TY - JOUR T1 - A Spiking Neural Integrator Model of the Adaptive Control of Action by the Medial Prefrontal Cortex JF - The Journal of Neuroscience JO - J. Neurosci. SP - 1892 LP - 1902 DO - 10.1523/JNEUROSCI.2421-13.2014 VL - 34 IS - 5 AU - Trevor Bekolay AU - Mark Laubach AU - Chris Eliasmith Y1 - 2014/01/29 UR - http://www.jneurosci.org/content/34/5/1892.abstract N2 - Subjects performing simple reaction-time tasks can improve reaction times by learning the expected timing of action-imperative stimuli and preparing movements in advance. Success or failure on the previous trial is often an important factor for determining whether a subject will attempt to time the stimulus or wait for it to occur before initiating action. The medial prefrontal cortex (mPFC) has been implicated in enabling the top-down control of action depending on the outcome of the previous trial. Analysis of spike activity from the rat mPFC suggests that neural integration is a key mechanism for adaptive control in precisely timed tasks. We show through simulation that a spiking neural network consisting of coupled neural integrators captures the neural dynamics of the experimentally recorded mPFC. Errors lead to deviations in the normal dynamics of the system, a process that could enable learning from past mistakes. We expand on this coupled integrator network to construct a spiking neural network that performs a reaction-time task by following either a cue-response or timing strategy, and show that it performs the task with similar reaction times as experimental subjects while maintaining the same spiking dynamics as the experimentally recorded mPFC. ER -