title: Robust time-varying multivariate coherence estimation: application to electroencephalogram recordings during general anesthesia.
abstract: Coherence analysis characterizes frequency-dependent covariance between signals, and is useful for multivariate oscillatory data often encountered in neuroscience. The global coherence provides a summary of coherent behavior in high-dimensional multivariate data by quantifying the concentration of variance in the first mode of an eigenvalue decomposition of the cross-spectral matrix. Practical application of this useful method is sensitive to noise, and can confound coherent activity in disparate neural populations or spatial locations that have a similar frequency structure. In this paper we describe two methodological enhancements to the global coherence procedure that increase robustness of the technique to noise, and that allow characterization of how power within specific coherent modes change through time.
authors.affiliation: Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA. kfwong@partners.org
authors.forename: Kin Foon Kevin
authors.initials: KF
authors.lastname: Wong
authors.forename: Eran A
authors.initials: EA
authors.lastname: Mukamel
authors.forename: Andrés Felipe
authors.initials: AF
authors.lastname: Salazar
authors.forename: Eric T
authors.initials: ET
authors.lastname: Pierce
authors.forename: P Grace
authors.initials: PG
authors.lastname: Harrell
authors.forename: John L
authors.initials: JL
authors.lastname: Walsh
authors.forename: Aaron
authors.initials: A
authors.lastname: Sampson
authors.forename: Emery N
authors.initials: EN
authors.lastname: Brown
authors.forename: Patrick L
authors.initials: PL
authors.lastname: Purdon
mesh_terms: D000768:Anesthesia, General; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D015999:Multivariate Analysis