Abstract / Description of output
The frequency spectrum of the magnetoencephalogram (MEG) background activity was analysed in 15 schizophrenia (SCH) patients with predominant positive symptoms and 17 age-matched healthy control subjects using the following variables: median frequency (MF), spectral entropy (SpecEn) and relative power in delta (RP delta), theta (RP theta), lower alpha (RP alpha 1), upper alpha (RP alpha 2), beta (RP beta) and gamma (RP gamma) bands. We found significant differences between the two subject groups in the average level of MF and RP gamma in some regions of the scalp. Additionally, the MF, SpecEn, RP beta and RP gamma values of SCH patients with positive symptoms had a different dependence on age as compared with the results of control subjects, suggesting that SCH affects the way in which the brain activity evolves with age. Moreover, we also classified the MEG signals by means of a cross-validated feature selection process followed by a logistic regression. The subjects were classified with 71.3% accuracy and an area under the ROC curve of 0.741. Thus, the spectral and classification analysis of the MEG in SCH may provide insights into how this condition affects the brain activity and may help in its early detection.
Original language | English |
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Pages (from-to) | 265-279 |
Number of pages | 15 |
Journal | Physiological Measurement |
Volume | 34 |
Issue number | 2 |
DOIs | |
Publication status | Published - Feb 2013 |
Keywords / Materials (for Non-textual outputs)
- classification
- early diagnosis
- magnetoencephalogram
- positive symptoms
- schizophrenia
- spectral analysis
- COMPLEXITY ANALYSIS
- ALZHEIMERS-DISEASE
- EEG
- BRAIN
- CLASSIFICATION
- DEPRESSION
- SIGNALS
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Javier Escudero Rodriguez discusses the analysis of brain electromagnetic activity and it's potential for monitoring schizophrenia
1/12/13
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