title: Neural bases of individual variation in decision time.
abstract: People make decisions by evaluating existing evidence against a threshold or level of confidence. Individuals vary widely in response times even when they perform a simple task in the laboratory. We examine the neural bases of this individual variation by combining computational modeling and brain imaging of 64 healthy adults performing a stop signal task. Behavioral performance was modeled by an accumulator model that describes the process of information growth to reach a threshold to respond. In this model, go trial reaction time (goRT) is jointly determined by the information growth rate, threshold, and movement time (MT). In a linear regression of activations in successful go and all stop (Go+Stop) trials against goRT across participants, the insula, supplementary motor area (SMA), pre-SMA, thalamus including the subthalamic nucleus (STN), and caudate head respond to increasing goRT. Among these areas, the insula, SMA, and thalamus including the STN respond to a slower growth rate, the caudate head responds to an elevated threshold, and the pre-SMA responds to a longer MT. In the regression of Go+Stop trials against the stop signal reaction time (SSRT), the pre-SMA shows a negative correlation with SSRT. These results characterize the component processes of decision making and elucidate the neural bases of a critical aspect of inter-subject variation in human behavior. These findings also suggest that the pre-SMA may play a broader role in response selection and cognitive control rather than simply response inhibition in the stop signal task.
authors.affiliation: Department of Psychiatry, Yale University, New Haven, Connecticut.
authors.forename: Sien
authors.initials: S
authors.lastname: Hu
authors.forename: Yuan-Chi
authors.initials: YC
authors.lastname: Tseng
authors.forename: Alissa D
authors.initials: AD
authors.lastname: Winkler
authors.forename: Chiang-Shan R
authors.initials: CS
authors.lastname: Li
mesh_terms: D000328:Adult; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping; D003198:Computer Simulation; D003657:Decision Making / Q000502:physiology*; D005260:Female; D006801:Humans; D007206:Individuality; D007257:Information Theory; D016014:Linear Models; D008279:Magnetic Resonance Imaging; D008297:Male; D008959:Models, Neurological; D009483:Neuropsychological Tests; D011930:Reaction Time / Q000502:physiology*; D012044:Regression Analysis; D013647:Task Performance and Analysis
keywords: accumulator model; caudate; growth rate; pre-SMA; subthalamic nucleus; threshold
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