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NeuroImage 11, 111–123 (2000)doi:10.1006/nimg.1999.0528, available online at http://www.idealibrary.com on

Cortical Activity Related to Accuracy of Letter Recognition1

A. S. Garrett,* D. L. Flowers,† J. R. Absher,† F. H. Fahey,† H. D. Gage,† J. W. Keyes,†L. J. Porrino,† and F. B. Wood†

*University of California at Davis, Davis, California 95616; and †Wake Forest University School of Medicine,Winston-Salem, North Carolina 27157-1043

Received April 6, 1999

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Previous imaging and neurophysiological studiesave suggested that the posterior inferior temporalegion participates in tasks requiring the recognitionf objects, including faces, words, and letters; however,he relationship between accuracy of recognition andctivity in that region has not been systematicallynvestigated. In this study, positron emission tomogra-hy was used to estimate glucose metabolism in 60ormal adults performing a computer-generated letter-ecognition task. Both a region of interest and a voxel-ased method of analysis, with subject state and traitariables statistically controlled, found task accuracyo be: (1) negatively related to metabolism in the leftentrolateral inferior temporal occipital cortex (Brod-ann’s area 37, or ventrolateral BA 37) and (2) posi-

ively related to metabolism in a region of the rightentrolateral frontal cortex (Brodmann’s areas 47 and1, or right BA 47/11). Left ventrolateral BA 37 wasignificantly related both to hits and to false alarms,hereas the right BA 47/11 finding was related only to

alse alarms. The results were taken as supporting anutomaticity mechanism for left ventrolateral BA 37,hereby task accuracy was associated with automatic

etter recognition and in turn to reduced metabolismn this extrastriate area. The right BA 47/11 finding wasnterpreted as reflecting a separate component of taskccuracy, associated with selectivity of attentionroadly and with inhibition of erroneous respondingn particular. The findings are interpreted as support-ng the need for control of variance due to subject andask variables, not only in correlational but also inubtraction designs. r 2000 Academic Press

INTRODUCTION

The processing of certain visual functions of theerception of discrete objects is widely recognized to beediated by a ventral visual processing system that

1 This work was supported by National Institute of Child Health

nnd Development PHS Grant P01 HD 21887.

111

riginates in striate and extrastriate visual cortex itselfnd extends through the lower lateral and inferiorccipital–temporal cortical region. Also known as the

‘object’’ or ‘‘what is it’’ pathway (Ungerleider and Mish-in, 1982), it is distinguished from a dorsal ‘‘location’’ or

‘where is it’’ pathway coursing upward into the parietalegion. Successive regions in the ventral pathway aresually considered to involve progressively elaboratedspects of visual processing (Mishkin et al., 1983;affan et al., 1986; Maunsell and Newsome, 1987;elleman and Van Essen, 1991; Young, 1992), andithin this putative hierarchy the posterior inferior

emporal portion (Brodmann’s area 37) is selectivelynvolved in object recognition, as first demonstrated in

onkeys (Schwartz et al., 1983; Desimone et al., 1984,991; Tanaka et al., 1991; Perrett et al., 1987).Studies in human subjects also show a posterior

nferior temporal role in object recognition and objectaming (Ungerleider and Haxby, 1994; Price et al.,996; Ungerleider et al., 1998; Moore and Price, 1999).unctional magnetic resonance imaging (fMRI) andositron emission tomography studies (PET) of re-ional cerebral blood flow (rCBF) show activation of BA7 by tasks involving face (Haxby et al., 1991; Sergentt al., 1992), visual patterns (Roland and Gulyas, 1995;chacter et al., 1995; Kawashima et al., 1998), andbjects viewed from different perspectives (Kosslyn etl., 1994). From a clinical perspective, intraoperativelectrophysiological recordings in the human extrastri-te cortex of epileptic patients carried out by Allison etl. (1994) have shown that cells in the bilateral inferioremporo-occipital cortex, in the region of BA 37, re-pond selectively to the presentation of faces, lettertrings, and numbers. Also, patients with damage tohe occipito-temporal region often are unable to recog-ize familiar faces (Damasio et al., 1982), words (Bindernd Mohr, 1992), or symbolic representations of wordsSoma et al., 1989).

Studies of nonpatient volunteers have demonstratedhat the left BA 37 role in object recognition alsoncludes language-relevant objects such as words, pho-

etically regular nonwords, and letter strings. For

1053-8119/00 $35.00Copyright r 2000 by Academic Press

All rights of reproduction in any form reserved.

