Introduces Decomposed Transfer Entropy (DTE) to separate phase, spectral amplitude, and interaction contributions to directed EEG connectivity and shows PD patients off medication exhibit a phase-dominant reweighting from frontal midline (Fz) that shifts toward healthy patterns with dopaminergic…

Provides a mechanism-aware, noninvasive EEG biomarker that discriminates PD from controls and tracks medication-related normalization of network communication—useful for stratifying patients and monitoring therapeutic effects, though it does not directly identify new molecular drug targets.

Clarifying the mechanisms of altered brain network communication in Parkinson's disease is crucial, yet conventional connectivity measures do not distinguish whether directed information flow is driven by phase synchrony or spectral amplitude modulation. To address this, we introduce Decomposed Transfer Entropy (DTE), which represents directed information flow as a mechanistic profile comprising phase, spectral, and interaction components. Simulations indicate that DTE identifies distinct coupling types and remains robust under noise; we further benchmark DTE against representative baseline measures and assess parameter sensitivity. Applied to $\theta $ band resting EEG, DTE reveals that the unmedicated (PD-OFF) state is characterized by a phase-dominant reweighting originating from the frontal midline hub Fz; medication shifts this mechanistic composition toward that of healthy reference. Hub-centric composition metrics derived from DTE discriminate PD-OFF from healthy controls, and the normalization of phase dominance relates to motor improvement ( $\Delta $ UPDRS-III). Overall, DTE offers a mechanism-aware perspective on PD pathophysiology, suggesting that therapeutic benefit aligns with normalization of mechanistic composition rather than simple changes in connection strength, and provides a promising route toward mechanism-oriented biomarkers.