Dynamic effective connectivity in cortically embedded systems of recurrently coupled synfire chains.

ABSTRACT: As a candidate mechanism of neural representation, large numbers of synfire chains can efficiently be embedded in a balanced recurrent cortical network model. Here we study a model in which multiple synfire chains of variable strength are randomly coupled together to form a recurrent system. The system can be implemented both as a large-scale network of integrate-and-fire neurons and as a reduced model. The latter has binary-state pools as basic units but is otherwise isomorphic to the large-scale model, and provides an efficient tool for studying its behavior. Both the large-scale system and its reduced counterpart are able to sustain ongoing endogenous activity in the form of synfire waves, the proliferation of which is regulated by negative feedback caused by collateral noise. Within th

SUBMITTER: Trengove C 

PROVIDER: S-EPMC4762935 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature