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INTRODUCTION: Transcranial alternating current stimulation (tACS) at 5-Hz to the right hemisphere can effectively alleviate anxiety symptoms. This study aimed to explore the neural mechanisms that drive the therapeutic benefits. METHODS: We collected electroencephalography (EEG) data from 24 participants with anxiety disorders before and after a tACS treatment session. tACS was applied over the right hemisphere, with 1.0 mA at F4, 1.0 mA at P4, and 2.0 mA at T8 (10-10 EEG convention). With eLORETA, we transformed the scalp signals into the current source density in the cortex. We then assessed the differences between post- and pre-treatment brain maps across multiple spectra (delta to low gamma) with non-parametric statistics. RESULTS: We observed a trend of heightened power in alpha and reduced power in mid-to-high beta and low gamma, in accord with the EEG markers of anxiolytic effects reported in previous studies. Additionally, we observed a consistent trend of de-synchronization at the stimulating sites across spectra. CONCLUSION: tACS 5-Hz over the right hemisphere demonstrated EEG markers of anxiety reduction. The after-effects of tACS on the brain are intricate and cannot be explained solely by the widely circulated entrainment theory. Rather, our results support the involvement of plasticity mechanisms in the offline effects of tACS.

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INTRODUCTION: One of the most common applications of transcranial electrical stimulation (tES) at low current intensity is to induce a relaxed state or reduce anxiety. With technical advancement, different waveforms, montages, and parameters can be incorporated into the treatment regimen. We developed a novel protocol to treat individuals with anxiety disorders by transcranial alternating current stimulation (tACS). METHODS: A total of 27 individuals with anxiety disorders underwent tACS treatment for 12 sessions, with each session lasting 25 min. tACS at 5 Hz was applied to F4 (1.0 mA), P4 (1.0 mA), and T8 (2.0 mA) EEG lead positions (tripod), with sinewave oscillation between T8 and F4/P4. We evaluated the primary and secondary outcomes using the Beck Anxiety Inventory (BAI) and neuropsychological assessments. RESULTS: Of the 27 patients, 19 (70.4 %) experienced a reduction in symptom severity >50 %, with an average reduction of BAI 58.5 %. All reported side effects were mild, with itching or tingling being the most common complaint. No significant differences were noted in attention, linguistic working memory, visuospatial working memory, or long-term memory in neuropsychological assessments. CONCLUSION: The results suggest the potential of this novel tripod tACS design as a rapid anxiety alleviator and the importance of a clinical trial to verify its efficacy.

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INTRODUCTION: Despite its complexity, deciphering nodal interaction is imperative to understanding a neural network. Network interaction is an even more complicated topic that must be addressed. This study aimed to examine the relationship between the brain waves of two canonical brain structures, i.e., the frontoparietal and limbic compartments, during a resting state. METHODS: Electroencephalography (EEG) of 51 subjects in eye-closed condition was analyzed, and the eLORETA method was applied to convert the signals from the scalp to the brain. By way of community detection, representative neural nodes and the associated mean activities were retrieved. Total and lagged coherences were computed to indicate functional connectivity between those neural nodes. Two global network properties were elucidated based on the connectivity measures, i.e., global efficiency and mean functional connectivity strength. The temporal correlation of the global network indices between the two studied networks was explored. RESULTS: It was found that there was a significant trend of positive correlation across the four metrics (lagged vs. total coherence x global efficiency vs. average connectivity). In other words, when the neural interaction in the FP network was stronger, so did that in the limbic network, and vice versa. Notably, the above interaction was not spectrally specific and only existed at a finer temporal scale (under hundreds of milliseconds level). CONCLUSION: The concordant change in network properties indicates an intricate balance between FP and LM compartments. Possible mechanisms and implications for the findings are discussed.

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OBJECTIVE: Alzheimer's disease (AD) has prolonged asymptomatic or mild symptomatic periods. Given that there is an increase in treatment options and that early intervention could modify the disease course, it is desirable to devise biological indices that may differentiate AD and nonAD at mild cognitive impairment (MCI) stage. METHODS: Based on two well-acknowledged observations of background slowing (attenuation in alpha power and enhancement in theta and delta powers) and early involvement of posterior cingulate cortex (PCC, a neural hub of default-mode network), this study devised novel neural markers, namely, spectral ratios of alpha1 to delta and alpha1 to theta in the PCC. RESULTS: We analysed 46 MCI patients, with 22 ADMCI and 24 nonADMCI who were matched in age, education, and global cognitive capability. Concordant with the prediction, the regional spectral ratios were lower in the ADMCI group, suggesting its clinical application potential. CONCLUSION: Previous research has verified that neural markers derived from clinical electroencephalography may be informative in differentiating AD from other neurological conditions. We believe that the spectral ratios in the neural hubs that show early pathological changes can enrich the instrumental assessment of brain dysfunctions at the MCI (or pre-clinical) stage.

