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Open Access Publications from the University of California

Scholarly Works (2 results)

  • Thesis
  • Peer Reviewed
UC San Francisco Electronic Theses and Dissertations (2024)

In Parkinson’s disease, imbalances between “antikinetic” and “prokinetic” patterns of neuronal oscillatory activity are related to motor dysfunction. Invasive brain recordings from the motor network have suggested that medical or surgical therapy can promote a prokinetic state by inducing narrowband gamma rhythms (60-90 Hz), which are associated with dyskinesia. Here, I investigate the behavioral and statistical properties of levodopa-induced and deep brain stimulation-entrained narrowband gamma rhythms. Collaborating with Oxford researchers, we also model the deep brain stimulation induced entrainment of gamma oscillations using interacting neuronal populations and patient-specific features of the levodopa-induced gamma oscillations. Using a sensing-enabled deep brain stimulation system, attached to both motor cortex and subthalamic or pallidal leads, the Starr Lab recorded over 900 hours of multisite field potentials prior to initiating deep brain stimulation, and over 600 hours with deep brain stimulation. I find that levodopa-induced gamma oscillations are more strongly associated with dyskinesia than deep brain stimulation-entrained gamma oscillations. Statistical comparisons revealed that levodopa-induced gamma oscillations exhibit increased variance in peak frequency, decreased spectral power, and higher variance in spectral power. Furthermore, I also work with collaborators at Oxford to show that entrainment can be predicted using neural circuit models fitted to patient data at various stimulation parameters. Put together, this work suggests that gamma oscillations as programming biomarkers should be leveraged distinctly across medical and surgical interventions to mitigate dyskinesia – while excessive levodopa-induced gamma oscillations are a marker for dyskinesia, increased entrained gamma oscillations may be a marker of a non-pathological prokinetic movement state. Our modeling work can subsequently be leveraged to predict the amount of entrained gamma across stimulation parameters.

    Cover page: Levodopa-induced gamma oscillations in patients with Parkinson’s disease using chronic invasive brain recording: detection, entrainment, and functional relevance
    • Article
    • Peer Reviewed
    UC San Francisco Previously Published Works (2021)

    Purpose

    fMRI is increasingly used for presurgical language mapping, but lack of standard methodology has made it difficult to combine/compare data across institutions or determine the relative efficacy of different approaches. Here, we describe a quantitative analytic framework for determining language laterality in clinical fMRI that addresses these concerns.

    Methods

    We retrospectively analyzed fMRI data from 59 patients who underwent presurgical language mapping at our institution with identical imaging and behavioral protocols. First, we compared the efficacy of different regional masks in capturing language activations. Then, we systematically explored how laterality indices (LIs) computed from these masks vary as a function of task and activation threshold. Finally, we determined the percentile threshold that maximized the correlation between the results of our LI approach and the laterality assessments from the original clinical radiology reports.

    Results

    First, we found that a regional mask derived from a meta-analysis of the fMRI literature better captured language task activations than masks based on anatomically defined language areas. Then, we showed that an LI approach based on this functional mask and percentile thresholding of subject activation can quantify the relative ability of different language tasks to lateralize language function at the population level. Finally, we determined that the 92nd percentile of subject-level activation provides the optimal LI threshold with which to reproduce the original clinical reports.

    Conclusion

    A quantitative framework for determining language laterality that uses a functionally-derived language mask and percentile thresholding of subject activation can combine/compare results across tasks and patients and reproduce clinical assessments of language laterality.
      Cover page: A quantitative approach for measuring laterality in clinical fMRI for preoperative language mapping
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