Open AccessWhen shared concept cells support associations: Theory of overlapping memory engrams
Author(s) -
Chiara Gastaldi,
Tilo Schwalger,
Emanuela De Falco,
Rodrigo Quian Quiroga,
Wulfram Gerstner
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.1009691
Subject(s) - encode , recall , computer science , neuroscience , association (psychology) , fraction (chemistry) , forgetting , hippocampal formation , artificial neural network , artificial intelligence , biology , theoretical computer science , psychology , cognitive psychology , gene , genetics , chemistry , organic chemistry , psychotherapist
Assemblies of neurons, called concepts cells, encode acquired concepts in human Medial Temporal Lobe. Those concept cells that are shared between two assemblies have been hypothesized to encode associations between concepts. Here we test this hypothesis in a computational model of attractor neural networks. We find that for concepts encoded in sparse neural assemblies there is a minimal fraction c min of neurons shared between assemblies below which associations cannot be reliably implemented; and a maximal fraction c max of shared neurons above which single concepts can no longer be retrieved. In the presence of a periodically modulated background signal, such as hippocampal oscillations, recall takes the form of association chains reminiscent of those postulated by theories of free recall of words. Predictions of an iterative overlap-generating model match experimental data on the number of concepts to which a neuron responds.