Neuronal competition: microcircuit mechanisms define the sparsity of the engram

Priyanka Rao-Ruiz, Julia Yu, Steven A. Kushner, Sheena A. Josselyn

Research output: Contribution to JournalReview articleAcademicpeer-review

Abstract

Extensive work in computational modeling has highlighted the advantages for employing sparse yet distributed data representation and storage Kanerva (1998), properties that extend to neuronal networks encoding mnemonic information (memory traces or engrams). While neurons that participate in an engram are distributed across multiple brain regions, within each region, the cellular sparsity of the mnemonic representation appears to be quite fixed. Although technological advances have enabled significant progress in identifying and manipulating engrams, relatively little is known about the region-dependent microcircuit rules governing the cellular sparsity of an engram. Here we review recent studies examining the mechanisms that help shape engram architecture and examine how these processes may regulate memory function. We speculate that countervailing forces in local microcircuits contribute to the generation and maintenance of engrams and discuss emerging questions regarding how engrams are formed, stored and used.

Original languageEnglish
Pages (from-to)163-170
Number of pages8
JournalCurrent Opinion in Neurobiology
Volume54
Early online date10 Nov 2018
DOIs
Publication statusPublished - Feb 2019

Fingerprint

Information Storage and Retrieval
Maintenance
Neurons
Brain

Cite this

Rao-Ruiz, Priyanka ; Yu, Julia ; Kushner, Steven A. ; Josselyn, Sheena A. / Neuronal competition : microcircuit mechanisms define the sparsity of the engram. In: Current Opinion in Neurobiology. 2019 ; Vol. 54. pp. 163-170.
@article{26fe415ddf4d48808fa6ba564aaa607e,
title = "Neuronal competition: microcircuit mechanisms define the sparsity of the engram",
abstract = "Extensive work in computational modeling has highlighted the advantages for employing sparse yet distributed data representation and storage Kanerva (1998), properties that extend to neuronal networks encoding mnemonic information (memory traces or engrams). While neurons that participate in an engram are distributed across multiple brain regions, within each region, the cellular sparsity of the mnemonic representation appears to be quite fixed. Although technological advances have enabled significant progress in identifying and manipulating engrams, relatively little is known about the region-dependent microcircuit rules governing the cellular sparsity of an engram. Here we review recent studies examining the mechanisms that help shape engram architecture and examine how these processes may regulate memory function. We speculate that countervailing forces in local microcircuits contribute to the generation and maintenance of engrams and discuss emerging questions regarding how engrams are formed, stored and used.",
author = "Priyanka Rao-Ruiz and Julia Yu and Kushner, {Steven A.} and Josselyn, {Sheena A.}",
year = "2019",
month = "2",
doi = "10.1016/j.conb.2018.10.013",
language = "English",
volume = "54",
pages = "163--170",
journal = "Current Opinion in Neurobiology",
issn = "0959-4388",
publisher = "Elsevier Limited",

}

Neuronal competition : microcircuit mechanisms define the sparsity of the engram. / Rao-Ruiz, Priyanka; Yu, Julia; Kushner, Steven A.; Josselyn, Sheena A.

In: Current Opinion in Neurobiology, Vol. 54, 02.2019, p. 163-170.

Research output: Contribution to JournalReview articleAcademicpeer-review

TY - JOUR

T1 - Neuronal competition

T2 - microcircuit mechanisms define the sparsity of the engram

AU - Rao-Ruiz, Priyanka

AU - Yu, Julia

AU - Kushner, Steven A.

AU - Josselyn, Sheena A.

PY - 2019/2

Y1 - 2019/2

N2 - Extensive work in computational modeling has highlighted the advantages for employing sparse yet distributed data representation and storage Kanerva (1998), properties that extend to neuronal networks encoding mnemonic information (memory traces or engrams). While neurons that participate in an engram are distributed across multiple brain regions, within each region, the cellular sparsity of the mnemonic representation appears to be quite fixed. Although technological advances have enabled significant progress in identifying and manipulating engrams, relatively little is known about the region-dependent microcircuit rules governing the cellular sparsity of an engram. Here we review recent studies examining the mechanisms that help shape engram architecture and examine how these processes may regulate memory function. We speculate that countervailing forces in local microcircuits contribute to the generation and maintenance of engrams and discuss emerging questions regarding how engrams are formed, stored and used.

AB - Extensive work in computational modeling has highlighted the advantages for employing sparse yet distributed data representation and storage Kanerva (1998), properties that extend to neuronal networks encoding mnemonic information (memory traces or engrams). While neurons that participate in an engram are distributed across multiple brain regions, within each region, the cellular sparsity of the mnemonic representation appears to be quite fixed. Although technological advances have enabled significant progress in identifying and manipulating engrams, relatively little is known about the region-dependent microcircuit rules governing the cellular sparsity of an engram. Here we review recent studies examining the mechanisms that help shape engram architecture and examine how these processes may regulate memory function. We speculate that countervailing forces in local microcircuits contribute to the generation and maintenance of engrams and discuss emerging questions regarding how engrams are formed, stored and used.

UR - http://www.scopus.com/inward/record.url?scp=85056238592&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85056238592&partnerID=8YFLogxK

U2 - 10.1016/j.conb.2018.10.013

DO - 10.1016/j.conb.2018.10.013

M3 - Review article

VL - 54

SP - 163

EP - 170

JO - Current Opinion in Neurobiology

JF - Current Opinion in Neurobiology

SN - 0959-4388

ER -