Spatiotemporal connectivity maps abnormal communication pathways in major depressive disorder underlying gamma oscillations.

Auditory steady-state response underlying gamma oscillations (gamma-ASSR) have been explored in patients with major depressive disorder (MDD), while ignoring the spatiotemporal dynamic characteristics. This study aims to construct dynamic directed brain networks to explore the disruption of spatiotemporal dynamics underlying gamma-ASSR in MDD. This study recruited 29 MDD patients and 30 healthy controls for a 40 Hz auditory steady-state evoked experiment. The propagation of gamma-ASSR was divided into early, middle, and late time interval. Partial directed coherence was applied to construct dynamic directed brain networks based on graph theory. The results showed that MDD patients had lower global efficiency and out-strength in temporal, parietal, and occipital regions over three time intervals. Additionally, distinct disrupted connectivity patterns occurred in different time intervals with abnormalities in the early and middle gamma-ASSR in left parietal regions cascading forward to produce dysfunction of frontal brain regions necessary to support gamma oscillations. Furthermore, the early and middle local efficiency of frontal regions were negatively correlated with symptom severity. These findings highlight patterns of hypofunction in the generation and maintenance of gamma-band oscillations across parietal-to-frontal regions in MDD patients, which provides novel insights into the neuropathological mechanism underlying gamma oscillations associated with aberrant brain network dynamics of MDD.

Altered fronto-central theta-gamma coupling in major depressive disorder during auditory steady-state responses.

OBJECTIVE: Neural oscillations during sensory and cognitive events interact at different frequencies. However, such evidence in major depressive disorder (MDD) remains scarce. We explored the possible abnormal neural oscillations in MDD by analyzing theta-phase/gamma-amplitude coupling (TGC). METHODS: Resting-state and auditory steady-state response (ASSR) electroencephalography recordings were obtained from 35 first-episode MDD and 35 healthy controls (HCs). TGC during rest, ASSR stimulation, and ASSR baseline between and within groups were analyzed to evaluate MDD alterations. Receiver operating characteristic (ROC), TGC comparison between MDD severity subgroups (mild, moderate, major), and correlations were investigated to determine the potential use of altered TGC for identifying MDD. RESULTS: In MDD, left fronto-central TGC decreased during stimulation, while right fronto-central TGC increased during baseline. The area under ROC curve for altered TGC was 0.863. Furthermore, during stimulation, moderate and major MDD groups exhibited significantly lower TGC than mild group, and fronto-central TGC was negatively correlated with depression scale scores. CONCLUSIONS: Our results provided the first evidence for an abnormal TGC response of fronto-central regions in MDD during an ASSR task. Importantly, altered TGC may be promising biomarkers of MDD. SIGNIFICANCE: Our findings enhance the understanding of physiological mechanisms underlying MDD and aid in its clinical diagnosis.

Neurophysiological markers of depression detection and severity prediction in first-episode major depressive disorder.

OBJECTIVE: Deviant γ auditory steady-state responses (γ-ASSRs) have been documented in some psychiatric disorders. Nevertheless, the role of γ-ASSR in drug-naïve first-episode major depressive disorder (FEMD) patients remains equivocal. This study aimed to examine whether γ-ASSRs are impaired in FEMD patients and predict depression severity. METHODS: Cortical reactivity was assessed in a cohort of 28 FEMD patients relative to 30 healthy control (HC) subjects during an ASSR paradigm randomly presented at 40 and 60 Hz. Event-related spectral perturbation and inter-trial phase coherence (ITC) were calculated to quantify dynamic changes of the γ-ASSR. Receiver operating characteristic curve combined with binary logistic regression were then employed to summarize ASSR variables that maximally differentiated groups. RESULTS: FEMD patients exhibited significantly inferior 40 Hz-ASSR-ITC in the right hemisphere versus HC subjects (p = 0.007), along with attenuated θ-ITC that reflected underlying impairments in θ responses during 60 Hz clicks (p < 0.05). Moreover, the 40 Hz-ASSR-ITC and θ-ITC in the right hemisphere can be used as a combinational marker to detect FEMD patients with 84.0 % sensitivity and 81.5 % specificity (area under the curve was 0.868, 95 % CI: 0.768-0.968). Pearson's correlations between the depression severity and ASSR variables were further conducted. The symptom severity of FEMD patients was negatively correlated with 60 Hz-ASSR-ITC in the midline and right hemisphere, possibly indicating that depression severity mediated high γ neural synchrony. CONCLUSIONS: Our findings provide critical insight into the pathological mechanism of FEMD, suggesting first that 40 Hz-ASSR-ITC and θ-ITC in right hemisphere constitute potential neurophysiological markers for early depression detection, and second, that high γ entrainment deficits may contribute to underlying symptom severity in FEMD patients.

