Depression uncouples brain hate circuit

Transdiagnostic white matter controllability deficits across patients with affective and anxiety spectrum disorders

BACKGROUND

Affective and anxiety disorders including major depression disorder (MDD), post-traumatic stress disorder (PTSD), and social anxiety disorder (SAD) are characterized by network dysconnectivity. Network controllability quantifies the capability of specific brain regions to impact functional dynamics based on the underlying structural connectome. This study aimed to investigate transdiagnostic and illness-specific network controllability alterations across these three disorders.

MATERIALS AND METHODS

The study enrolled 233 currently untreated and non-comorbid subjects, including 68 MDD patients, 51 PTSD patients, 46 SAD patients, and 68 healthy controls (HCs). White matter network controllability was compared among the four groups, and its associations with symptom severity and duration of untreated illness were evaluated.

RESULTS

Compared with HCs, patients with PTSD, MDD and SAD exhibited reduced average controllability in the somatomotor, subcortical, and default mode network, notably in brain regions such as the superior frontal gyrus, postcentral gyrus, paracentral gyrus, pallidum, posterior cingulate, and putamen. MDD and SAD patients exhibited reduced average controllability in the left lateral occipital gyrus and bilateral accumbens. SAD patients showed reduced average controllability in the dorsal attention network. These controllability changes did not correlate with illness duration or symptom severity.

LIMITATIONS

The cross-sectional design limits causal inference, and adjusting for age and sex differences may not completely eliminate their influence on the results.

CONCLUSION

The present study revealed shared and specific alterations of network controllability in MDD, PTSD, and SAD, suggesting reduced ability of specific brain regions/networks in driving the brain system into different functional states across these disorders.

Neural evidence of implicit emotion regulation deficits: An explorative study of comparing PTSD with and without alcohol dependence

BACKGROUND

Previous studies have identified psychiatric comorbidity, including alcohol dependence (AD), as a significant factor in treating posttraumatic stress disorder (PTSD), there is a lack of evidence on how best to treat comorbid PTSD and AD. Poor emotion regulation may be a key potential mechanism of PTSD and AD comorbidity.

METHODS

Seventy-four participants (48 women and 26 men) include three groups: a healthy control group (HC group, N = 20), a PTSD without alcohol dependence group (PTSD without AD group, N = 36), and a PTSD with alcohol dependence group (PTSD with AD group, N = 18). They completed the Shifted Attention Emotion Evaluation Task (SEAT) paradigm while undergoing fMRI.

RESULTS

Gender and hyperarousal symptoms were found to predict the risk of AD. In the whole-brain fMRI data, compared to PTSD without AD, the PTSD with AD group showed significant deactivations in the left middle Occipital Gyri (BA19_L), the right Rolandic Operculum (BA48_R), and the right Lingual Gyri (BA37_R). Furthermore, AD showed a significant correlation with the right Lingual Gyri (BA37_R) in individuals with PTSD.

CONCLUSION

These findings reveal possible neural mechanisms underlying the difference between PTSD patients with and without AD. These regions are involved in visual pathways, memory processing, and spatial cognition within the context of implicit emotion regulation. The observed alterations in these areas may serve as neural diagnostic markers for PTSD comorbid with AD and could be potential targets for developing novel treatments.

Middle frontal gyrus volume moderates the relationship between interleukin-1β and antidepressant response in major depressive disorder

Inflammation is a leading biological risk factor contributing to unfavorable outcomes of major depressive disorder (MDD). Both inflammation and depression are associated with similar alterations in brain structure, indicating that brain structural alterations could serve as a mediating factor in the adverse influence of inflammation on clinical outcomes in MDD. Nonetheless, longitudinal research has yet to confirm this hypothesis. Therefore, this study aimed at elucidating the relationships between peripheral inflammatory cytokines, gray matter volume (GMV) alterations, and antidepressant response in MDD. We studied 104 MDD patients treated with selective serotonin reuptake inhibitors and 85 healthy controls (HCs). Antidepressant response was assessed after 8-week antidepressant treatment by changes in 17-item Hamilton Depression Rating Scale (HAMD-17) scores. The GMV alterations were investigated using a voxel-based morphometry analysis. Inflammatory cytokines were measured using flow cytometry. Partial correlations were used to explore the relationships between inflammatory cytokines, GMV alterations, and antidepressant response. Compared to HCs, MDD patients showed reduced GMVs primarily in the frontal-limbic area, right insula, and right superior temporal gyrus. Furthermore, the alterations in GMVs, particularly in the right middle frontal gyrus and the left anterior cingulate gyrus, were associated with ΔHAMD-17 and inflammatory cytokines. Additionally, GMV alterations in the right middle frontal gyrus mediated the negative relationship between interleukin -1β and ΔHAMD-17. This study contributes to understanding the effect of inflammation on the brain and their relationships with antidepressant response, offering a potential explanation for the connection between inflammatory status and treatment efficacy.

Stable construction and analysis of MDD modular networks based on multi-center EEG data

BACKGROUND

The modular structure can reflect the activity pattern of the brain, and exploring it may help us understand the pathogenesis of major depressive disorder (MDD). However, little is known about how to build a stable modular structure in MDD patients and how modules are separated and integrated.

METHOD

We used four independent resting state Electroencephalography (EEG) datasets. Different coupling methods, window lengths, and optimized community detection algorithms were used to find a reliable and robust modular structure, and the module differences of MDD were analyzed from the perspectives of global module attributes and local topology in multiple frequency bands.

RESULTS

The combination of the Phase Lag Index (PLI) and the Louvain algorithm can achieve better results and can achieve stability at smaller window lengths. Compared with Healthy Controls (HC), MDD had higher Modularity (Q) values and the number of modules in low-frequency bands. In addition, MDD showed significant structural changes in the frontal and parietal-occipital lobes, which were confirmed by further correlation analysis.

CONCLUSION

Our results provided a reliable validation of the modular structure construction method in MDD patients and contributed strong evidence for the changes in emotional cognition and visual system function in MDD patients from a new perspective. These results would afford valuable insights for further exploration of the pathogenesis of MDD.

Individual large-scale functional network mapping for major depressive disorder with electroconvulsive therapy

Personalized functional connectivity mapping has been demonstrated to be promising in identifying underlying neurophysiological basis for brain disorders and treatment effects. Electroconvulsive therapy (ECT) has been proved to be an effective treatment for major depressive disorder (MDD) while its active mechanisms remain unclear. Here, 46 MDD patients before and after ECT as well as 46 demographically matched healthy controls (HC) underwent resting-state functional magnetic resonance imaging (rs-fMRI) scans. A spatially regularized form of non-negative matrix factorization (NMF) was used to accurately identify functional networks (FNs) in individuals to map individual-level static and dynamic functional network connectivity (FNC) to reveal the underlying neurophysiological basis of therepetical effects of ECT for MDD. Moreover, these static and dynamic FNCs were used as features to predict the clinical treatment outcomes for MDD patients. We found that ECT could modulate both static and dynamic large-scale FNCs at individual level in MDD patients, and dynamic FNCs were closely associated with depression and anxiety symptoms. Importantly, we found that individual FNCs, particularly the individual dynamic FNCs could better predict the treatment outcomes of ECT suggesting that dynamic functional connectivity analysis may be better to link brain functional characteristics with clinical symptoms and treatment outcomes. Taken together, our findings provide new evidence for the active mechanisms and biomarkers for ECT to improve diagnostic accuracy and to guide individual treatment selection for MDD patients.