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112 GARRETT ET AL.

xample, fMRI has shown left BA 37 activation byeneration of rhymes and semantic categories (Shay-itz et al., 1995) and viewing letter strings (Puce et al.,996), and PET studies of rCBF have shown activationf portions of left BA 37 by visual presentation of wordsnd nonwords (Petersen et al., 1989, 1990) or by viewingr reading words (Bookheimer et al., 1995; Buchel et al.,998, Moore and Price, 1999). Activation in the ventrolat-ral portion of BA37 is common to most of these studies.While the above studies indicate a role for BA 37 in

bject recognition, it is unclear how that role relates toccuracy of task performance. If the activation is dueolely to the stimuli involved, without regard to successn recognizing them, then accuracy of performance inecognizing those stimuli should have no relation toctivation. On the other hand, if activation is depen-ent on actual object recognition itself, as indexed byask accuracy, then the activation should be propor-ional to task accuracy. However, accurate performances often less effortful than inaccurate performance (see

ood, 1990, for a review). Consequently, if BA37 activations to any substantial extent proportional to the effortnvolved, and if poor performance indexes greater effort orifficulty, then the activation might be greater with inaccu-ate performance than with more accurate performance.lso the roles of demographic variables, such as age andender, or extraneous task-related variables, such as statenxiety, remain to be clarified.The present study addresses the above questions by

sing a correlational approach that tests the relation-hip of ventrolateral BA 37 activity, during letterecognition, to task performance accuracy, with controlor variance in age, gender, and state anxiety. Of course,ther regions may be expected to be involved in variousf these relationships, but we offer no specific a prioriypotheses about these except to test several appropri-te candidate regions of interest. This multivariateorrelational approach requires larger sample sizes inrder to achieve adequate degrees of freedom (approxi-ately 10 subjects for each variable including global

ctivation, according to the conservative criterion ofarris, 1975), so the present study invests scanning

esources across a large sample of N 5 60, using aingle activation condition. This between-subjects ap-roach, as in a classic study of individual differences,ontrasts with the classic subtraction rationale in whichhe scanning resources are invested within subjects acrossultiple activation conditions and baselines.

METHODS AND MATERIALS

Subjects

Sixty healthy adults (50% male, 18% non-Caucasianll of whom were African American) were recruitedrom the surrounding communities by advertisement

nd word of mouth. The subjects ranged in age from 20 W

o 66 years (mean 40.6, standard deviation 12.3). Theriggs and Nebes (1975) modification of the Annettandedness Inventory classified 51 of the 60 subjectss strongly preferring the right hand, 3 as stronglyreferring the left hand, and 6 as not strongly prefer-ing either hand. Table 1 provides further descriptivenformation of the sample.

Subjects were included if they had no history ofeurological disease, head injury, diabetes or otheretabolic disease, heart disease, drug or alcohol abuse,

eizures, liver disease, or glaucoma or current or recentse of psychoactive or metabolically relevant medica-ions. Subjects were also excluded if their urine drugcreen on the day of scanning showed any evidence ofllegal or centrally acting (e.g., antihistimine) drug use.ll subjects included in the sample had the absence ofpike discharges or observable slow wave activity onesting EEG, had normal MRI of the brain, and hadormal fasting blood glucose levels. By the criteria ofhe Schedule for Affective Disorders and Schizophre-ia—Lifetime Version (Endicott and Spitzer, 1978),ubjects were excluded for histories of bipolar affectiveisorder or schizophrenia or for current unipolar affec-ive disorder. Subjects were selected without referenceo reading ability or Wechsler Adult Intelligence Test—evised subtests (Wechsler, 1981), and their scores oningle-word reading (Letter–Word Identification Sub-est of the Woodcock Johnson—Revised; Woodcock andohnson, 1989) and selected Wechsler subtests wereypical of normal adults, as shown in Table 1.

All subjects were scanned in the morning and werenstructed to abstain from nicotine and caffeine for 24 hrior to the study and from food or drink except waterfter midnight on the day of the study. Subjects wereaid for their participation, the study was approved by

TABLE 1

Demographic and Task Performance Characteristics

Mean Minimum MaximumStandarddeviation

ge 40.6 20 66 12.3ducation (years) 16.2 11 21 2.2nxiety (STAI-S) 30.0 20 64 8.1ercentage hits 96.5 79 100 4.4ercentage false alarms 5.8 0 26 6.0ask d-prime 3.9 1.98 5.58 1.0umber of trials 554 332 762 90.9AIS-R vocabulary 11.5 5 18 2.6AIS-R block design 10.1 5 15 2.4AIS-R digit–symbol 10.2 5 15 2.4AIS-R digit span 9.3 6 17 2.4J-R Word ID 49.3 39.7 51.0 3.6

Note. STAI-S, State–Trait Anxiety Inventory of Spielberger;AIS-R, Wechsler Adult Intelligence Scale, Revised; WJ-R Word ID,

oodcock Johnson—Revised Letter–Word Identification Task.

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113CORTICAL ACTIVITY RELATED TO TASK ACCURACY

he medical school’s Institutional Review Board, and allubjects gave their written consent.

Procedure

Consistent positioning in the PET and MRI scannersas facilitated by individually molded thermosettinglastic masks along with fiducial markers on the mask.rior to FDG uptake, subjects practiced a computer-enerated letter-recognition task (described below) un-il confident of their performance of the task and until ariterion score was achieved (greater than 75% hits andess than 25% false alarms during the trial period).ubjects wore glasses if needed, and none complainedf problems seeing the stimuli. State anxiety (Spiel-erger et al., 1983) was measured just prior to the 10Ci FDG bolus injection, which was delivered into the

ight arm antecubital vein, through an intravenous (iv)ine previously placed but immediately removed afternjection. Blood samples were withdrawn every 15 sver the first 2 min and at minutes 3, 4, 6, 8, 13, 18, 28,nd 38 and following scanning, through a previouslylaced indwelling iv in the left arm, which had beeneated to 110°F. The subject performed the computerask for 35 min, voided, and returned to the PETcanner for acquisition of the emission scan.

