Cortical correlations in wavelet domain for estimation of emotional dysfunctions

In the present study, the level of nonlinear inter-hemispheric synchronization has been estimated by using wavelet correlation (WC) method for detection of emotional dysfunctions. Due to non-stationary nature of EEG series in addition to the assumption that the high-frequency band is possibly associated with emotional activation, WC has been applied to five distinct frequency band activities (fba) (Delta: 0.5-4Hz, Theta: 4-8Hz, Alpha: 8-16Hz, Beta: 16-32Hz, Gamma: 32-64Hz) embedded in non-averaged single-trial EEG series mediated by convenient affective pictures from International Affective Picture System. Experimental data were collected from both healthy controls and patients, diagnosed with first-episode psychosis, through a 16-channel EEG cap. WC estimations, which are computed for eight electrode pairs (pre-frontal, anterio-frontal, central, parietal, occipital, posterio-frontal, anterio-temporal, posterio-temporal), in accordance with each specified fba and emotional state (pleasant, un-pleasant, neutral) have been classified by using Least Squares Support Vector Machines with tenfold cross-validation to distinguish controls from patients. Results show that the highest classification accuracies of 88.06, 86.39, 83.89% are obtained in Gamma with respect to neutral, un-pleasant, and pleasant stimuli, respectively. In each group (controls and patients), the largest WCs are observed at anterio-frontal and central lobes; however, controls generate the high WC in response to pleasant stimuli, whereas the patients generate the high WC in response to neutral stimuli in Gamma. In conclusion, fronto-central lobes are the most activated brain regions during emotional stimulation by means of inter-hemispheric correlation. Gamma is the most sensitive fba to visual affective pictures. Emotional dysfunctions are found to be characterized by decreased WC in pleasant state, increased WC in neutral state in Gamma.