Proceedings of the Annual Meeting of the Cognitive Science Society

Decision making (DM) requires the coordination of anatom-ically and functionally distinct cortical and subcortical areas.While previous computational models have studied these sub-systems in isolation, few models explore how DM holisticallyarises from their interaction. We propose a spiking neuronmodel that unifies various components of DM, then show thatthe model performs an inferential decision task in a human-likemanner. The model (a) includes populations corresponding todorsolateral prefrontal cortex, orbitofrontal cortex, right inferiorfrontal cortex, pre-supplementary motor area, and basal ganglia;(b) is constructed using 8000 leaky-integrate-and-fire neuronswith 7 million connections; and (c) realizes dedicated cognitiveoperations such as weighted valuation of inputs, accumulationof evidence for multiple choice alternatives, competition be-tween potential actions, dynamic thresholding of behavior, andurgency-mediated modulation. We show that the model repro-duces reaction time distributions and speed-accuracy tradeoffsfrom humans performing the task. These results provide be-havioral validation for tasks that involve slow dynamics andperceptual uncertainty; we conclude by discussing how addi-tional tasks, constraints, and metrics may be incorporated intothis initial framework.