A neural theory for counting memories

Dasgupta, Sanjoy, Hattori, Daisuke, Navlakha, Saket (October 2022) A neural theory for counting memories. Nature Communications, 13 (1). p. 5961. ISSN 2041-1723

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Abstract

Keeping track of the number of times different stimuli have been experienced is a critical computation for behavior. Here, we propose a theoretical two-layer neural circuit that stores counts of stimulus occurrence frequencies. This circuit implements a data structure, called a count sketch, that is commonly used in computer science to maintain item frequencies in streaming data. Our first model implements a count sketch using Hebbian synapses and outputs stimulus-specific frequencies. Our second model uses anti-Hebbian plasticity and only tracks frequencies within four count categories ("1-2-3-many"), which trades-off the number of categories that need to be distinguished with the potential ethological value of those categories. We show how both models can robustly track stimulus occurrence frequencies, thus expanding the traditional novelty-familiarity memory axis from binary to discrete with more than two possible values. Finally, we show that an implementation of the "1-2-3-many" count sketch exists in the insect mushroom body.

Item Type: Paper
Subjects: organs, tissues, organelles, cell types and functions > cell types and functions > cell functions
organs, tissues, organelles, cell types and functions > cell types and functions
organs, tissues, organelles, cell types and functions > tissues types and functions > mushroom body
organs, tissues, organelles, cell types and functions > cell types and functions > cell functions > neural plasticity
organs, tissues, organelles, cell types and functions
organs, tissues, organelles, cell types and functions > sub-cellular tissues: types and functions
organs, tissues, organelles, cell types and functions > sub-cellular tissues: types and functions > synapse
organs, tissues, organelles, cell types and functions > tissues types and functions
CSHL Authors:
Communities: CSHL labs > Navlakha lab
SWORD Depositor: CSHL Elements
Depositing User: CSHL Elements
Date: 10 October 2022
Date Deposited: 20 Oct 2022 02:14
Last Modified: 11 Jan 2024 19:35
PMCID: PMC9551066
URI: https://repository.cshl.edu/id/eprint/40737

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