Atypical dynamic network reconfiguration and genetic mechanisms in patients with major depressive disorder

BACKGROUND

Brain dynamics underlie complex forms of flexible cognition or the ability to shift between different mental modes. However, the precise dynamic reconfiguration based on multi-layer network analysis and the genetic mechanisms of major depressive disorder (MDD) remains unclear.

METHODS

Resting-state functional magnetic resonance imaging (fMRI) data were acquired from the REST-meta-MDD consortium, including 555 patients with MDD and 536 healthy controls (HC). A time-varying multi-layer network was constructed, and dynamic modular characteristics were used to investigate the network reconfiguration. Additionally, partial least squares regression analysis was performed using transcriptional data provided by the Allen Human Brain Atlas (AHBA) to identify genes associated with atypical dynamic network reconfiguration in MDD.

RESULTS

In comparison to HC, patients with MDD exhibited lower global and local recruitment coefficients. The local reduction was particularly evident in the salience and subcortical networks. Spatial transcriptome correlation analysis revealed an association between gene expression profiles and atypical dynamic network reconfiguration observed in MDD. Further functional enrichment analyses indicated that positively weighted reconfiguration-related genes were primarily associated with metabolic and biosynthetic pathways. Additionally, negatively enriched genes were predominantly related to programmed cell death-related terms.

CONCLUSIONS

Our findings offer robust evidence of the atypical dynamic reconfiguration in patients with MDD from a novel perspective. These results offer valuable insights for further exploration into the mechanisms underlying MDD.

Neural substrates of affective temperaments: An intersubject representational similarity analysis to resting-state functional magnetic resonance imaging in nonclinical subjects

Previous research has suggested that certain types of the affective temperament, including depressive, cyclothymic, hyperthymic, irritable, and anxious, are subclinical manifestations and precursors of mental disorders. However, the neural mechanisms that underlie these temperaments are not fully understood. The aim of this study was to identify the brain regions associated with different affective temperaments. We collected the resting-state functional magnetic resonance imaging (fMRI) data from 211 healthy adults and evaluated their affective temperaments using the Temperament Evaluation of Memphis, Pisa, Paris and San Diego Autoquestionnaire. We used intersubject representational similarity analysis to identify brain regions associated with each affective temperament. Brain regions associated with each affective temperament were detected. These regions included the prefrontal cortex, anterior cingulate cortex (ACC), precuneus, amygdala, thalami, hippocampus, and visual areas. The ACC, lingual gyri, and precuneus showed similar activity across several affective temperaments. The similarity in related brain regions was high among the cyclothymic, irritable, and anxious temperaments, and low between hyperthymic and the other affective temperaments. These findings may advance our understanding of the neural mechanisms underlying affective temperaments and their potential relationship to mental disorders and may have potential implications for personalized treatment strategies for mood disorders.

Enhanced interhemispheric resting-state functional connectivity of the visual network is an early treatment response of paroxetine in patients with panic disorder

This study aimed to detect alterations in interhemispheric interactions in patients with panic disorder (PD), determine whether such alterations could serve as biomarkers for the diagnosis and prediction of therapeutic outcomes, and map dynamic changes in interhemispheric interactions in patients with PD after treatment. Fifty-four patients with PD and 54 healthy controls (HCs) were enrolled in this study. All participants underwent clinical assessment and a resting-state functional magnetic resonance imaging scan at (i) baseline and (ii) after paroxetine treatment for 4 weeks. A voxel-mirrored homotopic connectivity (VMHC) indicator, support vector machine (SVM), and support vector regression (SVR) were used in this study. Patients with PD showed reduced VMHC in the fusiform, middle temporal/occipital, and postcentral/precentral gyri, relative to those of HCs. After treatment, the patients exhibited enhanced VMHC in the lingual gyrus, relative to the baseline data. The VMHC of the fusiform and postcentral/precentral gyri contributed most to the classification (accuracy = 87.04%). The predicted changes were accessed from the SVR using the aberrant VMHC as features. Positive correlations (p < 0.001) were indicated between the actual and predicted changes in the severity of anxiety. These findings suggest that impaired interhemispheric coordination in the cognitive-sensory network characterized PD and that VMHC can serve as biomarkers and predictors of the efficiency of PD treatment. Enhanced VMHC in the lingual gyrus of patients with PD after treatment implied that pharmacotherapy recruited the visual network in the early stages.

Altered spontaneous neurological activity in methamphetamine use disorders and its association with cognitive function

BACKGROUND

Methamphetamine (MA) is a widely used and detrimental drug, yet the precise mechanisms by which MA affects cognitive function remain unclear. This study aims to investigate the relationship between cognitive function and brain functional imaging in individuals with MA use disorder (MUD).

METHODS

This study involved 45 patients diagnosed with MUD and 43 healthy controls (HC). Cognitive function assessment utilized the MATRICS Consensus Cognitive Battery, and functional data were acquired using a 3.0 Tesla magnetic resonance imaging scanner.

RESULTS

The MUD group exhibited lower regional homogeneity (ReHo) values in the bilateral postcentral, the left superior temporal, and the left lingual regions compared to the HC group. Additionally, the MUD group displayed higher amplitude of low-frequency fluctuation (ALFF) values in the bilateral fusiform and the left putamen compared to the HC group, along with lower ALFF values in the bilateral postcentral cortices and the left middle cingulate cortex compared to the HC group (all p < 0.05, with false discovery rate corrected). Linear regression analysis revealed a positive correlation between the ReHo value in the right postcentral cortex and the neuropsychology assessment battery-mazes test (p = 0.014). Furthermore, the ALFF value in the left putamen showed negative correlations with the scores of the digit-symbol coding test (p = 0.027), continuous performance test (p = 0.037), and battery-mazes test (p = 0.024).

CONCLUSION

Patients with MUD exhibit altered brain spontaneous neurological activities, and the intensity of spontaneous neurological activity in the left putamen is strongly associated with cognitive function.

Brain connectivity patterns derived from aging-related alterations in dynamic brain functional networks and their potential as features for brain age classification

Objective.Recent studies have demonstrated that the analysis of brain functional networks (BFNs) is a powerful tool for exploring brain aging and age-related neurodegenerative diseases. However, investigating the mechanism of brain aging associated with dynamic BFN is still limited. The purpose of this study is to develop a novel scheme to explore brain aging patterns by constructing dynamic BFN using resting-state functional magnetic resonance imaging data.Approach.A dynamic sliding-windowed non-negative block-diagonal representation (dNBDR) method is proposed for constructing dynamic BFN, based on which a collection of dynamic BFN measures are suggested for examining age-related differences at the group level and used as features for brain age classification at the individual level.Results.The experimental results reveal that the dNBDR method is superior to the sliding time window with Pearson correlation method in terms of dynamic network structure quality. Additionally, significant alterations in dynamic BFN structures exist across the human lifespan. Specifically, average node flexibility and integration coefficient increase with age, while the recruitment coefficient shows a decreased trend. The proposed feature extraction scheme based on dynamic BFN achieved the highest accuracy of 78.7% in classifying three brain age groups.Significance. These findings suggest that dynamic BFN measures, dynamic community structure metrics in particular, play an important role in quantitatively assessing brain aging.

