An integrated modelling framework for neural circuits with multiple neuromodulators

Joshi, A, Youssofzadeh, V, Vemana, V, McGinnity, TM ORCID: https://orcid.org/0000-0002-9897-4748, Prasad, G and Wong-Lin, K, 2017. An integrated modelling framework for neural circuits with multiple neuromodulators. Journal of The Royal Society Interface, 14 (126), p. 20160902. ISSN 1742-5689

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Abstract

Neuromodulators are endogenous neurochemicals that regulate biophysical and biochemical processes, which control brain function and behaviour, and are often the targets of neuropharmacological drugs. Neuromodulator effects are generally complex partly owing to the involvement of broad innervation, co-release of neuromodulators, complex intra- and extrasynaptic mechanism, existence of multiple receptor subtypes and high interconnectivity within the brain. In this work, we propose an efficient yet sufficiently realistic computational neural modelling framework to study some of these complex behaviours. Specifically, we propose a novel dynamical neural circuit model that integrates the effective neuromodulator-induced currents based on various experimental data (e.g. electrophysiology, neuropharmacology and voltammetry). The model can incorporate multiple interacting brain regions, including
neuromodulator sources, simulate efficiently and easily extendable to largescale brain models, e.g. for neuroimaging purposes. As an example, we model a network of mutually interacting neural populations in the lateral hypothalamus, dorsal raphe nucleus and locus coeruleus, which are major sources of neuromodulator orexin/hypocretin, serotonin and norepinephrine/noradrenaline, respectively, and which play significant roles in regulating many physiological functions. We demonstrate that such a model can provide predictions of systemic drug effects of the popular antidepressants (e.g. reuptake inhibitors), neuromodulator antagonists or their combinations. Finally, we developed user-friendly graphical user interface software for model simulation and visualization for both fundamental sciences and pharmacological studies.

Item Type:	Journal article
Publication Title:	Journal of The Royal Society Interface
Creators:	Joshi, A., Youssofzadeh, V., Vemana, V., McGinnity, T.M., Prasad, G. and Wong-Lin, K.
Publisher:	The Royal Society Publishing
Date:	18 January 2017
Volume:	14
Number:	126
ISSN:	1742-5689
Identifiers:	Number Type 10.1098/rsif.2016.0902 DOI
Rights:	© 2017 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
Divisions:	Schools > School of Science and Technology
Record created by:	Jill Tomkinson
Date Added:	18 Jan 2017 17:05
Last Modified:	09 Jun 2017 14:11
URI:	https://irep.ntu.ac.uk/id/eprint/29832

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