Brain-wide changes in excitation-inhibition balance of major depressive disorder: a systematic review of topographic patterns of GABA- and glutamatergic alterations.

The excitation-inhibition (E/I) imbalance is an important molecular pathological feature of major depressive disorder (MDD) as altered GABA and glutamate levels have been found in multiple brain regions in patients. Healthy subjects show topographic organization of the E/I balance (EIB) across various brain regions. We here raise the question of whether such EIB topography is altered in MDD. Therefore, we systematically review the gene and protein expressions of inhibitory GABAergic and excitatory glutamatergic signaling-related molecules in postmortem MDD brain studies as proxies for EIB topography. Searches were conducted through PubMed and 45 research articles were finally included. We found: i) brain-wide GABA- and glutamatergic alterations; ii) attenuated GABAergic with enhanced glutamatergic signaling in the cortical-subcortical limbic system; iii) that GABAergic signaling is decreased in regions comprising the default mode network (DMN) while it is increased in lateral prefrontal cortex (LPFC). These together demonstrate abnormal GABA- and glutamatergic signaling-based EIB topographies in MDD. This enhances our pathophysiological understanding of MDD and carries important therapeutic implications for stimulation treatment.

From Molecular to Behavior: Higher Order Occipital Cortex in Major Depressive Disorder.

Medial prefrontal cortex (MPFC) and other regions like the occipital cortex (OC) exhibit abnormal neural activity in major depressive disorder (MDD). Their relationship to specific biochemical, psychophysical, and psychopathological changes remains unclear, though. For that purpose, we focus on a particular subregion in OC, namely middle temporal (MT) visual area that is known to mediate the perception of visual motion. Using high-field 7 T magnetic resonance imaging (MRI), including resting state functional MRI and proton magnetic resonance spectroscopy, the amplitude of low-frequency fluctuations (ALFF) of the blood oxygen level-dependent signal in MT, MT-seeded functional connectivity (FC), and gamma-aminobutyric acid (GABA) in MT were investigated. Applying the vision motion psychophysical task, the motion suppression index of subjects was also examined. We demonstrate significantly elevated neural variability (as measured by ALFF) in MT together with decreases in both MT GABA and motion suppression in our MDD sample. Unlike in healthy subjects, MT neural variability no longer modulates the relationship of MT GABA and motion suppression in MDD. MT also exhibits reduction in global inter-regional FC to MPFC in MDD. Finally, elevated MT ALFF relates to specifically retardation in behavior as measured by the Hamilton subscore. Together, MT provides a strong candidate for biomarker in MDD.

Reduction of higher-order occipital GABA and impaired visual perception in acute major depressive disorder.

Major depressive disorder (MDD) is a complex state-dependent psychiatric illness for which biomarkers linking psychophysical, biochemical, and psychopathological changes remain yet elusive, though. Earlier studies demonstrate reduced GABA in lower-order occipital cortex in acute MDD leaving open its validity and significance for higher-order visual perception, though. The goal of our study is to fill that gap by combining psychophysical investigation of visual perception with measurement of GABA concentration in middle temporal visual area (hMT+) in acute depressed MDD. Psychophysically, we observe a highly specific deficit in visual surround motion suppression in a large sample of acute MDD subjects which, importantly, correlates with symptom severity. Both visual deficit and its relation to symptom severity are replicated in the smaller MDD sample that received MRS. Using high-field 7T proton Magnetic resonance spectroscopy (1H-MRS), acute MDD subjects exhibit decreased GABA concentration in visual MT+ which, unlike in healthy subjects, no longer correlates with their visual motion performance, i.e., impaired SI. In sum, our combined psychophysical-biochemical study demonstrates an important role of reduced occipital GABA for altered visual perception and psychopathological symptoms in acute MDD. Bridging the gap from the biochemical level of occipital GABA over visual-perceptual changes to psychopathological symptoms, our findings point to the importance of the occipital cortex in acute depressed MDD including its role as candidate biomarker.

