Rostral and dorsal anterior cingulate cortex
make dissociable contributions during
antisaccade error commission
Frida E. Polli†‡§, Jason J. S. Barton¶, Matthew S. Cain†, Katharine N. Thakkar†, Scott L. Rauch†, and Dara S. Manoach†储†Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02215; ‡Department of Psychology, Suffolk University,
Boston, MA 02114; ¶Departments of Neurology, Ophthalmology, and Visual Sciences, University of British Columbia, Vancouver, BC, Canada V6T 1Z4;
and 储Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA 02129

Edited by Edward E. Smith, Columbia University, New York, NY, and approved September 8, 2005 (received for review May 5, 2005)

The anterior cingulate cortex (ACC) participates in both performance optimization and evaluation, with dissociable contributions
from dorsal (dACC) and rostral (rACC) regions. Deactivation in rACC
and other default-mode regions is important for performance
optimization, whereas increased rACC and dACC activation contributes to performance evaluation. Errors activate both rACC anddACC. We propose that this activation reflects differential errorrelated involvement of rACC and dACC during both performance
optimization and evaluation, and that these two processes can be
distinguished by the timing of their occurrence within a trial. We
compared correct and error antisaccade trials. We expected errors
to correlate with an early failure of rACC deactivation and increased activation of both rACC and dACC later in the trial.
Eighteen healthy subjects performed a series of prosaccade andantisaccade trials during event-related functional MRI. We estimated the hemodynamic responses for error and correct antisaccades using a finite impulse-response model. We examined ACC
activity by comparing error and correct antisaccades with a fixation
baseline and error to correct antisaccades directly. Compared withcorrect antisaccades, errors were characterized by an early bilateral
failure of deactivation of rACC and other default-mode regions.
This difference was significant in rACC. Errors also were associatedwith increased activity in both rACC and dACC later in the trial.
These results show that accurate performance involves deactivation of the rACC and other default mode regions and suggestthat both rACC and dACC contribute to the evaluation of error
responses.
default-mode network 兩 performance evaluation 兩 task-induced
deactivation 兩 inhibition 兩 cognitionE

lectrophysiological and neuroimaging studies consistently report anterior cingulate cortex (ACC) activity during error
commission (1–5). The ACC, however, is a heterogeneous structurethat can be parsed into dorsal (dACC) and rostral (rACC) regions
based on cytoarchitecture, function, and connectivity (6–9). The
dACC extends caudally from the genu of the corpus callosum to thevertical plane of the anterior commissure and connects with thelateral prefrontal cortex and hippocampus to regulate effortful
cognitive operations. The rACC lies anterior and ventral to thegenu of the corpus callosum and forms a circuit with the amygdala,insula, and ventral striatum to oversee emotional processing (forreview, see ref. 10). Given these specializations, it is likely that thedACC and rACC make different contributions during error commission. In the present study, we examined activity in both theseregions during different phases of error commission.
Error-related activity in both rACC and dACC is thought toreflect their contributions to performance evaluation (2, 5, 11). The
dACC is believed to be the primary generator of the error-related
negativity (ERN) (5, 12), an event-related potential occurring
80–180 ms post-error (13), although a generator in the medial
prefrontal cortex (PFC) has also been reported (14). Two chief
theories exist regarding the functional significance of the ERN and
15700 –15705 兩 PNAS 兩 October 25, 2005 兩 vol. 102 兩 no. 43

