Proceedings of the Annual Meeting of the Cognitive Science Society

Constrained by results from classic behavioral experiments weprovide a neural-level cognitive architecture for modeling be-havior in working memory tasks. We propose a canonicalmicrocircuit that can be used as a building block for work-ing memory, decision making and cognitive control. The con-troller controls gates to route the flow of information betweenthe working memory and the evidence accumulator and setsparameters of the circuits. We show that this type of cognitivearchitecture can account for results in behavioral experimentssuch as judgment of recency, probe recognition and delayed-match-to-sample. In addition, the neural dynamics generatedby the cognitive architecture provides a good match with neu-rophysiological data from rodents and monkeys. For instance,it generates cells tuned to a particular amount of elapsed time(time cells), to a particular position in space (place cells) andto a particular amount of accumulated evidence.