Regional glucose metabolic changes after learning a complex visuospatial/motor task: a positron emission tomographic study

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1 134 Brain Research, 570 (1992) Elsevier Science Publishers B.V. BRES Regional glucose metabolic changes after learning a complex visuospatial/motor task: a positron emission tomographic study Richard J. Haier, Benjamin V. Siegel Jr., Andrew MacLachlan, Eric Soderling, Stephen Lottenberg and Monte S. Buchsbaum Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA (U.S.A.) (Accepted 29 August 1991) Key words: Learning; Intelligence; Fluorodeoxyglucose; Positron emission tomography; Glucose; Brain efficiency Regional cerebral glucose metabolic rate (GMR) quantified with positron emission tomography (PET) with 18-fluoro-2-deoxyglucose (FDG) was measured twice in 8 young men performing a complex visuospatial/motor task (the computer game Tetris), before and after practice. After 4-8 weeks of daily practice on Tetris, GMR in cortical surface regions decreased despite a more than 7-fold increase in performance. Subjects who improved their Tetris performance the most after practice showed the largest glucose metabolic decreases after practice in several areas. These results suggest that learning may result in decreased use of extraneous or inefficient brain areas. Changes in regional subcortical glucose metabolic rate with practice may reflect changes in cognitive strategy that are a part of the learning process. INTRODUCTION Superior performance of complex cognitive tasks has been associated with lower overall brain glucose metabolic rate (GMR) in 3 positron emission tomographic (PET) studies 1'7'1 and lower cerebral blood flow (CBF) in one study (Berman, personal communication). The PET studies, measuring regional brain uptake of 18- fluoro-2-deoxyglucose (FDG) uptake during the performance of the Raven's Advanced Progressive Matrices (RAPM) 7, verbal fluency 1, or on a separate session from assessment of one subtest of the Wechsler Adult Intelligence Scale (WAIS) ~, showed statistically significant negative correlations between glucose use and task performance in normal adults. These negative correlations suggest that the brains of the subjects doing the tasks well might function more efficiently than those of the poor performers 6'7'H. Subjects performing a complex task well may use a limited group of brain circuits and/or fewer neurons, thus requiring minimal glucose use, while poor performers use more circuits and/or neurons, some of which are inessential or detrimental to task performance, and this is reflected in higher overall brain glucose metabolism. Or efficiency could be a characteristic of neurons throughout the cortex so that any task performed in any combination of areas might use less glucose in a more efficient brain. Both views are consistent with the pattern of inverse correlations reported between psychometric task performance and GMR across the whole cortex. In the present study, we looked for within-individual changes in brain glucose use when performing a visuospatial/motor task (the Tetris computer game) for the first time and then after practice. The task, described below, was chosen because it is difficult enough so that marked and continuous improvement is shown over many sessions so that brain activity during good and poor performance can be compared. Also, to determine which brain regions are important in performing this task, regional brain glucose metabolic rate was compared to that in subjects viewing visual stimuli passively. We hypothesized that, with improved performance of the task after practice, there would be overall decreased brain FDG uptake, consistent with the inverse correlations found between GMR and complex task performance. We also predicted negative correlations between task performance and absolute glucose metabolic rate (GMR). We expected relative changes in GMR after practice might occur in those brain regions that are used in the performance of this kind of task, those important in attention, planning, visuospatial manipulation, problem-solving and motor learning, motor coordination, and sensory and motor functions of the right hand. Correspondence: R. Haier, Department of Psychiatry and Human Behavior, University of California, Irvine, Med. Sci. I, Rm. D404, Irvine, CA 92717, U.S.A.

