Inferring spatiotemporal network patterns from intracranial EEG data.

ABSTRACT:

Objective

The characterization of spatial network dynamics is desirable for a better understanding of seizure physiology. The goal of this work is to develop a computational method for identifying transient spatial patterns from intracranial electroencephalographic (iEEG) data.

Methods

Starting with bivariate synchrony measures, such as phase correlation, a two-step clustering procedure is used to identify statistically significant spatial network patterns, whose temporal evolution can be inferred. We refer to this as the composite synchrony profile (CSP) method.

Results

The CSP method was verified with simulated data and evaluated using ictal and interictal recordings from three patients with intractable epilepsy. Application of the CSP method to these clinical iEEG

SUBMITTER: Ossadtchi A 

PROVIDER: S-EPMC2887736 | biostudies-literature | 2010 Jun

REPOSITORIES: biostudies-literature