Hypofunction of directed brain network within alpha frequency band in depressive patients: a graph-theoretic analysis.

Directed brain networks may provide new insights into exploring physiological mechanism and neuromarkers for depression. This study aims to investigate the abnormalities of directed brain networks in depressive patients. We constructed the directed brain network based on resting electroencephalogram for 19 depressive patients and 20 healthy controls with eyes closed and eyes open. The weighted directed brain connectivity was measured by partial directed coherence for α, ß, γ frequency band. Furthermore, topological parameters (clustering coefficient, characteristic path length, and et al.) were computed based on graph theory. The correlation between network metrics and clinical symptom was also examined. Depressive patients had a significantly weaker value of partial directed coherence at alpha frequency band in eyes-closed state. Clustering coefficient and characteristic path length were significantly lower in depressive patients (both p < .01). More importantly, in depressive patients, disruption of directed connectivity was noted in left-to-left (p < .05), right-to-left (p < .01) hemispheres and frontal-to-central (p < .01), parietal-to-central (p < .05), occipital-to-central (p < .05) regions. Furthermore, connectivity in LL and RL hemispheres was negatively correlated with depression scale scores (both p < .05). Depressive patients showed a more randomized network structure, disturbed directed interaction of left-to-left, right-to-left hemispheric information and between different cerebral regions. Specifically, left-to-left, right-to-left hemispheric connectivity was negatively correlated with the severity of depression. Our analysis may serve as a potential neuromarker of depression.

Altered gamma oscillations and beta-gamma coupling in drug-naive first-episode major depressive disorder: Association with sleep and cognitive disturbance.

OBJECTIVE: Gamma oscillations contribute to the pathogenesis mechanisms of major depressive disorder (MDD) have been proposed, but gamma activity is not well characterized. This study is the first attempt to investigate the altered gamma oscillations in first-episode MDD, particularly the beta-gamma coupling, and to determine the potential symptomatic relationship with the identified gamma dysregulation. METHODS: Resting electroencephalography was recorded for 43 drug-naive first-episode MDD and 57 healthy control (HC) subjects. Integrated analysis of relative spectral power, weighted phase lag index, and phase-amplitude coupling (PAC) were utilized to reveal the alterations of gamma activities. Pearson's correlation was implemented to identify the relationship between altered gamma activities and the clinical depressive symptoms, which were categorized into four factors: anxiety somatization, retardation, cognitive disturbance, and sleep disturbance. RESULTS: Compared with HC subjects, MDD patients showed not only significantly decreased gamma powers in the left temporal and the bilateral occipital regions but also weakened gamma connectivity between the left hemisphere and the right frontal region. Furthermore, attenuated beta-gamma PAC of MDD patients was observed in the left temporal regions. Importantly, the suppression of left occipital mid- and high gamma oscillations were negatively correlated with sleep disturbance, while the deficits in left temporal beta-mid-gamma PAC and beta-high gamma PAC showed negative correlations with cognitive disturbance. LIMITATIONS: Important limitations are the small sample size and the possible inclusion of bipolar depression in the MDD group. CONCLUSIONS: Our findings provide the first evidence that in first-episode MDD, aberrant gamma powers and beta-gamma coupling are associated with sleep and cognitive impairments, respectively, deepening our understanding of the physiological mechanisms underlying sleep and cognitive symptoms in first-episode MDD. Altered gamma oscillations emerge as promising biomarkers for diagnosing MDD.

