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.
Keywords: accumulator model; caudate; growth rate; pre-SMA; subthalamic nucleus; threshold.
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