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Computational models link cellular mechanisms of neuromodulation to large-scale neural dynamics

Research output: Contribution to journalReview articlepeer-review

James M. Shine, Eli J. Müller, Brandon Munn, Joana Cabral, Rosalyn J. Moran, Michael Breakspear

Original languageEnglish
Pages (from-to)765-776
Number of pages12
JournalNature Neuroscience
Volume24
Issue number6
DOIs
Accepted/In press2021
PublishedJun 2021

Bibliographical note

Funding Information: We thank C. Whyte and G. Wainstein for their thoughtful comments on our manuscript. We acknowledge funding from the NHMRC (GNT1118153 (M.B.), GNT1095227 (M.B.), GNT1193857 (J.M.S.)), The University of Sydney (J.M.S.) and the Portuguese Foundation for Science and Technology projects (UIDB/50026/2020, UIDP/50026/2020 and CEECIND/03325/2017 (J.C.)). Publisher Copyright: © 2021, Crown. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

King's Authors

Abstract

Decades of neurobiological research have disclosed the diverse manners in which the response properties of neurons are dynamically modulated to support adaptive cognitive functions. This neuromodulation is achieved through alterations in the biophysical properties of the neuron. However, changes in cognitive function do not arise directly from the modulation of individual neurons, but are mediated by population dynamics in mesoscopic neural ensembles. Understanding this multiscale mapping is an important but nontrivial issue. Here, we bridge these different levels of description by showing how computational models parametrically map classic neuromodulatory processes onto systems-level models of neural activity. The ensuing critical balance of systems-level activity supports perception and action, although our knowledge of this mapping remains incomplete. In this way, quantitative models that link microscale neuronal neuromodulation to systems-level brain function highlight gaps in knowledge and suggest new directions for integrating theoretical and experimental work.

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