Letter Task during FDG Uptake

Stimuli for the letter-recognition task included 12etters (6 uppercase and 6 lowercase; for example, K, V,, and c) and 12 unfamiliar characters (for example, \,0 , ¥, and <) presented in either black or white inside a

agenta box at the center of a computer monitor. Thearget was any of the 12 letters regardless of color,ontarget characters were any of the 12 unfamiliarharacters. Probability of target versus nontarget itemsas 50%. The stimuli subtended a 0.7° visual angle.ach stimulus was flashed for 50 ms. A black dotxation point was displayed continuously in the centerf the screen within the magenta box.The subject controlled the pace of the game by

ressing and holding down the mouse button to start arial and lifting the right finger from the mouse buttons quickly as possible when a target stimulus wasresented. Subjects again depressed the mouse buttono start the next trial. If no finger lift response wasade, and the button remained down, then the next

timulus was presented at a random 1.5 to 2.0 s afterhe prior stimulus.

The computer provided auditory and visual feedbackor both correct and incorrect responses. The differen-ial auditory feedback was a short, higher pitched toner ‘‘beep’’ for correct and a moderately lower pitchedone or ‘‘boop’’ for incorrect. Tones were of equal inten-ity. Visually, several feedbacks were given, as follows.

correct response caused two dots, one below and one e

bove the fixation point, to move by a small incrementoward the fixation point. When five correct responsesere accumulated, then the dots ended up close outside

he magenta box in middle field and a message wasrinted on the screen informing the subject of theward of bonus points for that group of correct re-ponses. The dots were then reset. Incorrect responsesaused a printed statement to appear notifying theubject of the mistake, whether miss or false alarm.inally, after every 17 trials, a rest message wasrinted that informed the subject of a brief (3 s) restefore resuming the task. A critical reaction time waset at 900 ms (i.e., target relevant responses after thisime were recorded as misses). Percentages of hits andalse alarms were used to calculate d-prime, the mea-ure of signal detection accuracy (Green and Swets,966).

MRI Scanning

A 1.5-T GE Signa MRI scanner (GE Medical Systems,ilwaukee, WI) was used to acquire axial 3D spoiled

radient-echo T1-weighted images (2.5-mm thicknessith no interslice gap, TR 5 45 ms, TE 5 5 ms, flipngle 5 45°, NEX 5 1). This anatomic image was usedo localize regions of interest (ROIs) on the PET image.

PET Scanning

All scans in this study were performed using aiemens/CTI 951/31 ECAT scanner which has a resolu-ion of approximately 6.0 mm in all axes. The attenua-ion-corrected emission data were reconstructed withltered back-projection using a Hann filter with a 0.4ycle/pixel cutoff.Quantitative images of glucose metabolic rate were

enerated by applying the method of Phelps et al.1979), and the reconstructed PET images were regis-ered by trained investigators to their respective MRImages using the ‘‘Register’’ program (Neelin et al.,993), validated by Woods (1996). The MRI was placedn stereotaxic space (Talairach and Tournoux, 1988)sing an algorithm developed by Louis Collins ofontreal Neurological Institute (Collins et al., 1994)

nd the PET data were resampled to correspond to theRI image.

PET Regions of Interest Analysis

Gemini, a locally developed software package, simul-aneously displays the MRI and its coregistered PETtudy, allowing any point to be simultaneously viewedn three orthogonal planes (transverse, sagittal, andoronal). It also allows the placement of a spherical ROIo be guided by viewing all three planes simulta-eously.MRI segmentation to isolate the functionally rel-

vant (Kadekaro et al., 1985; Juliano et al., 1981, 1983)

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ray matter signal intensity boundaries was accom-lished by placing small spherical ROIs, of diameter.67 cm, bilaterally in the genu of the corpus callosumrepresenting white matter), the head of the caudateucleus (representing gray matter), and the anteriorerebral ventricles (representing CSF). Relative homo-eneity of tissue type was achieved by accepting onlypheres whose distribution of pixel values had a coeffi-ient of variation (standard deviation as percentage ofhe mean) not exceeding 5% for gray and white matterr 12% for cerebrospinal fluid. The average of theedian pixel values in the two spheres for each tissue

ype was then taken as the criterion pixel intensity forhat tissue. Midpoints between the gray and the white

TAB

Regions

Region of interest(ROI)

Size of spherical Rto locate

alcarine fissure 2.0 cm. Locate the calcarine fissure ontion the sphere entirely within the ocfissure. On coronal view, move the ce1 cm from midline.

rodmann area 37 2.5 cm. Find the most lateral sagittal pporal sulcus and the preoccipital inciT-intersects the occipitotemporal sulintersection by paging through the asphere at this intersection, moving itthe cerebrum.

ngular gyrus 2.0 cm. On saggital views, locate the sumedially to its termination or that ofverify on the axial view. Page down tSTS terminus, and center the sphereessary to place sphere wholly in the c

nferior frontal 2.5 cm. Observe the coronal view tangedisplays the superior, middle (when(IFS). The IFS is easily located as a nverified from the sagittal view. Centemoving it medially until sphere is wh

rbital frontal 2.5 cm. Beginning from a low axial viewbone is visualized around the eyes. Tboth orbits and locate the most medinext gyrus laterally will be the orbitasphere in the gyrus so that the edgesrounding the gyrus. Adjust it verticaoften includes other short sulci.