Childhood trauma mediates repetitive transcranial magnetic stimulation efficacy in major depressive disorder.

Childhood trauma is one of the most prominent risk factors in developing major depressive disorder (MDD) and may lead to unfavorable outcomes of pharmacotherapy and psychotherapy in MDD. While how it modulates the treatment outcome of the repetitive transcranial magnetic stimulation (rTMS) and how sex difference may play a role in mediating this relationship remain unknown. To evaluate this question, 51 (37 women) MDD patients were treated with 10 Hz rTMS to the left dorsolateral prefrontal cortex (lDLPFC). The experience of childhood trauma was quantified by the Childhood Traumatic Questionnaire (CTQ). The depressive severity was assessed by Hamilton Depression Scale (HAMD) and Beck Depression Inventory (BDI) as the primary and secondary assessments. Beck Hopelessness Scale (BHS) and Hamilton Anxiety Scale (HAMA) were also assessed for further confirmation. Thirty-six (70.6%) participants showed a response including 17 (33.3%) achieving remission to the rTMS treatment. The alleviation of depressive symptoms was negatively correlated with the CTQ scores, specifically in women but not men, in subjective BDI and BHS, but not objective HAMD or HAMA. We demonstrate that childhood trauma negatively affects the subjective perception of rTMS-lDLPFC treatment outcomes in female MDD patients. This highlights the importance of measuring childhood trauma-related symptoms in routine clinical rTMS treatment, as they may impact perceived efficacy.

Individualized diagnosis of major depressive disorder via multivariate pattern analysis of thalamic sMRI features.

BACKGROUND: Magnetic resonance imaging (MRI) studies have found thalamic abnormalities in major depressive disorder (MDD). Although there are significant differences in the structure and function of the thalamus between MDD patients and healthy controls (HCs) at the group level, it is not clear whether the structural and functional features of the thalamus are suitable for use as diagnostic prediction aids at the individual level. Here, we were to test the predictive value of gray matter density (GMD), gray matter volume (GMV), amplitude of low-frequency fluctuations (ALFF), and fractional amplitude of low-frequency fluctuations (fALFF) in the thalamus using multivariate pattern analysis (MVPA). METHODS: Seventy-four MDD patients and 44 HC subjects were recruited. The Gaussian process classifier (GPC) was trained to separate MDD patients from HCs, Gaussian process regression (GPR) was trained to predict depression scores, and Multiple Kernel Learning (MKL) was applied to explore the contribution of each subregion of the thalamus. RESULTS: The primary findings were as follows: [1] The balanced accuracy of the GPC trained with thalamic GMD was 96.59% (P < 0.001). The accuracy of the GPC trained with thalamic GMV was 93.18% (P < 0.001). The correlation between Hamilton Depression Scale (HAMD) score targets and predictions in the GPR trained with GMD was 0.90 (P < 0.001, r2 = 0.82), and in the GPR trained with GMV, the correlation between HAMD score targets and predictions was 0.89 (P < 0.001, r2 = 0.79). [2] The models trained with ALFF and fALFF in the thalamus failed to discriminate MDD patients from HC participants. [3] The MKL model showed that the left lateral prefrontal thalamus, the right caudal temporal thalamus, and the right sensory thalamus contribute more to the diagnostic classification. CONCLUSIONS: The results suggested that GMD and GMV, but not functional indicators of the thalamus, have good potential for the individualized diagnosis of MDD. Furthermore, the thalamus shows the heterogeneity in the structural features of thalamic subregions for predicting MDD. To our knowledge, this is the first study to focus on the thalamus for the prediction of MDD using machine learning methods at the individual level.

Altered fecal microbiota composition in patients with major depressive disorder.

