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

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.