Major cognitive functions such as language, memory, and decision-making are thought to rely on distributed networks of a large number of basic elements, called canonical microcircuits. In this theoretical study we propose a novel canonical microcircuit model and find that it supports two basic computational operations: a gating mechanism and working memory. By means of bifurcation analysis we systematically investigate the dynamical behavior of the canonical microcircuit with respect to parameters that govern the local network balance, that is, the relationship between excitation and inhibition, and key intrinsic feedback architectures of canonical microcircuits. We relate the local behavior of the canonical microcircuit to cognitive processing and demonstrate how a network of interacting canonical microcircuits enables the establishment of spatiotemporal sequences in the context of syntax parsing during sentence comprehension. This study provides a framework for using individualized canonical microcircuits for the construction of biologically realistic networks supporting cognitive operations.
A model of individualized canonical microcircuits supporting cognitive operations
Tim Kunze,A. Peterson,J. Haueisen,T. Knösche
Published 2017 in PLoS ONE
ABSTRACT
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- Publication year
2017
- Venue
PLoS ONE
- Publication date
2017-12-04
- Fields of study
Medicine, Computer Science
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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