Quantitative EEG Biomarkers in the Genetic Epilepsies and Associations With Neurologic Outcomes
These results suggest that some genetic epilepsies and functional outcome measures have distinct quantitative EEG signatures. Furthermore, EEG spectral features are predictive of some functional outcome measures. Large-scale retrospective quantitative analysis of clinical EEGs has the potential to discover novel biomarkers and to quantify and track individuals' disease progression across development.
Authors
- Shiva Ganesan (ORCID: https://orcid.org/0000-0002-2518-6505)
- Sarah McKeown Ruggiero (ORCID: https://orcid.org/0000-0002-0834-0750)
- Jillian L. McKee (ORCID: https://orcid.org/0000-0001-9724-0403)
- Alexander K. Gonzalez (ORCID: https://orcid.org/0000-0002-4402-398X)
- Brian Litt (ORCID: https://orcid.org/0000-0003-2732-6927)
- Peter D. Galer (ORCID: https://orcid.org/0000-0002-6408-0906)
- Erin C. Conrad (ORCID: https://orcid.org/0000-0001-8910-1817)
- Quy Cao (ORCID: https://orcid.org/0000-0002-6204-1305)
- Michael C. Kaufman (ORCID: https://orcid.org/0000-0003-2718-296X)
- William K.S. Ojemann (ORCID: https://orcid.org/0009-0007-5166-536X)
- Ian McSalley (ORCID: https://orcid.org/0009-0007-9131-4847)
- Ingo Helbig (ORCID: https://orcid.org/0000-0001-8486-0558)
Institutions
- Children's Hospital of Philadelphia (US)
- ATLAS Neuroengineering (Belgium) (BE)
- University of Pennsylvania (US)
Publication Details
- Journal
- Neurology
- Published
- 2025-09-23
- DOI
- https://doi.org/10.1212/wnl.0000000000214148
- Citations
- 5
- Primary Topic
- Diet and metabolism studies
- Type
- article
- Field-Weighted Citation Impact
- 5.82