dACC activity: error detection (13, 15) and conflict monitoring (4)(for review, see ref. 16). Both theories posit that the dACC interacts
with the lateral PFC to effect changes in future response selection
based on feedback from previous responses. Error-related rACC
activity is less consistently observed with functional MRI (2, 3, 11)than dACC activity (1), and the role of rACC in error processing
is less well understood. The rACC also has been implicated in ERN
generation (14), consistent with the finding that ERN amplitude
correlates with negative affect (17, 18). The error positivity, an
event-related potential occurring 300–500 ms post-error, has also
been localized to the rACC (5). Error-positivity amplitude correlates with error awareness (19), skin-conductance response during
error commission (20), and negative affect (17). These findings
suggest that the rACC is involved in the affective appraisal of errors.
In addition to their role in performance evaluation, rACC anddACC are thought to play reciprocal roles in performance optimization (21). With demanding cognitive activity, dACC activity
increases while rACC activity decreases [i.e., task-induced deactivation (TID)] (9, 21, 22). In addition to the rACC, TID also isobserved in regions comprising the default-mode network, including the orbitofrontal cortex, posterior cingulate cortex, superior
temporal cortex, dorsomedial PFC, and angular gyrus (22–25). The
putative function of TID in rACC and other default-mode regions
is to optimize performance by allocating resources to task-necessary
regions and away from task-extraneous ones (21). This hypothesis
is consistent with findings that performance impairments correlatewith increased activity in rACC and other default-mode regions(26). Thus, increased error-related rACC activity might reflect its
contribution to both performance optimization and evaluation.
These two processes could be distinguished by the timing of theiroccurrence within a trial: activity related to performance optimization should precede activity related to performance evaluation.
While dACC and presupplementary motor area activity is known
to increase during response preparation and to decreased prior toan error (27, 28), the timing and relationship of TID in rACC andassociated regions to error vs. correct responding have not been
determined.
In the present study, we used a saccadic task and rapidpresentation, event-related functional MRI to examine dACC andrACC activity during error commission. Event-related functional
MRI allows us to determine whether TID fails specifically during
error trials, and the timing of its occurrence within a trial. The task
consists of a pseudorandom sequence of prosaccade (PS) andantisaccade (AS) trials. PS trials require the simple prepotent
This paper was submitted directly (Track II) to the PNAS office.
Freely available online through the PNAS open access option.
Abbreviations: AS, antisaccade; PS, prosaccade; ACC, anterior cingulate cortex; dACC,
dorsal ACC; rACC, rostral ACC; TID, task-induced deactivation; ERN, error-related negativity; PFC, prefrontal cortex; HDR, hemodynamic response.
§To whom correspondence should be addressed at: CNY 149, Room 2608, 13th Street,Charlestown, MA 02129. E-mail: fpolli@nmr.mgh.harvard.edu.
© 2005 by The National Academy of Sciences of the USA

www.pnas.org兾cgi兾doi兾10.1073兾pnas.0503657102

Methods
Subjects. Twenty-one subjects were recruited from the community

by poster and web-site advertisements. Data from three subjects
were excluded, two because of eye-tracker malfunction and one
because of near-perfect (0.5% error rate) AS performance. Analyses were conducted on the remaining 18 subjects (11 male, 7
female; mean age, 33 ⫾ 11 years). All subjects were strongly
right-handed (mean Edinburgh score, 90 ⫾ 12) (32). Before
scanning, subjects practiced the task. Subjects were instructed torespond as quickly and accurately as possible and were told that theywould receive a five-cent bonus for each correct response, an
incentive intended to mitigate fatigue and boredom.
Apparatus. Images were acquired with a 3.0-T Trio whole-bodyhigh-speed imaging device equipped for echoplanar imaging (EPI)(Siemens, Iselin, NJ). Head stabilization was achieved with cushioning, and all subjects wore earplugs to attenuate noise. Eyemovement stimuli were generated by a Macintosh G4 Power Mac
using programs written in C⫹⫹ on the VISION SHELL programming
platform (MicroML, St. Hyacinthe, Quebec) and back-projectedwith a color liquid-crystal display projector (Sharp, XG-2000,
Osaka, Japan) onto a screen positioned on the head coil. The
ISCAN functional MRI Remote Eye-Tracking Laboratory (Burlington, MA) recorded saccades during scanning. This system used
a video camera mounted at the rear of the MRI bore. The camera
imaged the eye of the prone subject through an optical combiner,
a 45° cold transmissive mirror that reflects an infrared image of theeye. Infrared illumination was provided by a small light-emitting
diode cluster mounted on the head coil. Eye images were processedby ISCAN’s RK-726PCI high-resolution pupil兾corneal reflection
tracker. Eye position was sampled at 60 Hz.
Saccadic Paradigm. Each saccadic trial lasted 4,000 ms (Fig. 1). Trials

began with a 300-ms instructional cue at screen center. For half ofthe subjects, a yellow ring and blue cross were the cues for PS and
AS trials, respectively. The cues were reversed for the remaining
subjects. The cue was flanked horizontally by two small white dotsof 0.2° diameter that marked the potential locations of targets, 10°
left and right of center. These dots remained on the screen for theduration of each run. The cue was then replaced by a white fixation
ring at the center with a diameter of 0.4° and a luminance of 20
cd兾m2. After 1,700 ms, the ring shifted to one of the two target
locations chosen at random. This ring was the target to which thesubject responded. The ring remained in the peripheral location for
1,000 ms, then returned to the center, where subjects were required
to return their gaze for 1,000 ms before the start of the next trial.
Polli et al.

