The role of dopamine in the maintenance of working memory in prefrontal cortex neurons: Input-driven versus internally-driven networks

Massimiliano Versace, Marco Zorzi

Research output: Contribution to journalArticle

Abstract

How do organisms select and organize relevant sensory input in working memory (WM) in order to deal with constantly changing environmental cues? Once information has been stored in WM, how is it protected from and altered by the continuous stream of sensory input and internally generated planning? The present study proposes a novel role for dopamine (DA) in the maintenance of WM in the prefrontal cortex (Pfc) neurons that begins to address these issues. In particular, DA mediates the alternation of the Pfc network between input-driven and internally-driven states, which in turn drives WM updates and storage. A biologically inspired neural network model of Pfc is formulated to provide a link between the mechanisms of state switching and the biophysical properties of Pfc neurons. This model belongs to the recurrent competitive fields 33 class of dynamical systems which have been extensively mathematically characterized and exhibit the two functional states of interest: input-driven and internally-driven. This hypothesis was tested with two working memory tasks of increasing difficulty: a simple working memory task and a delayed alternation task. The results suggest that optimal WM storage in spite of noise is achieved with a phasic DA input followed by a lower DA sustained activity. Hypo and hyper-dopaminergic activity that alter this ideal pattern lead to increased distractibility from non-relevant pattern and prolonged perseverations on presented patterns, respectively.

Original languageEnglish
Pages (from-to)249-265
Number of pages17
JournalInternational Journal of Neural Systems
Volume20
Issue number4
DOIs
Publication statusPublished - Aug 2010

Keywords

  • cognitive control
  • dopamine
  • prefrontal cortex
  • Recurrent networks
  • working memory

ASJC Scopus subject areas

  • Computer Networks and Communications

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