Studies using animal models have shown that depression affects the stability of the microbiota, but the actual structure and composition in patients with major depressive disorder (MDD) are not well understood. Here, we analyzed fecal samples from 46 patients with depression (29 active-MDD and 17 responded-MDD) and 30 healthy controls (HCs). High-throughput pyrosequencing showed that, according to the Shannon index, increased fecal bacterial α-diversity was found in the active-MDD (A-MDD) vs. the HC group but not in the responded-MDD (R-MDD) vs. the HC group. Bacteroidetes, Proteobacteria, and Actinobacteria strongly increased in level, whereas that of Firmicutes was significantly reduced in the A-MDD and R-MDD groups compared with the HC group. Despite profound interindividual variability, levels of several predominant genera were significantly different between the MDD and HC groups. Most notably, the MDD groups had increased levels of Enterobacteriaceae and Alistipes but reduced levels of Faecalibacterium. A negative correlation was observed between Faecalibacterium and the severity of depressive symptoms. These findings enable a better understanding of changes in the fecal microbiota composition in such patients, showing either a predominance of some potentially harmful bacterial groups or a reduction in beneficial bacterial genera. Further studies are warranted to elucidate the temporal and causal relationships between gut microbiota and depression and to evaluate the suitability of the microbiome as a biomarker.

The association between gray matter volume in the hippocampal subfield and antidepressant efficacy mediated by abnormal dynamic functional connectivity.

An abnormality of structures and functions in the hippocampus may have a key role in the pathophysiology of major depressive disorder (MDD). However, it is unclear whether structure factors of the hippocampus effectively impact antidepressant responses by hippocampal functional activity in MDD patients. We collected longitudinal data from 36 MDD patients before and after a 3-month course of antidepressant pharmacotherapy. Additionally, we obtained baseline data from 43 healthy controls matched for sex and age. Using resting-state functional magnetic resonance imaging (rs-fMRI), we estimated the dynamic functional connectivity (dFC) of the hippocampal subregions using a sliding-window method. The gray matter volume was calculated using voxel-based morphometry (VBM). The results indicated that patients with MDD exhibited significantly lower dFC of the left rostral hippocampus (rHipp.L) with the right precentral gyrus, left superior temporal gyrus and left postcentral gyrus compared to healthy controls at baseline. In MDD patients, the dFC of the rHipp.L with right precentral gyrus at baseline was correlated with both the rHipp.L volume and HAMD remission rate, and also mediated the effects of the rHipp.L volume on antidepressant performance. Our findings suggested that the interaction between hippocampal structure and functional activity might affect antidepressant performance, which provided a novel insight into the hippocampus-related neurobiological mechanism of MDD.

Treatment Response Prediction for Major Depressive Disorder Patients via Multivariate Pattern Analysis of Thalamic Features.

Antidepressant treatment, as an important method in clinical practice, is not suitable for all major depressive disorder (MDD) patients. Although magnetic resonance imaging (MRI) studies have found thalamic abnormalities in MDD patients, it is not clear whether the features of the thalamus are suitable to serve as predictive aids for treatment responses at the individual level. Here, we tested the predictive value of gray matter density (GMD), gray matter volume (GMV), amplitude of low-frequency fluctuations (ALFF), and fractional ALFF (fALFF) of the thalamus using multivariate pattern analysis (MVPA). A total of 74 MDD patients and 44 healthy control (HC) subjects were recruited. Thirty-nine MDD patients and 35 HC subjects underwent scanning twice. Between the two scanning sessions, patients in the MDD group received selective serotonin reuptake inhibitor (SSRI) treatment for 3-month, and HC group did not receive any treatment. Gaussian process regression (GPR) was trained to predict the percentage decrease in the Hamilton Depression Scale (HAMD) score after treatment. The percentage decrease in HAMD score after SSRI treatment was predicted by building GPRs trained with baseline thalamic data. The results showed significant correlations between the true percentage of HAMD score decreases and predictions (p < 0.01, r 2 = 0.11) in GPRs trained with GMD. We did not find significant correlations between the true percentage of HAMD score decreases and predictions in GMV (p = 0.16, r 2 = 0.00), ALFF (p = 0.125, r 2 = 0.00), and fALFF (p = 0.485, r 2 = 0.10). Our results suggest that GMD of the thalamus has good potential as an aid in individualized treatment response predictions of MDD patients.