Fig. 1. Schematic depiction of a 4,000-ms saccadic trial. Trials began with a
300-ms cue instructing participants to make either a PS or an AS. The cue wasthen replaced by a fixation ring, which shifted to one of two target locations
flanking the cue horizontally. This target was the one to which subjects
responded. The ring remained in the peripheral location for 1,000 ms, thenreturned to the center for 1,000 ms.

Randomly interleaved with the saccadic trials were 2-, 4-, or 6-s
fixation trials. Subjects performed six runs of the task, with short
rests between runs. Each run consisted of a random sequence of PS(26–46), AS (24–46), and fixation trials (10–17), and lasted 5 min
22 s each. A technique to optimize the statistical efficiency of
event-related designs determined the schedule of events (33). The
total experiment lasted ⬇45 min and generated a total of 200 PS
and 200 AS trials and 79 fixation trials.
Image Acquisition. Automated shimming procedures were per-formed, and scout images were obtained. Two high-resolution
structural images were acquired for spatial normalization andcortical surface reconstruction using a 3D MPRAGE sequence[repeat time (TR)兾echo time (TE)兾Flip ⫽ 2530 ms兾3 ms兾7°; voxel
size, 1.3 ⫻ 1.3 ⫻ 1 mm]. T1- and T2-weighted structural images withthe same slice specifications as the blood oxygenation leveldependent (BOLD) scans were obtained to assist in registeringfunctional and structural images. Functional images were collectedusing a gradient echo T2*-weighted sequence (TR兾TE兾Flip ⫽2,000 ms兾30 ms兾90°). Twenty contiguous horizontal slices parallelto the intercommissural plane (voxel size, 3.13 ⫻ 3.13 ⫻ 5 mm) wereacquired interleaved. The functional sequences included prospective acquisition correction (PACE) for head motion (34). PACE
adjusts slice position and orientation in real time during dataacquisition, which reduces motion-induced effects on magnetization history.
Analysis of Imaging Data. All analyses were done by using FREESURFER (35) and FREESURFER FUNCTIONAL ANALYSIS STREAM(FS-FAST) (36) software. In addition to online motion correction(PACE), functional scans were corrected retrospectively for motion
using the AFNI algorithm (37), intensity-normalized, and smoothedusing a 3D 8-mm full width at half maximum (FWHM) Gaussian
kernel. Functional scans were aligned to the averaged MPRAGE
structural scans. The averaged MPRAGE scans were also used toconstruct inflated (2D) models of individual cortical surfaces using
an automated procedure involving segmentation of gray and whitematter (38), tessellation of the gray兾white border (35), and inflationof the folded cortical surface (39). Each subject’s reconstructed
brain was then transformed using sulcal兾gyral patterns to an
average spherical surface representation (35). This representation
provided a 2D surface-based spherical coordinate system onto
which functional data were resampled after further smoothing witha 2D 8-mm FWHM Gaussian kernel (40). Cortical activity was
localized using an automated surface-based parcellation system
PNAS 兩 October 25, 2005 兩 vol. 102 兩 no. 43 兩 15701

PSYCHOLOGY

response of looking toward a suddenly appearing visual target. AS
trials require the suppression of the prepotent PS and the substitution of the novel behavior of looking in the opposite direction. We
restricted our comparisons of correct and error responses to ASs
because errors occur almost exclusively on AS trials in healthy
subjects on this task (29). Moreover, AS performance has been
associated with TID in rACC and other default-mode regions (30),and AS errors generate robust performance evaluation indices (e.g.,
ERN and error positivity) (19). We hypothesized that, comparedwith correct ASs, AS errors would be characterized by (i) decreased
TID in rACC and other default-mode regions early in the trial,reflecting a failure of performance optimization, and (ii) increased
activity in both rACC and dACC later in error trials, consistent with
their purported roles in performance evaluation. We also investigated whether early rACC activity would correlate with error rate
in individual subjects, consistent with the notion that a failure of
TID would compromise performance. Finally, because TID inrACC (and other default-mode regions) during ASs may arise from
activation of these regions during fixation (31), we also comparedcorrect ASs with correct PSs to determine whether there wasdifferential TID.