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To investigate the properties of a large-scale brain network, it is a common practice to reduce the dimension of resting state functional magnetic resonance imaging (rs-fMRI) data to tens to hundreds of nodes. This study presents an analytic streamline that incorporates modular analysis and similarity measurements (MOSI) to fulfill functional parcellation (FP) of the cortex. MOSI is carried out by iteratively dividing a module into sub-modules (via the Louvain community detection method) and unifying similar neighboring sub-modules into a new module (adjacent sub-modules with a similarity index <0.05) until the brain modular structures of successive runs become constant. By adjusting the gamma value, a parameter in the Louvain algorithm, MOSI may segment the cortex with different resolutions. rs-fMRI scans of 33 healthy subjects were selected from the dataset of the Rockland sample. MOSI was applied to the rs-fMRI data after standardized pre-processing steps. The results indicate that the parcellated modules by MOSI are more homogeneous in content. After reducing the grouped voxels to representative neural nodes, the network structures were explored. The resultant network components were comparable with previous reports. The validity of MOSI in achieving data reduction has been confirmed. MOSI may provide a novel starting point for further investigation of the network properties of rs-fMRI data. Potential applications of MOSI are discussed.

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Research into cognitive emotion regulation (ER) extends our understanding of human cognition, which is capable of processing objective information and is crucial in maintaining subjective/internal homeostasis. Among various ER strategies, the alleviation of negative emotion via reappraisal is of particular importance for adaptation and psychological well-being. Although still debated, previous neuroimaging studies tend to infer that the reappraisal ER is mediated by the capability of working memory (WM), which has not been examined empirically. This meta-analytical study of published neuroimaging literature used activation likelihood estimation (ALE) to compare the neural circuits that regulate negative emotion (reappraisal tasks; 46 studies/1254 subjects) and execute WM (2-back tasks; 50 studies/1312 subjects), with special emphasis on the prefrontal cortex (PFC). Taking the canonical WM network as a reference, ALE results revealed that the dorsal midline PFC was partly shared by both ER and WM, whereas ER-specific PFC structures were delineated in the inferior, middle, and superior frontal cortices, as well as in the posterior brain regions. The peak coordinates of ER in the middle frontal cortex were dorsal to those of WM by 15.1 mm (left) and 21.6 mm (right). The results support specialized emotion-related neural substrates in the PFC, negating the assumption that reappraisal ER and WM rely on the same neural resources. The holistic picture of "emotional brain" may need to incorporate the emotion-related PFC circuit, together with subcortical and limbic emotion centers.

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Medial orbitofrontal cortex (mOFC) abnormalities have been observed in various anxiety disorders. However, the relationship between mOFC activity and anxiety among the healthy population has not been fully examined. Here, we conducted a resting state functional magnetic resonance imaging (R-fMRI) study with 56 healthy male adults from the Nathan Kline Institute/Rockland Sample (NKI-RS) to examine the relationship between the fractional amplitude of low-frequency fluctuation (fALFF) signals and trait anxiety across the whole brain. A Louvain method for module detection based on graph theory was further employed in the automated functional subdivision to explore subregional correlates of trait anxiety. The results showed that trait anxiety was related to fALFF in the mOFC. Additionally, the resting-state functional connectivity (RSFC) between the right subregions of the mOFC and the precuneus was correlated with trait anxiety. These findings provided evidence about the involvement of the mOFC in anxiety processing among the healthy population.

