title: COMBINED DELAY AND GRAPH EMBEDDING OF EPILEPTIC DISCHARGES IN EEG REVEALS COMPLEX AND RECURRENT NONLINEAR DYNAMICS.
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.
authors.affiliation: Computational Radiology Lab, Boston Children's Hospital, Harvard Medical School, Boston, USA.
authors.forename: B
authors.initials: B
authors.lastname: Erem
authors.affiliation: Computational Radiology Lab, Boston Children's Hospital, Harvard Medical School, Boston, USA.
authors.forename: D E
authors.initials: DE
authors.lastname: Hyde
authors.affiliation: Computational Radiology Lab, Boston Children's Hospital, Harvard Medical School, Boston, USA.
authors.forename: J M
authors.initials: JM
authors.lastname: Peters
authors.affiliation: Computational Radiology Lab, Boston Children's Hospital, Harvard Medical School, Boston, USA.
authors.forename: F H
authors.initials: FH
authors.lastname: Duffy
authors.affiliation: B-Spiral Group, Dept. of ECE, Northeastern University, Boston, USA.
authors.forename: D H
authors.initials: DH
authors.lastname: Brooks
authors.affiliation: Computational Radiology Lab, Boston Children's Hospital, Harvard Medical School, Boston, USA.
authors.forename: S K
authors.initials: SK
authors.lastname: Warfield
keywords: Electroencephalography (EEG); Graph Signal Processing; Manifold Learning; Nonlinear Dynamics