Neural biomarkers of parkinson's disease

A method comprising:

• providing a motor task to quantify rapidly fluctuating motor symptoms of Parkinson's Disease (PD) patients as a basis to identify corresponding neural biomarkers;
• correlating motor performance to specific features of neural activity from the basal ganglia (including the subthalamic nucleus and globus pallidus) to identify patient-specific correlates of motor performance fluctuations.

The method of claim 5 further comprising applying machine learning algorithms to neural activity recorded from the basal ganglia to classify and/or estimate motor fluctuations (a reflection of symptom severity).

A method comprising:

• providing a simple target-tracking task that enables a quantification of Parkinsonian motor dysfunction at short timescales using a set of metrics customized to maximally capture a patient's unique constellation of symptoms.