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Multimodal neuroimaging research has become increasingly popular, and structure-function correspondence is tacitly assumed. Researchers have not yet adequately assessed whether the functional connectivity (FC) and structural connectivity (SC) of large-scale cortical networks are in agreement. Structural magnetic resonance imaging (sMRI), resting-state functional MRI (rfMRI), and diffusion-weighted imaging (DWI) data sets from 36 healthy subjects (age 27.4) were selected from a Rockland sample (Enhanced Nathan Kline Institute). The cerebral cortex was parcellated into 62 regions according to the Desikan-Killiany atlas for FC and SC analyses. Thresholded correlations in rfMRI and tractography derived from DWI were used to construct FC and SC maps, respectively. A community detection algorithm was applied to reveal the underlying organization, and modular consistency was quantified to bridge cross-modal comparisons. The distributions of correlation coefficients in FC and SC maps were significantly different. Approximately one-fourth of the connections in the SC map were located at a correlation level below 0.2 (df 253). The index of modular consistency in the within-modality interindividual condition (either FC or SC) was considerably greater than that in the between-modality intraindividual analog. In addition, the SC-FC differential map (SC connections with lower correlations) revealed reliable modular structures. Based on these results, the hypothesized FC-SC agreement is partially valid. Contingent on extant neuroimaging tools and analytical conventions, the neural informatics of FC and SC should be regarded as complementary rather than concordant. Furthermore, the results verify the physiological significance of moderately (or mildly) correlated brain signals in rfMRI, which are often discarded by stringent thresholding.

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The default-mode network (DMN) has been reported to comprise a set of inter-connected transmodal cortical areas, including the posterior cingulate cortex (PCC), medial prefrontal cortex, posterior inferior parietal lobule, lateral temporal region and others. However, the subcortical constituents of the DMN are still not clear. This study aimed to examine whether the correlation maps derived from subcortical structures may also account for neural pattern of the DMN. Structural magnetic resonance imaging (MRI) and resting-state functional MRI scans of 36 subjects were selected from the Rockland sample (Nathan Kline Institute). The hippocampus and thalamus were chosen as subcortical regions of interest (ROIs). Each ROI was partitioned into composite modules which in turn provided simplified and representative dynamics of blood-oxygen-level-dependent (BOLD) signals. PCC-seeded and ROI-based correlation maps were compared by conjunction analyses and paired t-tests (corrected P < 0.05). Our results unveiled that the hippocampus-, thalamus- and PCC-centred correlation patterns actually overlapped to a substantial degree. Integrating the signals in the thalamus and hippocampus altogether fully explained the PCC-seeded DMN. Supplementary analyses based on the BOLD dynamics in several subcortical nuclei (caudate, putamen and globus pallidus) were dissimilar to the DMN. The DMN derived from the ROI/seed-based approach may represent combined limbic and region-specific informatics (and their closely interacting neural substrates). The possible causes for previous methods of task-induced deactivation and seed-based correlation that failed to depict the holistic limbic picture are discussed. The neocortical manifestation of DMN may reflect the limbic information in the transmodal brain regions.

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With the advancement in MRI, functional parcellation (FP) of brain structure(s) has become an important topic. However, the large number of voxels is a major obstacle. A-priori partitioning of the brain into several regions of interest (ROIs) is the main data-reduction strategy to simplify brain informatics. This study aims to examine the validity of ROI-based approach to FP by exploring the concordance of the relative distance structures between voxel-wise (raw data) and atlas-informed analyses. Structural and resting state functional MRI (rfMRI) scans of 26 right-handed healthy individuals were selected from the Rockland dataset. Four target regions were included in the analyses, that is, left and right thalamus and amygdala. For each voxel in the target region, four classes of correlation maps (sampling strategies) were constructed from the rfMRI: whole brain, cortex, 150 ROIs, and 70 ROIs (ROIs are informed by anatomical atlases). The relative distance metric between two different voxels was defined as the mean absolute difference of their associated correlation maps. Considering all the possible pairs of voxels in a target region, the relative distance structure was derived and stored in a matrix (distance map). For every target region, the distance maps were very similar across the four classes of sampling strategies, with the grand mean correlation coefficient reaching 0.95. The results confirm the validity of previous ROI-based analyses of rfMRI data in FP. The rationale and limitation are discussed and an analytic strategy of whole-brain FP is proposed.

