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University of Florida Health University of Florida
Norman Fixel Institute for
Neurological Diseases
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principal investigator

study rationale

Deep brain stimulation (DBS) targeted to the globus pallidus internus (GPi) effectively alleviates symptoms in movement disorders like Parkinson’s disease (PD) and dystonia. However, the mechanisms linking GPi DBS to symptom relief remain unclear. Understanding the fiber pathways mediating DBS effects could enable more precise targeting and parameter selection, ultimately improving treatment outcomes for these disorders.

hypothesis

GPi DBS modulates similar motor network fiber pathways in PD and dystonia, despite inducing disorder-specific neurophysiological effects. In PD, GPi DBS reduces beta power and pallido-cortical coherence, while in dystonia, it reduces theta/alpha power and modulates additional pathways involving the cerebellum and temporal cortex.

study design

  • Aim 1: Identify fiber pathways mediating neurophysiological effects of GPi DBS in PD using diffusion-weighted imaging (DWI) and tractography combined with magnetoencephalography (MEG) and local field potential (LFP) recordings.
  • Aim 2: Apply the same analysis pipeline to identify fiber pathways modulated by GPi DBS in dystonia.
  • Aim 3: Compare fiber pathways across PD and dystonia cohorts to determine shared and unique mechanisms of DBS across these disorders.

impact

This study will provide critical insights into the neuroanatomical pathways underlying GPi DBS, offering data-driven approaches for optimizing DBS programming. The results could lead to personalized stimulation parameters for quicker and more effective symptom relief, benefiting patients with PD and dystonia.

next steps for development

Findings from this pilot study will support applications for larger grants, including NIH R01 proposals and funding from organizations like the Michael J. Fox Foundation. The research lays the groundwork for innovative, mechanism-based DBS interventions.

additional information

The study will involve 10 PD and 5 dystonia patients, with MEG and LFP data collected at baseline (1 month post-surgery) and after 6 months of chronic DBS. Computational modeling and tractography will identify fiber pathways modulated by DBS, correlating them with neurophysiological changes and symptom severity improvements.

collaboration

  • Dr. Kara A. Johnson (PI): Leads data analysis, oversees manuscript preparation, and supervises the research assistant.
  • Dr. Coralie de Hemptinne (Mentor): Provides expertise in neurophysiology and LFP data interpretation.
  • Dr. Abbas Babajani-Feremi (Collaborator): Guides MEG data analysis and neuroimaging interpretation.
  • Dr. Joshua Wong (Collaborator): Offers clinical insights into DBS programming and patient outcomes.