Unified Topological Inference for Brain Networks in Temporal Lobe Epilepsy Using the Wasserstein Distance

التفاصيل البيبلوغرافية
العنوان: Unified Topological Inference for Brain Networks in Temporal Lobe Epilepsy Using the Wasserstein Distance
المؤلفون: Chung, Moo K., Ramos, Camille Garcia, De Paiva, Felipe Branco, Mathis, Jedidiah, Prabharakaren, Vivek, Nair, Veena A., Meyerand, Elizabeth, Hermann, Bruce P., Binder, Jeffrey R., Struck, Aaron F.
سنة النشر: 2023
المجموعة: Quantitative Biology
مصطلحات موضوعية: Quantitative Biology - Neurons and Cognition
الوصف: Persistent homology offers a powerful tool for extracting hidden topological signals from brain networks. It captures the evolution of topological structures across multiple scales, known as filtrations, thereby revealing topological features that persist over these scales. These features are summarized in persistence diagrams, and their dissimilarity is quantified using the Wasserstein distance. However, the Wasserstein distance does not follow a known distribution, posing challenges for the application of existing parametric statistical models.To tackle this issue, we introduce a unified topological inference framework centered on the Wasserstein distance. Our approach has no explicit model and distributional assumptions. The inference is performed in a completely data driven fashion. We apply this method to resting-state functional magnetic resonance images (rs-fMRI) of temporal lobe epilepsy patients collected from two different sites: the University of Wisconsin-Madison and the Medical College of Wisconsin. Importantly, our topological method is robust to variations due to sex and image acquisition, obviating the need to account for these variables as nuisance covariates. We successfully localize the brain regions that contribute the most to topological differences. A MATLAB package used for all analyses in this study is available at https://github.com/laplcebeltrami/PH-STATTest.
Comment: arXiv admin note: text overlap with arXiv:2201.00087
نوع الوثيقة: Working Paper
الوصول الحر: http://arxiv.org/abs/2302.06673Test
رقم الانضمام: edsarx.2302.06673
قاعدة البيانات: arXiv