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Steady State Behavior of the Free Recall Dynamics of Working Memory.

Authors :
Li, Tianhao
Liu, Zhixin
Liu, Lizheng
Hu, Xiaoming
Source :
Journal of Systems Science & Complexity; Dec2024, Vol. 37 Issue 6, p2424-2450, 27p
Publication Year :
2024

Abstract

This paper studies a dynamical system that models the free recall dynamics of working memory. This model is an attractor neural network with n modules, named hypercolumns, and each module consists of m minicolumns. Under mild conditions on the connection weights between minicolumns, the authors investigate the long-term evolution behavior of the model, namely the existence and stability of equilibria and limit cycles. The authors also give a critical value in which Hopf bifurcation happens. Finally, the authors give a sufficient condition under which this model has a globally asymptotically stable equilibrium consisting of synchronized minicolumn states in each hypercolumn, which implies that in this case recalling is impossible. Numerical simulations are provided to illustrate the proposed theoretical results. Furthermore, a numerical example the authors give suggests that patterns can be stored in not only equilibria and limit cycles, but also strange attractors (or chaos). [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10096124
Volume :
37
Issue :
6
Database :
Complementary Index
Journal :
Journal of Systems Science & Complexity
Publication Type :
Academic Journal
Accession number :
180988751
Full Text :
https://doi.org/10.1007/s11424-024-3154-8