P perform ance................................................................................... 13
Im aging A naly sis .............. ..... ..............................................13
Hemodynamic Response Function Analysis ...................................... 15
M ultivariate AN OVA ...................... ................................... .... ...........18

4 D ISC U SSIO N ...................................................... 19

L im itation s .................. ............................................................ 2 1
Implications and Future Directions.............................. ...... ........ 22



v









L IST O F R E F E R E N C E S ...................................... .................................... ....................23

B IO G R A PH IC A L SK E TCH ...................................................................... ..................29
















LIST OF TABLES

Table pge

1 Participant characteristics ......................................................... ...............

2 Talairach coordinates and volumes of active voxel clusters in the right Ml
during learned response executions................... .... ... .. ............... 16















LIST OF FIGURES


Figure page

1 Sample stimuli for response conditions are shown for: (A) GO; (B) NO GO; and
(C) N O V EL .......................................... .............................. 8

2 Estimated hemodynamic response functions in a younger participant (s12)...........14

3 Estimated hemodynamic response functions in an older p0061rticipant (s01)........15

4 These four graphs show representations of the estimated hemodynamic response
function av erages.......... ................................................................... ....... .. .... 17

5 Group means overlayed on axial images....................................... ............... 18















Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science

NEGATIVE BOLD AND AGING: AN fMRI INVESTIGATION

By

Keith Matthew McGregor

May 2006

Chair: Keith D. White
Major Department: Psychology

The goal of this event-related fMRI study was to investigate age differences using a

task previously reported to elicit negative BOLD signals. Six (to date) right-handed

individuals from two age groups were trained to perform a right hand, externally paced,

12 finger movements button press sequence. This task was performed during each of

three response conditions: (a) immediate execution of the learned sequence (GO); (b)

suppression of the learned sequence (NoGO); (c) initial suppression of the learned

sequence followed by execution (DelayGO). Four regions of interest (ROI) were selected

for analysis: both primary motor areas (LM1, RM1), and both supplementary motor areas

(LSMA, RSMA). Deconvolution analysis was used to estimate hemodynamic response

profiles (HDRs) of maximally active voxels in each ROI for each response condition.

Repeated measures analysis of variance of HDR profiles was performed across age

groups, response conditions, and ROI. Younger subjects exhibited positive BOLD signals

in LM1, LSMA and RSMA with negative BOLD signals in LM1 during GO and

DelayGO conditions, as expected. Older adults, in contrast, showed positive BOLD









signals in all four ROIs during those conditions. Amplitudes and times to peak of the

HDRs did not differ between age groups. These preliminary results indicate age

differences in activation of R Ml cortex during execution of the right-hand learned

button press sequence. These differences in BOLD signal across age could be related to

the hemispheric asymmetry reduction in older adults (HAROLD) model.














CHAPTER 1
INTRODUCTION

Functional Magnetic Resonance Imaging

Functional magnetic resonance imaging (fMRI) has greatly enhanced our

understanding of brain activation patterns during cognitive tasks. Blood oxygen level-

dependent (BOLD) contrast has been the leading technique used by researchers to

investigate neural correlates of cognitive activity using fMRI. Synaptic activity, whether

excitatory or inhibitory, causes an increase in the local concentration of deoxygenated

hemoglobin (deoxyhemoglobin) due to accelerated oxygen metabolism.

Deoxyhemoglobin reduces the bulk magnetization of nearby protons, reducing the

measured MR signal through a dephasing effect. An overcompensation of oxygenated

blood is then sent to the metabolically active area in a hemodynamic response (HDR)

coupled to the increased oxygen demand. Local deoxyhemoglobin is diluted, raising the

MR signal above baseline. As the oxygen demand returns to baseline levels, so too will

the MR signal gradually return to its baseline. The HDR results in a roughly bell-shaped

MR signal change, a positive BOLD response (PBR) over the course of 10 15 seconds

for a relatively brief interval of synaptic activity. A measurement volume (voxel)

exhibiting PBR signals during tasks is reported as being activated (Ogawa et al. 1990;

Logothetis et al. 2001).

