Psychiatric symptoms are often accompanied by somatic symptoms induced by the activity of the autonomic nervous system (ANS). The aim of this study was to calculate the time lag between electroencephalography (EEG) and electrocardiography (ECG) responses, to clarify the changes in the relationship between the cerebral cortex (CC) and the sympathetic nervous system (SNS) during emotional recall processing. Twenty-two healthy young adults were examined. Their EEG and ECG data were simultaneously recorded during emotional audiovisual recall tasks using pleasant and unpleasant stimuli for 180 s, with three repetitions (Epochs 1 & 2 and Epoch 3). The EEG data were analyzed using a fast Fourier transform (FFT) to obtain a time series of relative power spectra, X E , in the theta 1, theta 2, alpha 1, alpha 2, alpha 3, beta 1, beta 2, and beta 3 bands. Time series of RR (inter-beat) intervals (time intervals between successive R waves) derived from the ECG spectral analysis using FFT was applied to the resampled time series of RR intervals over about 60 s to obtain a time series of power spectra for the ratio low frequency/high frequency (LH/HF), X C , which reflects the activity of the sympathetic nervous function. The time lag between X E and X C was calculated using wavelet-crosscorrelation analysis. The results demonstrated that the brain responded to unfamiliar emotionally pleasant stimuli in Epochs 1 & 2 earlier than the SNS, whereas the brain and SNS responded to unfamiliar unpleasant stimuli nearly simultaneously. The brain was activated rapidly in response to familiar unpleasant stimuli, although SNS responded more rapidly to familiar pleasant stimuli than the brain in Epoch 3. Our results quantitatively describe the relationship between the CC and the ANS during emotional recall.
Interictal paroxysmal rhythmic activity can appear in electroencephalography (EEG) in patients with mental disorders. The abnormal EEG were analyzed by wavelet-crosscorrelation analysis. The EEG were categorized as following: 2-4 seconds (A) and 0-2 seconds (B) before the appearance of the abnormal EEG; 2 seconds during the abnormal EEG (C); 0-2 seconds (D) and 2-4 seconds (E) after the abnormal EEG. Wavelet-crosscorrelation coefficients (WCC) in the theta and alpha bands for each segment were calculated in all patients. The results in the theta band showed that the abnormal connections between the sites in the brain could continue although the EEG seemingly recovered from the interictal paroxysmal rhythmic activity. The results in the alpha band showed that the normal connections between the sites in the brain could be weakened in the 2 seconds prior to the beginning of the interictal paroxysmal rhythmic activity in the EEG.
In some individuals, alpha waves appear in many regions of the brain, and this is considered abnormal electroencephalography (EEG). This phenomenon is known as diffuse alpha pattern. This study aims to extract and compare the features of the connectivity between the parts of the brain. The EEGs of healthy individuals and mental disorder patients with the diffuse alpha pattern were analyzed using wavelet-crosscorrelation analysis. Five epochs of 2 seconds were analyzed for each subject. Wavelet-crosscorrelation coefficients were calculated for frequencies in the alpha band for all epochs in each subject. The results showed that the WCC values were higher in the patients with diffuse alpha. The highest wavelet power spectra in the alpha band of the patients occurred at a lower frequency. Our results suggest that the connectivity strength along the sagittal and occipital orientations in the brain of the patients could be stronger than healthy individuals.
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