Fractality analysis of frontal brain in major depressive disorder

International Journal of Psychophysiology : Official Journal of the International Organization of Psychophysiology
Mehran AhmadlouAmir Adeli

Abstract

EEGs of the frontal brain of patients diagnosed with major depressive disorder (MDD) have been investigated in recent years using linear methods but not based on nonlinear methods. This paper presents an investigation of the frontal brain of MDD patients using the wavelet-chaos methodology and Katz's and Higuchi's fractal dimensions (KFD and HFD) as measures of nonlinearity and complexity. EEGs of the frontal brain of healthy adults and MDD patients are decomposed into 5 EEG sub-bands employing a wavelet filter bank, and the FDs of the band-limited as well as those of their 5 sub-bands are computed. Then, using the ANOVA statistical test, HFDs and KFDs of the left and right frontal lobes in EEG full-band and sub-bands of MDD and healthy groups are compared in order to discover the FDs showing the most meaningful differences between the two groups. Finally, the discovered FDs are used as input to a classifier, enhanced probabilistic neural network (EPNN), to discriminate the MDD from healthy EEGs. The results of HFD show higher complexity of left, right and overall frontal lobes of the brain of MDD compared with non-MDD in beta and gamma sub-bands. Moreover, it is observed that HFD of the beta band is more discriminative than HF...Continue Reading

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