Independent component analysis and source localization of ECoG data
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1
University of California San Diego, United States
We have developed numerical methods to investigate the sources of electrical activity in invasive ECoG electrode (grid/strip) recordings from a patient with partial refractory epilepsy using an ICA mixture model (AMICA, Palmer, 2007). The goal of this work was to model the dynamic structure of the onset and spread of seizure activity. A 15-min dataset containing two seizures was decomposed using up to five competing ICA models. Single-model decompositions tended to focus on the seizure activity, obscuring analysis of transitions to seizure. Multiple models allowed adaptation to both (early, late) seizure and non-seizure activity, respectively, this segmentation remaining consistent across 3-5 model solutions. Additional models adapted to time-local changes in data source structure. Seizure component relationships were clustered based on residual pairwise mutual information during respective model periods. To perform component source localization, a realistic Boundary Element Method (BEM) head model (Akalin Acar, 2010) was constructed for the patient with custom skull opening and plastic (non-conductive) electrode holder features. Source localization was performed using Sparse Bayesian Learning (SBL) (Wipf, 2010). The source space comprised 80,000 dipoles in gray matter perpendicular to the cortical surface, combined into overlapping multi-scale patches (Ramirez, 2007). Using this approach, from the planar ECoG grid and strip data we were able to identify sources of seizure ECoG activity both on cortical gyri and on sulcal walls. The method appears promising for clinical research in epilepsy as well as for cognitive basic neuroscience research using other pre-surgical volunteer patients who undergo invasive monitoring for medical purposes. Funding: Supported by gifts from The Swartz Foundation (Old Field NY).
Keywords:
brain oscillations,
ECoG
Conference:
XI International Conference on Cognitive Neuroscience (ICON XI), Palma, Mallorca, Spain, 25 Sep - 29 Sep, 2011.
Presentation Type:
Poster Presentation
Topic:
Poster Sessions: Quantitative Analysis of EEG, MEG & Brain Oscillations
Citation:
Makeig
S,
Palmer
J and
Akalin Acar
Z
(2011). Independent component analysis and source localization of ECoG data.
Conference Abstract:
XI International Conference on Cognitive Neuroscience (ICON XI).
doi: 10.3389/conf.fnhum.2011.207.00140
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Received:
17 Nov 2011;
Published Online:
28 Nov 2011.
*
Correspondence:
Dr. Scott Makeig, University of California San Diego, San Diego, United States, smakeig@ucsd.edu