The altered temporal properties of dynamic functional connectivity associated with suicide attempt in bipolar disorders

OBJECTIVE

The suicide risk in bipolar disorder (BD) is the highest among psychiatric disorders, and the neurobiological mechanism of suicide in BD remains unclear. The study aimed to investigate the underlying relevance between the implicated abnormalities of dynamic functional connectivity (FC) and suicide attempt (SA) in BD.

METHODS

We used the sliding window method to analyze the dynamic FC patterns from resting-state functional MRI data in 81 healthy controls (HC) and 114 BD patients (50 with SA and 64 with none SA). Then, the temporal properties of dynamic FC and the relationship between altered measures and clinical variables were explored.

RESULTS

We found that one of the five captured brain functional states was more associated with SA. The SA patients showed significantly increased fractional window and dwell time in the suicide-related state, along with increased number of state transitions compared with none SA (NSA). In addition, the connections within subcortical network-subcortical network (SubC-SubC), default mode network-subcortical network (DMN-SubC), and attention network-subcortical network (AN-SubC) were significantly changed in SA patients relative to NSA and HC in the suicide-related state. Crucially, the above-altered measures were significantly correlated with suicide risk.

CONCLUSIONS

Our findings suggested that the impaired dynamic FC within SubC-SubC, DMN-SubC, and AN-SubC were the important underlying mechanism in understanding SA for BD patients. It highlights the temporal properties of whole-brain dynamic FC could serve as the valuable biomarker for suicide risk assessment in BD.

Aberrant interhemispheric structural and functional connectivity within whole brain in schizophrenia

OBJECTIVE

Schizophrenia is a serious mental disorder whose etiology remains unclear. Although numerous studies have analyzed the abnormal gray matter functional activity and whole-brain anatomical changes in schizophrenia, fMRI signal fluctuations from white matter have usually been ignored and rarely reported in the literature.

METHODS

We employed 45 schizophrenia subjects and 75 healthy controls (HCs) from a publicly available fMRI dataset. By combining the voxel-mirrored homotopic connectivity (VMHC) measure and fiber tracking method, we investigated the interhemispheric functional and structural connectivity within whole brain in schizophrenia.

RESULTS

Compared to HCs, patients with schizophrenia exhibited significantly reduced VMHC in the bilateral middle occipital gyrus, precentral gyrus, postcentral gyrus and corpus callosum. Fiber tracking results showed the changes in structural connectivity for the bilateral precentral gyrus, and the bilateral corpus callosum, and the fiber bundles connecting bilateral precentral gyrus and connecting the bilateral corpus callosum passed through the posterior midbody, isthmus and splenium of mid-sagittal corpus callosum, which closely related to the interhemispheric integration of visual and auditory information. More importantly, we observed a negative correlation between averaged VMHC values in the postcentral gyrus and SAPS scores, and a positive correlation between the fractional anisotropy of fiber bundle connecting the bilateral precentral gyrus and Matrix Reasoning scores in schizophrenia.

CONCLUSION

Our findings provide a novel perspective of white matter functional images on understanding abnormal interhemispheric visual and auditory information transfer in schizophrenia.

Classification of bipolar disorders using the multilayer modularity in dynamic minimum spanning tree from resting state fMRI

The diagnosis of bipolar disorders (BD) mainly depends on the clinical history and behavior observation, while only using clinical tools often limits the diagnosis accuracy. The study aimed to create a novel BD diagnosis framework using multilayer modularity in the dynamic minimum spanning tree (MST). We collected 45 un-medicated BD patients and 47 healthy controls (HC). The sliding window approach was utilized to construct dynamic MST via resting-state functional magnetic resonance imaging (fMRI) data. Firstly, we used three null models to explore the effectiveness of multilayer modularity in dynamic MST. Furthermore, the module allegiance exacted from dynamic MST was applied to train a classifier to discriminate BD patients. Finally, we explored the influence of the FC estimator and MST scale on the performance of the model. The findings indicated that multilayer modularity in the dynamic MST was not a random process in the human brain. And the model achieved an accuracy of 83.70% for identifying BD patients. In addition, we found the default mode network, subcortical network (SubC), and attention network played a key role in the classification. These findings suggested that the multilayer modularity in dynamic MST could highlight the difference between HC and BD patients, which opened up a new diagnostic tool for BD patients.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-022-09907-x.

Topological properties and connectivity patterns in brain networks of patients with refractory epilepsy combined with intracranial electrical stimulation

Objective

Although intracranial electrical stimulation has emerged as a treatment option for various diseases, its impact on the properties of brain networks remains challenging due to its invasive nature. The combination of intracranial electrical stimulation and whole-brain functional magnetic resonance imaging (fMRI) in patients with refractory epilepsy (RE) makes it possible to study the network properties associated with electrical stimulation. Thus, our study aimed to investigate the brain network characteristics of RE patients with concurrent electrical stimulation and obtain possible clinical biomarkers.

Methods

Our study used the GRETNA toolbox, a graph theoretical network analysis toolbox for imaging connectomics, to calculate and analyze the network topological attributes including global measures (small-world parameters and network efficiency) and nodal characteristics. The resting-state fMRI (rs-fMRI) and the fMRI concurrent electrical stimulation (es-fMRI) of RE patients were utilized to make group comparisons with healthy controls to identify the differences in network topology properties. Network properties comparisons before and after electrode implantation in the same patient were used to further analyze stimulus-related changes in network properties. Modular analysis was used to examine connectivity and distribution characteristics in the brain networks of all participants in study.

Results

Compared to healthy controls, the rs-fMRI and the es-fMRI of RE patients exhibited impaired small-world property and reduced network efficiency. Nodal properties, such as nodal clustering coefficient (NCp), betweenness centrality (Bc), and degree centrality (Dc), exhibited differences between RE patients (including rs-fMRI and es-fMRI) and healthy controls. The network connectivity of RE patients (including rs-fMRI and es-fMRI) showed reduced intra-modular connections in subcortical areas and the occipital lobe, as well as decreased inter-modular connections between frontal and subcortical regions, and parieto-occipital regions compared to healthy controls. The brain networks of es-fMRI showed a relatively weaker small-world structure compared to rs-fMRI.

Conclusion

The brain networks of RE patients exhibited a reduced small-world property, with a tendency toward random networks. The network connectivity patterns in RE patients exhibited reduced connections between cortical and subcortical regions and enhanced connections among parieto-occipital regions. Electrical stimulation can modulate brain network activity, leading to changes in network connectivity patterns and properties.