Fig. 2. Findings of differential rACC and dACC activity at early and later time points during correct and error antisaccade trials. Statistical activity maps displayedon the inflated medial cortical surfaces for the three contrasts (correct ASs vs. fixation, error ASs vs. fixation, and error vs. correct ASs) for the two early time points,
2 and 4 s (a), and the two later time points, 6 and 8 s (b). Gray masks cover noncortical regions in which any activation is displaced. (c) The HDRs for the dACC
and rACC, as well as posterior cingulate cortex (PCC), dorsomedial PFC (DMC), superior temporal cortex (STC), and angular gyrus (AG) minima in the correct vs.
fixation contrast. (d) The HDRs for the dACC and rACC maxima in the error vs. correct contrast. Time in seconds is on the x axis, and percent signal change relative
to the fixation baseline is on the y axis. All HDRs are an average of left- and right-hemisphere minima兾maxima HDRs. Although clusters ⬍120 mm2 are displayed,
they are not considered significant.

(41). The ACC was divided into dorsal and rostral regions using aline drawn at the anterior boundary of the genu of the corpus
callosum that was perpendicular to the intercommisural plane (6).
A finite impulse-response model (36) was used to estimate theevent-related hemodynamic responses (HDRs) for each of the four
15702 兩 www.pnas.org兾cgi兾doi兾10.1073兾pnas.0503657102

trial types (correct PSs, error PSs, correct ASs, and error ASs) for
each subject. A finite impulse-response model uses a linear model
to provide unbiased estimates of the average signal intensity at eachtime point for each trial type, rather than making a priori assumptions about the shape of the HDR. We used 12 time points with an
Polli et al.

Table 1. Minima兾maxima for dACC and rACC in the threecontrasts of interest at 4, 6, and 8s
Coordinates

Correct vs. fix 4 s
LH rACC
LH dACCRH rACCRH dACC
Error vs. fix 4 s
LH dACC兾preSMA
RH dACC
Error vs. correct 4 s
LH rACC兾dACC
RH rACC
Error vs. correct 6 s
LH dACCRH rACCRH dACC
Error vs. correct 8 s
LH rACCRH rACCRH dACCxyz

P value

mm2

⫺13
⫺11
12
10

48
⫺3
44
⫺2

11
32
6
33

6.3 ⫻ 10⫺7
1.6 ⫻ 10⫺7
7.9 ⫻ 10⫺6
7.9 ⫻ 10⫺7

821
2,976
696
2,310

⫺9
7

0
⫺9

35
37

5.0 ⫻ 10⫺8
2.0 ⫻ 10⫺7

2,696
539

⫺7
6

26
36

21
13

2.5 ⫻ 10⫺5
1.0 ⫻ 10⫺4

143
209

⫺11
8
4

22
28
9

27
22
25

1.0 ⫻ 10⫺7
2.0 ⫻ 10⫺6
2.0 ⫻ 10⫺6

908
1,215
1,215

⫺9
11
10

32
28
15

21
22
30

2.0 ⫻ 10⫺6
1.6 ⫻ 10⫺5
1.3 ⫻ 10⫺4

537
1,566
1,566

suboptimal TID in rACC during correct trials, increased rACC
activity during error trials, or a combination of both.
Finally, to investigate whether TID during correct ASs could be
due to activation of default-mode regions during fixation, we
compared correct ASs with PSs to determine whether TID differed
between them.
Results

If from the same cluster, minima兾maxima are ⱖ10 mm apart. LH, left
hemisphere; RH, right hemisphere.

