A canonical microcircuit for estimating Excitation/Inhibition (E/I) balance
11 affiliations
- 1Hawkes Institute, Department of Computer Science, University College London, London, UK
- 2Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- 3Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- 4King’s Institute for Artificial Intelligence, King’s College London, London, UK
- 5Department of Psychology and Neuroscience, City St George’s, University of London, London, UK
- 6Department of Psychology, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
- 7School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, UK
- 8Department of Imaging Neuroscience, Queen Square Institute of Neurology, University College London, London, UK
- 9Department of Psychiatry & Behavioral Sciences, University of California, San Francisco, CA USA
- 10Mental Health Service, San Francisco Veterans Affairs Health Care System, San Francisco, CA USA
- 11Institute of Cognitive Neuroscience, University College London, London, UK
Abstract
Excitation/inhibition (E/I) balance is crucial for maintaining healthy brain function and can be disrupted in various neurological and psychiatric disorders. Despite its importance, there are few tools to study E/I balance non-invasively in humans. Here, we propose a canonical microcircuit model to estimate E/I balance from non-invasive magnetoencephalography (MEG), electroencephalography (EEG) or optically pumped magnetometers (OPM) recordings by parameterising global pyramidal and inhibitory cell excitability. We first establish that E/I parameters are identifiable and recoverable. We then explore the effects of these new parameters and their interaction with other parameters in a series of simulations. To highlight the clinical relevance of this new model, we simulate changes in E/I balance and their impact on event-related potentials (ERPs) derived from paired-click, passive and active oddball paradigms, which are among the most robust clinical biomarkers of schizophrenia. Our simulations show that a loss of pyramidal cell excitability can explain reduced ERP amplitudes across all three paradigms, mirroring empirical findings in schizophrenia. This method may serve as a computational assay for estimating synaptopathy and E/I balance from non-invasive electrophysiological recordings across various clinical conditions thereby advancing efforts to develop personalised interventions to restore E/I balance.
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BibTeX
@article{hauke2026canonical,
title = {{A canonical microcircuit for estimating Excitation/Inhibition (E/I) balance}},
author = {Daniel J. Hauke and Julia Rodriguez-Sanchez and Hope Oloye and Lioba C. S. Berndt and Dimitris A. Pinotsis and Karl J. Friston and Daniel H. Mathalon and Rick A. Adams},
journal = {Translational Psychiatry},
year = {2026},
month = jul,
doi = {10.1038/s41398-026-04312-y},
url = {https://doi.org/10.1038/s41398-026-04312-y},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - A canonical microcircuit for estimating Excitation/Inhibition (E/I) balance
AU - Daniel J. Hauke
AU - Julia Rodriguez-Sanchez
AU - Hope Oloye
AU - Lioba C. S. Berndt
AU - Dimitris A. Pinotsis
AU - Karl J. Friston
AU - Daniel H. Mathalon
AU - Rick A. Adams
PY - 2026
DA - 2026/07/31
JO - Translational Psychiatry
DO - 10.1038/s41398-026-04312-y
UR - https://doi.org/10.1038/s41398-026-04312-y
AB - Excitation/inhibition (E/I) balance is crucial for maintaining healthy brain function and can be disrupted in various neurological and psychiatric disorders. Despite its importance, there are few tools to study E/I balance non-invasively in humans. Here, we propose a canonical microcircuit model to estimate E/I balance from non-invasive magnetoencephalography (MEG), electroencephalography (EEG) or optically pumped magnetometers (OPM) recordings by parameterising global pyramidal and inhibitory cell excitability. We first establish that E/I parameters are identifiable and recoverable. We then explore the effects of these new parameters and their interaction with other parameters in a series of simulations. To highlight the clinical relevance of this new model, we simulate changes in E/I balance and their impact on event-related potentials (ERPs) derived from paired-click, passive and active oddball paradigms, which are among the most robust clinical biomarkers of schizophrenia. Our simulations show that a loss of pyramidal cell excitability can explain reduced ERP amplitudes across all three paradigms, mirroring empirical findings in schizophrenia. This method may serve as a computational assay for estimating synaptopathy and E/I balance from non-invasive electrophysiological recordings across various clinical conditions thereby advancing efforts to develop personalised interventions to restore E/I balance.
SN - 2158-3188
ER -