| Literature DB >> 26366250 |
B Erem1, D E Hyde1, J M Peters1, F H Duffy1, D H Brooks2, S K Warfield1.
Abstract
The dynamical structure of the brain's electrical signals contains valuable information about its physiology. Here we combine techniques for nonlinear dynamical analysis and manifold identification to reveal complex and recurrent dynamics in interictal epileptiform discharges (IEDs). Our results suggest that recurrent IEDs exhibit some consistent dynamics, which may only last briefly, and so individual IED dynamics may need to be considered in order to understand their genesis. This could potentially serve to constrain the dynamics of the inverse source localization problem.Entities:
Keywords: Electroencephalography (EEG); Graph Signal Processing; Manifold Learning; Nonlinear Dynamics
Year: 2015 PMID: 26366250 PMCID: PMC4564064 DOI: 10.1109/ISBI.2015.7163884
Source DB: PubMed Journal: Proc IEEE Int Symp Biomed Imaging ISSN: 1945-7928