2 135 lil I::IIIIIHII I:: I.',~11111::11111o Io Io I I.-k'lll;:l::lllllo I ",/.17".1~!~, I:: x'lllil:: IIIIO IO IO I--I.~1 Fig. 1. The Tetris game in progress from left to right. Subjects attempt to manipulate configurations of 4 square blocks falling from the top of the screen to produce solid rows of blocks. Once a solid row of blocks is completed, it disappears and is replaced by the row above it. Symbol markings show individual shapes which have already been placed. Note the bottom row of the middle pannel is complete; in the panel on the fight it has disappeared (one point is scored) and the rows above moved down. MATERIALS AND METHODS Twenty-four right-handed males volunteered to undergo PET scans. Eight performed the Tetris learning task, and 16 were in the Continuous Performance Task (CPT) no task condition during the 35-rain glucose uptake period. Both conditions are described below. The group performing the learning task were years old (mean + S.D ), and the CPT no task group were years old (mean S.D. = ). All were recruited by advertisements on the UCI campus, and were screened and found to be without any history of psychiatric, neurological, or major medical disorder. Each of the subjects who performed the Tetris learning task was scanned with FDG PET on two occasions 4-8 weeks (mean + S.D. = days) apart. On the first occasion (naive scan), each subject was injected with FDG after a maximum of 3 min of practice playing the video game, Tetris, and on the second occasion (practiced scan), after Tetris practice sessions of rain in duration, 5 times/week. During the 35-min FDG uptake period for both scans, the subjects played the Tetris game, which requires the subject, using a computer keyboard, to rotate and move objects, consisting of 4 square blocks in various configurations (see Fig. 1) in such a fashion as to try to create a solid row of blocks. The objects move downward from the top of the screen, and as the game progresses, if performance is good, their speed increases. When a solid row is complete, the row disappears, and all the blocks above it drop down to replace the completed row. The score was visible on the screen at all times and equals the number of lines of blocks that are created filling the entire horizontal aspect of the computer screen. Subjects were instructed to try to get the highest score possible. All subjects used their right hand during task performance. The number of button presses and the amount of hand movement were not recorded. The subjects in the CPT no task condition 7'9 passively viewed visual stimuli on a screen during the 35 min following FDG injection. On the screen, single digits (0-9) were projected for 40 ms at a rate of one every 2 s. Subjects were told to view the stimuli, but were not asked to respond to them in any way. After the 35-min FDG uptake period, subjects were moved to the PET scanner, a NeuroECAT. Resolution in plane is 7.6 mm and 10.9 mm in the Z-dimension (verified at time of acceptance). Scanner resolution of 7.6 mm FWHM (full width half maximum) governed the structures selected for analysis. Many structures, includ- ing the medial areas of the frontal lobe, cingulate, thalamus, pons, and cerebellum extend vertically more than one slice thickness, diminishing further the risks of partial voluming. Nine or 10 slice planes were obtained parallel to the canthomental (CM) line at 10 mm increments starting at 85% of head height (vertex to CM line, usually about cm). Patients were scanned for min. Scans were transformed to glucose metabolic rates (GMR) as elsewhere 2. The min resolution of the deoxyglucose method in this study may have advantages over the shorter time resolution of blood flow measures. Since the task requires continuous performance on a series of randomly varying stimuli, a short time interval for assessment might be more variable both in physiological and behavioral response; no clear advantage of examining only 40 s of behavior using a shorter half-life tracer is apparent. Cortical regions of interest were measured using our cortical peel technique3"4; subcortical and medial cortical structures were located using stereotaxic coordinates derived from a standard neuroanatomical atlas 8. Where slice levels are indicated, they are expressed as percentage of head height measured perpendicular to the canthomeatal line from