Negative BOLD and the Present Study

A negative BOLD response (NBR) appears like a "mirror image" of the typical

PBR described above, that is a U-shaped rather than bell-shaped time course of MR









signal change. NBR indicates a decrease in metabolic/neuronal activity in the area in

which it is found (Shmuel et al. 2002; Stefanovic et al. 2004; Amedi, Malach, & Pascual-

Leone, 2005). Specifically, Stefanovic et al. (2004) correlated NBR to decreases of

regional metabolic rate of oxygen consumption (CMRO2). In some studies, voxels

exhibiting NBR are included as being activated because they pass a statistical test for

differing reliably from baseline.

Older adults have higher prevalence of NBR as compared to younger adults during

both motor and visual tasks (Aizenstein et al. 2005). Aizenstein et al. (2004) contended

that spatial averaging over a mixture of voxels having different directions of activations

(i.e., NBR versus PBR) could possibly account for previous findings of decreasing

amplitude of BOLD response with increasing age in the visual (Huettel et al. 2001; Ross

et al. 1997; Buckner et al. 2000) and motor cortices (D'Esposito et al. 1999; Hesselman et

al. 2001; Buckner et al. 2000). Older adults have higher inter-individual variability in

BOLD contrast, consistent with individual variations in the mixture of NBR and PBR

(see D'Esposito et al. 2003 for review). However, we are unaware of any studies that

were specifically designed to elicit NBR for the purpose of studying age effects. Many

studies have found NBRs serendipitously rather than by design (Allison et al. 2000;

Roether et al. 2002; Born et al. 2002; Aizenstein et al. 2004; Amedi, Malach, & Pascual-

Leone, 2005) while studies designed to elicit reliable NBRs have not included older

adults (Shmuel et al. 2002; Hamzei et al. 2002; Hamzei et al. 2005; Stefanovic et al.

2004; Hummel et al. 2004; Newton et al. 2005). We have adapted methods from the

latter studies, making some modifications to accommodate older adults, for the present

study.









The NBRs are often elicited in a unimanual motor task wherein the contralateral

(hand controlling) hemisphere's primary motor cortex shows PBR, as expected, but at the

same time and in the homologous location, the ipsilateral Ml shows NBR (Hamzei et al.

2002; Stefanovic et al. 2004; Hamzei et al. in press; Gardner et al. 2005). The amplitude

of the NBR has been shown to be reasonably proportional to, although comparatively

smaller than, than the other hemisphere's PBR (Newton et al. 2005).

Role of Interhemispheric Connectivity

Interhemispheric connectivity is widely believed to be the source of the NBR

(Allison et al. 2000; Shmuel et al. 2002; Stefanovic, et al, 2004). It is well known that

transcallosal synapses are mainly glutamatergic and exhibit excitatory effects on their

target (Gerloff et al. 1998). Thus, cortical cell bodies resident in one hemisphere, which

might extend actively firing axons transcallosally, generate increased metabolic activity

at the target location due to the release of excitatory neurotransmitter. At least one more

level of connections must exist involving inhibitory neurotransmission in order to reduce

neural/metabolic activity. Because cortical inhibitory intemeurons generally synapse

locally (nearly all axons extend <200 microns), the accompanying increase in synaptic

activity (due to both the transcallosal excitatory inputs and the local inhibitory outputs)

will necessarily require a subsequent increase in blood flow resulting in PBR in the target

vicinity. One possibility is that these inter-hemispheric excitatory axons terminate on

dendrites of inhibitory intemeurons that in turn project to multiple pyramidal cells

(Beaulieu and Colonnier, 1985) via axo-somatic or axo-axonal terminal branches (Koos

and Tepper, 1999). Therefore, the downstream synaptic outputs of the pyramidal cells

must be presumed to be disproportionately reduced in order to outweigh the PBR evoked

by the synaptic activities bringing about the volume-averaged synaptic activity reduction.









Negative BOLD could also be exhibited one level downstream of inhibitory

synapses distant from the target vicinity, for example in the thalamus, where reduced

spike frequency would result in reduction of those thalamic axons' synaptic outputs at the

cortex. This alternative means, possibly involving cortico-striatal-thalamo-cortical loops

(Alexander et al. 1990), would also reduce cortical metabolic activity by reducing its

synaptic inputs. If this alternative were to have merit then not only primary motor (Ml)

but also supplementary motor (SMA) cortices would be likely to evidence activations in

at least one but probably both hemispheres. Therefore, regions of interest for the present

study will include both hemispheres' Ml and SMA.

