Neurally Constrained Cognitive Modeling Clarifies How Action Plans Are Changed

Abstract

Review of Ramakrishnan et al.Cognitive neuroscience aims to explain how cognitive functions arise from brain processes using computational models to describe the mapping between behavioral and neural data. This approach has previously been used to understand the neural mechanisms of stopping an action. A paper recently published in The Journal of Neuroscience applies this method to explain how actions are changed.Stopping has typically been investigated with a task in which subjects are asked to respond to go-signals, but to stop their response when a stop-signal follows the go-signal. Stopping is easy when the stop-signal is presented early during action preparation (Ͻ100 ms after the gosignal), but becomes increasingly difficult when preparation gets closer to completion (Ͼ200 -300 ms after the go-signal), a relationship referred to as the inhibition function. The precise time of the inhibition function varies with natural response times and task demands. Furthermore, responses that escape inhibition are faster than the average response. These behavioral characteristics can be explained by a model that describes performance as the outcome of a race between a GO process and a STOP process that have independent random finish times (Logan and Cowan, 1984). However, accounting for both behavioral and neural data requires an interactive race model, in which STOP interrupts GO (Boucher et al., 2007).Changing actions closely resembles stopping (Logan and Burkell, 1986;Camalier et al., 2007). In the double-step eye-movement change task, subjects are asked to make a saccade to peripheral targets, but to redirect gaze when the target changes position. Change performance has the characteristics of a race: the probability of compensating for the change in position decreases with the delay between the initial onset of the target and when it moves, as described by the compensation function. Moreover, saccades that could not be redirected are faster than average; however, it is unclear which processes compete and how they interact. Is the race a direct competition between the processes producing the responses to the initial target (GO1) and final target (GO2) or is an additional STOP process involved? Additionally, when and how do these processes interact?These questions were recently addressed in a study by Ramakrishnan et al. (2012). Monkeys were trained to perform a modified double-step task. To measure the time course of the changing saccade plan, the authors used microstimulation of the frontal eye fields to evoke saccades at various times after the change-signal.This resulted in a profile of saccade deviation showing that saccades evoked earlier deviated toward the initial target, whereas saccades evoked later deviated toward the final target. The time at which the deviation crossed over from the initial to the final target (crossover time) was taken as an estimate of the time when the response changed.To identify the mechanism underlying change performance, Ramakrishnan et al. (2012) compared race models that differed...