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Latching dynamics as a basis for short-term recall
Author(s) -
Kwang Il Ryom,
Vezha Boboeva,
Oleksandra Soldatkina,
Alessandro Treves
Publication year - 2021
Publication title -
plos computational biology/plos computational biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.628
H-Index - 182
eISSN - 1553-7358
pISSN - 1553-734X
DOI - 10.1371/journal.pcbi.1008809
Subject(s) - recall , computer science , term (time) , short term memory , network dynamics , basis (linear algebra) , neuroscience , cognition , working memory , cognitive psychology , mathematics , biology , psychology , physics , discrete mathematics , quantum mechanics , geometry
We discuss simple models for the transient storage in short-term memory of cortical patterns of activity, all based on the notion that their recall exploits the natural tendency of the cortex to hop from state to state—latching dynamics. We show that in one such model, and in simple spatial memory tasks we have given to human subjects, short-term memory can be limited to similar low capacity by interference effects, in tasks terminated by errors, and can exhibit similar sublinear scaling, when errors are overlooked. The same mechanism can drive serial recall if combined with weak order-encoding plasticity. Finally, even when storing randomly correlated patterns of activity the network demonstrates correlation-driven latching waves, which are reflected at the outer extremes of pattern space.

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