Hypotheses

Furthermore, it is well known that aging has a large influence on the striatum,

specifically that dopamine uptake in caudate and putamen declines with age as indexed

by levels of dopamine transporters (Kish et al. 1992; van Dyck et al. 1995; van Dyck et

al. 2002; Erixon-Lindroth et al. 2005). Reduction of dopaminergic input onto the Dl

receptors in the "direct" path (striatum, globus pallidus internal, thalamus) would be

expected to cause reduced net inhibition of the thalamus, and thus increased cortical

input. This leads us to hypothesize that older adults will have a reduced magnitude of

NBR.














CHAPTER 2
METHODS

Participants

Data from 12 right-handed participants were used to estimate the presence of

negative BOLD in two age groups (6 Young, mean age = 22 yrs, sd = 3.09 yrs; 6 Old,

mean age = 71 yrs, sd = 6.49 yrs), see Table 1. All participants were prescreened by self-

report for claustrophobia, contraindicated medications or metal implants, pregnancy

(when applicable), and pre-existing neurological or psychiatric disorders. Participants

with over two years of recent (within five years) piano playing experience were also

excluded due to potential variation of signal dynamics (Ridding et al. 2000; Krampe,

2002). All participants were recruited and provided written consent after the experimental

procedures were fully explained to them in accordance with the Internal Review Board of

the University of Florida. Cognitive functioning in the older adults was assessed with the

Mini Mental Status Exam (MMSE) with a minimum score of 26 needed for participation.

All participants were asked to avoid caffeine for at least six hours prior to scanning (see

Laurienti et al. 2003; see also Laurienti et al. 2004).

Table 1: Participant characteristics.
Younger Older
N 6 (4 female) 6 (3 female)
Age Range: 19-27 60-76
SD: 3.09 6.49
Mean: 24.0 71.0
MMSE mean (range) N/A 29.2 (28-30)









Procedure

Prior to scanning, participants were trained to "overlearn" a 12 movement button

sequence with the fingers of their right hand. Task training outside the scanner room

began with the participants learning the proper numerical representation for each finger

of the right hand. The thumb was designated as 1 with integer increments for the

subsequent digits (e .g index finger 2, middle finger -3, etc.). The target sequence was

as follows: 5-4-2-3-4-4-2-5-2-3-3-4. Sequenced button press training was performed on a

five-button Model 300 PST Response Box (Psychology Software Tools, Pittsburgh, PA)

and consisted of three phases. The first, a "familiarity phase", required participants to

self-pace sequence practice while viewing a display of the sequence on a laptop

computer. This was followed by a "memorization phase" during which participants

continued self-paced sequence presses, but now with the visual sequence display

removed. Finally, in a cuedd phase", participants were asked to press button sequences in

rhythm with the 1 Hz flashes of a star displayed on a computer screen. After completing

target sequence executions 10 times in a row without error, participants advanced to the

next progressive training stage. Scanning commenced after the successful completion of

the cued phase. All participants were able to train to criterion within the allotted 1-hour

training time.

Event-Related Block (ER-Block) Imaging Paradigm

In the scanner, participants lay supine viewing a fixation cross in the center of the

screen at which they are instructed to maintain fixation throughout scanning. During

each run, button press trials begin after a pseudo-randomly generated resting-state

interval of 6, 7 or 8 TR (10.2, 11.9, OR 13.6 sec). Trials are consisted of four types: GO,

NO GO, DELAY, and NOVEL. The GO, NO GO, and DELAY trials are together









referred to as learned sequence trials, as they involve the execution or suppression of the

target finger movements. The NOVEL trial was added to mitigate boredom during

scanning (see Hummel et al. 2004). Subjects are informed of the trial type through two

different "prepare" cues. Participants are notified of an impending learned sequence trial

by the presentation of a single green "prepare" star in the top center of the screen. After

1 TR (1.7 seconds), the prepare star disappears and one of three trial types commences:

GO, NO GO, or DELAY. Participants were cued of the NOVEL sequence in a similar

manner except that a yellow star is used instead of a green star. An explanation of each

trial type follows and sample images are presented in Figure 1.

In a GO trial, a green "go" star begins to flash at 1 Hz in the center of the screen at

the end of the "prepare" period. The participant was instructed to press the learned

button sequence by timing their button presses with 12 flashes of the green go star. Stars

remain on the screen for 500 ms. We instructed participants to continue through the

sequence even if they believed they made an error at any point during its execution.