the line to the highest point on the head. Greater percentages of head height indicate higher (more dorsal) regions. In addition to the analysis of the entire cortical surface, in order to measure activity in the motor and sensory cortical regions for the hand, we analyzed GMR for the precentral and postcentral cortical peel regions exactly as in our previous study 4, but included only the 80, 74, and 68% atlas levels. These areas approximate those characterized by Penfield and Rasmussen 12 in their classical intraoperative brain stimulation studies. In addition to the 63 bilateral (126 total) subcortical and medial cortical regions-of-interest (ROI) included in our standard template used in our previous studies, we added regions of interest in the pons and cerebellum (Fig. 5). The coordinates of these areas were developed from magnetic resonance images (MRI) of 10 normal subjects. The structures were analyzed at the 14% Matsui and Hirano atlas level, but the anterior/posterior and left/right brain dimensions were taken from a higher slice (28% level) to avoid potential variability in the frontal lobe edges on the PET scan from affecting the position of the template. Boxes, 3 by 3 pixels (57.8 mm 2) in size, were placed in the cerebellum and one by one pixel (6.3 mm 2) boxes were placed in the pons. The cerebellar peduncle boxes were placed immediately lateral and posterior to the lateral and posterior edges of the pons. In the anteroposterior dimension, the vermis boxes were placed anterior to the posterior edge of the cerebellum, at a distance of one third the maximum distance between anterior pons and the posterior edge of the cerebellum (MAP). In the left/right dimension, these boxes were placed in the midline, such that left and right vermis boxes overlapped. The anterior cerebellar cortex boxes were placed 15% of the maximum width of the cerebellum (MWC) away from the lateral edges of the cerebellum and at half the MAP from the posterior edge of the cerebellum. The posterior cerebellar cortex boxes were placed at 20% of MWC from the lateral edges and 20% of MAP from the posterior edge of the cerebellum. The middle cerebellar cortex box was placed exactly halfway between the anterior and posterior cerebellar boxes. Errors in ROI placement result primarily from two sources: failure to return the head to the same position in the second scan, and individual divergence from the proportional atlas coordinates. We measured variation in our headholder using MRI in a separate study in which a triangle of vaseline-filled tubes was placed on the thermoplastic mask. The transection of this set of tubing shows up as two dots and slices at different heights above the CM line will have varying distances between the two points. In 5 subjects scanned twice, we measured the distance between the two tubing marks on each occasion. Using the proportion of the triangle, we were then able to calculate the variation in vertical (axial) height. The mean of the absolute value of the axial height differences was 2.6 mm, S.D. = 2.3 mm. We also measured the anteroposterior distance

3 136 between a horizontal line drawn from one tube reference mark and the posterior tip of the caudate nucleus. The mean absolute value of this distance was 2.3 mm, S.D. = 1.7 mm. Thus, our repositioning error was about 2 mm on repeat MRI (small with respect to PET FWHM) and is expected to be in the same range for repeat PET on the same subject since the identical mask and headholder are used for both MRI and PET. Individual divergence from proportional atlas coordinates would affect the metabolic measurement, but would be the same from scan 1 to scan 2 and not produce spurious learning effects. However, we have measured the accuracy and limits of the stereotaxic method with MRI for our smaller structures, including the caudate nucleus and vermis. Comparisons for these brain areas show a good correspondence between our sterotaxic and our MRI templates. For example, the caudate (center of mass) is located at stereotaxic atlas proportional coordinates x = 59.8%, y = 30.9%; actual MRI measurement in 20 subjects selected at random showed the caudate center of mass at x = 58.6% (S.D. = 1.8) and y = 33.6% (S.D. = 2.0). The vermis was clearly visible on 18 of 20 subjects. We measured the width of the vermis at its widest point. The anteroposterior (y) position and left and right margins (x) were recorded and transformed to percentages as described above. The measurements showed a mean (y) position of 78.5% and left and right (x) positions of 45.1% and 54.1% Our atlas coordinates of 79.3% (y) and 49% thus fall well within the vermis. For individuals one S.D. below the mean width, our entire box falls inside the vermis. Further calculation shows that for 94.1% of individuals, the box is entirely within the vermis. Anxiety might decline from scan 1 to scan 2, and this decline could be associated with changes in metabolic rate. Therefore, we assessed state anxiety with the Spielberger scale t3 just before FDG injection and again just after the end of the uptake (before the scan). BMDP 5 was used for all statistical analyses including analysis of variance (ANOVA, BMDP 4V), t-tests (3D), and correlations (8D). For each region the Tetris subjects were compared to themselves in the two conditions (naive vs practiced), and each condition was compared to the CPT no task group. Because of the large intersubject variability of whole brain glucose metabolic rate, we routinely calculate a ratio of regional GMR to whole brain mean GMR (for surface cortical structures) or to whole scan slice mean GMR (for subcortical structures) for each region. This ratio, termed the relative glucose metabolic rate, controls for this source of variance. All statistical analyses were done for both GMR and relative GMR. For cortical regions, 3 4-way ANOVA's were done with condition (naive vs practiced conditions, and each of these conditions vs CPT no task), hemisphere (left, right), brain lobe (frontal, parietal, temporal, occipital), and anteroposterior lobar segment (4 gyral areas in each lobe). To generate new hypotheses of learning, exploratory t-tests were performed for all brain regions for both GMR and relative GMR (GMR divided by whole slice mean GMR). Because the same group of subjects was scanned twice, one-sample t-tests were performed for practiced minus naive GMR for each region for comparisons between naive and practiced conditions. For the Tetris subjects, for each scan and for scan 2 minus scan 1, correlations between GMR and task performance for GMR and relative metabolic rates were calculated and tested for 2-tailed significance. Only correlations for analogous score and GMR are reported, i.e. naive GMR vs naive score, practiced GMR vs practiced score, and practiced minus naive GMR vs practiced minus naive score; not naive GMR vs practiced score etc. Bonferroni corrections for multiple comparisons were applied post-hoc in any tests of significance where P < We are also reporting any P < 0.05 differences uncorrected for multiple tests, because the number of comparisons done in an exploratory PET study is necessarily quite large, making it extremely difficult for any one comparison to reach statistical significance by Bonferroni criteria. On the one hand, those regions reaching significance prior to c O 10'4 0 ~----~ I O- I -- ~0 215 I 4-- 4iO ---I 0 5, Doys of Pro(rice Fig. 2. Tetris learning curve. Plots average score (lines completed) at each practice session. Some later sessions included fewer subjects. Bonferroni correction may be useful for hypothesis generation and comparison to other studies. But, given the large number of comparisons, a P < 0.05 level of significance must be interpreted with caution. RESULTS Game performance All 8 Tetris subjects showed markedly improved scores from the first to the second scan. The average + S.D. number of lines completed during the first scan was with a range of , and during the second scan, average + S.D. was with a range of The correlation between practiced score and naive score was 0.23 (NS). A learning curve (Fig. 2) was generated by averaging the scores of all the subjects on their nth practice session. Some subjects had more prac- tice sessions than others, so fewer subjects were averaged for the later sessions. The learning curve demonstrates that performance improves at the most rapid rate during the first sessions and at a slower rate after that. Since the points in the curve for the later times represent fewer subjects, no accurate estimate of the time after which no improvement occurs can be made. Anxiety There were no differences in state anxiety score before and after either the naive or the practiced scans (mean for prenaive scan, 31.3; S.D. = 9.1 and postnaive, 33.4; S.D. = 6.8; mean for prepractice scan, 31.3; S.D. = 5.6 and postpractice, 34.8; S.D. = 7.0; all comparisons not significant by t-tests). Comparisons of the CPT no task group to the Tetris groups Tables I and II show GMR and relative GMR com- parisons, respectively, among the Tetris naive and prac- ticed conditions and the CPT no task group for cortical