Cerebral blood flow changes and their genetic mechanisms in major depressive disorder: a combined neuroimaging and transcriptome study

BACKGROUND

Extensive research has shown abnormal cerebral blood flow (CBF) in patients with major depressive disorder (MDD) that is a heritable disease. The objective of this study was to investigate the genetic mechanisms of CBF abnormalities in MDD.

METHODS

To achieve a more thorough characterization of CBF changes in MDD, we performed a comprehensive neuroimaging meta-analysis of previous literature as well as examined group CBF differences in an independent sample of 133 MDD patients and 133 controls. In combination with the Allen Human Brain Atlas, transcriptome-neuroimaging spatial association analyses were conducted to identify genes whose expression correlated with CBF changes in MDD, followed by a set of gene functional feature analyses.

RESULTS

We found increased CBF in the reward circuitry and default-mode network and decreased CBF in the visual system in MDD patients. Moreover, these CBF changes were spatially associated with expression of 1532 genes, which were enriched for important molecular functions, biological processes, and cellular components of the cerebral cortex as well as several common mental disorders. Concurrently, these genes were specifically expressed in the brain tissue, in immune cells and neurons, and during nearly all developmental stages. Regarding behavioral relevance, these genes were associated with domains involving emotion and sensation. In addition, these genes could construct a protein-protein interaction network supported by 60 putative hub genes with functional significance.

CONCLUSIONS

Our findings suggest a cerebral perfusion redistribution in MDD, which may be a consequence of complex interactions of a wide range of genes with diverse functional features.

Abnormalities of Regional Brain Activity in Patients With Schizophrenia: A Longitudinal Resting-State fMRI Study

BACKGROUND

Evidence from functional and structural research suggests that abnormal brain activity plays an important role in the pathophysiology of schizophrenia (SZ). However, limited studies have focused on post-treatment changes, and current conclusions are inconsistent.

STUDY DESIGN

We recruited 104 SZ patients to have resting-state functional magnetic resonance imaging scans at baseline and 8 weeks of treatment with second-generation antipsychotics, along with baseline scanning of 86 healthy controls (HCs) for comparison purposes. Individual regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF), and degree centrality values were calculated to evaluate the functional activity. The Positive and Negative Syndrome Scale (PANSS) and MATRICS Consensus Cognitive Battery were applied to measure psychiatric symptoms and cognitive impairment in SZ patients.

RESULTS

Compared with HCs at baseline, SZ patients had higher ALFF and ReHo values in the bilateral inferior temporal gyrus, inferior frontal gyrus, and lower ALFF and ReHo values in fusiform gyrus and precuneus. Following 8 weeks of treatment, ReHo was increased in right medial region of the superior frontal gyrus (SFGmed) and decreased in the left middle occipital gyrus and the left postcentral gyrus. Meanwhile, ReHo of the right SFGmed was increased after treatment in the response group (the reduction rate of PANSS ≥50%). Enhanced ALFF in the dorsolateral of SFG correlated with improvement in depressive factor score.

CONCLUSIONS

These findings provide novel evidence for the abnormal functional activity hypothesis of SZ, suggesting that abnormality of right SFGmed can be used as a biomarker of treatment response in SZ.

Voxel-based meta-analysis of gray matter and white matter changes in patients with spinocerebellar ataxia type 3

Purpose

Increasing neuroimaging studies have revealed gray matter (GM) and white matter (WM) anomalies of several brain regions by voxel-based morphometry (VBM) studies on patients with spinocerebellar ataxia type 3 (SCA3); however, the findings of previous studies on SCA3 patients by VBM studies remain inconsistent. The study aimed to identify consistent findings of gray matter (GM) and white matter (WM) changes in SCA3 patients by voxel-wise meta-analysis of whole-brain VBM studies.

Methods

VBM studies comparing GM or WM changes in SCA3 patients and healthy controls (HCs) were retrieved from PubMed, Embase, Web of Science, and Medline databases from January 1990 to February 2023. Manual searches were also conducted, and authors of studies were contacted for additional data. The coordinates with significant differences in GM and WM between SCA3 patients and HCs were extracted from each cluster. A meta-analysis was performed using anisotropic effect size-based signed differential mapping (AES-SDM) software.

Results

A total of seven studies comprising 160 SCA3 patients and 165 HCs were included in the GM volume meta-analysis. Three studies comprising 57 SCA3 patients and 63 HCs were included for WM volume meta-analysis. Compared with HC subjects, the reduced GM volume in SCA3 patients was found in the bilateral cerebellar hemispheres, cerebellar vermis, pons, right lingual gyrus, and right fusiform gyrus. The decreased WM volume was mainly concentrated in the bilateral cerebellar hemispheres, right corticospinal tract, middle cerebellar peduncles, cerebellar vermis, and left lingual gyrus. No increased density or volume of any brain structures was found. In the jackknife sensitivity analysis, the results remained largely robust.

Conclusion

Our meta-analysis clearly found the shrinkage of GM and WM volume in patients with SCA3. These lesions are involved in ataxia symptoms, abnormal eye movements, visual impairment, cognitive impairment, and affective disorders. The findings can explain the clinical manifestations and provide a morphological basis for SCA3.

Depression circuit adaptation in post-stroke depression

BACKGROUND

Lesion locations of post-stroke depression (PSD) mapped to a depression circuit which centered by the left dorsolateral prefrontal cortex (DLPFC). However, it remains unknown whether the compensatory adaptations that may occur in this depression circuit due to the lesions in PSD.

METHODS

Rs-fMRI data were collected from 82 non-depressed stroke patients (Stroke), 39 PSD patients and 74 healthy controls (HC). We tested the existence of depression circuit, examined PSD-related alterations of DLPFC-seeded connectivity and their associations with depression severity, and analyzed the connectivity between each repetitive transcranial magnetic stimulation (rTMS) target and DLPFC to find the best treatment target for PSD.

RESULTS

We found that: 1) the left DLPFC showed significantly stronger connectivity to lesions of PSD than Stroke group; 2) in comparison to both Stroke and HC groups, PSD exhibited increased connectivity with DLPFC in bilateral lingual gyrus, contralesional superior frontal gyrus, precuneus, and middle frontal gyrus (MFG); 3) the connectivity between DLPFC and the contralesional lingual gyrus positively correlated with depression severity; 4) the rTMS target in center of MFG showed largest between-group difference in connectivity with DLPFC, and also reported the highest predicted clinical efficacy.

LIMITATIONS

Longitudinal studies are required to explore the alterations of depression circuit in PSD as the disease progress.

CONCLUSION

PSD underwent specific alterations in depression circuit, which may help to establish objective imaging markers for early diagnosis and interventions of the disease.

Association between decreased interhemispheric functional connectivity of the insula and duration of illness in recurrent depression

OBJECTIVE

To investigate the altered interhemispheric functional connectivity in the resting state in patients with recurrent major depressive disorder (MDD).

METHODS

Voxel-mirrored homotopic connectivity (VMHC), a measure of the functional connectivity between any pair of symmetrical interhemispheric voxels, and pattern classification were examined in 41 recurrent MDD patients (22 during the depressive state and 19 during the remitted state) and 60 age, sex, and education level-matched healthy controls (HC) using resting-state functional magnetic resonance imaging (fMRI).