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BACKGROUND: Previous empirical research has treated regional neural responses and network architecture separately. However, anecdotal reports have suggested a close relationship between the two. This study aims to investigate the influence of structural connectivity on regional spontaneous activities. METHODS: Datasets of structural magnetic resonance imaging (sMRI), resting state functional MRI (rs-fMRI) and diffusion weighted imaging (DWI) of 36 right-handed healthy subjects (average age 27.4) were selected from the NKI Rockland sample. In the sMRI data, the cerebral cortex was parcellated into 70 regions of interest (ROIs) according to an anatomical atlas. Two indices were calculated from rs-fMRI for each ROI: the regional homogeneity (ReHo) and the amplitude of low frequency fluctuation (ALFF). Diffusion tensor imaging was computed from DWI and was converted to tractography. Four graph indices of structural connectivity were retrieved from the tractography results and the 70 ROIs, as follows: nodal degree, clustering coefficient, local efficiency and betweenness centrality. RESULTS: ReHo values were significantly correlated with all 4 graph features, whereas ALFF values were significantly correlated with nodal degrees and clustering coefficients. Both ReHo and ALFF tended to increase with segregation (clustering coefficient and local efficiency) and decrease with centrality (nodal degree and betweenness centrality). DISCUSSION: Though derived from local spontaneous activities, ReHo and ALFF may reflect the network properties of the underlying anatomical architecture. The results supported the hypothesis that the properties of the network structure may shape the regional neural response profiles.

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Only half of the geriatric patients with major depressive disorder (MDD) can reach full remission after treatment of half a year. This study was designed to examine the neural responses in the partial responders of late-onset MDD. We used 3-Tesla functional magnetic resonance imaging to assess the patterns of cerebral activation/deactivation in the performance of a one-back version of the n-back working memory task. We recruited 14 major depressive patients who reached partial remission after at least half a year of pharmacological intervention, compared with 14 non-depressive controls. There were no significant between-group differences in the demographical profiles and working memory performance, which was true for both accuracy and reaction time. Brain masks encompassing the neural responses of activation/deactivation were constructed from the non-depressive controls. The depressive group shows enhanced activities at left middle frontal and left parietal regions, and reduced deactivation at several temporal regions and left amygdala within the masks. Besides, the depressive group activates extra neural nodes at middle frontal and middle temporal regions outside the masks. The neural responses in the left amygdala are significantly correlated with the severity of depression and comorbid anxiety. The loss of deactivation in the left amygdala and the temporal areas in cognitive endeavor may be related to the refractoriness to treatment.

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The epsilon4 allele of the Apolipoprotein E (ApoE) gene has been linked to various neurological conditions and the aging process in the elderly. However, evidence has suggested that the influence of ApoE epsilon4 may commence in early life. This study examined the modulatory effects of ApoE epsilon4 on regional neural activity as well as inter-regional neural interactions in a young population aged 19-21. Blood samples and resting state eyes-closed EEG signals were collected from 265 healthy females, and stratified into two groups: epsilon4 carriers and non-carriers. The values of the log-transformed mean power of 18 electrodes and the mutual information of 20 channel pairs across delta, theta, alpha and beta frequencies were analyzed. Our connectivity analysis was based on information theory, which combined Morlet wavelet transform and mutual information calculation. Between-group statistics were performed by independent t-test. We notice a consistent trend across the brain, in which ApoE epsilon4 carriers possess lower regional power at the alpha band. The epsilon4 allele is also associated with lower regional power at the theta frequency in the left frontal and posterior brain regions. Functional connectivity analyses reveal a right-lateralized network that differentiates epsilon4 carriers and non-carriers, with lower connectivity strengths for the former. Our tonic EEG analyses complement those of previous reports in that the ApoE epsilon4 allele has a negative impact on regional neural synchronization and inter-regional neural interaction.

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The polymorphism of variable number of tandem repeat (VNTR) in dopamine receptor D4 (DRD4) gene exon III has been linked to various neuro-psychiatric conditions with disinhibition/impulsivity as one of the core features. This study examined the modulatory effects of long-allele variant of DRD4 VNTR on the regional neural activity as well as inter-regional neural interactions in a young female population. Blood sample and resting state eyes-closed EEG signals were collected in 233 healthy females, stratified into two groups by polymerase chain reaction: long-allele carriers (>4- repeat) and non-carriers (<=4-repeat/<=4-repeat). The values of mean power of 18 electrodes and mutual information of 38 channel pairs across theta, alpha, and beta frequencies were analyzed. Our connectivity analysis was based on information theory, which combined Morlet wavelet transform and mutual information calculation. Between-group differences of regional power and connectivity strength were quantified by independent t-test, while between-group differences in global trends were examined by non-parametric analyses. We noticed that DRD4 VNTR long-allele was associated with decreased global connectivity strength (from non-parametric analysis), especially over bi-frontal, biparietal and right fronto-parietal and right fronto-temporal connections (from independent t-tests). The between-group differences in regional power were not robust. Our findings fit with the networks of response inhibition, providing evidence bridging DRD4 long-allele and disinhibition/impulsivity in neuropsychiatric disorders. We suggest future DRD4 studies of imaging genetics incorporate connectivity analysis to unveil its impact on cerebral network.

