Effective Functional Pattern Between Prefrontal fNIRS Activity and Cognitive Performance in Patients With Parkinson's Disease: A Data-Driven PLS Approach.

ABSTRACT:

Background

Current clinical assessments often fail to detect early prefrontal dysfunction in Parkinson's disease (PD), highlighting the need for objective neuroimaging biomarkers to quantify causal connectivity patterns for early impairment detection.

Methods

We enrolled 91 PD patients (71.08 ± 5.53 years) who underwent functional near-infrared spectroscopy (fNIRS) recording during both resting-state and verbal fluency task (VFT). Transfer entropy (TE) analysis was performed to quantify effective connectivity (EC) between prefrontal regions. Partial least squares (PLS) was then applied to examine multivariate relationships between task design, MoCA subscales, and VFT performance (verbal output).

Results

PLS analysis revealed distinct EC patterns associated with task-s

SUBMITTER: Chen X 

PROVIDER: S-EPMC12463692 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature