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Multiple component networks support working memory in prefrontal cortex.

David A Markowitz1, Clayton E Curtis2, Bijan Pesaran3

  • 1Center for Neural Science, New York University, New York, NY 10003;

Proceedings of the National Academy of Sciences of the United States of America
|August 19, 2015
PubMed
Summary
This summary is machine-generated.

The lateral prefrontal cortex (PFC) uses distinct neural networks for working memory (WM). Different neuronal activity modes support information storage and response preparation, suggesting specialized WM components within the PFC.

Keywords:
coherencemacaqueprefrontal cortexworking memory

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Area of Science:

  • Neuroscience
  • Cognitive Neuroscience

Background:

  • The lateral prefrontal cortex (PFC) is considered central to working memory (WM).
  • It is debated whether WM relies on a single distributed network or multiple specialized components within the PFC.

Purpose of the Study:

  • To investigate the network organization of working memory (WM) within the lateral prefrontal cortex (PFC).
  • To determine if WM is supported by a single distributed network or multiple specialized components.

Main Methods:

  • Neuronal activity was recorded from the PFC in monkeys performing delayed eye movement tasks.
  • Tasks involved memory-guided or vision-guided movements to differentiate WM-related activity.

Main Results:

  • Neuronal responses aligned with three distinct modes of persistent activity.
  • These modes corresponded to early information storage, late information storage, and response preparation.
  • Neurons associated with these modes were anatomically segregated and showed distinct firing patterns, indicating specialized networks.

Conclusions:

  • Findings support multiple component models of working memory (WM).
  • WM in the PFC is likely supported by distinct, anatomically specialized neural networks.
  • This specialization predicts specific patterns of dysfunction in neurological disorders affecting the PFC.