In a NO GO trial, a red, "no go" star is displayed in the screen's center cueing the

participant to refrain from pressing the button press sequence.

In a DELAY, as in a NO GO trial, a red "no go" star follows the aforementioned

"prepare" cue. However, after a delay of either 1 or 2 TR (1.7 or 3.4 sec), the red star is

replaced by 12 flashes (also at 1 Hz) of a green "go" star, instructing the participant to

begin pressing the sequence in rhythm with the flashing star. We instructed participants

to maintain attention to the red star as "it may change to green at any point during its

presentation". After the trial's prepare period, the NOVEL response trial requires

participants to press pseudorandomly generated integers ranging from 2-5. The integers








are individually flashed near the bottom of the screen, each remaining visible for 500 ms.

12 of these random integers are flashed during the trial at 1 Hz. The time of display for

each integer is identical to the "go" star flashes in the learned response executions

conditions.










A B








4
C
Figure 1: Sample stimuli for response conditions are shown for: (A) GO; (B) NO GO;
and (C) NOVEL.

In the scanner room, participants were reminded of the task procedures prior to

entering the scanner apparatus and then again immediately before commencement of

functional imaging. After structural acquisition but prior to EPI image acquisition,

participants performed a practice run with representative stimuli. The scanner operator

visually monitored participant performance on an LCD computer monitor in the control

room which displayed the button responses. After successful completion of a full trial

run (6 minutes 41 seconds), functional imaging proceeded. No participants required









additional training or reported discomfort with the task as verified by verbal report

immediately prior to EPI acquisition.

Each of the 6 functional scanning runs (6 min 41 sec each; 1368 total images)

included 12 stimulus presentations in pseudo-randomized order for a total of 72 trials in

the imaging session. Of these presentations, 20 trials each were GO, NO GO, and

DELAY. DELAY trials were further divided into 10 each of 1-TR and 2-TR delays. As

they were mainly used in the paradigm to mitigate boredom, NOVEL trials were

presented only 12 times (2 per run). Pseudo-randomization of the NOVEL button presses

was done during paradigm design and, as such, all subjects received the same NOVEL

press sequences.

Performance Evaluation

Older and younger adults were not expected to vary on behavioral performance

(accuracy and reaction time) due the training procedures and the timed nature of the task

(Janahashi et al. 1995; Rao et al. 1993). Button press performance during scanning was

evaluated on an individual response basis with each button press in the sequence taken as

a response point (52 trials X 12 presses/trial = 624 total response points per participant).

Evaluation of accuracy of each response point takes into consideration not only the

specific button pressed, but also the reaction time. If a participant did not make a

response within 500ms of the cue or made a response within 300ms prior to the cue, then

the button press is marked as incorrect regardless of key identity. Evaluation of errors

was completed with E-Prime 1.1, Microsoft Excel, and simple Perl 5.0 scripts written by

the author. Error rates for tasks of the current study's types have been reported to be less

than 10 percent (Liepert et al. 2001; Verstynen et al. 2005; Gerloff et al. 1998; Hummel









et al. 2004). Reaction times and error rates were averaged across age groups for each

condition and independent samples t-tests were used to compare these means.

Apparatus

All scanning was performed on a Siemens Allegra 3T MRI machine located at the

McKnight Brain Institute of the University of Florida. After each participant was fitted

with an MR-compatible headset (Resonance Technologies Inc.), their head was

positioned within a standard quadrature RF head coil with padding to limit head motion.

First surface mirrors attached to the head coil were positioned above the participant's

eyes and rotated to allow viewing along the scanner bore axis. After the participant had

been moved into the bore, three single slice orthogonally oriented scout images were

obtained to ensure that all parts of the head were within the homogeneous portion of the

magnetic field. The scout images (TR = 18, TE = 4.28, FA = 25 degrees, 256x256,

multiplane slice thickness = 3.0 mm, FOV = 280 mm) were also used to prescribe slice

alignment parallel to the participant's interhemispheric longitudinal fissure. Next, a

magnetic resonance time-of-flight angiogram (MRA) was acquired using TR = 23, TE =

6.15, FA = 30 degrees, matrix = 256x256, axial slice thickness = 5.0 mm, FOV = 240

mm. The MRA allowed slice prescriptions aligned parallel to the anterior commissure -

posterior commissure line as well as to the longitudinal fissure. Slice prescriptions for all

other image acquisitions were copied from the MRA. High resolution anatomic images

were next obtained using a Siemens MPRAGE sequence with TR = 23 ms, TE = 6 ms,

flip angle = 25 degrees, matrix = 256x192, 128 axial slices at 1.3 mm thickness (no gap),

FOV = 240 mm. Lastly, the behavioral task was executed during multiple acquisitions of

gradient echo echo-planar images (EPI) with the following parameters: TR = 1700 ms,









TE = 50 ms, flip angle = 70 degrees, matrix = 64x64, 32 axial slices at 4 mm thickness,

FOV = 240 mm.

Participants viewed stimuli on an IFIS-SA presentation system (InVivo Systems,

Gainesville, FL) using a Dell model 2100MP data projector, rear projection screen, and

first surface mirror display system. Stimuli were projected at 1024 x 768 pixel

resolution, visible to the participant through two mirrors (one on the head coil, another

outside the scanner bore). A MR-compatible button response pad, part of the IFIS-SA

system, attached to the participant's hand and wrist was used to record individual finger

presses throughout the duration of scanning.

Functional Imaging Data Analysis

Imaging analysis was performed with AFNI software (Cox, 1996). The eight initial

magnetization equilibration images (called discarded acquisitions or "disdaqs") from

each functional run were omitted from subsequent analysis. Using a 3-dimensional rigid

body registration, functional images were aligned to a base image from the functional

volume acquired closest in time to structural images. Linear trends in the time series of

each run were removed, and all imaging runs were then concatenated. Deconvolution, a

multiple regression analysis procedure for estimation of hemodynamic response in each

voxel, was performed using AFNI's 3dDeconvolve program. As the GO and DELAY

conditions were very much alike in their execution, the two conditions were combined

into a "learned response execution" condition to enhance statistical power (n = 40

response trials). (A previous analysis of activation patterns both within and across age

groups confirmed that GO and DELAY response conditions do not significantly vary in

correlates of functional activity.) As negative BOLD is believed to be a "mirror image"

of the positive BOLD signal, the non-directional F-statistic was chosen as the output









statistical measure. Activation for a given voxel was determined if the F statistic from the

deconvolution exceeded a value of 3.5 (p<.00001, uncorrected for multiple comparisons).

Hemodynamic response function analysis

We hypothesized that younger adults show a different NBR in R Ml than older

adults during learned response execution. To test this, we compared the time courses of

the estimated hemodynamic response functions as calculated by the 3dDeconvolve

application (Ward, 2002) across older and younger adults. These hemodynamic response

function (HRF) estimates were created as follows. Four regions of interest were

identified: left and right primary motor cortex (L/R Ml), and left and right supplementary

motor cortex (L/R SMA). For each participant and each region of interest, the voxel with

the highest F-statistic was identified and the 16 numerical values from its estimated HRF

time course were saved. An additional four active voxels (F > 3.5, p<.00001) in spatial

contiguity with the maximally active voxel were also identified and 16 numerical values

from each voxel's estimated HRF time courses were also saved. The five saved voxel-

wise estimates of the HRF were averaged for each of the 16 time points, for each

participant and region of interest, to represent the time course of the estimated

hemodynamic response under those provisos. This HRF averaging procedure was carried

out for all 4 regions of interest in all 12 participants. A repeated measures ANOVA (2 X

4 X 16) compared age (young, old); region of interest (L Ml, R Ml, L SMA, R SMA),

and time (16 HRF points).














CHAPTER 3
RESULTS

Behavioral Performance

While learning the button-press response sequence prior to scanning, the older

participants made more errors (older mean = 90.5; younger mean = 32.5, t(10) = 2.38,

p<.04) and required longer to train to criterion (older mean = 34.2 minutes, younger mean

= 24.6 minutes; t(10) = 2.61, p<.03). During scanning, however, there were no

significant differences due to age in either number of errors or reaction times on GO, NO

GO, and DELAY trials. Older participants had slightly longer reaction times on the

NOVEL trials (older mean = 405 msec, younger mean = 365 msec; t(10) = 4.66, p<.01).

The generally comparable accuracies and speeds of executing the learned response

sequence are noteworthy because behavioral performance does not require inclusion as a

covariate in subsequent imaging analyses.

