<p>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.</p>

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

  • Daniel J. Hauke,
  • Julia Rodriguez-Sanchez,
  • Hope Oloye,
  • Lioba C. S. Berndt,
  • Dimitris A. Pinotsis,
  • Karl J. Friston,
  • Daniel H. Mathalon,
  • Rick A. Adams

摘要

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.