orsal caudate 2.0 cm. Select the axial slice showing thCenter the sphere on this plane anddoes not infringe on the putamen. It

halamus 3.0 cm. Using all views, position the spmidline and excluding all adjacent bmay include portions of the ventricle

nterior cingulate 2.5 cm. Center the sphere midway betwintersection of the axial and coronaland anterior surfaces of the callosum

Note. Anatomical description for positioning on high-resolution MRalairach and Tournoux (1988); x, sagittal plane (negative indicateertical plane through the anterior commissure); z, axial plane (neg

n mm.

nd between the gray and the CSF tissue criteria thenefined the thresholds for segmenting the MRI pixelsnto tissue types. Gemini then allowed into the analy-es only the PET voxels whose MRI intensities wereithin the gray matter thresholds. The interscorer

eliability (A.S.G. and D.L.F.) for both upper and lowerray matter thresholds, calculated as described for 15andomly selected MRIs, was 0.99.Three-dimensional ROI spheres, chosen a priori to

epresent candidate areas of general interest, wereocated on the MRI image, according to rules presentedn Table 2, which also shows their average location inalairach space (for a more complete description of ROI

ocation rules, see Wood and Flowers, 1999). Separate

2

nterest

and instructione ROI

Average Talairachcoordinates

(x, y, z)

sagittal view nearest midline. Posi-ital pole, its center in the calcariner laterally in the calcarine to a point

Left: 210, 282, 8Right: 11, 282, 8

e passing through the inferior tem-a (occipital notch), which usuallyon the ventral surface. Locate that

l planes in this region. Center thertically to ensure it is wholly within

Left: 246, 268, 211Right: 48, 263, 212

ior temporal sulcus (STS). Pagesuperior (angular) branch andaxial plane that is 1 cm below the

the STS. Page down farther if nec-brum.

Left: 246, 258, 41Right: 47, 253, 42

to the genu of the corpus callosum; itsent), and inferior frontal sulcirly horizontal feature and can bee sphere in the IFS on this plane,

y within the cerebrum.

Left: 240, 35, 12Right: 44, 35, 12

age upward until the orbital frontale observe a coronal plane throughentral gyrus, the gyrus rectus. Theontal gyrus (OFG). Center thethe sphere include both sulci sur-to avoid ocular muscle. The ROI

Left: 230, 40, 29Right: 32, 39, 29

ead of the caudate at its widest.ust from all views, so the spherey extend into the lateral ventricle.

Left: 210, 15, 4Right: 11, 15, 4

e within the thalamus, tangent tol ganglia structures. The sphere

Left: 211, 216, 8Right: 11, 216, 8

n the hemispheres, on the line ofnes tangent to the midline dorsal

(Mid:) 0, 33, 37

izes, and average locations of their centers in the stereotaxic space offt hemisphere); y, coronal plane (negative indicates posterior to a

ve indicates inferior to a horizontal plane through the AC-PC line);

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115CORTICAL ACTIVITY RELATED TO TASK ACCURACY

bservers (A.S.G. vs D.L.F.) had especially close agree-ent (between 0 and 3 mm difference in any plane) for

ll regions except the angular gyri (between 4.5 and 6.0m absolute difference in the x and y planes) and the

rbital frontal gyri (between 4.5 and 6.0 mm absoluteifference in the y plane). Placement of the ventrolat-ral temporal occipital BA 37 sphere is shown in Fig. 1.Histograms of voxel intensity on the PET scan were

aken for each spherical ROI, and the 95th percentileas taken as the glucose metabolic value for each ROI,

onsistent with our prior phantom studies showing it toe the most accurate and reliable measure of metabolicntensity in a region of known intensity (Fahey et al.,998). Similar high-percentile methods have been usedith FDG PET data (Moeller et al., 1987) and 15O PETata (Raichle et al., 1994). Reliability coefficients for

FIG. 1. A three-dimensional ROI sphere (2.75 cm in diameter) enc

ET image. Images are oriented by radiological convention (left is right).

OI values calculated as described were between r 5.87 and r 5 0.99 except for the right inferior frontalr 5 0.75) and right BA 37 (r 5 0.81).

Statistical Analysis

Data were analyzed in two ways, both employingeneral linear models (GLM) to predict glucose meta-olic rate from task accuracy, controlling for individualifferences variables in age, gender, and state anxietynd for whole brain metabolism (Moeller and Strother,991; Friston et al., 1990, 1991). The first methodmployed the ROI calculations described in detailbove using Statistical Analysis Software (SAS Insti-ute, Carey, NC) to construct the general linear models.he second method, voxel-based Statistical Parametric

es left Brodmann’s area 37 on an MRI (on the left) and a coregistered

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apping (SPM), was carried out using SPM96 softwareFriston et al., 1991, 1994, 1995; Worsley et al., 1992),fter conversion to ANALYZE format (Mayo Clinic,ochester, Minnesota). Conversion to standard space

Talairach and Tournoux, 1988) was done using aocally constructed template that is the average of 40 ofhe 60 normal glucose metabolized PET brains. Theormalized PET images were then conventionallymoothed using a 13-mm (FWHM) Gaussian kernel.In the SPM multisubject, single-condition design,

ubject and covariate effects were estimated accordingo the general linear model at every voxel exceeding0% of the mean global gray matter threshold. A heighthreshold of P 5 0.001, uncorrected, was set to identifylusters. Inasmuch as the ROI analyses had alreadyonstrained the total volume to prespecified areas, amall volume correction was employed (Worsley, 1996).

