Anterior Cingulate Conflict Monitoring and Adjustments in Control

Transcription

1 Kerns, p. 1 Science Supporting Online Material Anterior Cingulate Conflict Monitoring and Adjustments in Control John G. Kerns, Jonathan D. Cohen, Angus W. MacDonald III, Raymond Y. Cho, V. Andrew Stenger, Cameron S. Carter doi: /science Materials and Methods Participants and Task Twenty-three participants (35% female; mean age = 28) after providing informed consent underwent fmri scanning while performing a version of the Stroop color naming task. Stimuli consisted of one of three words (RED, GREEN, BLUE) printed in one of three colors. Trials were either congruent (e.g., the word "RED" in red ink) or incongruent (e.g., the word "RED" in green ink). For all trials, participants were instructed to name the color of the stimulus and to ignore the word. They were told to be accurate with speed also being strongly emphasized. Participants responded with a button press using their right hand. Trials were 3 s long and consisted of a color word for 1.5 s followed by 1.5 s of a fixation cross (+). There were 3 blocks of 88 trials each. To increase conflict effects, based on previous research, the first and last 4 trials of every block were congruent. The other 80 trials within each block had 70% congruent trials. In this study, as expected, there was a large Stroop effect, t(22) = 6.49, P < 0.001, with longer reaction times for incongruent trials (mean reaction time = 716.3, SD = 197.9) than for congruent trials (mean RT = 596.7, SD = 129.8). As expected, there were enough errors in the imaging study to analyze error-related activity (mean number of errors = 15.4, SD = 7.5, range: 5 to 31). Moreover, there was also a significant posterror adjustment effect, as congruent trials after errors (mean RT = 619.5, SD = 135.8) were slower than congruent trials that followed correct trials [mean RT = 593.7, SD = 116.3, t(22) = 2.02, P < 0.05]. [We restricted the post-error analysis to congruent posterror trials since there were too few post-error incongruent errors per subject (median = 2) to analyze reliably; in addition, there was significant post-error slowing for both posterror congruent trials ( P < 0.01) and for post-error incongruent trials(p < 0.05), without a significant difference between post-error congruent and post-error incongruent trials, P = 0.59.] Overall, the error rates did not suggest a speed-accuracy tradeoff could account for post-conflict adjustment effects. The mean error rates for cc trials (0.0367, SD = 0.026) and ic trials (0.0352, SD = 0.022) were very similar (P > 0.80). The mean error rate for ii trials (0.123, SD = 0.133) was nonsignificantly (P > 0.25) but arithmetically larger than for ci trials (0.097, SD = 0.075). However, this difference seemed to be entirely due to 2 outliers with large ii error rates (> 30%). After removing these outliers, the mean error rate for ii trials was lower than for ci trials yet the postconflict behavioral RT adjustment effect was still significant. Image Acquisition and Analysis A 3.0 T scanner with a standard head coil acquired all images. Three gradient echo functional scouts were used to localize the anterior commissure and the posterior commissure. T2* spiral scans (3.2 mm 3 voxels, repetition time = 1.5 s, echo time = 18 ms, flip angle = 70 o ) acquired 28 axial slices. Incremental (scan to scan) and total movement were corrected using AIR (S1). Structural images were cross-registered to a

2 Kerns, p. 2 reference brain by minimizing signal intensity differences with 12-parameter AIR, after which images were set to a standard mean intensity and smoothed (8-mm FWHM). Imaging data were analyzed with a random effects single-subjects general linear model using AFNI (S2) and NIS software (S3). For all analyses, we ran individual participant GLMs using a canonical, double gamma hemodynamic response function to obtain a parameter estimate (r value) for each covariate for each subject. Then we performed t tests to examine significant activity across the entire group of participants. Statistical significance threshold was P < and 8 contiguous voxels (S4), except for ROI-based analyses for which the threshold was P < This study involved a constant intertrial interval (ITI). It is important to note that a jittered ITI is likely to interact with cognitive control processes in meaningful and as yet still unexplored ways. At the same time, valid between-condition contrast results (e.g., incongruent vs. congruent trials) can be obtained in fast-event related designs with a constant ITI (S5). With a constant ITI, this should produce a relatively constant baseline level of activity (S6, S7). Between-conditions differences (e.g., increased activity for incongruent trials relative to congruent trials) should then be manifest as departures from the baseline level of activity, which previous research has consistently found can be robustly measured (S8 S10) (see fig. S1 for expected hemodynamic response for either equal or different activity for two conditions). Indeed, a priori calculations of efficiency (S11) showed that our current design has essentially the equivalent efficiency for detecting between-condition differences as either a comparable slow-event related design or a fast-event related design with a variable ITI. By way of illustration, as can be seen in fig. S2, there was a close similarity between the estimated hemodynamic response to ci trials in the current study compared to a canonical double gamma hemodynamic response function. An initial analysis was performed that included three mutually exclusive covariates (congruent, incongruent, and error trials). This basic analysis produced ROI s of ACC conflict and error activity that were used in subsequent ROI-based analyses to test specific hypotheses. One additional analysis examined whether ACC activity predicted trial-to-trial adjustments. This analysis included 3 pairs of covariates. One pair was for incongruent trials, segregated by whether they were followed by either slow or fast congruent (ic) trials (using the third slowest or third fastest trials). A second pair was for incongruent trials, segregated by whether they were followed by either slow or fast incongruent (ii) trials (using a median split because of the smaller number of this trial type). A third pair was for error trials, segregated by whether they were followed by either slow or fast correct congruent trials. [We only report results for individuals with at least 10 error trials, n = 18; note that, in contrast to post-error trials, the number of congruent and incongruent error trials was roughly the same (mean difference = 1.0, P for difference > 0.25) because of the greater proportion of congruent trials overall.] A second additional analysis examined whether PFC or other brain regions were associated with behavioral adjustments. This analysis included two pairs of covariates. One pair was for post-incongruent (ii and ic) trials, with covariates for greater (i.e., the fastest ii and the slowest ic trials) and for less (i.e., the slowest ii and the fastest ic trials) adjustment. A second pair was for post-error trials, with covariates for greater (i.e., the slowest post-error trials) and for less (i.e., the fastest post-error trials)

3 Kerns, p. 3 adjustment. To directly examine the association between the ACC and the PFC, using regions we identified in the above analyses, we computed the amount of brain activity in the ACC region for incongruent and error trials by summing the 3rd, 4th, and 5th scans (corresponding to between 3.0 and 7.5 s of that trial). Similarly, we computed the amount of brain activity in a PFC region for post-conflict and post-error trials. To control for effects of general brain activity, we also examined associations with a control region, in the left temporal lobe, which was also significantly activated by the Stroop task. Analogous to a GLM analysis, for each participant, we calculated the partial correlation between ACC activity on conflict and error trials and PFC activity on post-conflict and post-error trials after having removed shared variance with the temporal region (either for conflict and error trials or for post-conflict and post-error trials). Then we performed a t test to examine whether the ACC and PFC activity were significantly associated across the entire group of participants.

4 Kerns, p. 4 Fig. S1. Expected hemodynamic response for equal activity between two conditions (with both conditions activity = the blue line) vs. different levels of activity between two conditions (with one condition s activity = the red line and the other condition s activity = the blue line).

5 Kerns, p. 5 Fig. S2. Close correspondence between observed hemodynamic response for ci trials (i.e., the highest conflict trials in the current study) versus an idealized double gamma hemodynamic response function. s = scan number.

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