Phase cone detection optimization in EEG data

Author

Myers, M.H. ; Kozma, Robert ; Davis, J.J.J. ; Ilin, Roman

Author_Institution

Health Sci. Center, Univ. of Tennessee, Memphis, TN, USA

fYear

2014

fDate

6-11 July 2014

Firstpage

2504

Lastpage

2511

Abstract

Signals measured by electroencephalogram (EEG) arrays were decomposed using Hubert Transformations to produce the spatial amplitude and phase modulation (AM and PM) patterns. Spatial PM patterns intermittently exhibit synchronization-desynchronization transitions. During desynchronization, the spatial PM patterns intermittently conform to conic shapes. These phase cones mark the onset of emergent AM patterns, which carry cognitive content. In this work, various temporal band pass filters were applied to study the frequency dependence of phase cones in the beta-gamma range (10-40 Hz). The results are interpreted in the context of the cognitive cycle of knowledge generation.

Keywords

band-pass filters; electroencephalography; medical signal detection; AM pattern; EEG data; Hubert transformations; PM pattern; beta-gamma range; conic shapes; electroencephalogram data; frequency 10 Hz to 40 Hz; knowledge generation; phase cone detection optimization; phase cone frequency dependence; phase modulation; spatial amplitude; synchronization-desynchronization transitions; temporal band pass filters; Arrays; Band-pass filters; Brain modeling; Data models; Electroencephalography; Rabbits;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks (IJCNN), 2014 International Joint Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4799-6627-1

Type

conf

DOI

10.1109/IJCNN.2014.6889880

Filename

6889880