epilepsy | neuroimaging | connectomics
✅ Using these individual deviation maps, machine learning models achieved precise diagnosis, seizure onset zone lateralization, and prediction of postsurgical seizure outcome. 💊 📃
✅ Using these individual deviation maps, machine learning models achieved precise diagnosis, seizure onset zone lateralization, and prediction of postsurgical seizure outcome. 💊 📃
🎯 SWM microstructure disruption primarily underpins cortical functional alterations in TLE.
🎯 SWM microstructure disruption primarily underpins cortical functional alterations in TLE.
🧩 Functional alteration patterns are strongly shaped by the white matter network architecture.
🧩 Functional alteration patterns are strongly shaped by the white matter network architecture.
📊 The greatest overlap is in the temporolimbic cortex, but no two patients are exactly the same.
📊 The greatest overlap is in the temporolimbic cortex, but no two patients are exactly the same.
📈 Highlighted brain regions with extreme deviations — for every single TLE patient.
📈 Highlighted brain regions with extreme deviations — for every single TLE patient.
Findings are robustly replicated in the UNAM #TLE cohort, demonstrating strong generalizability and reliability.
Findings are robustly replicated in the UNAM #TLE cohort, demonstrating strong generalizability and reliability.
Regions structurally and functionally connected to atypical clusters are more vulnerable, facilitating disease spread. Temporal and frontal cortices emerge as potential disease epicenters.
Regions structurally and functionally connected to atypical clusters are more vulnerable, facilitating disease spread. Temporal and frontal cortices emerge as potential disease epicenters.