title: A computational model of anterior cingulate function in speeded response tasks: effects of frequency, sequence, and conflict.
abstract: A growing body of evidence from functional neuroimaging and computational modeling studies indicates that the anterior cingulate cortex (ACC) detects the presence of response conflict and conveys this information to other brain regions, enabling subsequent adjustments in cognitive control. The present study examined previous empirical findings of increased ACC for low-frequency stimuli across three distinct speeded response tasks (two-alternative forced choice, go/no-go, and oddball). Simulations conducted in a neural network model incorporating sequential priming mechanisms (developed in Cho et al., 2002) confirmed that a computational measure of response conflict was higher on low-frequency trials across all three tasks. In addition, the model captured detailed aspects of behavioral reaction time and accuracy data, predicted the dynamics of ACC activity related to trial sequence effects, and provided evidence for the functional role of conflict information in performance monitoring and optimization. The results indicate that the conflict-monitoring hypothesis, augmented by mechanisms for encoding stimulus history, can explain key phenomena associated with performance in sequential speeded response tasks.
authors.affiliation: Washington University, St. Louis, Missouri 63130, USA.
authors.forename: Andrew D
authors.initials: AD
authors.lastname: Jones
authors.forename: Raymond Y
authors.initials: RY
authors.lastname: Cho
authors.forename: Leigh E
authors.initials: LE
authors.lastname: Nystrom
authors.forename: Jonathan D
authors.initials: JD
authors.lastname: Cohen
authors.forename: Todd S
authors.initials: TS
authors.lastname: Braver
mesh_terms: D000293:Adolescent; D000328:Adult; D001931:Brain Mapping; D003220:Conflict, Psychological; D005071:Evoked Potentials; D005260:Female; D006179:Gyrus Cinguli / Q000502:physiology*; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D016571:Neural Networks, Computer; D011597:Psychomotor Performance / Q000502:physiology*; D011930:Reaction Time / Q000502:physiology*; D013647:Task Performance and Analysis