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A neural circuit model for a contextual association task inspired by recommender systems
Author(s) -
Zhu Henghui,
Paschalidis Ioannis Ch.,
Chang Allen,
Stern Chantal E.,
Hasselmo Michael E.
Publication year - 2020
Publication title -
hippocampus
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.767
H-Index - 155
eISSN - 1098-1063
pISSN - 1050-9631
DOI - 10.1002/hipo.23194
Subject(s) - hebbian theory , computer science , gating , context (archaeology) , artificial intelligence , generalization , neurophysiology , association (psychology) , machine learning , artificial neural network , task (project management) , neuroscience , psychology , management , economics , psychotherapist , paleontology , mathematical analysis , mathematics , biology
Abstract Behavioral data shows that humans and animals have the capacity to learn rules of associations applied to specific examples, and generalize these rules to a broad variety of contexts. This article focuses on neural circuit mechanisms to perform a context‐dependent association task that requires linking sensory stimuli to behavioral responses and generalizing to multiple other symmetrical contexts. The model uses neural gating units that regulate the pattern of physiological connectivity within the circuit. These neural gating units can be used in a learning framework that performs low‐rank matrix factorization analogous to recommender systems, allowing generalization with high accuracy to a wide range of additional symmetrical contexts. The neural gating units are trained with a biologically inspired framework involving traces of Hebbian modification that are updated based on the correct behavioral output of the network. This modeling demonstrates potential neural mechanisms for learning context‐dependent association rules and for the change in selectivity of neurophysiological responses in the hippocampus. The proposed computational model is evaluated using simulations of the learning process and the application of the model to new stimuli. Further, human subject behavioral experiments were performed and the results validate the key observation of a low‐rank synaptic matrix structure linking stimuli to responses.