RESULTS

Compared with HC, the recurrent MDD patients exhibited decreased VMHC values in the bilateral fusiform, inferior occipital gyrus, posterior insula, precentral gyrus, precuneus, superior temporal gyrus, and thalamus. A significant negative correlation between the VMHC value of the bilateral posterior insula and illness duration in recurrent MDD was identified. Support vector machine (SVM) analysis showed that VMHC in the fusiform and posterior insula could be used to distinguish recurrent MDD patients from HC with a sensitivity and accuracy >0.6.

CONCLUSION

Our findings revealed a reduction in the resting-state brain activity across several neural networks in patients with recurrent MDD, including within the posterior insula. Lower VMHC values in the posterior insula were associated with longer illness duration, suggesting that impairment in interhemispheric synchronization within the salience network may be due to the accumulated pathology of depression and may contribute to future depression relapse. VMHC changes in the posterior insula may serve as a potential imaging marker to discriminate recurrent MDD patients from HC.

Abnormal functional connectivity of the nucleus accumbens subregions mediates the association between anhedonia and major depressive disorder

BACKGROUND

The nucleus accumbens (Nac) is a crucial brain region in the pathophysiology of major depressive disorder (MDD) patients with anhedonia. However, the relationship between the functional imaging characteristics of Nac subregions and anhedonia remains unclear. Thus, this study aimed to investigate the role of resting-state functional connectivity (rsFC) of the Nac subregions between MDD and anhedonia.

METHODS

We performed resting-state functional magnetic resonance imaging (fMRI) to measure the rsFC of Nac subregions in 55 MDD patients and 30 healthy controls (HCs). A two-sample t test was performed to determine the brain regions with varying rsFC among Nac subregions between groups. Then, correlation analyses were carried out to investigate the relationships between the aberrant rsFC of Nac subregions and the severity of anhedonia. Furthermore, we constructed a mediation model to explain the role of the aberrant rsFC of Nac subregions between MDD and the severity of anhedonia.

RESULTS

Compared with the HC group, decreased rsFC of Nac subregions with regions of the prefrontal cortex, insula, lingual gyrus, and visual association cortex was observed in MDD patients. In the MDD group, the rsFC of the right Nac shell-like subregions with the middle frontal gyrus (MFG)/superior frontal gyrus (SFG) was correlated with consummatory anhedonia, and the rsFC of the Nac core-like subdivisions with the inferior frontal gyrus (IFG)/insula and lingual gyrus/visual association cortex was correlated with anticipatory anhedonia. More importantly, the functional alterations in the Nac subregions mediated the association between anhedonia and depression.

CONCLUSIONS

The present findings suggest that the functional alteration of the Nac subregions mediates the association between MDD and anhedonia, which provides evidence for the hypothesis that MDD patients have neurobiological underpinnings of reward systems that differ from those of HCs.

Shared and differential fractional amplitude of low-frequency fluctuation patterns at rest in major depressive disorders with or without sleep disturbance

Objective

Sleep disturbances (SD) are commonly found in patients with major depressive disorder (MDD). This study aims to explore the influence of SD symptoms on clinical characteristics in patients with MDD and to investigate the shared and distinct fractional amplitude of low-frequency fluctuation (fALFF) patterns in these patients with or without SD symptoms.

Methods

Twenty-four MDD patients with SD symptoms (Pa_s), 33 MDD patients without SD symptoms (Pa_ns) and 32 healthy controls (HCs) were included in this study. The fALFF and correlation analyses were applied to analyze the features of imaging and clinical data.

Results

Pa_s showed more severe anxiety and depression than Pa_ns. Compared with Pa_ns, Pa_s exhibited increased fALFF value in the left precuneus. Patients shared abnormal fALFF in the frontal-occipital brain regions. There was a positive correlation between fALFF values of the left precuneus and sleep disturbance scores (r = 0.607, p = 0.0000056734) in all patients in addition to a negative correlation between fALFF values of the left MOG/cuneus and HAMD-17 total scores (r = -0.595, p = 0.002141) in Pa_s. The receiver operating characteristic (ROC) results of the fALFF could be used to discriminate Pa_s from Pa_ns with a specificity of 72.73% and a sensitivity of 70.83%.

Conclusion

Pa_s displayed more serious anxiety and depression symptoms. Patients shared abnormal fALFF in the frontal-occipital brain regions, which may be a common characteristic for MDD. And increased fALFF value in the left precuneus might be a specific neuroimaging feature of MDD patients with SD symptoms.

A voxel-based meta-analysis comparing medication-naive patients of major depression with treated longer-term ill cases

Structural neuroimaging studies have identified brain areas implicated in the pathogenesis of major depressive disorder (MDD). However, findings have been inconsistent, potentially due to variable illness duration and effects of antidepressant treatment. Using a meta-analytic approach, we compared gray matter (GM) volumes in patients grouped by medication status (naïve and treated) and illness duration (early course and long-term ill) to identify potential treatment and illness duration effects on brain structure. A total of 70 studies were included, including 3682 patients and 3469 controls. The pooled analysis found frontal, temporal and limbic regions with decreased GM volume in MDD patients. Additional analyses indicated that larger GM volume in the right striatum and smaller GM volume in the right precuneus are likely to be associated with drug effects, while smaller GM volume in the right temporal gyrus may correlate with longer illness duration. Similar GM decreases in bilateral medial frontal cortex between patient subgroups suggest that this alteration may persist over the course of illness and drug treatment.

Dynamic local metrics changes in patients with toothache: A resting-state functional magnetic resonance imaging study

Objective

To study the dynamic changes of local metrics in patients with toothache (TA, Toothache) in the resting state, in order to further understand the changes of central neural mechanism in patients with dental pain and its effect on cognition and emotion.

Methods

Thirty patients with TA and thirty matched healthy (HC) control volunteers were recruited, and resting-state functional magnetic resonance (rs-MRI) scans were performed on all subjects, and data were analyzed to compare group differences in three dynamic local indices: dynamic regional homogeneity (dReHO), dynamic low-frequency fluctuation amplitude (dALFF) and dynamic fractional low-frequency fluctuation amplitude (dfALFF). In addition, the association between dynamic local metrics in different brain regions of TA patients and scores on the Visual Analog Scale (VAS) and the Hospital Anxiety and Depression Scale (HADS) was investigated by Pearson correlation analysis.

Results

In this study, we found that The local metrics of TA patients changed with time Compared with the HC group, TA patients showed increased dReHo values in the left superior temporal gyrus, middle frontal gyrus, precentral gyrus, precuneus, angular gyrus, right superior frontal gyrus, middle temporal gyrus, postcentral gyrus and middle frontal gyrus, increased dALFF values in the right superior frontal gyrus, and increased dfALFF values in the right middle temporal gyrus, middle frontal gyrus and right superior occipital gyrus (p < 0.01, cluster level P < 0.05). Pearson correlation analysis showed that dReHo values of left precuneus and left angular gyrus were positively correlated with VAS scores in TA group. dReHo value of right posterior central gyrus was positively correlated with HADS score (P < 0.05).