Charting the dorsal-medial functional gradient of the default mode network in major depressive disorder.

Major depressive disorder (MDD) is a common and disabling psychiatric condition associated with aberrant functional activity of the default mode network (DMN). However, it is unclear how the DMN dysfunction in MDD patients is characterized by functional connectivity diversity or gradient and whether antidepressant therapy causes the abnormal functional gradient of the DMN to change toward normalization. In current work, we estimated the functional gradient of the DMN derived from resting state functional magnetic resonance imaging in MDD patients (n = 70) and matching healthy controls (n = 43) and identified MDD-related functional connectivity diversity of the DMN. The longitudinal changes of the DMN functional gradient in 36 MDD patients were assessed before and after 12-week antidepressant treatment. Compared to the healthy controls, the functional gradient of the DMN exhibited relatively relative compression along the dorsal-medial axis in MDD patients at baseline and antidepressant treatment could normalize these DMN gradient abnormalities. A regularized least-squares regression model based on DMN gradient features at baseline significantly predicted the change of Hamilton Depression Rating (HAMD) Scale scores after antidepressant treatment. The medial prefrontal cortex gradient had a more contribution to prediction of antidepressant efficacy. Our findings provided a novel insight into the neurobiological mechanism underlying MDD from the perspective of the DMN functional gradient.

Decreased modular segregation of the frontal-parietal network in major depressive disorder.

Major depressive disorder (MDD) is a common psychiatric condition associated with aberrant large-scale distributed brain networks. However, it is unclear how the network dysfunction in MDD patients is characterized by imbalance or derangement of network modular segregation. Fifty-one MDD patients and forty-three matched healthy controls (HC) were recruited in the present study. We analyzed intrinsic brain activity derived from resting-state functional magnetic resonance imaging (R-fMRI) and then examined brain network segregation by computing the participation coefficient (PC). Further intra- and inter-modular connections analysis were preformed to explain atypical PC. Besides, we explored the potential relationship between the above graph theory measures and symptom severity in MDD. Lower modular segregation of the frontal-parietal network (FPN) was found in MDD compared with the HC group. The MDD group exhibited increased inter-module connections between the FPN and cingulo-opercular network (CON), between the FPN and cerebellum (Cere), between the CON and Cere. At the nodal level, the PC of the anterior prefrontal cortex, anterior cingulate cortex, inferior parietal lobule (IPL), and intraparietal sulcus showed larger in MDD. Additionally, the inter-module connections between the FPN and CON and the PC values of the IPL were negatively correlated with depression symptom in the MDD group. These findings might give evidence about abnormal FPN in MDD from the perspective of modular segregation in brain networks.

Rapid Eye Movement Sleep Deprivation Combined With Fluoxetine Protects Against Depression-Induced Damage and Apoptosis in Rat Hippocampi via A1 Adenosine Receptor.

Background: Rapid eye movement sleep deprivation (REMSD) and fluoxetine affect depression, yet the detailed molecular mechanisms were not clear. Methods: Rat depression chronic unpredictable stress was constructed, and the body weight of rats was measured. The efficacy of REMSD and fluoxetine on the pleasure experience, exploration, and cognition of rats with depression was determined by the Sucrose preference test, the open field test, and Morris water task, respectively. The effects of REMSD and fluoxetine on depression-induced damage and apoptosis in rat hippocampi were detected using hematoxylin-eosin staining and terminal transferase-mediated biotin 2'-deoxyuridine, 5'-triphosphate nick end labeling. A1 adenosine receptor content was measured by immunohistochemistry. Relative expressions of the A1 adenosine receptor, proteins related to apoptosis (B Bcl-2-associated X protein; B-cell lymphoma 2), phosphoinositide 3-kinase, P38 mitogen-activated protein kinase, cFos, and adenosine deaminase RNA specific two were quantified by quantitative real-time polymerase chain reaction and Western blot as needed. Results: Depression decreased rat weight. REMSD combined with fluoxetine increased body weight, prompted rat behavior, alleviated depression-induced damage, attenuated apoptosis, and promoted A1 adenosine receptor level in rat hippocampi. Furthermore, the combined therapy upregulated expressions of A1 adenosine receptor, B-cell lymphoma 2, and phosphoinositide 3-kinase but downregulated those of B-cell lymphoma 2-associated X protein, P38 mitogen-activated protein kinase, cFos, and adenosine deaminase RNA specific 2 in the hippocampi of rats with depression. Conclusion:REMSD combined with fluoxetine protected rats against depression-induced damage and apoptosis in the hippocampus via the A1 adenosine receptor, providing a possible treatment strategy for depression.

