Reservoir Computing Properties of Neural Dynamics in Prefrontal Cortex
Fig 2
Model architecture, modeled task and test-activity example.
A. Model architecture. A recurrent network of 1000 randomly connected neurons (the reservoir) received input from 5 units representing the presence of the fixation point, the lever, the targets, the reward and the signal to change. Output choice of the network was represented in two sets of 4 readout neurons corresponding to target fixation and arm touch respectively. Connections between the reservoir and readout (dashed arrows) were modified, through learning, to reproduce the behavior given by sequence of correct input/output examples. A contextual memory version of the model included a trained context neuron (in brown) that represented phase information (search or repeat). B. Time course of a modeled trial. A trial started with the activation of the lever and fixation point. Fixation point neuron deactivated concomitantly with targets appearance which was the GO signal for saccade to a target after a reaction time. Fixation of the target followed and was represented in the activation of one readout neuron among the four dedicated to target fixation. The lever input deactivation was the GO signal for arm touch that was represented in the activation of the readout neuron, after a reaction time, that represented the target chosen with the saccade in the second set of four readout neurons. Touch event occurred at the middle of arm choice and was the start of a 0.6 second delay to feedback. Feedback was simulated as the activation of the reward input for correct trials and the absence of activation in incorrect trials. A 2.15 seconds inter-trial interval started at the onset of feedback and ended at the onset of the next trial except for the last trial of problem (COR4: fourth correct trial) in which the inter-trial interval was extended to 4.25 seconds and the signal to change activated for 1.2 seconds. (Rwd: reward) C. Example of the network performing the task after learning to explore the targets with a circular search. Upper panel: A sequence of stimuli neurons activation. Middle panel: Activity of 4 example reservoir neurons. Lower panel: Readout of the network showing the successive choices of the model. The example shows the end of a repetition period where red target was rewarded. After signal to change input was activated (grey block), a new search for the rewarded target began with the exploration of blue target, then yellow and finally purple which was rewarded and then repeated.