Conclusion

There are differences in the patterns of neural activity changes in resting-state brain areas of TA patients, and the brain areas that undergo abnormal changes are mainly pain processing brain areas, emotion processing brain areas and pain cognitive modulation brain areas, which help to reveal their underlying neuropathological mechanisms. In the hope of further understanding its effects on cognition and emotion.

Associations between disrupted functional brain network topology and cognitive impairment in patients with rectal cancer during chemotherapy

Introduction

Cognitive impairment has been identified in patients with non-central nervous system cancer received chemotherapy. Chemotherapy-induced changes in the brain are considered as the possible causes of the cognitive deficits of patients. This study aimed to explore chemotherapy-related functional brain changes and cognitive impairment in rectal cancer (RC) patients who had just finished chemotherapy treatment.

Methods

In this study, RC patients after chemotherapy (on the day patients received the last dose of chemotherapy) (n=30) and matched healthy controls (HCs) (n=30) underwent cognitive assessments, structural magnetic resonance imaging (MRI) and resting-state functional MRI. The functional brain networks were constructed by thresholding the partial correlation matrices of 90 brain regions in the Anatomical Automatic Labeling template and the topologic properties were evaluated by graph theory analysis. Moreover, correlations between altered topological measures and scores of cognitive scales were explored in the patient group.

Results

Compared with HCs, RC patients had lower scores of cognitive scales. The functional brain network had preserved small-world topological features but with a tendency towards higher path length in the whole network. In addition, patients had decreased nodal global efficiency (E_glo(i)) in the left superior frontal gyrus (dorsolateral), superior frontal gyrus (orbital part), inferior frontal gyrus (opercular part), inferior frontal gyrus (triangular part) and right inferior frontal gyrus (triangular part). Moreover, values of E_glo(i) in the superior and inferior frontal gyrus were positively associated with cognitive function in the patient group.

Conclusion

These results suggested that cognitive impairment was associated with disruptions of the topological organization in functional brain networks of RC patients who had just finished chemotherapy, which provided new insights into the pathophysiology underlying acute effects of chemotherapy on cognitive function.

Altered spontaneous brain activity in major depressive disorder: An activation likelihood estimation meta-analysis

BACKGROUND

Wide application of resting-state functional magnetic resonance imaging (fMRI) in psychiatric research has revealed that major depressive disorder (MDD) manifest abnormal neural activities in several brain regions involving key resting state networks. However, inconsistent results have hampered our understanding of the exact neuropathology associated with MDD. Therefore, our aim was to conduct a meta-analysis to identify the consistent vulnerable brain regions of MDD in resting state, and to reveal the potential pathogenesis of MDD.

METHODS

A systematic review analysis was conducted on studies involving brain resting-state changes in MDD using low-frequency amplitude (ALFF), fractional low-frequency amplitude (fALFF) and regional homogeneity (ReHo) analysis. The meta-analysis was based on the activation likelihood estimation method, using the software of Ginger ALE 2.3.

RESULTS

25 studies (892 MDD and 799 healthy controls) were included. Based on the meta-analysis results of ReHo, we found robust reduction of resting-state spontaneous brain activity in MDD, including the left cuneus and right middle occipital gyrus (cluster size = 216, 256 mm³, uncorrected P < 0.0001), while no increased spontaneous activation in any of the brain regions. We also found reduced ALFF in the left middle occipital gyrus (cluster size = 224 mm³, uncorrected P < 0.0001), and no increased spontaneous brain activation in any regions.

CONCLUSION

Our meta-analysis study using the activation likelihood estimation method demonstrated that MDD showed significant abnormalities in spontaneous neural activity, compared with healthy controls, mainly in areas associated with visual processing, such as the cuneus and the middle occipital gyrus. Dysfunction of these brain regions may be one of the pathogenesis of MDD.

Brain Signatures During Reward Anticipation Predict Persistent Attention-Deficit/Hyperactivity Disorder Symptoms

OBJECTIVE

Children experiencing attention-deficit/hyperactivity disorder (ADHD) symptoms may retain symptoms into adulthood, but little is known about the underlying mechanism.

METHOD

To identify biomarkers of persistent ADHD symptom development, we carried out whole-brain analyses of neuroimaging data during the anticipation phase of the Monetary-Incentive-Delay (MID) task in 1,368 adolescents recruited by the IMAGEN Consortium at age 14 years, whose behavioral measurements were followed up longitudinally at age 16. In particular, we focused on comparing individuals with persistent high ADHD symptoms at both ages 14 and 16 years to unaffected control individuals, but also exploring which individuals demonstrating symptom remission (with high ADHD symptoms at age 14 but much reduced at age 16).

RESULTS

We identified reduced activations in the medial frontal cortex and the thalamus during reward anticipation as neuro-biomarkers for persistent ADHD symptoms across time. The genetic relevance of the above findings was further supported by the associations of the polygenic risk scores of ADHD with both the persistent and control status and the activations of both brain regions. Furthermore, in an exploratory analysis, the thalamic activation might also help to distinguish persons with persistent ADHD from those remitted in both an exploratory sample (odds ratio = 9.43, p < .001) and an independent generalization sample (odds ratio = 4.64, p = .003).

CONCLUSION

Using a well-established and widely applied functional magnetic resonance imaging task, we have identified neural biomarkers that could discriminate ADHD symptoms that persist throughout adolescence from controls and potentially those likely to remit during adolescent development as well.

Widespread aberrant functional connectivity throughout the whole brain in obstructive sleep apnea

Objective

Obstructive sleep apnea (OSA) is a sleep-related breathing disorder with high prevalence and is associated with cognitive impairment. Previous neuroimaging studies have reported abnormal brain functional connectivity (FC) in patients with OSA that might contribute to their neurocognitive impairments. However, it is unclear whether patients with OSA have a characteristic pattern of FC changes that can serve as a neuroimaging biomarker for identifying OSA.

Methods

A total of 21 patients with OSA and 21 healthy controls (HCs) were included in this study and scanned using resting-state functional magnetic resonance imaging (fMRI). The automated anatomical labeling (AAL) atlas was used to divide the cerebrum into 90 regions, and FC between each pair of regions was calculated. Univariate analyses were then performed to detect abnormal FCs in patients with OSA compared with controls, and multivariate pattern analyses (MVPAs) were applied to classify between patients with OSA and controls.

Results

The univariate comparisons did not detect any significantly altered FC. However, the MVPA showed a successful classification between patients with OSA and controls with an accuracy of 83.33% (p = 0.0001). Furthermore, the selected FCs were associated with nearly all brain regions and widely distributed in the whole brain, both within and between, many resting-state functional networks. Among these selected FCs, 3 were significantly correlated with the apnea-hypopnea index (AHI) and 2 were significantly correlated with the percentage of time with the saturation of oxygen (SaO₂) below 90% of the total sleep time (%TST < 90%).