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BACKGROUND: The oddball paradigm is widely applied to the investigation of cognitive function in neuroscience and in neuropsychiatry. Whether cortical oscillation in the resting state can predict the elicited oddball event-related potential (ERP) is still not clear. This study explored the relationship between resting electroencephalography (EEG) and oddball ERPs. The regional powers of 18 electrodes across delta, theta, alpha and beta frequencies were correlated with the amplitude and latency of N1, P2, N2 and P3 components of oddball ERPs. A multivariate analysis based on partial least squares (PLS) was applied to further examine the spatial pattern revealed by multiple correlations. RESULTS: Higher synchronization in the resting state, especially at the alpha spectrum, is associated with higher neural responsiveness and faster neural propagation, as indicated by the higher amplitude change of N1/N2 and shorter latency of P2. None of the resting quantitative EEG indices predict P3 latency and amplitude. The PLS analysis confirms that the resting cortical dynamics which explains N1/N2 amplitude and P2 latency does not show regional specificity, indicating a global property of the brain. CONCLUSIONS: This study differs from previous approaches by relating dynamics in the resting state to neural responsiveness in the activation state. Our analyses suggest that the neural characteristics carried by resting brain dynamics modulate the earlier/automatic stage of target detection.

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Predicting treatment response in major depressive disorder (MDD) has been an important clinical issue given that the initial intent-to-treat response rate is only 50 to 60%. This study was designed to examine whether functional connectivity strengths of resting EEG could be potential biomarkers in predicting treatment response at 8 weeks of treatment. Resting state 3-min eyes-closed EEG activity was recorded at baseline and compared in 108 depressed patients. All patients were being treated with selective serotonin-reuptake inhibitors. Baseline coherence and power series correlation were compared between responders and non-responders evaluated at the 8th week by Hamilton Depression Rating Scale. Pearson correlation and receiver operating characteristic (ROC) analyses were applied to evaluate the performance of connectivity strengths in predicting/classifying treatment responses. The connectivity strengths of right fronto-temporal network at delta/theta frequencies differentiated responders and non-responders at the 8th week of treatment, such that the stronger the connectivity strengths, the poorer the treatment response. ROC analyses supported the value of these measures in classifying responders/non-responders. Our results suggest that fronto-temporal connectivity strengths could be potential biomarkers to differentiate responders and slow responders or non-responders in MDD.

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BACKGROUND: The serotonin transporter gene (5-HTT) is a key regulator of serotonergic neurotransmission and has been linked to various psychiatric disorders. Among the genetic variants, polymorphisms in the 5-HTT gene-linked polymorphic region (5-HTTLPR) and variable-number-of-tandem-repeat in the second intron (5-HTTVNTR) have functional consequences. However, their genetic impact on cortical oscillation remains unclear. This study examined the modulatory effects of 5-HTTLPR (L-allele carriers vs. non-carriers) and 5-HTTVNTR (10-repeat allele carriers vs. non-carriers) polymorphism on regional neural activity in a young female population. METHODS: Blood samples and resting state eyes-closed electroencephalography (EEG) signals were collected from 195 healthy women and stratified into 2 sets of comparisons of 2 groups each: L-allele carriers (N=91) vs. non-carriers for 5-HTTLPR and 10-repeat allele carriers (N=25) vs. non-carriers for 5-HTTVNTR. The mean power of 18 electrodes across theta, alpha, beta, gamma, gamma1, and gamma2 frequencies was analyzed. Between-group statistics were performed by an independent t-test, and global trends of regional power were quantified by non-parametric analyses. RESULTS: Among 5-HTTVNTR genotypes, 10-repeat allele carriers showed significantly low regional power at gamma frequencies across the brain. We noticed a consistent global trend that carriers with low transcription efficiency of 5-HTT possessed low regional powers, regardless of frequency bands. The non-parametric analyses confirmed this observation, with P values of 3.071×10-8 and 1.459×10-12 for 5-HTTLPR and 5-HTTVNTR, respectively. CONCLUSIONS AND LIMITATIONS: Our analyses showed that genotypes with low 5-HTT activity are associated with less local neural synchronization during relaxation. The implication with respect to genetic vulnerability of 5-HTT across a broad range of psychiatric disorders is discussed. Given the low frequency of 10-repeat allele of 5-HTTVNTR in our research sample, the possibility of false positive findings should also be considered.