interval of 2 s (corresponding to the TR), ranging from 4 s before
the start of a trial to 18 s after the start. Temporal correlations in
the noise were accounted for by prewhitening using a global
estimate of the residual error autocorrelation function truncated at
30 s (36). Using the finite impulse-response parameter estimates, we
examined the following four contrasts: correct ASs vs. fixation,
error ASs vs. fixation, error vs. correct ASs, and correct ASs vs.
correct PSs. The significance of each contrast was tested using arandom effects model in which the mean and standard error werecomputed across subjects. We used cluster thresholding to correct
for multiple comparisons (42). We ran 1,000 Monte Carlo simulations of the averaging and clustering procedures using synthesizedwhite Gaussian noise data smoothed and resampled to the sphericalspace as input volumes. Clusters of voxels of P ⱕ 0.001 and 120 mm2
in surface area were found only 44 times, setting the overall P levelto 0.044.
We derived cortical surface maps for two early time points (2 and4 s after the start of the trial; 2 s corresponds to target onset) andtwo later time points (6 and 8 s) in the trial to temporally andspatially dissociate ACC activity due to performance optimization
vs. evaluation. We also examined the HDRs of minima and maximafor (i) the rACC, other default-mode regions, and the dACC in thecorrect AS vs. fixation contrast to determine whether the timing ofchanges in activity was consistent with performance optimization;and (ii) the maxima for rACC and dACC from the error vs. correct
AS contrast to determine whether the shape of their HDRs wasconsistent with a role in performance evaluation. Because previous
studies report that event-related HDRs begin ⬇2 s after stimulus
onset and peak between 4 and 7 s (43–45), we expected optimization activity to begin at 2 s and peak at around 4 s and evaluation
activity to begin later at 4 s and peak at around 6 s.
To determine whether early rACC activity correlated with errorrate, we performed linear regressions of the number of errors by
raw estimates of the hemodynamic activity in each vertex for thethree contrasts of interest (correct ASs vs. fixation, error ASs vs.
fixation, and correct vs. error ASs) at 4 s, when we expected
performance-optimization activity to be maximal. These analyses
allowed us to determine whether error rate was correlated with
Polli et al.

Fig. 3. Statistical map for vertex-wise cortical surface linear regression of
number of errors by raw estimates of the hemodynamic activity (BOLD, blood
oxygen level-dependent) at 4 s in the correct ASs vs. fixation contrast displayedon the inflated right medial surface.

Behavioral. As expected, subjects had significantly higher AS thanPS error rates [AS, 8.0 ⫾ 5.5%; PS, 2.6 ⫾ 1.8%; t(17) ⫽ 4.97, P ⬍0.0001]. Only 0.3% of fixation trials were characterized by a loss offixation.

Cortical Surface Analyses. Early time points (2 and 4 s). Error andcorrect AS trials vs. fixation. Deactivation was observed bilaterally

in posterior cingulate cortex and in the left superior temporalgyrus during correct but not error trials at both 2 and 4 s (Fig.
2a). At 4 s, deactivation also occurred bilaterally in rACC,
dorsomedial PFC, angular and inferior frontal gyri, and rightsuperior temporal and orbitofrontal cortices during correct but
not error trials. In contrast, dACC and neighboring supplementary motor area and presupplementary motor area showedbilaterally increased activity at 4 s for both correct and error ASs.
Examination of the HDRs for the minima in rACC and otherdefault-mode regions, as well as the maxima for dACC兾presupplementary motor area, derived from the correct AS vs.
fixation contrast, indicated that activity changes began at 2 s andwere maximal at 4 s (Fig. 2c). See Table 1 for Talairach
coordinates (46), P values, and cluster sizes for rACC and dACC
minima兾maxima.
Error vs. correct AS trials. Increased activity was observed on therACC兾dACC border in the left hemisphere and in the right
rACC at 4 s. The HDRs for the rACC and dACC revealed thatat 4 s, increased activity in rACC was primarily due to a decreasein activation from baseline during correct but not error ASs(Fig. 2d).
Correct AS vs. correct PS. The only default-mode area thatshowed significantly greater TID at 4 s was the left angular gyrus(Fig. 4).
Later time points (6 and 8 s). There was significantly greater dACC andrACC activity in the error vs. correct contrast at both 6 and 8 s (Fig.
2b). The basis of this increased activity was greater activity during
error trials rather than deactivation during correct trials. Inspectionof the HDRs revealed that activity in both dACC and rACC was
increased starting at 4 s but differed in shape. dACC activity peaked
sharply at 6 s and dropped off rapidly, whereas rACC activity
peaked later at 8 s and rose and fell more gradually (Fig. 2d). There
was also significantly greater activity in bilateral insula, inferior
frontal gyrus, and medial frontal gyrus for error vs. correct trials at
6 and 8 s.
Cortical surface-based regression analyses. Contrary to our hypotheses,
error rate was not related to rACC activity at 4 s in any of the threecontrasts. The only significant correlation with errors was in theright dACC during the correct vs. fixation contrast (coordinates of
PNAS 兩 October 25, 2005 兩 vol. 102 兩 no. 43 兩 15703

