Freezing event prediction in Parkinsons disease by integration of multimodal biomechanic and electrophysiological signatures

• Applicant: Professor Dr. Daniel Weiß
• Subject Area: Clinical Neurology; Neurosurgery and Neuroradiology ; Cognitive, Systems and Behavioural Neurobiology
• Term: from 2013 to 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 230631029

Freezing phenomena in Parkinsons disease (PD) constitute an important unmet therapeutic need. Nevertheless, in recent years, advances were made towards a more comprehensive understanding of the underlying pathological network state of the large-scale neuro-muscular circuitries with respect to PD motor symptoms including freezing phenomena. This begins to translate now into more sophisticated on demand adaptive therapeutic strategies. During the previous funding period, we found that freezing phenomena of upper limb movement and gait are indicated by low frequency activation of antagonistic muscles and cortical activity. Moreover, we found that during transitions from regular movement to freezing, there is a pathological attenuation of movement-related cortical activity desynchronization and a phasic increase of theta and beta activity. We now aim to obtain predictions on freezing behaviour on single trial basis using regression models and more sophisticated machine learning techniques. This shall provide the ground for preventive neurostimulation applications for upper limb freezing based in order to trigger adaptive transcranial magnetic stimulation to reset pathological motor network activity. We expect to provide a pathophysiological proof-of-concept and methodological framework for adaptive and preventive freezing therapy. This shall translate in future into neurostimulation techniques in order to prevent emergence of freezing of gait.

• DFG Programme: Research Grants