Alterations in Patients With First-Episode Depression in the Eyes-Open and Eyes-Closed Conditions: A Resting-State EEG Study.

Altered resting-state EEG activity has been repeatedly reported in major depressive disorder (MDD), but no robust biomarkers have been identified until now. The poor consistency of EEG alterations may be due to inconsistent resting conditions; that is, the eyes-open (EO) and eyes-closed (EC) conditions. Here, we explored the effect of the EO and EC conditions on EEG biomarkers for discriminating MDD subjects and healthy control (HC) subjects. EEG data were recorded from 30 first-episode MDD and 26 HC subjects during an 8-min resting-state session. The features were extracted using spectral power, Lempel-Ziv complexity, and detrended fluctuation analysis. Significant features were further selected via the sequential backward feature selection algorithm. Support vector machine (SVM), logistic regression, and linear discriminate analysis were used to determine a better resting condition to provide more reliable estimates for identifying MDD. Compared with the HC group, we found that the MDD group exhibited widespread increased ß and γ powers ( ) in both conditions. In the EO condition, the MDD group showed increased complexity and scaling exponents in the α band relative to HC subjects ( ). The best classification performance of the combined feature sets was found in the EO condition, with the leave-one-out classification accuracy of 89.29%, sensitivity of 90.00%, and specificity of 88.46% using SVM with the linear kernel classifier when the threshold was set to 0.7, followed by the ß and γ spectral features with an average accuracy of 83.93%. Overall, EO and EC conditions indeed affected the between-group variance, and the EO condition is suggested as the more separable resting condition to identify depression. Specially, the ß and γ powers are suggested as potential biomarkers for first-episode MDD.

Abnormal brain activity in fronto-central regions in mental disorders with suicide: An EEG Study.

Suicide is a global health problem, and early and accurate identification of suicide attempt individuals has very important clinical significance. Thus the exploration of neurobiological mechanisms underlying suicidal behavior is crucial for systematically preventing suicide. However, the neurophysiological biomarkers for identifying affective disorders with suicidal attempt are remain unknown. Here, we recruited 28 patients with mental disorders from Tianjin Anding Hospital, and the subjects were divided into suicide attempt group (SA=14) and non suicide attempt group (NSA=14) according to whether they had attempted suicide. We also recruited 14 healthy subjects matched with age and sex ratio as healthy control group (HC=14). By recording the electroencephalogram(EEG) data of 60 electrodes in resting state for eight minutes (four minutes with open eyes and four minutes with close eyes), the absolute power of five frequency bands( delta(0.5-4Hz), theta(4-8Hz), alpha(8-13Hz), beta (13-30Hz), gamma(30-65Hz)) were analyzed to explore the changes of brain rhythm. And then the Modulation index (MI) was calculated to quantify the intensity of phase amplitude coupling (PAC) between different frequency bands in different brain regions, so as to observe the mechanism of neuronal synchronization in different frequency bands. We found that the absolute power of SA group was significantly higher than NSA group and HC group in delta (P<0.05), beta (P<0.05) and gamma (P<0.05) bands. The PAC strength between beta and gamma was calculated and it showed that the PAC strength of SA group was significantly weaker than NSA group in fronto-central regions, indicating that decreased synchronization between neurons could bring about brain function impairment. These findings suggest that the brain electrical activity in the fronto-central regions of the SA group may be damaged, which may lead to an increased suicidal risk in mental disoders. The EEG activity in delta, beta, gamma band and PAC in fronto-central regions may be used as a potential clinical biomarker for preventing suicide.