Aberrant state-related dynamic amplitude of low-frequency fluctuations of the emotion network in major depressive disorder.

Major depressive disorder (MDD) is a highly prevalent mental disorder that is typically characterized by pervasive and persistent low mood. This durable emotional disturbance may represent a key aspect of the neuropathology of MDD, typified by the wide-ranging distribution of brain alterations involved in emotion processing. However, little is known about whether these alterations are represented as the state properties of dynamic amplitude of low-frequency fluctuation (dALFF) variability in the emotion network. To address this question, we investigated the time-varying intrinsic brain activity derived from resting-state functional magnetic resonance imaging (R-fMRI). Data were obtained from 50 MDD patients and 37 sex- and age-matched healthy controls; a sliding-window method was used to assess dALFF in the emotion network, and two reoccurring dALFF states throughout the entire R-fMRI scan were then identified using a k-means clustering method. The results showed that MDD patients had a significant decrease in dALFF variability in the emotion network and its three modules located in the lateral paralimbic, media posterior, and visual association regions. Altered state-wise dALFF was also observed in MDD patients. Specifically, we found that these altered dALFF measurements in the emotion network were related to scores on the Hamilton Rating Scale for Depression (HAMD) among patients with MDD. The detection and estimation of these temporal dynamic alterations could advance our knowledge about the brain mechanisms underlying emotional dysfunction in MDD.

Time is of essence - Abnormal time perspectives mediate the impact of childhood trauma on depression severity.

BACKGROUND: Major depressive disorder (MDD) is a multifaceted mental disorder where participants, in addition to various symptoms, often suffer from increased focus on past time perspective and higher incidence of childhood trauma. Whether the abnormal time perspective is a result of the depressive symptoms or, alternatively, mediates between childhood trauma and depression remains unclear. AIMS: To examine the triangular relationship between early life trauma, time perspective, and depressive symptoms. METHOD: We investigated a large-scale MDD sample (n = 93) and healthy subject sample (n = 69) with Beck depression inventory-II (BDI-II), Beck hopelessness scale (BHS), childhood traumatic questionnaire-Short Form (CTQ-SF), and the Zimbardo time perspective inventory (ZTPI). RESULTS: The MDD patients reported more childhood trauma experiences, and were featured by abnormal time perspectives on past and future when compared to healthy control. By applying two alternative mediation models, we observed that the time perspective acted as a mediator between childhood trauma and depressive symptom severity, rather than as a consequence of depressive symptom. Furthermore, this abnormal time perspective was a risk factor to MDD, as the childhood trauma only mediated the time perspective in MDD. Finally, we showed that time perspective was a long-term personal trait and unchanged after the remission of depression symptoms under five-day transcranial magnetic stimulation. CONCLUSIONS: Abnormal time perspective mediates the impact of early childhood trauma on depressive symptomatology. Besides better understanding of the temporal basis of depressive symptoms, we highlight the importance of preventive time perspective therapy in subjects with childhood trauma.

Effective Connectivity of Right Amygdala Subregions Predicts Symptom Improvement Following 12-Week Pharmacological Therapy in Major Depressive Disorder.

