Altered SNr activity under dopamine depletion: mechanistic predictions from data-driven network models
bioRxiv 2025.08.15.670540
Applied dynamical systems · Computational neuroscience
John E. Parker, PhD
Assistant Professor of Mathematics and Computer Science, Massachusetts College of Liberal Arts
How structured perturbations reshape nonlinear and chaotic dynamics, from stabilizing chaotic neurons to data-driven models of the Parkinsonian basal ganglia.
- Nonlinear dynamics
- Control of chaos
- Mathematical neuroscience
- Data-driven circuit models
- Neural data analysis
Welcome
I am an Assistant Professor of Mathematics and Computer Science at the Massachusetts College of Liberal Arts. Previously, I was a Visiting Assistant Professor in the Department of Computer Science at Williams College.
Research contains an overview of my research and results are found at Publications. I routinely discuss my results at conferences and seminars, listed at Presentations. Teaching contains course descriptions from the courses I have taught. Visit the About Me page to learn more.
Please feel free to get in touch!
News
Our paper on medial SNr stimulation for sustained motor recovery in dopamine-depleted mice was accepted in Nature Neuroscience. See Publications.
Gave an invited talk on data-driven network assembly in the parkinsonian basal ganglia at the Brandeis University Math Bio Seminar.
Started as Assistant Professor of Mathematics and Computer Science at MCLA.
Presented data-driven network assembly in the parkinsonian basal ganglia at SIAM Life Sciences 2026 in Cleveland.
Organized the mini-symposium "Oscillatory Transitions and Stability in Neural Networks" at ICMNS 2026 in Montreal.
Research areas
01
Data-Driven Modeling of Neural Circuits
Building circuit models constrained by the full variability of experimental recordings, then using them to uncover the mechanisms behind pathological activity.
02Control of Nonlinear and Chaotic Dynamics
Using small, structured perturbations to stabilize hidden periodic behavior in chaotic systems, and following how that control spreads through coupled networks.
03Quantitative Methods for Neural Data
Open-source statistical and machine-learning tools for characterizing neural activity and comparing models with recordings.
Recent publications & preprints
All publications →Stimulation of the Medial SNr Promotes Sustained Motor Recovery and Counteracts Parkinsonian Pathophysiology in Dopamine Depleted Mice
Nature Neuroscience (accepted). Preprint at bioRxiv 2024.12.09.627637
Dopamine depletion weakens direct pathway modulation of SNr neurons
Neurobiology of Disease (Apr. 2024), p. 106512