RESULTS

General Linear Models of Regional Metabolism

Pearson correlations between task variables andubject variables are listed in Table 3.The formal GLM predicted metabolism for each ROI

rom d-prime (task accuracy) age, gender, state anxiety,nd whole brain average metabolism. Table 4 lists the Falues and significance levels for each variable in eachLM.A significant F value indicates unique contribution of

hat variable to the regional metabolic-dependent mea-ure after all other sources of variance in the modelave been taken into account (Type III sums of squares).ven after statistical control, d-prime contributed sig-ificantly—and inversely—to the variance in left lat-ral BA 37 metabolism (P , 0.0005). D-prime alsoegatively predicted left angular gyrus metabolismhile it positively predicted left thalamus and right

TABLE 3

Pearson Product-Moment Correlations between TaskPerformance Variables and Individual Difference Variables

Task variable Age GenderAnxiety(STAI-S) Handedness

ccuracy (d-prime) 20.60*** 20.04 20.23 20.08Hits 20.57*** 0.01 20.19 20.12False alarms 0.52*** 0.05 0.33* 20.12

timulus rate(items per minute) 0.12 0.27* 20.14 0.08

rinted messages 0.45** 0.23 0.21 0.03

Note. Gender is coded as male, 1; female, 2. STAI-S, State–Traitnxiety Inventory of Spielberger. ‘‘2’’ indicates an inverse correla-

ion. Nonsignificant correlations with task variables are omitted.* P , 0.05.

** P , 0.005.

s*** P , 0.0001.

rbital frontal metabolism (all at P , 0.05). No otherOI was significantly related to task accuracy. As apecial test for possible confounding effects of handed-ess, rate of stimulus presentation, and number ofrinted error messages delivered to the subjects, welso produced subsequent GLMs for these four regions,dding each of the potential confounding variableseparately. These confirmed that the addition of hand-dness or stimulus presentation rate had little effect onhe relationship of d-prime to regional metabolism.dding the number of printed error messages as atatistical covariate control did not change the area 37nding, but did abolish, i.e., explain, the right orbital

rontal (BA 47/11) relationship to d-prime. Table 5ummarizes these effects on the d-prime affect in theasic general linear model.The calculation of glucose metabolic rate is exponen-

ially weighted from the moment of injection and isherefore dominated by the earlier minutes of theptake period. We addressed this issue by examiningata from the 37 subjects in the experiment on whome had individual trial data. These subjects did notiffer from the total 60 in any demographic or taskariables or in the regional metabolic findings. Withinhe 37 subjects, d-prime for the first 40 or 80 trials was

TABLE 4

F Values (Type III Sums of Squares) for Linear Regres-ion Models of ROI Metabolism Predicted by Individualifferences

ROI

Individual difference variables includedin each general linear model

Globalmetabolism Age Gender

Stateanxiety

Taskaccuracy(d-prime)

calcarine 250.44***calcarine 290.09***BA 37 484.88*** 6.15* (2)14.61***BA 37 568.63*** 12.83**inf frontal 450.89***inf frontal 631.04***orbital 212.51***orbital 272.56*** 4.80*thalamus 334.55*** 4.34*thalamus 386.84*** 9.78**angular G 325.68*** (2)6.34* (2)5.26*angular G 322.76***caudate 243.51***caudate 473.60***nt cing 309.06*** (2)6.13*

Note. ‘‘2’’ indicates an inverse relation. L, left; R, right; Inf, inferior;, gyrus; Ant cing, anterior cingulate.P . 0.05 not shown.

* P , 0.05.** P , 0.005.

*** P , 0.0005.

ignificantly related (r 5 0.64, P , 0.0001 and r 5 0.77,

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117CORTICAL ACTIVITY RELATED TO TASK ACCURACY

, 0.0001, respectively) to d-prime over the entireask period. More importantly, all relations to taskccuracy were the same if the d-prime accuracy scoreas calculated only from the first 40 or 80 trials (onverage, the first 2.5 or 5 min). There was a tendencyor d-prime to improve over trials, but measures of thismprovement showed no relation to the metabolic find-ngs.

Table 6 summarizes the correlations between ROI-alculated glucose metabolism and components of theask performance calculations, including percentage ofits and false alarms, after partialling for age, gender,nxiety, and global metabolism.Scatter plots of left ventrolateral BA 37 and BA 47/11etabolism as a function of d-prime task accuracy are

TABLE 5

F(P) Values for the Independent Contribution to Variancen Region of Interest Activation by Task Accuracy (D-Prime)fter Systematically Adding Rate of Stimulus Presentation,andedness, or Number of Feedback Messages to the Basiceneral Linear Model (Predicting Regional Metabolism from-Prime with Age, Gender, State Anxiety, and Global Activa-

ion Included as Covariates)a

Region of interest

Stimulusrate Handedness

Feedbackmessages

F P F P F P

A 37 13.99 (0.0005) 14.60 (0.0004) 12.93 (0.0007)A 47/11 5.09 (0.0282) 4.65 (0.0356) 0.04 (0.5506)eft thalamus 4.01 (0.0504) 4.27 (0.0438) 4.44 (0.0399)eft angular gyrus 6.10 (0.0168) 5.20 (0.0267) 1.39 (0.2438)

a F(P) in the basic model for d-prime prediction of BA 37 is 14.61P 5 0.0003) and for BA 47/11 is 4.80 (P 5 0.0329).

