A canonical microcircuit for estimating Excitation/Inhibition (E/I) balance

28/10/2026

AI Summary

Canonical microcircuit model estimates E/I balance from non-invasive MEG, EEG, OPM by parameterising pyramidal and inhibitory cell excitability.
Parameters are identifiable and recoverable; simulations probe parameter interactions and effects on electrophysiological signals.
Simulated loss of pyramidal excitability reproduces reduced ERP amplitudes across paired-click, passive and active oddball paradigms, paralleling schizophrenia findings.

TL;DR (AI Generated)

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.

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.

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.

Basic summary

Transl Psychiatry. 2026 Jul 31;16(1):588. doi: 10.1038/s41398-026-04312-y.

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.

PMID:42946699 | DOI:10.1038/s41398-026-04312-y

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