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Principles for coding associative memories in a compact neural network

Authors :
Christian Pritz
Eyal Itskovits
Eduard Bokman
Rotem Ruach
Vladimir Gritsenko
Tal Nelken
Mai Menasherof
Aharon Azulay
Alon Zaslaver
Source :
eLife, Vol 12 (2023)
Publication Year :
2023
Publisher :
eLife Sciences Publications Ltd, 2023.

Abstract

A major goal in neuroscience is to elucidate the principles by which memories are stored in a neural network. Here, we have systematically studied how four types of associative memories (short- and long-term memories, each as positive and negative associations) are encoded within the compact neural network of Caenorhabditis elegans worms. Interestingly, sensory neurons were primarily involved in coding short-term, but not long-term, memories, and individual sensory neurons could be assigned to coding either the conditioned stimulus or the experience valence (or both). Moreover, when considering the collective activity of the sensory neurons, the specific training experiences could be decoded. Interneurons integrated the modulated sensory inputs and a simple linear combination model identified the experience-specific modulated communication routes. The widely distributed memory suggests that integrated network plasticity, rather than changes to individual neurons, underlies the fine behavioral plasticity. This comprehensive study reveals basic memory-coding principles and highlights the central roles of sensory neurons in memory formation.

Details

Language :
English
ISSN :
2050084X
Volume :
12
Database :
Directory of Open Access Journals
Journal :
eLife
Publication Type :
Academic Journal
Accession number :
edsdoj.4fe896c8942c4a4cb471e00cb5117bd6
Document Type :
article
Full Text :
https://doi.org/10.7554/eLife.74434