Imaging Analysis

During processing of the fMRI images for individual participants, it became readily

apparent that negative BOLD responses existed, as hypothesized, in the right (ipsilateral)

motor cortex (R Ml) of the younger subjects (see an example in Figure 2) but positive

BOLD response instead existed in the R Ml of the older participants (see an example in

Figure 3). Figures 2 and 3 each present for individual subjects (younger, s12; older, s01):

(a) five examples of estimated hemodynamic response functions (HRFs) from voxels in R

Ml, and (b) sample fMRI axial slices incorporating the "hand knob" region of R Ml. All

brain images are in neurological convention (left = left on axial view). Voxels within R









Ml were selected to form a contiguity group using the following criteria: First, the voxel

having the highest F-statistic associated with deconvolution relative to GO and DELAY

(response execution) conditions combined was identified as the "max-voxel". Next, four

acquisition voxels touching max-voxel and having F > 3.5 were identified. The five

HRFs shown in Figure 2(B) and Figure 3(B) were obtained from the R Ml contiguity

groups for s12 (younger) and s01 (older), respectively.



















A B
Figure 2: Estimated hemodynamic response functions in a younger participant (s12) (A).
Five estimated hemodynamic response functions from four voxel contiguous
to the most highly active voxel (bottom HRF in A) in R Ml of s12 (young
adult) during learned response execution conditions. Voxel locations in
cortex are represented in (B) with colors coding probability associated with
the F statistics (yellow: p<.0001; orange: p<.001; red: p<.005) from
deconvolution analysis.Contiguity group multivariate ANOVA




























A B
Figure 3: Estimated hemodynamic response functions in an older participant (s01) (A)
Five estimated hemodynamic response functions from four voxel contiguous
to the most highly active voxel (bottom HRF in A) in R Ml of s01 (older
adult) during learned response execution conditions. Voxel locations in
cortex are represented in (B) with colors coding probability associated with
the F statistics (yellow: <.0001; orange: p<.001; red: p<.005) from
deconvolution analysis.

Hemodynamic Response Function Analysis

The example HRFs in Figure 2(B) each resemble negative BOLD responses, while

the example HRFs in Figure 3(B) are typical (positive) BOLD responses. This striking

age-related difference in the polarity of BOLD hemodynamic response in these

individuals has been confirmed more generally by: (1) localizing the most statistically

robust contiguity groups, as described above, within four hypothesis-driven regions of

interest (specifically the left and right Ml and the left and right supplementary motor

cortices (SMA), and (2) extracting HRFs from each voxel of these contiguity groups,

calculating area-under-the-curve for each HRF and subjecting these to multi-factor

ANOVA.









Table 2 presents localizations and activation volumes of R Ml contiguity groups,

as defined above, for all subjects for deconvolutions relative to response execution

conditions. Localizations are given in Talairach coordinates. Activation volumes are

based on 1.8 mm contiguity radius for 1 mm3 isotropic voxels centered on max-voxel.

All six younger adults evidenced negative BOLD in the R Ml, while all but one older

adult evidenced positive BOLD in the same area.

Table 2: Talairach coordinates and volumes of active voxel clusters in the right Ml
during learned response executions. Clusters were defined using an F-statistic
threshold set at 3.5 (p<.00001, uncorrected) with a contiguity radius of 1.8
mm3. and volume threshold of 50 [tL. Negative BOLD clusters are shown in
BOLD typeface.
Older Talairach Volume Younger Talairach Volume
Adults Coordinates Adults Coordinates
S01 (-46, -2, 53) 285 LtL s07 (-46 ,-2, 53) 64 pL
S02 (-35, 7, 56) 106 [L s08 (-58, 2, 42) 83 pL
S03 (-30, 14, 52) 110 lL s09 (-39, 19, 40) 74 pL
S04 (-28, 26,57) 454 [tL sl0 (-43, 11,50) 109 pL
S05 (-23, 6, 58) 118 pL sll (-23, 6, 58) 92 L
S06 (-32, 26, 52) 325 tL s12 (-35, 36, 58) 193 pL

Four regions of interest (ROI), left and right Ml and left and right SMA, were

selected within each subject and five-voxel contiguity groups were identified for each

ROI. HRFs were obtained from each of these 20 voxels per subject. Figure 4 shows the

averages of these HRF time courses within each ROI and age group. The ordinates on

Figure 4 show magnitude of HRFs from deconvolution relative to response execution

events. Each ordinate is plotted against image acquisition time (in TRs) relative to the

response execution event, and compares younger and older age groups. This kind of plot

is shown for each ROI. Starting from the top left panel, representing L Ml, large positive

BOLD HRFs were found as expected for both younger and older groups..






