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CNNP Lab
  • Home
  • Events
    • NEERM2025
    • Computational Neurology 2023
    • Computational Neurology 2017
  • About
  • People
  • Projects
  • Research
  • Publications
  • Participate
  • Resources
    • IDEAS data
    • BrainMoNoCle
    • Other Resources
  • Contact
  • More
    • Home
    • Events
      • NEERM2025
      • Computational Neurology 2023
      • Computational Neurology 2017
    • About
    • People
    • Projects
    • Research
    • Publications
    • Participate
    • Resources
      • IDEAS data
      • BrainMoNoCle
      • Other Resources
    • Contact

Welcome. Here you will find links to the IDEAS data set, comprising MRI scans from 442 individuals with epilepsy, along with 100 healthy controls.

Detailed demographic and metadata information is also provided.

For updates please subscribe to the mailing list.


  • Raw T1w and FLAIR scans organised in BIDS format. Nifti and json descriptors included

  • Resection masks for IDEAS cohort in native, and freesurfer orig.mgz space

  • skullstripped brain from freesurfer in nifti format

  • freesurfer orig.mgz converted to nifti format

  • freesurfer surface and volumetric reconstructions

  • Freesurfer thickness, volume, and surface areas for the Desikan-Kiliany parcellation.

  • clinical and demographic metadata

  • table indicating the percentage of each brain region in the Desikan-Kiliany atlas subsequently resected by surgery.

  • Freesurfer thickness, volume, and surface areas for the Desikan-Kiliany parcellation, z-scored against normative controls post-combat.

  • Group effect size differences to controls


If you use this data please cite the following publication:

Taylor, P.N., Wang, Y., Simpson, C., Janiukstyte, V., Horsley, J., Leiberg, K., Little, B., Clifford, H., Adler, S., Vos, S.B. and Winston, G.P., McEvoy, A.W., Miserocchi, A., de Tisi, J., Duncan, J.S., 2024. The Imaging Database for Epilepsy And Surgery (IDEAS). Epilepsia. https://doi.org/10.1111/epi.18192 

Poster presented at AES2024, Los Angeles.


Visualise the IDEAS data against a normative reference

You may want to compare the outputs from IDEAS to a larger normative dataset. If so, you may find the following tool useful: https://cnnplab.shinyapps.io/BrainMoNoCle/  

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