UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Model-based prediction of muscarinic receptor function from auditory mismatch negativity responses.

Schöbi, D; Homberg, F; Frässle, S; Endepols, H; Moran, RJ; Friston, KJ; Tittgemeyer, M; ... Stephan, KE; + view all (2021) Model-based prediction of muscarinic receptor function from auditory mismatch negativity responses. Neuroimage , Article 118096. 10.1016/j.neuroimage.2021.118096. (In press). Green open access

[thumbnail of 1-s2.0-S1053811921003736-main.pdf]
Preview
Text
1-s2.0-S1053811921003736-main.pdf - Accepted Version

Download (3MB) | Preview

Abstract

Drugs affecting neuromodulation, for example by dopamine or acetylcholine, take centre stage among therapeutic strategies in psychiatry. These neuromodulators can change both neuronal gain and synaptic plasticity and therefore affect electrophysiological measures. An important goal for clinical diagnostics is to exploit this effect in the reverse direction, i.e., to infer the status of specific neuromodulatory systems from electrophysiological measures. In this study, we provide proof-of-concept that the functional status of cholinergic (specifically muscarinic) receptors can be inferred from electrophysiological data using generative (dynamic causal) models. To this end, we used epidural EEG recordings over two auditory cortical regions during a mismatch negativity (MMN) paradigm in rats. All animals were treated, across sessions, with muscarinic receptor agonists and antagonists at different doses. Together with a placebo condition, this resulted in five levels of muscarinic receptor status. Using a dynamic causal model - embodying a small network of coupled cortical microcircuits - we estimated synaptic parameters and their change across pharmacological conditions. The ensuing parameter estimates associated with (the neuromodulation of) synaptic efficacy showed both graded muscarinic effects and predictive validity between agonistic and antagonistic pharmacological conditions. This finding illustrates the potential utility of generative models of electrophysiological data as computational assays of muscarinic function. In application to EEG data of patients from heterogeneous spectrum diseases, e.g. schizophrenia, such models might help identify subgroups of patients that respond differentially to cholinergic treatments.

Type: Article
Title: Model-based prediction of muscarinic receptor function from auditory mismatch negativity responses.
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.neuroimage.2021.118096
Publisher version: https://doi.org/10.1016/j.neuroimage.2021.118096
Language: English
Additional information: © 2021 Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/)
Keywords: Acetylcholine, computational assay, computational psychiatry, generative embedding, translational neuromodeling
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience
URI: https://discovery.ucl.ac.uk/id/eprint/10127520
Downloads since deposit
44Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item