Objective: We aimed to assess the ability of the Brain Network Activation (BNA) EEG analysis algorithm to differentiate between early-stage Parkinson’s disease (PD) patients and healthy individuals.

Background: Neurodegeneration in PD begins long before the onset of motor manifestations, which mark the onset of PD and its diagnosis, yet at this point potential disease-modifying therapies might have no effect. Thus, identification of the earliest stage of the disease process is an important goal in PD research.

Methods: 20 established PD patients (disease duration > 2 y), 20 early-stage PD patients (disease duration of ≤ 2 y, no l-dopa therapy) and 30 healthy controls (HC) were enrolled. All participants performed 2 tasks, simultaneously with EEG recording: 1) Auditory oddball task (AOB). 2) visual Go/NoGo (VGNG) task. HC/PD cut-offs were produced per task condition, based on the differentiation between HC and established PD patients and validated using the standard leave-one-out procedure.

Results: Using a non-motor network – the Perception and sustained attention (N100) 15 out of 19 early-stage PD patients were diagnosed as PD (sensitivity=0.75, specificity=0.81) Whereas in the motor networks there was no significant effect between the HC/early-stage PD.

Conclusions: These preliminary BNA EEG analysis results suggest that impaired Perception and sustained attention function is found among PD patients; it is apparent in the early disease stages and may provide a potential diagnostic tool for early PD.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/brain-network-activation-bna-a-new-biomarker-for-parkinsons-disease/