Conclusion

There existed widespread abnormal FCs in the whole brain in patients with OSA. This aberrant FC pattern has the potential to serve as a neurological biomarker of OSA, highlighting its importance for understanding the complex neural mechanism underlying OSA and its cognitive impairment.

Reduced cortical complexity in patients with thyroid-associated ophthalmopathy

Psychical and functional disturbances of thyroid-associated ophthalmopathy (TAO) patients are drawing increasingly attention, despite the characterized ophthalmic symptoms. We aimed to investigate the alterations of structural complexity using fractal dimension (FD) analysis in patients with TAO. Thirty-nine TAO patients and 25 healthy controls underwent high-resolution 3.0 T structural brain magnetic resonance imaging (MRI). FD values of brain regions were calculated by Computational Anatomy Toolbox (CAT12) and compared between groups. The associations between clinical variables and FD values were further estimated. We found that TAO patients exhibited significantly decreased FD values in right caudal anterior cingulate cortex, right lingual gyrus, right pars orbitalis and right cuneus cortex (FDR corrected p < 0.05). FD values of right cuneus cortex were positively correlated with visual acuity, and FD values of right caudal anterior cingulate cortex were also positively correlated with cognitive performance. Meanwhile, FD values of right lingual gyrus were found to be negatively correlated with emotional function. Our study indicated disturbed cortical complexity in brain regions corresponding to known functional deficits of vision, emotion and cognition in TAO. FD might be a potential marker for reflecting the underlying neurobiological basis of TAO.

Reduced nucleus accumbens functional connectivity in reward network and default mode network in patients with recurrent major depressive disorder

The nucleus accumbens (NAc) is considered a hub of reward processing and a growing body of evidence has suggested its crucial role in the pathophysiology of major depressive disorder (MDD). However, inconsistent results have been reported by studies on reward network-focused resting-state functional MRI (rs-fMRI). In this study, we examined functional alterations of the NAc-based reward circuits in patients with MDD via meta- and mega-analysis. First, we performed a coordinated-based meta-analysis with a new SDM-PSI method for all up-to-date rs-fMRI studies that focused on the reward circuits of patients with MDD. Then, we tested the meta-analysis results in the REST-meta-MDD database which provided anonymous rs-fMRI data from 186 recurrent MDDs and 465 healthy controls. Decreased functional connectivity (FC) within the reward system in patients with recurrent MDD was the most robust finding in this study. We also found disrupted NAc FCs in the DMN in patients with recurrent MDD compared with healthy controls. Specifically, the combination of disrupted NAc FCs within the reward network could discriminate patients with recurrent MDD from healthy controls with an optimal accuracy of 74.7%. This study confirmed the critical role of decreased FC in the reward network in the neuropathology of MDD. Disrupted inter-network connectivity between the reward network and DMN may also have contributed to the neural mechanisms of MDD. These abnormalities have potential to serve as brain-based biomarkers for individual diagnosis to differentiate patients with recurrent MDD from healthy controls.

Effects of Bilateral Subthalamic Nucleus Stimulation on Depressive Symptoms and Cerebral Glucose Metabolism in Parkinson's Disease: A 18F-Fluorodeoxyglucose Positron Emission Tomography/Computerized Tomography Study

Subthalamic nucleus (STN) deep brain stimulation (DBS) can improve motor symptoms in Parkinson's disease (PD), as well as potentially improving otherwise intractable comorbid depressive symptoms. To address the latter issue, we evaluated the severity of depressive symptoms along with the severity of motor symptoms in 18 PD patients (mean age, 58.4 ± 5.4 years; 9 males, 9 females; mean PD duration, 9.4 ± 4.4 years) with treatment-resistant depression (TRD) before and after approximately 1 year of STN-DBS treatment. Moreover, to gain more insight into the brain mechanism mediating the therapeutic action of STN-DBS, we utilized ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography (PET) to assess cerebral regional glucose metabolism in the patients at baseline and 1-year follow-up. Additionally, the baseline PET data from patients were compared with PET data from an age- and sex-matched control group of 16 healthy volunteers. Among them, 12 PD patients underwent post-operative follow-up PET scans. Results showed that the severity of both motor and depressive symptoms in patients with PD-TRD was reduced significantly at 1-year follow-up. Also, patients used significantly less antiparkinsonian medications and antidepressants at 1-year follow-up, as well as experiencing improved daily functioning and a better quality of life. Moreover, relative to the PET data from healthy controls, PD-TRD patients displayed widespread abnormalities in cerebral regional glucose metabolism before STN-DBS treatment, which were partially recovered at 1-year follow-up. Additionally, significant correlations were observed between the patients' improvements in depressive symptoms following STN-DBS and post-operative changes in glucose metabolism in brain regions implicated in emotion regulation. These results support the view that STN-DBS provides a promising treatment option for managing both motor and depressive symptoms in patients who suffer from PD with TRD. However, the results should be interpreted with caution due to the observational nature of the study, small sample size, and relatively short follow-up.

Disrupted Topological Organization of Resting-State Functional Brain Networks in Age-Related Hearing Loss

Purpose

Age-related hearing loss (ARHL), associated with the function of speech perception decreases characterized by bilateral sensorineural hearing loss at high frequencies, has become an increasingly critical public health problem. This study aimed to investigate the topological features of the brain functional network and structural dysfunction of the central nervous system in ARHL using graph theory.

Methods

Forty-six patients with ARHL and forty-five age, sex, and education-matched healthy controls were recruited to undergo a resting-state functional magnetic resonance imaging (fMRI) scan in this study. Graph theory was applied to analyze the topological properties of the functional connectomes by studying the local and global organization of neural networks.

Results

Compared with healthy controls, the patient group showed increased local efficiency (E_loc) and clustering coefficient (C_p) of the small-world network. Besides, the degree centrality (Dc) and nodal efficiency (Ne) values of the left inferior occipital gyrus (IOG) in the patient group showed a decrease in contrast with the healthy control group. In addition, the intra-modular interaction of the occipital lobe module and the inter-modular interaction of the parietal occipital module decreased in the patient group, which was positively correlated with Dc and Ne. The intra-modular interaction of the occipital lobe module decreased in the patient group, which was negatively correlated with the E_loc.

Conclusion

Based on fMRI and graph theory, we indicate the aberrant small-world network topology in ARHL and dysfunctional interaction of the occipital lobe and parietal lobe, emphasizing the importance of dysfunctional left IOG. These results suggest that early diagnosis and treatment of patients with ARHL is necessary, which can avoid the transformation of brain topology and decreased brain function.

