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Kristen A. Ford, Goltz C. Goltz, Stefan Everling; Anti-saccade performance predicted by event-related fMRI. Journal of Vision 2004;4(8):100. doi: 10.1167/4.8.100.
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One of the hallmarks of executive control is the suppression of prepotent but inappropriate responses in favour of voluntary motor acts. A stimulus-response incompatibility paradigm that is frequently used to test both of these abilities is the anti-saccade task, because it requires subjects not to look to a flashed stimulus (pro-saccade) but instead to look away from it (anti-saccade). Here we used event-related functional magnetic resonance imaging to measure neural activity in humans during a task in which they were instructed before a stimulus appeared either to make a pro- or anti-saccade. Eye movements were recorded so that neural activity could be grouped into pro-saccades, correct anti-saccades and errors (saccades towards the stimulus on anti-saccade trials). A general linear model was used with one predictor for the 10s instruction period and another predictor for the stimulus/saccade period. The analysis of the instruction period predictor revealed that correct anti-saccade trials were associated with significantly more activity bilateral in the frontal eye field (FEF), supplementary eye field (SEF), anterior cingulate, anterior medial frontal gyrus, and caudate than pro-saccade trials. Correct anti-saccades evoked more activity than errors in the right anterior medial frontal gyrus, SEF, and right FEF during the instruction period. When we analyzed the saccade predictor, we found no differences between correct anti-saccades and pro-saccades. Error trials, however, showed a greater activation than correct anti-saccade trials in the SEF. Our findings demonstrate that 1) pro-saccade and anti-saccade trials differ in their activation before stimulus onset, 2) the activity before stimulus presentation predicts task performance, 3) activation of the supplementary eye field for erroneous saccades is consistent with an involvement of this area in performance monitoring.
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