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Poisson Flow of Cortical Folding in Juvenile Myoclonic Epilepsy

arXiv 2606.08404 ↗First posted 7 Jun 2026cs.CVcited by 0

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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.

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.

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References · 5

  1. 2019Fast Polynomial Approximation of Heat Kernel Convolution on Manifolds and Its Application to Brain Sulcal and Gyral Graph Pattern Analysiscited by 6
  2. 2014Unified Heat Kernel Regression for Diffusion, Kernel Smoothing and Wavelets on Manifolds and Its Application to Mandible Growth Modeling in CT Imagescited by 3
  3. 2026Counterfactual Analysis of Brain Network Dynamicscited by 2
  4. 2025Mapping Brain-Behavior Correlations in Autism Using Heat Kernel Smoothingcited by 1
  5. 2026Poisson Flow Model of Cortical Folding Patterncited by 1

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