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The catechol-O-methyl-transferase (COMT) gene has been linked to a wide spectrum of human phenotypes, including cognition, affective response, pain sensitivity, anxiety and psychosis. This study examined the modulatory effects of COMT Val158Met on neural interactions, indicated by connectivity strengths. Blood samples and resting state eyes-closed EEG signals were collected in 254 healthy young females. The COMT Val158Met polymorphism was decoded into 3 groups: Val/Val, Val/Met and Met/Met. The values of mutual information of 20 frontal-related channel pairs across delta, theta, alpha and beta frequencies were analyzed based on the time-frequency mutual information method. Our one-way ANOVA analyses revealed that the significant connection-frequency pairs were relatively left lateralized (P<0.01) and included F7-T3 and F7-C3 at delta frequency, and F3-F4, F7-T3, F7-C3, F7-P3, F3-C3, F3-F7 and F4-F8 at theta frequency. The F-test at F7-T3 and F7-C3 theta surpassed the statistical threshold of P<0.003 (after Bonferroni correction). For all the above connection-frequency pairs, there was a dose-dependent trend in the connectivity strengths of the alleles as follows: Val/Val>Val/Met>Met/Met. Our analyses complemented previous literature regarding neural modulation by the COMT Val158Met polymorphism. The implication to the pathogenesis in schizophrenia was also discussed. Further studies are needed to clarify whether there is gender difference on this gene-brain interaction.

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BACKGROUND: Diagnosis and treatment rely on symptom criteria in modern psychiatry. However, the cortical mechanisms of symptomatology in major depressive disorder (MDD) are still not clear. This study examined neural correlates of symptom clusters of MDD by electroencephalography (EEG). METHODS: Resting state eye-closed EEG signals were recorded in 196 depressive patients. Quantitative EEG (qEEG) of regional power, coherence and power series correlation across delta, theta, alpha and beta frequencies were used to correlate with overall depression severity evaluated by the Hamilton Depression Rating Scale (HDRS). Further, statistical comparisons between patients with high vs. low qEEG indices (median-split) were undertaken regarding symptom severity of core depression, sleep, activity, psychic anxiety, somatic anxiety, and delusion. RESULTS: None of the qEEG indices significantly correlated with overall depression severity or differentiated symptom severity of core depression, sleep, activity and psychic anxiety. A higher symptom severity of somatic anxiety was associated with higher regional power over widespread cortical regions and lower strengths at bi-temporal, temporo-parietal and fronto-parietal connections. A higher symptom severity of delusion was associated with higher regional power in the frontal and temporal regions, and lower strengths at inter-hemispheric (frontal, temporal and parietal) and fronto-temporo-parietal connections. LIMITATIONS: Our EEG recording with sampling rate of 128Hz and 20 electrodes may provide restricted spatial and temporal precision. CONCLUSIONS: Our results suggest that cortical mechanisms play important roles in the symptom manifestation of cognitive distortion (sub-score of delusion) and somatic anxiety in MDD. Our findings further imply that psychic anxiety and somatic anxiety are distinct entities.

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Late-onset major depression is thought to have a biological (vascular) basis, which could be a result of brain structure change. Vascular lesions can affect both the gray matter (GM) and white matter (WM), while most previous studies addressed WM abnormality. This study explored the disease- and symptom (history of suicide attempt) -related GM morphometry in elderly male patients with late-onset depression. A total of 70 patients with depression admitted to our geriatric psychiatric ward were investigated, and 26 age-matched males were recruited as controls. We used T1-weighted magnetic resonance imaging (MRI) to obtain cerebral structural information and adopted voxel-based morphometry (VBM) to investigate brain volume change related to disease (depression vs control) and symptom (depression with history of suicide attempt vs depression without history of suicide attempt). Late-onset depression was associated with smaller volumes in several regions of GM (insula and the posterior cingulate region) and WM (subcallosal cingulate cortex, floor of lateral ventricles, parahippocampal region, insula, and the cerebellum). Compared with nonsuicidal counterpart, suicidal depression was associated with decreased GM and WM volume in the frontal, parietal, and temporal regions, and the insula, lentiform nucleus, midbrain, and the cerebellum. Marked regional volume reduction was noticed at dorsal medial prefrontal cortex. Our results demonstrate that the development of suicidal behaviors in major depression is related to widespread but discrete volume reduction in several cortical and subcortical structures, fitting with the hypothesis that decreased cerebral volume in certain regions renders biological susceptibility to attempt suicide during depressive states.

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