The low rates of treatment response still exist in the pharmacological therapy of major depressive disorder (MDD). Exploring an optimal neurological predictor of symptom improvement caused by pharmacotherapy is urgently needed for improving response to treatment. The amygdala is closely related to the pathological mechanism of MDD and is expected to be a predictor of the treatment. However, previous studies ignored the heterogeneousness and lateralization of amygdala. Therefore, this study mainly aimed to explore whether the right amygdala subregion function at baseline can predict symptom improvement after 12-week pharmacotherapy in MDD patients. We performed granger causality analysis (GCA) to identify abnormal effective connectivity (EC) of right amygdala subregions in MDD and compared the EC strength before and after 12-week pharmacological therapy. The results show that the abnormal EC mainly concentrated on the frontolimbic circuitry and default mode network (DMN). With relief of the clinical symptom, these abnormal ECs also change toward normalization. In addition, the EC strength of right amygdala subregions at baseline showed significant predictive ability for symptom improvement using a regularized least-squares regression predict model. These findings indicated that the EC of right amygdala subregions may be functionally related in symptom improvement of MDD. It may aid us to understand the neurological mechanism of pharmacotherapy and can be used as a promising predictor for symptom improvement in MDD.

Antidepressant Treatment-Induced State-Dependent Reconfiguration of Emotion Regulation Networks in Major Depressive Disorder.

Deficits in emotion regulation are the main clinical features, common risk factors, and treatment-related targets for major depressive disorder (MDD). The neural bases of emotion regulation are moving beyond specific functions and emphasizing instead the integrative functions of spatially distributed brain areas that work together as large-scale brain networks, but it is still unclear whether the dynamic interactions among these emotion networks would be the target of clinical intervention for MDD. Data were collected from 70 MDD patients and 43 sex- and age-matched healthy controls. The dynamic functional connectivity (dFC) between emotion regions was estimated via a sliding-window method based on resting-state functional magnetic resonance imaging (R-fMRI). A k-means clustering method was applied to classify all time windows across all participants into several dFC states reflecting recurring functional interaction patterns among emotion regions over time. The results showed that four dFC states were identified in the emotion networks. Their alterations of state-related occurrence proportion were found in MDD and subsequently normalized following 12-week antidepressant treatment. Baseline strong dFC could predict the reduction rate of Hamilton Depression Rating Scale (HAMD) scores. These findings highlighted the state-dependent reconfiguration of emotion regulation networks in MDD patients owing to antidepressant treatment.

An Acute Manic Episode During 2019-nCoV Quarantine.

BACKGROUND: The 2019-nCov pandemic is currently a stressor for the general public worldwide. In China, people who have a history of contact with infected or suspected individuals need to quarantine for at least 2 weeks. Many people experienced anxiety, panic and depression in the quarantine period. However, acute manic episode triggered by stressful events is not common and was neglected. CASE PRESENTATION: A 32-year-old woman with direct contact history with her infected colleagues showed elevated mood and increased activity when she was identified negative of nuclear acid amplification test, after experiencing extreme stress in quarantine. She was diagnosed with acute manic episode finally. The social zeitgeber and reward hypersensitivity theoretical models have attempted to use psychobiological perspectives to determine why life stress can trigger a mood episode, including (hypo)mania. Besides, the temporal correlation between her somatic symptoms and psychological stimuli indicated a possibility of functional disturbance under acute stress. CONCLUSION: Quarantine is a major stressful event disrupting social zeitgebers for people who have had contact with infected individuals, especially for vulnerable individuals with a hypersensitive reward system. Stress could act as a trigger in the onset of manic episode, so psychological support should be more targeted at the vulnerable individuals in the initial phase of emergent crisis.

Abnormal Functional Relationship of Sensorimotor Network With Neurotransmitter-Related Nuclei via Subcortical-Cortical Loops in Manic and Depressive Phases of Bipolar Disorder.