4 137 TABLE I GMR in cortical lobes compared among CPT no task (n = 16), naive and practiced Tetris conditions (n = 8) Surface cortical GMR compared by 4-way ANOVA with repeated measures, condition (naive, praticed) x lobe (frontal, parietal, temporal, occipital) x segment (1-4) x hemisphere (left, right), shows trend for main effect for condition (F = 5.18, df 1,7; P = 0.057). See Tables III and IV for cortical segment differences. Same 4-way ANOVA (non-repeated measures) for naive vs CPT no task: group! lobe F = 4.66, Huynh-Feldt df 1.46, 32.08; P = 0.026; group! segment! hemisphere F = 2.78, Huynh-Feldt df 2.98, 65.49; P = 0.048; group! segment! hemisphere x lobe F = 2.18, Huynh-Feldt df 5.79, ; P = For practiced vs CPT no task: no significant effects. The analysis of the hand motor and sensory areas revealed a left greater than right asymmetry in GMR for the Tetris naive group compared to the opposite asymmetry in the CPT no task group. This was tested by ANOVA: group (Tetris, CPT) x level (top 3 brain slices) x structure (precentral, postcentral gyrus; see Fig. 3)! hemisphere (right, left); for GMR, level! hemisphere x group, F = 16.14, df 1,22; P = ; for relative GMR, hemisphere x group interaction, F = 14.43, df 1,22; P = Means showed the left greater than right asymmetry in levels 74 and 68% of head height for Naive Practiced CPT no task Mean S.D. Mean S.D. Mean S.D. Frontal Parietal Temporal Occipital Whole cortex areas. GMR is most similar between the CPT no task group and the practiced Tetris condition. The naive Tetris condition shows the highest GMR for cortex. An ANOVA comparing naive Tetris to CPT no task (group! lobe! segment x hemisphere) showed significant interactions for group x lobe; group! segment x hemisphere; and group! lobe x segment x hemisphere (see legend Table I). These differences are illustrated in Fig. 3. For relative GMR, the same ANOVA showed significant effects for group and for group x lobe interaction (see legend Table II). There were no significant effects in the ANOVAs comparing the practiced Tetris condition with the CPT no task group. TABLE II Relative GMR in cortical lobes compared among CPT no task (n = 16), naive and practiced Tetris conditions (n = 18) Surface cortical relative GMR compared by 4-way ANOVA with repeated measures, condition (naive, practiced)! lobe (frontal, parietal, temporal, occipital)! segment (1-4) x hemisphere (left, right): no significant effects. Same 4-way ANOVA (nonrepeated measures) for naive vs CPT no task: group effect, F = 4.72, df 1,22; P = 0.04; group! lobe F = 5.03, Huynh-Feldt df 1.84, 40.37; P = For practiced vs CPT no task: no significant effects. Naive Practiced CPT no task Mean S.D. Mean S.D. Mean S.D. Frontal Parietal Temporal Occipital Whole cortex Precentral / Postcentral.... / Supramarginal M,ddle r r n t. ~ e i. i o r ~ _ parietal Iobule Superior, I f l ~ / ~ ~,.Angular gyrus frontal \ J,,x~1111iii~i~i.:'.~i~J.liii:: ::~::i~::::::~//'~'~ll'~l Lateral occipital l I~!:.::i:.:.lvJ77/~i~i~i~T '.--~B--19 I'f:iiii~K/'///~ ~ilililiiii~////,i t::i~ ~7 kll:iiiilf///////lr ' / ~ 1 9 Inferior frontal / ~. ~. ~ ~ 7. / Middle tempora-'~ Infertor temporal Superior temporal Posterior temporal Fig. 3. Surface cortical regions differing in relative GMR between subjects in the Tetris naive condition and subjects in the CPT no task condition. The bottom illustration shows the position of the cortical gyri with individual gyri shaded to show anatomy. In the top illustrations (right and left hemispheres, respectively), areas where Tetris naive was higher than CPT no task are shaded black, indicating two-tailed P < , (P < 0.05 after Bonferroni correction). Diagonal lines indicate P < 0.05 (but NS after Bonferroni correction), and no shading indicates areas not significant. Speckling indicates the regions where CPT no task subjects had higher relative GMR than did Tetris subjects (P < 0.05, NS after Bonferroni correction).