PSYCHOLOGYContrastFig. 4. Statistical maps displayed on the inflated medial and lateral corticalsurfaces for the correct AS vs. PS trials at 4 s.

maxima, 10.0, 2.8, 32.5; cluster size, 187 mm2) (Fig. 3), where
increased activity correlated with a lower error rate.
Discussion
Consistent with our hypotheses, rACC and dACC were differentially involved in the early and late phases of error commission. In
the early phase of the trial, correct, but not erroneous, AS performance was associated with bilateral deactivation of the rACC andother regions thought to comprise the default-mode network. This
result suggests that deactivation of rACC and associated defaultmode regions is associated with accurate task performance. In
contrast, dACC and neighboring supplementary motor area andpresupplementary motor area showed increased activity early inboth error and correct trials and did not differ between them. Thisfinding, along with the finding that early increased activity in dACC
was associated with fewer errors, suggests that these regions contribute to effortful cognitive performance and兾or conflict monitoring. In the later phase of the trial, relative to correct trials, ASerrors were associated with increased activity in both rACC anddACC. This result is consistent with previous findings that implicate
these regions in performance evaluation (1). More generally, ourfindings suggest that rACC and dACC make distinct contributions
to the optimization and evaluation of cognitive performance overthe course of a trial.
These findings are consistent with other evidence that TID intask-extraneous regions facilitates optimal performance, and thatits absence is associated with performance decrements (26, 47).
These findings extend this work in two important ways. First, they
demonstrate that TID occurs during correct but not error trials.
This association may have been missed by previous studies of error
commission that compared error trials with correct trials but not toa baseline condition. A baseline comparison is necessary to resolve
whether differential activity between two conditions, such as error
vs. correct trials, is due to a relative increase in activation during
errors, a relative decrease in activation during correct trials, or both(24). Two studies that compared error and correct trials with
fixation did not report differential TID between the two conditions(2, 47). Differences in various factors that influence TID, including
stimulus presentation rate and task difficulty (48), may account fordiscrepant findings.
The second extension of previous work concerns the timing of
TID. Using an event-related design, we found that TID in thedefault-mode network during correct trials began 2 s after cue
presentation, was significantly different from baseline at this time
point in superior temporal cortex and posterior cingulate cortex,
and was maximal throughout the network at the 4-s time point.
Increased dACC兾presupplementary motor area activity followed
the same pattern. Activity in rACC and dACC during error trials,
15704 兩 www.pnas.org兾cgi兾doi兾10.1073兾pnas.0503657102

