Resumen:
Significance Statement Excitatory-inhibitory balance (EIB) is compromised in neurologic disorders. Our study demonstrates that pharmacologically-induced effects on EIB can be quantified by decomposing the quantitative electroence-phalography (qEEG) power spectrum signal into the oscillatory periodic and the 1/f aperiodic components. MK-801 and diazepam showed distinct signatures across brain regions and EEG components. Specific features of these components are sensitive to relatively small changes in measured exposure. This methodological ap-proach and the features identified as sensitive to EIB modulation could be key for the development of new therapies and functional biomarkers in disorders with excitatory-inhibitory imbalance.Brain function depends on complex circuit interactions between excitatory and inhibitory neurons embedded in local and long-range networks. Systemic GABAA-receptor (GABAAR) or NMDA-receptor (NMDAR) modulation alters the excitatory-inhibitory balance (EIB), measurable with electroencephalography (EEG). However, EEG sig-natures are complex in localization and spectral composition. We developed and applied analytical tools to in-vestigate the effects of two EIB modulators, MK801 (NMDAR antagonist) and diazepam (GABAAR modulator), on periodic and aperiodic EEG features in freely-moving male Sprague Dawley rats. We investigated how, across three brain regions, EEG features are correlated with EIB modulation. We found that the periodic component was composed of seven frequency bands that presented region-dependent and compound-dependent changes. The aperiodic component was also different between compounds and brain regions. Importantly, the parametri-zation into periodic and aperiodic components unveiled correlations between quantitative EEG and plasma con-centrations of pharmacological compounds. MK-801 exposures were positively correlated with the slope of the aperiodic component. Concerning the periodic component, MK-801 exposures correlated negatively with the peak frequency of low -y oscillations but positively with those of high -y and high-frequency oscillations (HFOs). As for the power, 0 and low -y oscillations correlated negatively with MK-801, whereas mid -y correlated posi-tively. Diazepam correlated negatively with the knee of the aperiodic component, positively to f3 and negatively to low -y oscillatory power, and positively to the modal frequency of 0 , low -y , mid -y , and high -y. In conclusion, correlations between exposures and pharmacodynamic effects can be better-understood thanks to the paramet-rization of EEG into periodic and aperiodic components. Such parametrization could be key in functional bio-marker discovery.
