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Updated: Mar 8, 2026
A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy
Published on: November 13, 2016
Open diffusion magnetic resonance imaging and connectivity data for epilepsy and surgery: The IDEAS II release
Peter N Taylor1,2,3, Gerard Hall1, Jonathan Horsley1
1Computational Neurololgy Neuroscience and Psychiatry (CNNP) Lab, Computational Medicine Group, School of Computing, Newcastle University, Newcastle Upon Tyne, UK.
Objective:
Epileptic seizures are generated in cerebral networks that propagate ictal and interictal activity. The structure of cerebral networks underpinning epileptic activity can be inferred from diffusion-weighted magnetic resonance imaging (DWI). However, publicly available DWI data in individuals with epilepsy are scarce, and processing is technically challenging due to scan-specific artifacts, limiting research progress.
Methods:
Here, we release raw DWI data from 216 individuals with epilepsy and 98 healthy controls. Subject identifiers align with our previous data release (IDEAS), which includes T1-weighted and FLAIR magnetic resonance imaging, surgical details, and long-term seizure outcomes after surgery. Preprocessing reduced distortions and artifacts, and fully processed data include diffusion metric maps in native and template space. We also provide parcellated structural connectomes using multiple atlases and connectivity measures.
Results:
To illustrate the utility of these IDEAS II data, we replicated ENIGMA consortium findings, observing widespread reductions of fractional anisotropy, particularly ipsilateral to the area of seizure onset. We further demonstrate localized abnormality, and network connectivity using streamline tractography in a patient who subsequently underwent temporal lobe resection.
Significance:
This open dataset offers a comprehensive resource to advance research on structural connectivity and surgical outcomes in epilepsy.
