TY - GEN
T1 - Multivariate principal oscillation pattern analysis of ICA sources during seizure
AU - Mullen, Tim
AU - Worrell, Gregory
AU - Makeig, Scott
PY - 2012
Y1 - 2012
N2 - Mapping the dynamics of neural source processes critically involved in initiating and propagating seizure activity is important for effective epilepsy diagnosis, intervention, and treatment. Tracking time-varying shifts in the oscillation modes of an evolving seizure may be useful for both seizure onset detection as well as for improved non-surgical interventions such as microstimulation. In this report we apply a multivariate eigendecomposition method to analyze the time-varying principal oscillation patterns (POPs, or eigenmodes) of maximally-independent (ICA) sources of intracranial EEG data recorded from subdural electrodes implanted in a human patient for evaluation of surgery for epilepsy. Our analysis of a subset of the most dynamically important eigenmodes reveals distinct shifts in characteristic frequency and damping time before, throughout, and following seizures providing insight into the dynamical structure of the system throughout seizure evolution.
AB - Mapping the dynamics of neural source processes critically involved in initiating and propagating seizure activity is important for effective epilepsy diagnosis, intervention, and treatment. Tracking time-varying shifts in the oscillation modes of an evolving seizure may be useful for both seizure onset detection as well as for improved non-surgical interventions such as microstimulation. In this report we apply a multivariate eigendecomposition method to analyze the time-varying principal oscillation patterns (POPs, or eigenmodes) of maximally-independent (ICA) sources of intracranial EEG data recorded from subdural electrodes implanted in a human patient for evaluation of surgery for epilepsy. Our analysis of a subset of the most dynamically important eigenmodes reveals distinct shifts in characteristic frequency and damping time before, throughout, and following seizures providing insight into the dynamical structure of the system throughout seizure evolution.
UR - http://www.scopus.com/inward/record.url?scp=84883035984&partnerID=8YFLogxK
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U2 - 10.1109/EMBC.2012.6346575
DO - 10.1109/EMBC.2012.6346575
M3 - Conference contribution
C2 - 23366536
AN - SCOPUS:84883035984
SN - 9781424441198
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 2921
EP - 2924
BT - 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012
T2 - 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012
Y2 - 28 August 2012 through 1 September 2012
ER -