presumably related to performance evaluation, showed a different
pattern of activity. It began 2 s after target presentation at the 4-stime point and peaked at the 6- and 8-s time points. These results
demonstrate that TID during correct trials occurs earlier thanincreased rACC兾dACC activity during error trials. We interpret
this finding to reflect that TID is preparatory whereas increased
ACC activity is evaluative.
However, our interpretations regarding the exact roles of TID vs.
increased ACC activity must be tempered, given the limited temporal resolution provided by the paradigm that we used. Althougha longer cue-target delay might have provided greater temporalsensitivity, TID increases with faster stimulus presentation rate(48), and, therefore, we believed that a short cue-target delay would
maximize TID. A variable cue-target delay would have allowed us
to model the cue and target separately, but this temporal jitter
would not have been possible in the context of a finite impulseresponse design while maintaining a short cue-target delay. Thus,
the fixed timing and short duration (2 s) of the delay prevented us
from unequivocally distinguishing cue from response-related hemodynamic activity. Therefore, given event-related potential studies showing that the ERN occurs almost immediately after posterror (13), peak hemodynamic activity at the 4-s time period,
instead of reflecting performance optimization activity, may reflect
response-related activity. If the hemodynamic activity at 4 s wererelated to the response, it would indicate that TID was occurring
during or after response execution, rather than before. However,
the regions that show a peak response at 6 s have been consistently
implicated in performance evaluation (1), whereas the regions thatpeak at 4 s are more consistently implicated in performance
optimization (28, 47). Thus, the hypothesis that peak TID at 4 s
reflects activity related to the response would suggest that there
were two distinct phases of evaluative activity. The hypothesis thatpeak TID at 4 s is related to performance optimization is moreconsistent with previous work and provides a more parsimonious
explanation of our findings. Nonetheless, although this study has
established differential TID during error vs. correct responding andsuggested timing differences between TID and evaluation activity,
future studies are needed to more precisely delineate the timing of
the two processes.
The finding of increased dACC and rACC activity later in error
vs. correct trials is consistent with previous error studies (1) andsupports the hypothesis that these regions are involved in theevaluation of the error response. Examination of the HDRs demonstrates differential timing of the dACC and rACC responses toerrors that are consistent with their proposed cognitive and affective specializations. It is possible that the fast rise and sharp fall ofactivity in dACC reflect a role in updating of stimulus-response
mappings immediately after the error response (49), whereas themore gradual rise, later peak, and slower fall of rACC activity could
be consistent with a role in the affective appraisal of the error (20).
The reward for correct responses represents a potential confoundin the interpretation of increased error-related activity in thedACC, given the demonstrated sensitivity of this region to reward
loss (50). Reward loss has not been associated with changes in TID,
however, and is, therefore, unlikely to account for the finding of
TID failure with errors.
The current findings also enhance our understanding of ACC
function by showing that rACC and dACC have reciprocal activation patterns during correct performance yet similar activation
patterns during erroneous performance. Interestingly, different
regions of the rACC and dACC, both of which are comprised ofseveral Brodmann areas, appeared to be maximally involved inperformance optimization vs. evaluation. Consistent with otherstudies, performance optimization activity appeared maximal in thesulcus of the rACC (24–26) and in posterior dACC bordering onpresupplementary motor area (27), whereas later performance
evaluation activity was maximal on the gyrus of rACC (2, 3, 11) andPolli et al.

We thank Dr. George Bush for his thoughtful comments. This work was
supported by National Institute of Mental Health Grants F31 MH72120(to F.E.P.), R01 MH67720 (to D.S.M.), and K08 NS01920 (to J.J.S.B.).

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Polli et al.

PNAS 兩 October 25, 2005 兩 vol. 102 兩 no. 43 兩 15705

PSYCHOLOGY

oxygen extraction fraction in rACC and other default-mode regions
did not differ significantly from its mean throughout the brain
during fixation (24). This finding suggests that differences of themagnitude observed in rACC between correct ASs vs. fixation areunlikely to be accounted for by increased rACC activity during
fixation.
The finding of TID failure during errors provides a possible
mechanism for emotional interference of cognition by emotion.
Negative emotional states are known to increase rACC activity (21)and impair performance accuracy (51) in healthy controls. TID
failure also may contribute to cognitive dysfunction in depression
and obsessive compulsive disorder, both of which are associatedwith increased rACC metabolism (52, 53) and impaired cognitive
performance (54). A better delineation of the systems responsible
for the dynamic optimization and evaluation of cognitive performance may elucidate the basis of performance variation in both
health and disease.

in anterior dACC (1). However, these finer anatomical distinctions
may strain the limits of spatial resolution.
Finally, it is possible that deactivation in the default-mode
network during AS performance resulted from increased activationof these regions during fixation (31). To address this issue, we
contrasted correct ASs with the nonfixation baseline of correct PSs
and found significant TID differences only in the left angular gyrus.
These results differ from those of a previous block-design study thatreported increased TID in ventromedial PFC with ASs vs. PSs (30).
These differences may arise from the current paradigm presenting
trials in a pseudorandom order rather than in single-trial blocks.
This design gives rise to increased working memory requirements
and task-switching costs (29). In this context, PSs may have been
more cognitively demanding than the block PSs of previous studies.
Because TID increases with task difficulty (48), more difficult PSs
would lead to less differential TID between ASs and PSs. The useof PSs as a nonfixation baseline also does not address the central
question of whether TID during correct ASs vs. fixation represents
deactivation during AS trials or activation during fixation. A
positron-emission tomography study assessing an absolute measureof brain activity, namely oxygen extraction fraction, reported that