TABLE 6

Pearson Product-Moment Correlations between Task Per-ormance Variables and Regional Glucose Metabolism inegions of Interest, Controlling for Age, Sex, State Anxiety,nd Global Metabolism

Taskvariable

Region of interest

Lefthemisphere

Righthemisphere

BA 37Angular

gyrus ThalamusOrbitalfrontal

Hits 20.38** 20.11 0.15 0.24False alarms 0.30* 0.12 20.21 20.29*

ccuracy (d-prime) 20.46*** 20.30* 0.27* 0.29*

Note. ‘‘2’’ indicates an inverse correlation.* P , 0.05.

** P , 0.005.*** P , 0.0005.

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Statistical Parametric Mapping Result

With the same covariance for age, gender, statenxiety, and global metabolic rate, the SPM ANCOVAsFriston et al., 1990) corroborated the ROI findings foreft ventrolateral BA 37 and right orbital BA 47/11z 5 3.32, P , 0.05 and z 5 3.73, P , 0.005, respec-ively). These results are summarized in Table 7. Bothhe positive and the negative contrasts are shown inhe ‘‘glass brain’’ renderings in Fig. 4. Notably, the leftngular gyrus and thalamus ROI findings were notuplicated by SPM.ROI a posteriori testing was carried out by placing

-cm spheres centered on the maximum voxels of thewo additional clusters in the right frontal lobe identi-ed with SPM. The center of the a priori selected

nferior frontal 3.0-cm ROI was separated from the twoposteriori SPM maximum voxels within BA 47 and BA1 by 2.6 and 2.8 cm in the axial direction, respectively.either a posteriori ROI reached significance (P . 0.10)

n its prediction of task accuracy.As a final step, a cross correlation was carried out in

PM to determine the shared variance between leftateral BA 37 and all other voxels. The opposingorrelations between d-prime and left lateral BA 37negative) and between d-prime and right orbital BA7/11 (positive) naturally predicted a reciprocal relation-hip between these two regions, but the calculationerved to determine its strength and it also exploredhe possibility of other statistical connectivity to BA 37.or consistency, the calculation covaried for age, gen-er, state anxiety, and mean global metabolic rate. Onlyhe expected negative correlation between the twoegions was found (F 5 3.42; P , 0.01, corrected formall volume of a 2.0-cm sphere).

DISCUSSION

In brief, both the ROI and the voxel-based mappingSPM) methods converged to demonstrate an inverseelationship between left inferior posterior temporalccipital cortex (left ventrolateral BA 37) and taskccuracy as measured by d-prime and separately byits and false alarms. The relationship was statistically

ndependent of age, gender, state anxiety, handedness,ate of subject-paced stimulus presentation, and printedeedback during the task. Right orbital frontal cortexBA 47/11) activity was also positively related to taskccuracy, but only to false alarms and not hits. Theelationship was independent of age, gender, state

nxiety, handedness, and stimulus presentation rate, All other correlations are P . 0.05.

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118 GARRETT ET AL.

ut was abolished (explained) by including feedback inhe statistical model. SPM analysis also found statisti-al connectivity between left ventrolateral BA 37 andctivation in three right frontal regions. The mostentral of these corresponded to the orbital frontalocation. The other two did not show a relationship to-prime.The inverse relationship between task performance

nd left ventrolateral BA 37 metabolism plausiblyuggests that inefficient, or at least less automatized,ask performance is more metabolically demanding

FIG. 2. Scatter plot and regression line of left ventrolateral Btudentized residuals (z scores) after partialling for total metabolism,

FIG. 3. Scatter plot and regression line of right orbitofrontal B

tudentized residuals (z scores) after partially for total metabolism, age,

either in terms of magnitude or spatial extent) of theosterior neural mechanisms than efficient, automaticask performance. The demonstration of inverse rela-ionships between regional activation and task perfor-ance is not novel (Wood et al., 1980; Haier et al., 1992;

enkins et al., 1994; Schlaug et al., 1994; Grady et al.,996; see also the review by Wood, 1990). That thending survives all relevant statistical controls sug-ests that it must relate to task performance specifi-ally. Descriptively, at least, an automaticity ex-lanation whereby better task performance is less

37 metabolism over d-prime task accuracy. Values are plotted ase, gender, and state anxiety, as provided in the GLMs in the text.

7/11 metabolism over d-prime task accuracy. Values are plotted as

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119CORTICAL ACTIVITY RELATED TO TASK ACCURACY

ffortful and less metabolically demanding, is difficulto avoid.