17


LMI LSMA












S'9




















Figure 4: These four graphs show representations of the estimated hemodynamic
response function averages of the most highly active voxel and four of its
suprathreshold contiguous neighbors for older and younger adults during
learned response execution. Each of the four graphs shows a different region
of interest (clockwise from top left: L Ml, LSMA, RSMA, RM1). The
ordinate values are the magnitude of the hemodynamic response function
(HRF) shown against time (in TR units) relative to the response event. Large
positive BOLD responses can be seen for older and younger adults in L Ml.
Moderate positive BOLD responses are shown for each age group for SMA
bilaterally. However, in R Ml, younger adults show a moderate negative
BOLD response while the older adults show a large positive BOLD response.

Proceeding clockwise, L SMA and R SMA each showed moderate positive BOLD HRFs

for both age groups. For R Ml, however, younger adults had a moderately negative HRF









while older adults had a large positive HRF. Figure 4 confirms in group averages the

observations illustrated for individual subjects by Figures 2 and 3. Figure 5 compares

averaged Talairached younger and older groups' brains, showing HRF magnitude color-

coded across brain locations in a "glass brain" view

Multivariate ANOVA

Results from a contiguity group repeated measures, multivariate ANOVA indicated

an interaction between age groups and area across the hemodynamic response function

(Hotelling's F(3, 10) = 8.345, p = .003). As this finding was consistent with our

hypothesis of differences in HRF across age groups and regions, we did not interpret

higher-order interactions.


A
Figure 5: Group means overlayed on axial images for A) older adults and B) younger
adults during learned response execution after area-under-the-curve analysis
of estimated HRF. (Yellow indicates large positive area, orange indicates
moderate positive area, and blue indicates negative (below baseline) area.














CHAPTER 4
DISCUSSION

The primary goal of this investigation was to compare negative BOLD responses

(NBR) in older and younger adults on a task previously shown to exhibit NBR. The main

findings are as follows. Individual subject analysis of maximally active voxels in the

primary (Ml) and supplementary motor (SMA) cortices showed different results for older

and younger adults during execution of learned button press sequences. All individuals

in each group evidenced typical positive BOLD responses (PBR) in Ml contralateral to

the response hand as well as in bilateral SMAs during response executions. Younger

participants showed the expected NBR in ipsilateral Ml while, surprisingly, all but one

older adult showed positive BOLD in this region. This difference in BOLD contrast

directions (NBR vs PBR) cannot be explained by performance differences, because the

age groups were nearly identical on measures of accuracy and reaction time for execution

of the learned button press sequence. These results indicate that healthy aging is linked

to changes in interhemispheric communication (see Peinnemann et al. 2002).

The present results are consistent with recent fMRI findings by Newton et al.

(2005). They studied 6 young adult participants (mean age 28) who were instructed to

execute or withhold a 4 Hertz thumb button press after a prepare cue while being scanned

in a block paradigm at 3T. Response execution versus passive fixation point viewing

elicited ipsilateral (to the response hand) Ml NBR with concomitant PBR in the

contralateral Ml. Newton et al. (2005) suggested that negative BOLD might signify

preparation of the ipsilateral Ml for potential cooperation with contralateral Ml if motor









processing became complex enough to require bilateral recruitment. Reduced activity in

ipsilateral Ml could serve to suppress its recruitment by other connections into this area.

The present results are also generally consistent with the model of hemispheric

asymmetry reduction in older adults, or HAROLD (Cabeza, 2002). The HAROLD model

evolved to explain an accumulation of neuroimaging studies comparing BOLD

activations of older and younger adults performing the same tasks, which showed with

some consistency that older adults have less lateralized activation than that seen in

younger adults (Rueter-Lorenz et al. 2000; Garavan et al. 1999; Dixon et al. 2004;

Cabeza et al. 2004). The HAROLD model has been used to describe aging related

activation patterns for a number of specific tasks involving the prefrontal cortex including

verbal working memory, visuo-spatial working memory and pre-potent response

inhibition. Support for the model has also accrued from investigations of hippocampus

(Maguire & Frith, 2003) and motor cortex (Naccarato et al. 2004; James, 2005; Baliz et

al. 2005). One explanation for the HAROLD phenomenon is compensation for declining

functionality in the aging brain by recruitment of cortical homologues (Cabeza, 2002;

Cabeza et al. 2004; Baliz et al. 2005; see also Salthouse & Babcock, 1991).

