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Cited by 104EEG and Brain-Computer InterfacesEpilepsy research and treatmentBlind Source Separation Techniques

The DOI matches its Crossref record; 29 of the 31 references it cites were found in a registry or an index.

Automated interictal spike detection and source localization in magnetoencephalography using independent components analysis and spatio-temporal clustering

Ossadtchi, A., Baillet, S., Mosher, J.C., Thyerlei, D., Sutherling, W., Leahy, R.M.·2004·Clinical Neurophysiology
DOI 10.1016/j.clinph.2003.10.036
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Abstract

Objective Magnetoencephalography (MEG) dipole localization of epileptic spikes is useful in epilepsy surgery for mapping the extent of abnormal cortex and to focus intracranial electrodes. Visually analyzing large amounts of data produces fatigue and error. Most automated techniques are based on matching of interictal spike templates or predictive filtering of the data and do not explicitly include source localization as part of the analysis. This leads to poor sensitivity versus specificity characteristics. We describe a fully automated method that combines time-series analysis with source localization to detect clusters of focal neuronal current generators within the brain that produce interictal spike activity.Methods We first use an ICA (independent components analysis) method to decompose the multichannel MEG data and identify those components that exhibit spike-like characteristics. From these detected spikes we then find those whose spatial topographies across the array are consistent with focal neural sources, and determine the foci of equivalent current dipoles and their associated time courses. We then perform a clustering of the localized dipoles based on distance metrics that takes into consideration both their locations and time courses. The final step of refinement consists of retaining only those clusters that are statistically significant. The average locations and time series from significant clusters comprise the final output of our method.Results and significance Data were processed from 4 patients with partial focal epilepsy. In all three subjects for whom surgical resection was performed, clusters were found in the vicinity of the resectioned area.Conclusions The presented procedure is promising and likely to be useful to the physician as a more sensitive, automated and objective method to help in the localization of the interictal spike zone of intractable partial seizures. The final output can be visually verified by neurologists in terms of both the location and distribution of the dipole clusters and their associated time series. Due to the clinical relevance and demonstrated promise of this method, further investigation of this approach is warranted.

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Metadata

Authors
Ossadtchi, A., Baillet, S., Mosher, J. C., Thyerlei, D., Sutherling, W., & Leahy, R. M.
Affiliations
  • University of Southern California (US)
  • Centre National de la Recherche Scientifique (FR)
  • Los Alamos National Laboratory (US)
  • Huntington Hospital (US)
Corresponding author
Leahy, R.M.
ORCID
Venue
Clinical Neurophysiology
Publisher
Elsevier BV
Published
2004-03
Volume
115
Issue
3
Pages
508-522
ISSN
1388-2457 (ISSN-L)
DOI
10.1016/j.clinph.2003.10.036
OpenAlex
W1967815854
Cited by
104
References
31
Citations by year
2026: 2 · 2025: 5 · 2024: 1 · 2023: 7 · 2022: 9 · 2021: 5 · 2020: 5 · 2019: 10 · 2018: 5 · 2017: 2 · 2016: 1 · 2015: 4 · 2014: 7 · 2013: 3 · 2012: 3
FWCI
3.03
Type
journal article
Language
en
Open access
closed
Licence
Locations
  • Clinical Neurophysiology (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • National Institutes of Health
  • National Institute of Neurological Disorders and Stroke (R01NS020806)
  • National Institute of Biomedical Imaging and Bioengineering (R01EB002010)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
  • Health Sciences › Medicine › Clinical Neurology › Epilepsy research and treatment
  • Physical Sciences › Computer Science › Signal Processing › Blind Source Separation Techniques
Keywords
magnetoencephalography, source localization, epilepsy surgery, independent component analysis, spatiotemporal clustering, equivalent current dipole
MeSH terms
Action Potentials, Adolescent, Adult, Automation, Brain Mapping, Computer Simulation, Epilepsies, Partial, Female, Humans, Male, Models, Neurological, Postoperative Period, Time Factors, Magnetoencephalography, Cluster Analysis

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