Brain-on-a-Chip Devices and Their Potential for Psychiatric Electrophysiology: A Scoping Review

Abstract

Introduction: Circuit dysfunction is central to schizophrenia, bipolar disorder, and major depressive disorder, but current models cannot connect human-relevant microcircuit activity to the electrophysiological abnormalities seen clinically. While changes in alpha and gamma activity, coherence, and cross-frequency coupling are well-established biomarkers, traditional in vitro systems lack the controlled architecture needed to study their cellular origins. Brain-on-a-chip platforms offer engineered control over neural geometry and connectivity, making them a promising tool for bridging this gap. This scoping review evaluates how these systems have been used to study neuronal electrophysiology and their relevance to psychiatric biomarker research.

Methods: A structured database search, combined with manual screening and citation tracing, identified studies using chip-based neural platforms that reported direct electrophysiological recordings. Non-neural systems, organoid-only studies, and models lacking electrophysiology were excluded. Four studies met inclusion criteria.

Results: Experimental platforms primarily reported spikes, firing rates, bursting, and basic correlation measures. None captured low-frequency activity, oscillatory power, synchrony, coherence, or local-field-potential-like signals that define psychiatric electrophysiological biomarkers. Most studies used rodent neurons or generic excitatory stem-cell-derived neurons, and none included defined interneuron subclasses required for modelling gamma oscillations or balanced circuit dynamics.

Discussion: Findings show that current brain-on-a-chip systems are architecturally advanced but electrophysiologically limited. Their outputs capture excitability but not the mesoscale dynamics relevant to psychiatric biomarkers.

Conclusion: Progress in this field will require integration of patient-derived neurons, defined inhibitory interneuron types, and analytical pipelines aligned with clinical electrophysiology to enable brain-on-a-chip platforms to model microcircuit dysfunction in psychiatric illness.