OBJECTIVE: Manic and depressive phases of bipolar disorder (BD) show opposite psychomotor symptoms. Neuronally, these may depend on altered relationships between sensorimotor network (SMN) and subcortical structures. The study aimed to investigate the functional relationships of SMN with substantia nigra (SN) and raphe nuclei (RN) via subcortical-cortical loops, and their alteration in bipolar mania and depression, as characterized by psychomotor excitation and inhibition. METHOD: In this resting-state functional magnetic resonance imaging (fMRI) study on healthy (n = 67) and BD patients (n = 100), (1) functional connectivity (FC) between thalamus and SMN was calculated and correlated with FC from SN or RN to basal ganglia (BG)/thalamus in healthy; (2) using an a-priori-driven approach, thalamus-SMN FC, SN-BG/thalamus FC, and RN-BG/thalamus FC were compared between healthy and BD, focusing on manic (n = 34) and inhibited depressed (n = 21) patients. RESULTS: (1) In healthy, the thalamus-SMN FC showed a quadratic correlation with SN-BG/thalamus FC and a linear negative correlation with RN-BG/thalamus FC. Accordingly, the SN-related FC appears to enable the thalamus-SMN coupling, while the RN-related FC affects it favoring anti-correlation. (2) In BD, mania showed an increase in thalamus-SMN FC toward positive values (ie, thalamus-SMN abnormal coupling) paralleled by reduction of RN-BG/thalamus FC. By contrast, inhibited depression showed a decrease in thalamus-SMN FC toward around-zero values (ie, thalamus-SMN disconnection) paralleled by reduction of SN-BG/thalamus FC (and RN-BG/thalamus FC). The results were replicated in independent HC and BD datasets. CONCLUSIONS: These findings suggest an abnormal relationship of SMN with neurotransmitters-related areas via subcortical-cortical loops in mania and inhibited depression, finally resulting in psychomotor alterations.

Altered hypothalamic functional connectivity patterns in major depressive disorder.

The hypothalamus is a limbic structure involved in the emergence and persistence of major depressive disorder symptoms. Previous studies have indicated that major depressive disorder patients exhibited dysregulation between the hypothalamus and cerebral regions. However, it is still unclear about the exact hypothalamic functional connectivity patterns with other brain regions based on resting-state functional MRI in major depressive disorder. Here, we investigated the whole-brain voxel-based hypothalamic resting-state functional connectivity in 55 patients with major depressive disorder and 40 age sex-matched healthy controls. The results showed that major depressive disorder patients had a significant decrease in resting-state functional connectivity of the bilateral hypothalamus with the right insula, superior temporal gyrus, inferior frontal gyrus, and Rolandic operculum compared with healthy controls. This study suggests that the pathophysiology of major depressive disorder might be associated with the abnormal hypothalamic resting-state functional connectivity.

Disrupted Brain Entropy And Functional Connectivity Patterns Of Thalamic Subregions In Major Depressive Disorder.

PURPOSE: Entropy analysis of resting-state functional magnetic resonance imaging (R-fMRI) has recently been adopted to characterize brain temporal dynamics in some neuropsychological or psychiatric diseases. Thalamus-related dysfunction might be a potential trait marker of major depressive disorder (MDD), but the abnormal changes in the thalamus based on R-fMRI are still unclear from the perspective of brain temporal dynamics. The aim of this study was to identify local entropy changes and subregional connectivity patterns of the thalamus in MDD patients. PATIENTS AND METHODS: We measured the sample entropy of the R-fMRI data from 46 MDD patients and 32 matched healthy controls. We employed the Louvain method for the module detection algorithm to automatically identify a functional parcellation of the thalamus and then examined the whole-brain subregional connectivity patterns. RESULTS: The results indicated that the MDD patients had decreased entropy in the bilateral thalami compared with healthy controls. Increased functional connectivity between the thalamic subregions and the medial part of the superior frontal gyrus (mSFG) was found in MDD patients. CONCLUSION: This study showed new evidence about sample entropy changes in MDD patients. The functional connectivity alterations that were widely distributed across almost all the thalamic subregions with the mSFG in MDD suggest a general involvement independent of the location and function of the subregions.