Of course, ventrolateral BA 37 is not the only ventralxtrastriate region to be implicated in lexical process-ng and discrimination. For example, Petersen et al.1990) showed both lateral and medial extrastriatectivation by words and nonwords compared to fixationontrol, but the effect disappeared in the Howard et al.tudy (1992) when the control task was unpronounce-ble letter strings or false fonts. In contrast, activationf the ventrolateral posterior temporo-occipital visualrocessing stream, near or including our ventrolateralA 37 ROI, does survive a number of different compari-

TABLE 7

Stereotaxic Location and Confidence Levels for Maximumoxels Within Clusters Identified by SPM in Predicted Loca-ions (P , 0.001 for Height, Uncorrected, with Small Volumeorrection)

z scoreor height

Coordinates:x, y, z

Brodmann’sarea Cortical area

3.73 40, 46, 214 47/11** Right orbital frontal

Negative contrast

3.32 246, 258, 212 37* Left temporal occipital

Note. Gray matter threshold at 0.80 of mean global metabolic rate.NCOVA normalization for mean global metabolism; confounding

ovariates age, gender, and state anxiety.* P , 0.05.

** P , 0.005.

FIG. 4. Statistical parametric maps (thresholded at P , 0.001,ormal adults during a letter-identification task with age, gender, aetabolism. The orthogonal set on the left shows higher glucose met

hows lower glucose metabolic rate relative to better performance.

on conditions, as in simple viewing of real words vsiewing of face or texture controls (Puce et al., 1996) orvert discriminations such as real words vs lettertrings (Buchel et al., 1998). Activation in this area alsoppears to involve tasks in which silent or overtaming of visual objects is required (Bookheimer et al.,995; Price et al., 1996; Moore and Price, 1999). To beure, objects other than lexical ones also activate thisegion—e.g., pattern matching vs pattern scanningKawashima et al., 1998). Consistent with the above,hen, the ventrolateral BA 37 activity we observe in ourtudy is plausibly relevant to discrimination task perfor-ance, more so than medial extrastriate activity would

e. Furthermore, the fact that ventrolateral BA 37ctivation is inverse to task performance is explainabley the naming data reviewed above (Price et al., 1996;oore and Price, 1999): if subjects adopted a strategy of

ven subvocal naming of the stimuli (Bookheimer et al.,995), and if that strategy is more often adopted byndividuals having more difficulty with the task, thenhe excess ventrolateral BA 37 activity with poorerformance is understandable.The role of the right orbital cortex in this letter

ecognition task was not explicitly predicted. Neverthe-ess, right frontal lateral and orbital activity has beenositively related to percentage of correct responses onface recognition task (Grady et al., 1996), to perfor-ance on a Stroop task (Bench et al., 1993), to task

erformance feedback (Elliot et al., 1997), and to theumber of successive correct responses while shiftingttention between color and shape (Nagahama et al.,

corrected) predicting normalized glucose metabolic rate in N 5 60state anxiety covaried. Voxel values are normalized by global meanlic rate with better performance (d-prime), and the set on the right

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120 GARRETT ET AL.

998). Of special note is the fact that the first two ofhese studies showed reciprocal decreases in otheregions, including extrastriate visual cortex.Reciprocities of activation (some regions increasinghile others decrease) are elsewhere familiar in the

iterature. For example, reciprocal changes in activa-ion with diminishing difficulty over trials of practicen motor tasks have been demonstrated (Grafton et al.,992, 1994; Schlaug et al., 1994; Jenkins et al., 1994).ther studies involving identification of object or word

timuli have suggested an inverse response betweeneft posterior cortical and frontal areas. Howard et al.1992) found a reduction in right inferior prefrontalortex activation (and in other right hemisphere areas)nd increased activation of the left posterior middleemporal gyrus during a single-word reading taskhen the control task was viewing false font stringshile repeating a single word (thus controlling forrocessing of visual patterns, articulation, and audi-ory feedback of subject’s own voice). Buckner et al.1996) also reported opposing anterior versus posteriorctivation, but in the reverse direction with increasedight frontal and decreased bilateral parietal activity,hen subjects performed an auditory semantic memory

ask wherein they recalled practiced word–word oricture–word pairs when the control task was theimple repetition of words.Another example of reciprocity—demonstrating neu-

al system responses to both increases and decreasesn difficulty—occurs in a cleverly designed study byaichle et al. (1994), who examined cortical activationuring verb generation to visually presented nounscontrasted with simply reading a string of nouns).hey found increased activation in left posterior tempo-al cortices (including BA 37) and other regions (ante-ior cingulate, left prefrontal, and right cerebellum) butoncomitant decreased activation in bilateral Sylviannsular cortex and the left medial extrastriate cortex.fter 15 min of practice, however, activity in theseegions reversed while task performance, as measuredy reaction time, decreased simultaneously. Introduc-ng a novel list of nouns returned most of these regionsand reaction time) to the ‘‘naive’’ state, leading thesenvestigators to conclude that separate circuits serve

ore effortful and automatic response choice selectionn a word generation task when visual stimuli are used.otably, however, the method of averaging scans across

ubjects did not allow for a direct analysis of the effectf individual task accuracy on focal neuronal activity.A relationship similar to that of the present studyas reported by Grady et al. (1996) who found that,

