Evaluation of the Relationship between Childhood Traumas and Adulthood Obesity Development.

This study aimed to delineate the relationship between childhood traumas and adulthood obesity. A total of 314 individuals (157 obese and 157 nonobese) were recruited in the study. After obtaining anthropometric and sociodemographic variables, the Childhood Trauma Questionnaire (CTQ) was administered to the participants. Overall scores of CTQ were determined to be 42.6 ± 10.5 (higher trauma) in obese group and 37.2 ± 6.6 (lower trauma) in nonobese group (P < 0.001). Frequency rates of childhood traumatic experience were found to be 68.8% for obese people and 38.8% for nonobese people. In conclusion, an increased risk for adulthood obesity development was significantly associated with childhood traumatic experience.

Investigation of heart rate variability in major depression patients using wavelet packet transform.

Studies conducted in major depression (MD) patients have reported a high risk of cardiac morbidity as a result of the relationship between changed cardiovascular activity (CA) and autonomic dysfunctions. The investigation of heart rate variability (HRV) gives valuable idea about variances in autonomic CA of MD patients. To get this knowledge, frequency-domain HRV analysis is frequently performed using Fourier transformation (FT) or discrete-wavelet transformation (DWT) to decompose the data into high-frequency (HF) and low-frequency (LF) bands. Nevertheless, it has been reported that the FT is not useful for nonstationary HRV signals and the DWT does not ensure required frequency boundaries of each band. This study aims to compare the frequency-domain HRV features using wavelet-packet-transform (WPT) with absolutely excellent approximation to required band ranges between the controls and patients. In addition to LF and HF band energies, sympathovagal balance that indicates the variation of sympathetic and parasympathetic activities were compared between two groups. Patients had a significantly lower HF energy, higher values of LF energy and higher LF/HF ratio. Our results recommend that impairments in coordination between parasympathetic and sympathetic behavior in MD patients can be assessed by HRV analysis using WPT with high resolution decomposition for needed bands.

Nonlinear analysis of EEGs of patients with major depression during different emotional states.

BACKGROUND: Although patients with major depressive disorder (MDD) have dysfunctions in cognitive behaviors and the regulation of emotions, the underlying brain dynamics of the pathophysiology are unclear. Therefore, nonlinear techniques can be used to understand the dynamic behavior of the EEG signals of MDD patients. METHODS: To investigate and clarify the dynamics of MDD patients׳ brains during different emotional states, EEG recordings were analyzed using nonlinear techniques. The purpose of the present study was to assess whether there are different EEG complexities that discriminate between MDD patients and healthy controls during emotional processing. Therefore, nonlinear parameters, such as Katz fractal dimension (KFD), Higuchi fractal dimension (HFD), Shannon entropy (ShEn), Lempel-Ziv complexity (LZC) and Kolmogorov complexity (KC), were computed from the EEG signals of two groups under different experimental states: noise (negative emotional content) and music (positive emotional content) periods. RESULTS: First, higher complexity values were generated by MDD patients relative to controls. Significant differences were obtained in the frontal and parietal scalp locations using KFD (p<0.001), HFD (p<0.05), and LZC (p=0.05). Second, lower complexities were observed only in the controls when they were subjected to music compared to the resting baseline state in the frontal (p<0.05) and parietal (p=0.005) regions. In contrast, the LZC and KFD values of patients increased in the music period compared to the resting state in the frontal region (p<0.05). Third, the patients׳ brains had higher complexities when they were exposed to noise stimulus than did the controls׳ brains. Moreover, MDD patients׳ negative emotional bias was demonstrated by their higher brain complexities during the noise period than the music stimulus. Additionally, we found that the KFD, HFD and LZC values were more sensitive in discriminating between patients and controls than the ShEn and KC measures, according to the results of ANOVA and ROC calculations. CONCLUSION: It can be concluded that the nonlinear analysis may be a useful and discriminative tool in investigating the neuro-dynamic properties of the brain in patients with MDD during emotional stimulation.

Analysis of sympathovagal balance in patients with major depressive disorder using wavelet packet transform.

Elevated rates of cardiac morbidity have been frequently reported in major depressive disorder (MDD) patients as a result of the relationship between autonomic dysfunctions and varied cardiovascular activity. Heart rate variability (HRV) analysis is an important and non-invasive way for assessing the variances in autonomic nervous system activity of MDD patients. In spectral domain, HRV analysis is usually done by either Fourier transformation (FT) or discrete wavelet transformation (DWT) to divide the data into lowfrequency (LF) and high-frequency (HF) bands. However, while FT is not a proper method for non-stationary HRV data, DWT does not exactly produce required frequency ranges of each LF and HF bands. The purpose of the present study is to investigate the spectral HRV measures obtained by wavelet packet transform (WPT) with absolutely excellent approximation to predefined frequency ranges of bands. Eighteen healthy controls and age- and gender-match eighteen patients with MDD were participated in this study. Sympathovagal balance (LF/HF ratio) that reflects the variation of sympathetic and parasympathetic activities was compared between two groups. Individuals with depression had a significantly higher LF/HF ratio. Our findings suggest that dysfunctions in coordination between sympathetic and parasympathetic nervous system activity in MDD patients can be evaluated by WPT based HRV analysis with high resolution decomposition for required LF and HF bands.

Nonlinear analysis of EEG in major depression with fractal dimensions.

Major depressive disorder (MDD) is a psychiatric mood disorder characterized by cognitive and functional impairments in attention, concentration, learning and memory. In order to investigate and understand its underlying neural activities and pathophysiology, EEG methodologies can be used. In this study, we estimated the nonlinearity features of EEG in MDD patients to assess the dynamical properties underlying the frontal and parietal brain activity. EEG data were obtained from 16 patients and 15 matched healthy controls. A wavelet-chaos methodology was used for data analysis. First, EEGs of subjects were decomposed into 5 EEG sub-bands by discrete wavelet transform. Then, both the Katz's and Higuchi's fractal dimensions (KFD and HFD) were calculated as complexity measures for full-band and sub-bands EEGs. Last, two-way analyses of variances were used to test EEG complexity differences on each fractality measures. As a result, a significantly increased complexity was found in both parietal and frontal regions of MDD patients. This significantly increased complexity was observed not only in full-band activity but also in beta and gamma sub-bands of EEG. The findings of the present study indicate the possibility of using the wavelet-chaos methodology to discriminate the EEGs of MDD patients from healthy controls.

Analysis of heart rate variability during auditory stimulation periods in patients with schizophrenia.

The vulnerability-stress model is a hypothesis for symptom development in schizophrenia patients who are generally characterized by cardiac autonomic dysfunction. Therefore, measures of heart rate variability (HRV) have been widely used in schizophrenics for assessing altered cardiac autonomic regulations. The goal of this study was to analyze HRV of schizophrenia patients and healthy control subjects with exposure to auditory stimuli. More specifically, this study examines whether schizophrenia patients may exhibit distinctive time and frequency domain parameters of HRV from control subjects during at rest and auditory stimulation periods. Photoplethysmographic signals were used in the analysis of HRV. Nineteen schizophrenic patients and twenty healthy control subjects were examined during rest periods, while exposed to periods of white noise (WN) and relaxing music. Results indicate that HRV in patients was lower than that of control subjects indicating autonomic dysfunction throughout the entire experiment. In comparison with control subjects, patients with schizophrenia exhibited lower high-frequency power and a higher low-frequency to high-frequency ratio. Moreover, while WN stimulus decreased parasympathetic activity in healthy subjects, no significant changes in heart rate and frequency-domain HRV parameters were observed between the auditory stimulation and rest periods in schizophrenia patients. We can conclude that HRV can be used as a sensitive index of emotion-related sympathetic activity in schizophrenia patients.