MOTOR LEARNING IN PARKINSONS DISEASE

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The proposed mentored research award aims to develop the applicant's basic research skills and to prepare her for independent investigations directed at exploring and dissecting the neural bases of motor and related dysfunctions in neurological disorders and normal aging using imaging techniques, psychophysical studies and brain network modeling. The primary mentor for this plan is Dr. David Eidelberg, a neurologist with vast experience in the field of PET imaging and movement disorders. Dr. Claude Ghez, a neuroscientist who has worked in the field of motor control for over 25 years will serve as co-mentor. Dr. Glyn Johnson, experienced physicist in the field of magnetic resonance, will serve as consultant to instruct the applicant in functional MRI. Drs. Jim Moeller and Eva Petkova will further the applicant's education in advanced statistics. Dr. Vijay Dhawan will be consultant for PET biophysics and quantification. Dr. Ken Perrine, neuropsychologist, will also be available as consultant. Research plan: The goal of this study is to characterize changes in neural processing underlying implicit and explicit forms of motor learning in patients with Parkinson's disease and in a control normal aging population. A new family of motor tasks developed in Dr. Ghez's lab will be used during 150-H2O positron emission tomography. A new analytical methodology based on principal component analysis will be applied on measures of regional blood flow to determine how inter- subject differences in motor learning are reflected in modulations of brain network expression. These same methods will be used to determine the neural bases of two therapeutic inventions in Parkinson's disease, ventral pallidotomy and pallidal stimulation, and to assess their effectiveness in reversing alterations in motor learning. Educational plan: The educational plan will focus on the following objectives: 1) Completion of the research plan. 2) Learning imaging techniques, including image acquisition and analysis using PET and fMRI. 3) Development of testing techniques to be used in fMRI. 4) Acquisition of skills in brain network analysis (including SSM) to be applied to both PET and NMR imaging. 5) Furthering the applicants statistical and computational skills through courses taken at Columbia University School of Public Health. 6) Developing the applicant's laboratory management, supervision, research communication and mentoring skills. 7) Receiving instruction in the responsible conduct of research.