Reactivation in Working Memory: an Attractor Network Model of Free Recall

Overview

Journal PLoS One

Specialties General Medicine
Science

Date 2013 Sep 12

PMID 24023690

Citations 15

Authors

Anders Lansner

Petter Marklund

Sverker Sikstrom

Lars-Goran Nilsson

Affiliations

Soon will be listed here.

Abstract

The dynamic nature of human working memory, the general-purpose system for processing continuous input, while keeping no longer externally available information active in the background, is well captured in immediate free recall of supraspan word-lists. Free recall tasks produce several benchmark memory phenomena, like the U-shaped serial position curve, reflecting enhanced memory for early and late list items. To account for empirical data, including primacy and recency as well as contiguity effects, we propose here a neurobiologically based neural network model that unifies short- and long-term forms of memory and challenges both the standard view of working memory as persistent activity and dual-store accounts of free recall. Rapidly expressed and volatile synaptic plasticity, modulated intrinsic excitability, and spike-frequency adaptation are suggested as key cellular mechanisms underlying working memory encoding, reactivation and recall. Recent findings on the synaptic and molecular mechanisms behind early LTP and on spiking activity during delayed-match-to-sample tasks support this view.

Citing Articles

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Hribkova H, Svoboda O, Bartecku E, Zelinkova J, Horinkova J, Lacinova L Front Cell Neurosci. 2022; 16:830757.

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Free recall scaling laws and short-term memory effects in a latching attractor network.

Boboeva V, Pezzotta A, Clopath C Proc Natl Acad Sci U S A. 2021; 118(49).

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An Indexing Theory for Working Memory Based on Fast Hebbian Plasticity.

Fiebig F, Herman P, Lansner A eNeuro. 2020; 7(2).

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Probabilistic associative learning suffices for learning the temporal structure of multiple sequences.

Martinez R, Lansner A, Herman P PLoS One. 2019; 14(8):e0220161.

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