Greydon Gilmore

Greydon Gilmore

Intraoperative Neurophysiologist Biomedical Engineer

London Health Sciences Centre

About

I earned my Ph.D. in Biomedical Engineering at Western University, where I built open-source stereotactic planning software for functional neurosurgery. My work focuses on improving targeting accuracy and post-operative electrode localization for movement disorders and epilepsy through imaging, electrophysiology, and clinical software.

Interests
  • deep brain stimulation
  • stereoelectroencephalography
  • medical image processing
  • clinical software development
Education
  • Postdoctoral in Mathematics, 2022-2024

    Western University

  • Ph.D. Biomedical Engineering, 2017-2022

    Western University

  • M.Sc. Neuroscience, 2013-2015

    Western University

  • B.Sc. Neuroscience, 2010-2013

    Carleton University

Programming

Python, MATLAB, R, Bash, Git

Neuroimaging

ANTs, FSL, NiftyReg, 3D Slicer

spike
Intraoperative Neurophysiology

Single-unit & LFP (DBS/SEEG), EEG/iEEG

Recent Publications

(2025). The impact of localization and registration accuracy on estimates of deep brain stimulation electrode position in stereotactic space. In Imaging Neuroscience.

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(2025). Mapping the topographic organization of the human zona incerta using diffusion MRI. In eLife.

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(2025). Radiofrequency-thermocoagulation in pediatric epilepsy surgery: a systematic review and pooled analysis of cases. In Seizure: European Journal of Epilepsy.

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(2024). Disrupting the epileptogenic network with stereoelectroencephalography-guided radiofrequency thermocoagulation. In Epilepsia.

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(2024). MRI-degad: toward accurate conversion of gadolinium-enhanced T1w MRIs to non-contrast-enhanced scans using CNNs. In International Journal of Computer Assisted Radiology and Surgery.

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(2023). Lack of spontaneous typical seizures during intracranial monitoring with stereo-electroencephalography. In Epileptic Disorders.

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(2023). A population-averaged structural connectomic brain atlas dataset from 422 HCP-aging subjects. In Data in Brief.

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(2023). Magnetic resonance imaging datasets with anatomical fiducials for quality control and registration. In Scientific Data.

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(2022). An Indirect Deep Brain Stimulation Targeting Tool Using Salient Anatomical Fiducials. In Neuromodulation.

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Grants

Graduate Student Award

  • Year: 2020-2022
  • Granting Agency: Parkinson’s Society of Canada
  • Amount: $20,000 CAD

Intern Talentedge Program

  • Year: 2017-2019
  • Granting Agency: OCE Talent Edge Internship Program
  • Amount: $60,000 CAD

Graduate Student Award

  • Year: 2017-2019
  • Granting Agency: Parkinson’s Society of Canada
  • Amount: $40,000 CAD

Graduate Student Innovation Scholars

  • Year: 2017
  • Granting Agency: WORLDDiscoveries – Western University
  • Amount: $1,500 CAD

Canadian Graduate Scholarship

  • Year: 2014-2016
  • Granting Agency: Canadian Institute of Health Research
  • Amount: $37,000 CAD

Training

Neurohackademy

  • Year: 2019
  • Institute: University of Washington
  • Website

Deep Learning Reinforcement Learning Summer School

  • Year: 2018
  • Institute: Vector Institute and CIFAR
  • Website

Intraoperative Neurophysiological Monitoring Course

  • Year: 2017
  • Institute: Greenville Neuromodulation Centre
  • Website

Contact