Journal article
The algorithmic complexity of multichannel EEGs is sensitive to changes in behavior
Psychophysiology, v 40(1), pp 77-97
01 Jan 2003
PMID: 12751806
Abstract
Symbolic measures of complexity provide a quantitative characterization of the sequential structure of symbol sequences. Promising results from the application of these methods to the analysis of electroencephalographic (EEG) and event-related brain potential (ERP) activity have been reported. Symbolic measures used thus Car have two limitations, however. First, because the value of complexity increases with the length of the message, it is difficult to compare signals of different epoch lengths. Second, these symbolic measures do not generalize easily to the multichannel case. We address these issues in studies in which both single and multichannel EEGs were analyzed using measures of signal complexity and algorithmic redundancy, the latter being defined as a sequence-sensitive generalization of Shannon's redundancy. Using a binary partition of EEG activity about the median, redundancy was shown to be insensitive to the size of the data set while being sensitive to changes in the subject's behavioral state (eyes open vs. eyes closed). The covariance complexity, calculated from the singular value spectrum of a multichannel signal was also found to be sensitive to changes in behavioral state. Statistical separations between the eyes open and eyes closed conditions were found to decrease following removal of the 8- to 12-Hz content in the EEG, but still remained statistically significant. Use of symbolic measures in multivariate signal classification is described.
Metrics
Details
- Title
- The algorithmic complexity of multichannel EEGs is sensitive to changes in behavior
- Creators
- TAA WatanabeC J CellucciE Kohegyi - Norristown State HospitalT R Bashore - University of Northern ColoradoR C Josiassen - Norristown State HospitalN N Greenbaun - College of New JerseyP E Rapp - Norristown State Hospital
- Publication Details
- Psychophysiology, v 40(1), pp 77-97
- Publisher
- Wiley
- Number of pages
- 21
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Psychiatry
- Web of Science ID
- WOS:000180455300009
- Scopus ID
- 2-s2.0-12244286027
- Other Identifier
- 991019167833004721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Neurosciences
- Physiology
- Psychology
- Psychology, Biological
- Psychology, Experimental