Towards a neural-level cognitive architecture: modeling behavior in working memory tasks with neurons
Files
Published version
Date
2019
DOI
Authors
Tiganj, Zoran
Howard, Marc W.
Cruzado, Nathanael
Version
OA Version
Accepted manuscript
Citation
Zoran Tiganj, Marc Howard, Nathaniel Cruzado. 2019. "Towards a neural-level cognitive architecture: modeling behavior in working memory tasks with neurons." Proceedings of the 41st Annual Meeting of the Cognitive Science Society. Montreal,
Abstract
Constrained by results from classic behavioral experiments we
provide a neural-level cognitive architecture for modeling behavior
in working memory tasks. We propose a canonical
microcircuit that can be used as a building block for working
memory, decision making and cognitive control. The controller
controls gates to route the flow of information between
the working memory and the evidence accumulator and sets
parameters of the circuits. We show that this type of cognitive
architecture can account for results in behavioral experiments
such as judgment of recency, probe recognition and delayedmatch-
to-sample. In addition, the neural dynamics generated
by the cognitive architecture provides a good match with neurophysiological
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) and
to a particular amount of accumulated evidence.