This review surveys methods to separate oscillatory and aperiodic components of neural signals, arguing that aperiodic parameters are meaningful biomarkers linked to excitation–inhibition balance and neurodegeneration and that standardized metrics could inform closed-loop neuromodulation.
By proposing standardized estimation of aperiodic neural features and linking them to Parkinsonism and DBS modulation, the paper offers moderate translational value for developing reliable biomarkers and adaptive neuromodulation strategies, though it lacks direct molecular or therapeutic targets.