The Newton et al. (2005) suggestion that NBR in young adults might signify

preparation of R Ml for potential cooperation with L Ml should motor processing

became complex enough, combined with normally declining functionality in the aging

brain and HAROLD, would lead one to expect the BOLD signal direction change

(younger RM1 NBR to older RM1 PBR) observed in the present study. Our findings thus

add further support to the notion of neural compensation by recruitment of cortical

homologues in normal aging.









There are many plausible candidates to serve as the neurophysiological basis for

age-related decline in brain functionality. Age-related vascular changes are common

(Fang, 1976). Structural magnetic resonance imaging has shown that normal aging is

associated with a decrease in the thickness of the neocortex (Salat et al. 2005). Diffusion

tensor imaging has shown that aging is associated with significant increases of water

diffusion, probably resulting from decreases in the diffusion-limiting myelinated fibers

connecting cortical and/or subcortical areas (Pfefferbaum et al. 2005; Salat et al. 2005;

see also Madden et al. 2004). Dopamine uptake in caudate and putamen declines with

age as indexed by levels of striatal dopamine transporters (Kish et al. 1992; van Dyck et

al. 1995; van Dyck et al. 2002; Erixon-Lindroth et al. 2005). Evidence exists that

interhemispheric signaling could make use of cortico-striato-thalamo-cortical loops

(Gerloff et al. 1998; Kuhn et al. 2004; but see also Chen et al. 2004). As an example, a

recent case study reported that a patient lacking the corpus callosum showed TMS-

evoked reduction in ipsilateral motor evoked potentials, thus implicating subcortical

pathways in interhemispheric communication (McNair, 2004; though see Reddy et al.

2000).

Limitations

The present study has two key limitations. First, locations of the NBRs in younger

adults were rather variable (see Table 2), but such variability is common for NBRs

(Allison et al. 2000; Nirkko et al. 2001; Born et al. 2002; Shmuel et al. 2002; Hamzei et

al. 2002; Aizenstein et al. 2004; Stefanovic et al. 2004; Stefanovic et al.. 2005; Newton et

al. 2005). Second, age group comparisons with such a small sample size (n=6 per group)

have questionable generality to the older population. Both Cabeza (2002) and Reuter-

Lorenz & Lustig (2005) emphasize inter-individual variability of functional imaging









results across older adults. This was apparent in the present study because one older

adult (s05, age 68, a champion marathon runner) showed NBR, not PBR, in R Ml during

response execution, a finding which was similar to the NBRs of younger adults. It is quite

likely that variations in social activity, exercise patterns, mental engagement, and other

factors, all contribute to the effects of normal aging on brain activations (Peinnemann et

al. 2002; Dixon et al. 2004). Both of these limitations could be mitigated by expanding

the sample size.

Implications and Future Directions

The current findings may have important implications for the focused development

of motor rehabilitation treatments because the age of the individual has an important

influence on how their primary motor cortical homologues interact. Both practitioners

and researchers are beginning to better grasp the manner in which the brain reorganizes

after stroke or other damage. A primary consideration for the development of treatment

regimens is the ability to identify substrates in the remaining viable tissue to which

functions formerly resident in the damaged tissue can migrate. The use of fMRI to

monitor brain plasticity during recovery of function provides a new tool for the continued

development of customized rehabilitation programs. The present evidence implies that

brain rehabilitation programs may need to be different for people of different age ranges.
















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BIOGRAPHICAL SKETCH

Keith Matthew McGregor was born in Norwood, MA. After his 1997 graduation

from the College of the Holy Cross in Worcester, MA, with a B.A. in psychology, he

began a career in information technology. After working in the technology industry for a

number of years, Mr. McGregor returned to graduate school in 2003 at the University of

Florida entering a PhD program in cognitive psychology. He is married and currently

resides in Gainesville, FL.