Changes in the MEG background activity in patients with positive symptoms of schizophrenia: spectral analysis and impact of age

• Published in: Physiological measurement 2013-02, Vol.34 (2), p.265-279
• Main Authors: Escudero, Javier, Ifeachor, Emmanuel, Fernández, Alberto, López-Ibor, Juan José, Hornero, Roberto
• Format: Article
• Language: English
• Subjects: Adult; Aging; Algorithms; Brain; Brain - physiopathology; classification; Diagnosis, Computer-Assisted - methods; early diagnosis; Female; Humans; magnetoencephalogram; Magnetoencephalography - methods; Male; Nerve Net - physiopathology; positive symptoms; Reproducibility of Results; schizophrenia; Schizophrenia - diagnosis; Schizophrenia - physiopathology; Sensitivity and Specificity; spectral analysis
• ISSN: 0967-3334; 1361-6579
• DOI: 10.1088/0967-3334/34/2/265

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 (RPδ), theta (RPθ), lower alpha (RPα1), upper alpha (RPα2), beta (RPβ) and gamma (RPγ) bands. We found significant differences between the two subject groups in the average level of MF and RPγ in some regions of the scalp. Additionally, the MF, SpecEn, RPβ and RPγ 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.