Evidence map›Paper›PMID 41793174›Full record

ArticleEpilepsia2026

Open diffusion magnetic resonance imaging and connectivity data for epilepsy and surgery: The IDEAS II release.

Peter N Taylor, Gerard Hall, Jonathan Horsley, Yujiang Wang, Sjoerd B Vos, Gavin P Winston, Andrew W McEvoy, Anna Miserocchi, Jane de Tisi, John S Duncan

Abstract read
In one paragraph

Article in Epilepsia, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Peter N TaylorComputational Neurololgy Neuroscience and Psychiatry (CNNP) Lab, Computational Medicine Group, School of Computing, Newcastle University, Newcastle Upon Tyne, UK.ORCID https://orcid.org/0000-0003-2144-9838
Gerard HallComputational Neurololgy Neuroscience and Psychiatry (CNNP) Lab, Computational Medicine Group, School of Computing, Newcastle University, Newcastle Upon Tyne, UK.ORCID https://orcid.org/0000-0002-5212-7850
Jonathan HorsleyComputational Neurololgy Neuroscience and Psychiatry (CNNP) Lab, Computational Medicine Group, School of Computing, Newcastle University, Newcastle Upon Tyne, UK.
Yujiang WangComputational Neurololgy Neuroscience and Psychiatry (CNNP) Lab, Computational Medicine Group, School of Computing, Newcastle University, Newcastle Upon Tyne, UK.ORCID https://orcid.org/0000-0002-4847-6273
Sjoerd B VosCentre for Medical Image Computing, Department of Computer Science, UCL, London, UK.ORCID https://orcid.org/0000-0002-8502-4487
Gavin P WinstonUCL Queen Square Institute of Neurology, Queen Square, London, UK.ORCID https://orcid.org/0000-0001-9395-1478
Andrew W McEvoyUCL Queen Square Institute of Neurology, Queen Square, London, UK.
Anna MiserocchiUCL Queen Square Institute of Neurology, Queen Square, London, UK.
Jane de TisiUCL Queen Square Institute of Neurology, Queen Square, London, UK.ORCID https://orcid.org/0000-0002-7666-2268
John S DuncanUCL Queen Square Institute of Neurology, Queen Square, London, UK.ORCID https://orcid.org/0000-0002-1373-0681

Funding

Medical Research Council G0802012Medical Research Council MR/M00841X/1UK Research and Innovation MR/T04294X/1UK Research and Innovation MR/V026569/1UK Research and Innovation MR/Y034104/1
6 · The paper itself

Abstract

objectiveEpileptic 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.

methodsHere, 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.

resultsTo 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.

Indexed as

BrainConnectomeDiffusion Magnetic Resonance ImagingEpilepsyNerve NetAdolescentAdultDiffusion Tensor ImagingFemaleHumansMaleMiddle AgedYoung Adultconnectomedata sharingnetworksopen datasurgery

Identifiers

PMID41793174
PMCPMC13285235

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.