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bioRxiv · 10.64898/2026.10.15.759313

Multi-parametric spectral modeling disentangles synaptic kinetics and neural excitability from non-invasive electrophysiological recordings

Philippe, V.·Tombroff, L.·Akbarian, F.·De Witte, S.·Trotta, N.·Van Schependom, J.·Engelborghs, S.·Bier, J.-C.·Strauss, M.·De Tiege, X.·Wens, V.
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Abstract

Spectral modeling of electrophysiological recordings enables non-invasive characterization of neural excitability. However, current approaches rely on a single spectral index, limiting insight into the multiple biophysical processes underlying excitation-inhibition balance. Here, we introduce a biologically informed, multi-parametric spectral analysis that disentangles neural excitability and synaptic kinetics from recordings. As a proof of concept, we demonstrate that this approach captures signatures of hyperexcitability and glutamate reuptake dysfunction characteristic of Alzheimer's disease.

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Philippe, V., Tombroff, L., Akbarian, F., De Witte, S., Trotta, N., Van Schependom, J., Engelborghs, S., Bier, J.-C., Strauss, M., De Tiege, X., Wens, V.. 2026-10-18. Multi-parametric spectral modeling disentangles synaptic kinetics and neural excitability from non-invasive electrophysiological recordings. https://doi.org/10.64898/2026.10.15.759313

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