5 138,,,~//,g///4 k' "~-'/////~ NI life I/ ~/4F//,A.,, L. _, ~ ~l ( I J ~////~ y ~ "X,N ~ ~, 4 / t_..4r_l~i JA" A I~ I'k-x-k M I...f~ V~:~..,el7 Fig. 4. Cortical regions showing decreases in GMR with practice (see Table IV). The name of each region is shown in Fig. 3 (bottom). All significant decreases (shading) were bilateral except for the posterior temporal gyrus (left only). Tetris but not for CPT no task. The 80% level was sym- metrical, suggesting a hand area localization. We ex- pected Tetris to activate the left motor strip more than CPT no task. The precentral gyrus had the expected asymmetrical motor activation -- asymmetry scores (right minus left/left plus right) were for Tetris and 0.01 for CPT no task (t = 2.43, P = 0.027). These results demonstrate that this sample size was sufficient to reveal regional task effects. Cortical glucose metabolic rate changes with practice A condition (naive vs practiced Tetris) by hemisphere by lobe by segment repeated measures ANOVA for cerebral cortical GMR showed a nearly significant condition effect (F = 5.18, df 1,7; P = 0.057). As predicted, this effect was a decrease in GMR with practice (whole cortex mean GMR naive, 39.2, S.D ; mean practiced, 28.8, S.D. = 7.1, see Table I). This condition effect was not significant for relative GMR. Since all higher order interactions with condition had trend level (<0.10) significance, we performed exploratory simple interaction analyses for each lobe (repeated measures, condition by hemisphere by segment). These showed a condition effect (F = 5.22, df 1,7; P = 0.056) and a condition! segment effect (F = 5.31, Huynh-Feldt df 1.95, 13.65; P = 0.02) for the frontal lobe, a condition effect for the parietal lobe (F = 5.51, df 1,7; P = 0.051), TABLE III GMR and relative GMR for each surface cortical region in naive and practiced conditions: left and right hemisphere values averaged Condition by lobe by segment by hemisphere ANOVA showed a nearly significant condition effect (F = 5.18, df 1,7; P = 0.057). Condition (naive vs practiced) by segment by hemisphere ANOVA's (simple interactions) for GMR for each lobe showed the following effects: a: frontal lobe: condition (F = 5.22, df 1,7; P = 0.056); condition by segment (F , Huynh-Feldt df 1.95, 13.65; P ). b: parietal lobe: condition (F = 5.51, df 1,7; P = 0.051). c: temporal lobe: none. d: occipital lobe: condition by segment (F = 5.86, Huyn- Feldt df 1.77, 12.38; P = 0.02); condition by segment by hemisphere (F = 4.12, Huynh-Feldt df 2.11, 14.78; P = 0.04). For relative GMR, the only significant simple interaction was condition by segment for the frontal lobe (F = 3.41, Huynh-Feldt df 2.56, 17.93; P = 0.046). Cortical regions GMR Relative GMR Frontal lobe gyri Superior frontal Middle frontal Inferior frontal Precentral 46.1" Parietal lobe gyri Postcentral 40.8* Supramarginal 41.9* Angular 45.3* Superior parietal Temporal lobe gyri Superior temporal Middle temporal Inferior temporal Posterior temporal Occipital lobe Brodmann's areas Area Area * Area 17, dorsal half Area 17, ventral half * Differs from practiced condition by one sample, 2-tailed t-test, P < Naive Practiced Naive Practiced Mean S.D. Mean S.D. Mean S.D. Mean S.D "

6 139 Sul~rlor F Svl~rlor From~ml G ~ v s ~ ~ Frlmtol Gyra Medial FrontIl N '~;..i~i ~ %1, ~+~ ~!i:~i White Matter " CinQulatl Gytul IdickJlll.+.+~+ L COl+pUS ~OIO414Ht Cingulota Gyrul ~ [i ~L... i, poltlrior CinlFltOll G),rul ~ V prtcuniul- PatallUl~ h'~ I~t "-.~P'_~,~ ~ 'j +-'-" - + ~ W~ Ant~rtm' ktol Gyrul Orblto4 G y r ~ PoItlriOr RIctol Gyrw - i 1 ~cl~ Pmllri0+ Cerebellum- br~-~' ++ +.!, i+ ram, I% pxllrkdr l~rlllllror 4Mlrltl Fig. 5. Subcortical regions-of-interest showing changes in GMR between naive and practiced Tetris scans, as detailed in Table V. Each slice is labeled with percent head height above the canthomeatal line. Black boxes are locations where P < 0.05.