ompared to a sensorimotor control task (viewing noiseatterns), the task of matching progressively degradedaces was related to progressive increases in rightrontal BA 9/46 and concomitant decreases in medial

triate and bilateral fusiform (BA 19/37) regions. Accu- t

ate judgments during this self-paced task correspond-ngly declined, as might be expected. It is tempting tonfer a relationship between task accuracy and specificortical changes; however, unexpectedly—and consis-ent with the present findings—a direct correlationetween task performance and cortical blood flow dur-ng the high degradation condition revealed positiveorrelations between accuracy and a right frontal re-ion (BA 45) and negative correlations between accu-acy and left prefrontal cortex and striate cortex.lthough the present study does not systematicallyanipulate quality of the stimuli, targets are made

hallenging to detect by their 50-ms duration and byestricting response time, whereas the Grady study didot constrain stimulus duration or response time.hus, both studies point to the interpretative error thatould be made if the relationship between strength oferformance and regional activity is not specificallyxamined. Of course, forces driving these similar find-ngs may not be the same.

Even though working memory was not explictlylicited by the present task, if a memory strategy wereo be adopted by the subject—such as maintaining aepresentation of ‘‘letters’’ or ‘‘nonletter characters’’—erformance might be enhanced. Consider the findingsf McIntosh et al. (1996) that as retention delay wasncreased on a delayed match-to-sample face percep-ion task there was a decrease in striate and ventralxtrastriate area activity as measured by cerebrallood flow, interpreted as reflecting transient visualerceptual processes, while right prefrontal activityncreased, interpreted as a greater reliance in the moreustained task of holding the object’s icon in workingemory. Right frontal BA 47/11 activation has also

een reported in response to delayed match-to-sampleasks involving face matching (Haxby et al., 1994,995). Thus, if the subjects in the present study differedn their reliance on a strategy that minimized the effortn earlier sensory processing and maximized the effortn maintaining a working memory representation ofhe target stimuli, and if that strategy engenderedetter performance, then the reciprocity of left extrastri-te and right orbital activation could be explained.gainst this explanation, however, is the fact that theegree of a subject’s improvement in performance overrials—which would be expected to reflect an increas-ngly available working memory of the target stimuli—as not related to localized brain activity in our study.Perhaps a more satisfying interpretation of the pre-

ent results relates to task demands, which in this caseequire subjects to withhold responses to particulartimuli as well as to emit responses to target stimuli.otably, in the present study orbital metabolism is

nversely related to the percentage of false alarms butot significantly related to percentage of hits. In con-

rast, BA 37 is related to both hits and false alarms. The

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121CORTICAL ACTIVITY RELATED TO TASK ACCURACY

rbital frontal component, therefore, may be particu-arly related to the allocation of resources to inhibitmpulsive responses, whereas the ventrolateral BA 37omponent may be more directly related to basic targets nontarget discriminations. That would also explainhy statistical control for the number of printed feed-ack messages, which were more highly correlated withariance in errors than in hits, would abolish or explainhe right orbital frontal finding.

Consistent with our a priori decision to interpret onlyhose sites corroborated both by ROI and by SPM, weave declined to interpret the angular gyrus andhalamic findings, which should then be the object ofurther investigation.

Our technique of validating ROI methods by SPM isimilar, albeit directionally reversed, to that of Koepp etl. (1997). They propose that, because of SPM’s moder-te liability to partial volume effects, the conservativeest approach would be to use SPM to generate candi-ate maps and then test them by an ROI method. Inhis case, we had a priori candidate regions, to confirmy SPM.Finally, the role of stimulus familiarity in object

ecognition is not addressed by this study. Hits andisses reflect responses to letters, while false alarms

nd correct rejections are responses to characters.owever, since left ventrolateral BA 37 metabolism is

reater for any correct decision, whether hits or correctejections, then familiarity is not confounded with theecision process itself. However, this explanation muste tested further. The length of the glucose uptakeeriod (35 min) may allow the subject to gain enoughxperience with the foil characters to consider themamiliar; however, no posttest of this was administered.

The present study reduces unexplained variance byccounting for age, gender, and state anxiety. This isariance that would otherwise be treated as errorariance, so some inconsistencies across studies in theiterature may be explained by these sources of vari-nce. On the other hand, despite these controls, thereemains a significant proportion of unexplained vari-nce in localized activation, in the present study andther studies. Future strategies for exploring this ques-ion should include both a correlational approach thatddresses other demographic or state variables andlso a subtraction approach that uses appropriateaseline controls. Both strategies remain important,ince the subtraction strategy would still be subject toonfounds due to such factors as accuracy and statenxiety, which could vary not only between subjects butlso within subjects.The present study, therefore, suggests the followingethodological considerations. Individual task perfor-ance measures should be considered in interpreting

ortical activation. Subject samples need to be of suffi-

ient size to allow for statistical control of subject

ariables. Interactions among task variables, subjectariables, and localized brain activity are not onlyossible but should be expected. Finally, inverse corre-ations and reciprocities of localized brain activityhould not be overlooked, and data analytic strategieshould routinely examine for them.

ACKNOWLEDGMENTS

The authors thank Cathy Eades for her invaluable help in develop-ng and refining the Gemini software used to measure the PET datand also Dennis Vickland, Natalie Price, and Beth Harkness for theirechnical assistance.

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