Brain Network Activation in Patients With Movement Disorders

Objective: The primary aim of the current project is to assess the utility of the BNA as a quantitative, objective, neurophysiological marker for diagnosis and monitoring of the above most common MDi in man. The secondary aim is to find predictive bio-types (electrophysiological fingerprint) of the above MDi and within these disorders identifying patients with high likelihood of developing: 1) psychiatric complications such as dopaminergic medication induced-impulse control disorder (ICD) for PD; 2) Depression; 3) Gait and balance Impairment; or 4) Cognitive deterioration, including (PD-MCI) or PD-dementia (PDD). The technology: BNA technology is based on non-invasive recordings of multi-channel EEG event-related potentials (ERPs), and a comprehensive multi-dimensional analysis of such recordings, aimed at understanding and visualizing the network complexity (or Brain Networks Activation patterns) of brain function. BNA takes cognitive ERPs, a direct measure of neural activity associated with cognitive functions, to a new frontier, unparalleled by EEG, QEEG or ERP alone or by any other anatomic and functional brain imaging and evaluation tools. The BNA algorithms use innovative sets of signal processing, pattern recognition and machine learning techniques to seek and map activated neural pathways while patients are engaged in a cognitive task. The resulting BNA network patterns can aid clinicians with profiling of changes in functionality and/or dysfunctionality. BNA received an FDA clearance and a CE mark approval during 2014, and is commercially available in the US, with more than 20 active clinical and research sites focusing on numerous neurological and neuropsychological disorders. More than 30,000 data sets of functional brain networks of healthy subjects have been already collected and may serve as normative data for comparison.