7 140 and condition! segment (F = 5.86, Huynh-Feldt df 1.77, 12.38; P = 0.02) and condition! segment x hemi- sphere (F = 4.12, Huynh-Feldt df 2.11, 14.78; P = 0.04) effects for the occipital lobe (see Tables I and III). For relative GMR only the frontal lobe (condition! seg- ment, F = 3.41, Huynh-Feldt df 2.56, 17.93; P = 0.046) was significant (see Tables II and III). Two-tailed t-tests comparing each cortical region between the two condi- tions (see Table IV and Fig. 4) showed significant GMR decreases with practice for the left and right precentral cortex, the left and right postcentral cortex, the left an- gular gyrus (right angular gyrus P = 0.052), the left posterior temporal cortex, and the left area 17 of the occipital cortex (right area 17 P = 0.052). For relative GMR, significant decreases were in the left postcentral gyrus and the left angular gyrus. A significant GMR increase was in area 18 of the right occipital cortex. Since we noted the greatest relative activation be- tween Tetris and CPT no task in the left motor strip area at the 74% level, we examined metabolic change with practice in this area. A significant decrease was confirmed (-20.0, practice minus naive difference score, one sample t = 3.55, P = 0.009). Levels 80 and 68% were not significant, nor was the difference for the right side. Thus, the largest drop was for an area identified as the left hand area in the Tetris naive vs control task contrast. TABLE IV GMR and relative GMR in cortical segments compared between naive and practiced conditions (areas significant by t-test only) All these comparisons were non-significant after Bonferroni correction. Segment GMR Naive Practiced 2-tailed P level Mean S.D. Mean S.D. Left precentral Right precentral Left post. central Right post. central Left angular gyrus Right angular gyrus (0.052) 1 Left post. temp Left area Right area (0.052) 1 Relative GMR Left post. central Left angular gyrus Right area These nearly significant results are included to show bilaterality comparisons. TABLE V Subcortical and medial cortical regions showing significant differences (by t-test, 2-tailed) in GMR between naive and practiced conditions All these comparisons were non-significant after Bonferroni correction. Region Naive Practiced Mean S.D. Mean S.D. P Right paracentral 80% Left superior frontal 74% Right superior frontal 74% Left paracentral 74% Right paracentral 74% Left precuneus 74% Right precuneus 74% Left paracentral 68% Left superior frontal 61% Right ant. cingulate 54% Left post. cingulate 54% Right post. cingulate 54% Left precuneus 54% Right precuneus 54% Left mid. corpus coll. 47% Left caudate 41% Left ant. cingulate 34% Left frontal white 34% Left putamen 34% Right putamen 34% Right globus pallidus 34% Left superior coll. 34% Left fusiform 34% Right fusiform 34% Left ant. cingulate 28% Left putamen 28% Right inferior coll. 28% Left orbital gyrus 21% Left uncus 21% Right posterior pons 14% Right cereb. vermis 14% Left mid. cereb. cortex 14% Left ant. cereb. cortex 14% Right post. cereb. cortex 14% % indicates percent of head height from CM line of the slice in which the structure is measured according to Matsui and Hirano. 2 These nearly significant results are included to show bilaterality comparisons.

8 141 TABLE VI TABLE VII Subcortical and medial cortical regions showing significant differences (by t-test, 2-tailed) in relative GMR between naive and practiced conditions Regions with significant correlations between Tetris score and glucose metabolic rate in each condition All these comparisons were non-significant after Bonferroni correction. Region Right precuneus 74% 1 Left sup. frontal 61% Left cingulate 61% Right post. cingulate 54% Left ant. cingulate 28% Right hippocampus 28% Left mid. cereb, cort. 14% Left ant. cereb, cort. 14% Right post. cereb, cort. 14% Naive Practiced Mean S.D. Mean S.D. P ' % indicates percent of head height from CM line of the slice in which the structure is measured according to Matsui and Hirano. S u b c o r t i c a l a n d m e d i a l cortical g l u c o s e m e t a b o l i c rate comparisons between naive and practiced conditions E x p l o r a t o r y t w o - t a i l e d t-tests b e t w e e n the n a i v e and practiced conditions for G M R are shown in Table V (only areas w h e r e there is a significant difference are shown). G M R decreases significantly with practice in 7 areas bilaterally, 7 areas on the fight only and 13 areas on the left only. R e l a t i v e G M R (see Table VI) significant decreases are in t h e left s u p e r i o r frontal c o r t e x, the left a n t e r i o r cingulate, the right p o s t e r i o r cingulate gyrus, t h e left Naive condition r Practiced condition r GMR Relative GMR left caudate right superior colliculus right posterior rectal gyrus none GMR Relative GMR left superior frontal left putamen left inferior temporal right cerebellar vermis none Practiced minus naive condition GMR r Relative GMR r Left paracentral gyrus Right mid. corpus cal. Right post. corpus cal. Right frontal white Left globus pallidus Right globus pallidus Left putamen 28% Right inferior coll. Left ant. rectal gyrus Right ant. rectal gyrus Left post. rectal gyrus Left amygdala Left hippocampus Right hippocampus Right post. cerebellum Left anterior pons Right anterior pons Left posterior pons Right mid. cereb, cort Right frontal white Left anterior thai. Left med. thalamus Right lateral thai. Right caudate Left putamen 34% Right putamen 34% Left sup. coll. Right putamen 28% Fig. 6. PET images (41% atlas slice) of a subject in naive and practiced conditions, showing decreases in GMR.

9 142 anterior and middle cerebellar cortex, and right posterior cerebellar cortex. Significant relative GMR increases are in the right precentral frontal cortex, the right hippocampus, and the left cingulate gyrus. All these significant areas are shown in Fig. 5. Fig. 6 shows an example of a PET slice for one subject before and after practice. Correlations between GMR and task performance No correlations between GMR and Tetris score in either condition were significant (Table VII) in an exploratory analysis. For relative GMR, 3 areas showed correlations between metabolic rate and score in the naive condition and another 4 areas showed correlations in the practiced condition. The change in GMR (practiced minus naive), however, shows widespread correlations with the change in score (practiced minus naive). For GMR, all 19 significant correlations are negative whereas, for relative GMR, eight of nine significant correlations are positive. None of these areas (listed in Table VII) overlap between GMR and relative GMR with the exception of fight frontal white matter. No cortical areas showed significant correlations between GMR change and score change. DISCUSSION The major finding of this study was the decrease in overall brain glucose metabolism following practice. This is consistent with our previous study 6'7 which showed a correlation between better performance on a difficult test of abstract reasoning and lower glucose metabolism. The findings of the 1988 study generated the hypothesis that the brains of those who are better at a task are more efficient, i.e. use less energy during the task. The findings of the current study that, after learning, brain energy use is reduced during task performance is not inconsistent with our hypothesis. While it is possible that individual brain cells metabolize glucose more efficiently after learning (e.g. derive more phosphate bonds per mole of glucose), this explanation for our findings seems unlikely. We believe that during the first attempts at playing the game, the subjects are trying out many different cognitive strategies for the task, thus using many different brain circuits involving varied brain areas. After much practice, it is likely that subjects have developed a set strategy for performance of the task and thus use fewer brain circuits and/or fewer neurons per circuit with the resulting less overall brain activity. The correlation between improvement on the task and decreasing brain glucose use suggests then that those who honed their cognitive strategy to the fewest circuits improved the most. The absence of significant correlations between task performance and overall brain metabolism in both the practiced and naive conditions fails to support our 1988 findings. The Tetris task involves hand-eye coordination and spatial operations. It is therefore, interesting that Table III reveals that the cortical areas which change with practice involve motor and sensory strip, the primary visual region, and the angular gyrus. GMR in these areas decreases significantly after learning, as predicted. Additional regions in the medial temporal lobe, medial frontal lobe, basal ganglia, and cerebellum may be important both for attention and hand-eye coordination. No area showed an increase in GMR but some areas showed increases relative to the brain slice. These areas (Tables IV, VI), including the right area 18 and parts of the cingulate gyrus and hippocampus, may be involved in a shift of cognitive strategy to use these areas. SUMMARY AND CONCLUSIONS Our PET study of changes in regional glucose metabolic rate after practice of a complex visuospatial/motor task showed a significant decrease in whole brain glucose metabolism with learning, and showed changes in GMR in several medial cortical and subcortical regions, the precuneus, medial superior frontal gyrus, cingulate gyrus, hippocampus, and cerebellum. We believe that the decrease in overall brain glucose with practice reflects a more selective use of brain circuitry, reflecting a better-honed cognitive strategy which was formed during the learning process. Changes in metabolism in hippocampus and frontal cortex with practice may reflect the importance of those regions in learning and planning. 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