# Poisson Flow of Cortical Folding in Juvenile Myoclonic Epilepsy

arXiv: https://arxiv.org/abs/2606.08404 · HTML: https://mlsanity.com/paper/2606.08404/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 5 of its 62 references that are in the map.
- First posted on arXiv 7 Jun 2026.

## Builds on (most cited first, 5 of 5)

- [Fast Polynomial Approximation of Heat Kernel Convolution on Manifolds and Its Application to Brain Sulcal and Gyral Graph Pattern Analysis](https://mlsanity.com/paper/1911.02721/) (2019)
- [Unified Heat Kernel Regression for Diffusion, Kernel Smoothing and Wavelets on Manifolds and Its Application to Mandible Growth Modeling in CT Images](https://mlsanity.com/paper/1409.6498/) (2014)
- [Counterfactual Analysis of Brain Network Dynamics](https://mlsanity.com/paper/2603.29843/) (2026)
- [Mapping Brain-Behavior Correlations in Autism Using Heat Kernel Smoothing](https://mlsanity.com/paper/2507.00473/) (2025)
- [Poisson Flow Model of Cortical Folding Pattern](https://mlsanity.com/paper/2604.17291/) (2026)

## Abstract (arXiv)

Cortical folding reflects coordinated neurodevelopmental processes and is increasingly recognized as a sensitive marker of neurological disease. However, most existing analyses rely on indirect scalar summaries that do not explicitly model folding geometry itself. In juvenile myoclonic epilepsy (JME), a common genetic epilepsy, cortical abnormalities are often subtle, spatially distributed, and difficult to detect using conventional morphometric measures. We introduce a Poisson-equation--based framework that models cortical folding as a geometry-driven flow derived from mean curvature on the cortical manifold. By treating folding patterns as a stationary source--sink structure, the proposed approach yields a smooth, globally balanced potential field whose surface gradient defines a physically interpretable flux. This framework enables spatially coherent analysis of sulcal--gyral folding organization and provides a principled representation of geometry-driven cortical structure in JME.