Altered Brain Volume, Microstructure Metrics and Functional Connectivity Features in Multiple System Atrophy

In order to deeply understand the specific patterns of volume, microstructure, and functional changes in Multiple System Atrophy patients with cerebellar ataxia syndrome (MSA-c), we perform the current study by simultaneously applying structural (T1-weighted imaging), Diffusion tensor imaging (DTI), functional (BOLD fMRI) and extended Network-Based Statistics (extended-NBS) analysis. Twenty-nine MSA-c type patients and twenty-seven healthy controls (HCs) were involved in this study. First, we analyzed the whole brain changes of volume, microstructure, and functional connectivity (FC) in MSA-c patients. Then, we explored the correlations between significant multimodal MRI features and the total Unified Multiple System Atrophy Rating Scale (UMSARS) scores. Finally, we searched for sensitive imaging biomarkers for the diagnosis of MSA-c using support vector machine (SVM) classifier. Results showed significant grey matter atrophy in cerebellum and white matter microstructural abnormalities in cerebellum, left fusiform gyrus, right precentral gyrus and lingual gyrus. Extended-NBS analysis found two significant different connected components, featuring altered functional connectivity related to left and right cerebellar sub-regions, respectively. Moreover, the reduced fiber bundle counts at right Cerebellum_3 (Cbe3) and decreased fractional anisotropy (FA) values at bilateral Cbe9 were negatively associated with total UMSARS scores. Finally, the significant features at left Cbe9, Cbe1, and Cbe7b were found to be useful as sensitive biomarkers to differentiate MSA-c from HCs according to the SVM analysis. These findings advanced our understanding of the neural pathophysiological mechanisms of MSA from the perspective of multimodal neuroimaging.

Dynamic connectivity alterations in anterior cingulate cortex associated with suicide attempts in bipolar disorders with a current major depressive episode

OBJECTIVE

Considering that the physiological mechanism of the anterior cingulate cortex (ACC) in suicide brain remains elusive for bipolar disorder (BD) patients. The study aims to investigate the intrinsic relevance between ACC and suicide attempts (SA) through transient functional connectivity (FC).

METHODS

We enrolled 50 un-medicated BD patients with at least one SA, 67 none-suicide attempt patients (NSA) and 75 healthy controls (HCs). The sliding window approach was utilized to study the dynamic FC of ACC via resting-state functional MRI data. Subsequently, we probed into the temporal properties of dynamic FC and then estimated the relationship between dynamic characteristics and clinical variables using the Pearson correlation.

RESULTS

We found six distinct FC states in all populations, with one of them being more associated with SA. Compared with NSA and HCs, the suicide-related functional state showed significantly reduced dwell time in SA patients, accompanied by a significantly increased FC strength between the right ACC and the regions within the subcortical (SubC) network. In addition, the number of transitions was significantly increased in SA patients relative to other groups. All these altered indicators were significantly correlated with the suicide risk.

CONCLUSIONS

The results suggested that the dysfunction of ACC was relevant to SA from a dynamic FC perspective in BD patients. It highlights the temporal properties in dynamic FC of ACC that could be used as a putative target of suicide risk assessment for BD patients.

Global Functional Connectivity Analysis Indicating Dysconnectivity of the Hate Circuit in Major Depressive Disorder

Background

Abnormalities of functional connectivity (FC) in certain brain regions are closely related to the pathophysiology of major depressive disorder (MDD). Findings are inconsistent with different presuppositions in regions of interest. Our research focused on voxel-wise brain-wide FC changes in patients with MDD in an unbiased manner.

Method

We examined resting-state functional MRI in 23 patients with MDD and 26 healthy controls. Imaging data were analyzed by using global-brain FC (GFC) and used to explore the correlation of abnormal GFC values with clinical variables.

Results

Increased GFC values in the left medial superior frontal gyrus (SFGmed) and decreased GFC values in the right supplementary motor area (SMA) were observed in the patients with MDD compared with the controls. The decreased GFC values in the right SMA had a positive correlation with vitamin D and Hamilton Anxiety Scale (HAM-A) scores.

Conclusion

Abnormal GFC in the hate circuit, particularly increased GFC in the left SFGmed and decreased GFC in the right SMA, appears to be a new sight for comprehending the pathological alterations in MDD.

Diurnal mood variation symptoms in major depressive disorder associated with evening chronotype: Evidence from a neuroimaging study

BACKGROUND

Major depressive disorder (MDD) is often accompanied with classic diurnal mood variation (DMV) symptoms. Patients with DMV symptoms feel a mood improvement and prefer activities at dusk or in the evening, which is consistent with the evening chronotype. Their neural alterations are unclear. In this study, we aimed to explore the neuropathological mechanisms underlying the circadian rhythm of mood and the association with chronotype in MDD.

METHODS

A total of 126 depressed patients, including 48 with DMV, 78 without, and 67 age/gender-matched healthy controls (HC) were recruited and underwent a resting-state functional magnetic resonance imaging. Spontaneous neural activity was investigated using amplitude of low-frequency fluctuation (ALFF) and region of interest (ROI)-based functional connectivity (FC) analyses were conducted. The Morningness-Eveningness Questionnaire (MEQ) was utilized to evaluate participant chronotypes and Pearson correlations were calculated between altered ALFF/FC values and MEQ scores in patients with MDD.

RESULTS

Compared with NMV, DMV group exhibited lower MEQ scores, and increased ALFF values in the right orbital superior frontal gyrus (oSFG). We observed that increased FC between the left suprachiasmatic nucleus (SCN) and supramarginal gyrus (SMG). ALFF in the oSFG and FC of rSCN-SMG were negatively correlated with MEQ scores.

LIMITATION

Some people's chronotypes information is missing.

CONCLUSION

Patients with DMV tended to be evening type and exhibited abnormal brain functions in frontal lobes. The synergistic changes between frontotemporal lobe, SCN-SMG maybe the characteristic of patients with DMV symptoms.

Discriminating subclinical depression from major depression using multi-scale brain functional features: A radiomics analysis

BACKGROUND

The diagnosis of subclinical depression (SD) currently relies exclusively on subjective clinical scores and structured interviews, which shares great similarities with major depression (MD) and increases the risk of misdiagnosis of SD and MD. This study aimed to develop a method of disease classification for SD and MD by resting-state functional features using radiomics strategy.

METHODS

Twenty-six SD, 36 MD subjects and 33 well-matched healthy controls (HC) were recruited and underwent resting-state functional magnetic resonance imaging (rs-fMRI). A novel radiomics analysis was proposed to discriminate SD from MD. Multi-scale brain functional features were extracted to explore a comprehensive representation of functional characteristics. A two-level feature selection strategy and support vector machine (SVM) were employed for classification.

RESULTS

The overall classification accuracy among SD, MD and HC groups was 84.21%. Particularly, the model excellently distinguished SD from MD with 96.77% accuracy, 100% sensitivity, and 92.31% specificity. Moreover, features with high discriminative power to distinguish SD from MD showed a strong association with default mode network, frontoparietal network, affective network, and visual network regions.

LIMITATION

The sample size was relatively small, which may limit the application in clinical translation to some extent.

CONCLUSION

These findings demonstrated that a valid radiomics approach based on functional measures can discriminate SD from MD with a high classification performance, facilitating an objective and reliable diagnosis individually in clinical practice. Features with high discriminative power may provide insight into a profound understanding of the brain functional impairments and pathophysiology of SD and MD.

The aberrant dynamic amplitude of low-frequency fluctuations in melancholic major depressive disorder with insomnia

BACKGROUND

Insomnia is considered one of the manifestations of sleep disorders, and its intensity is linked to the treatment effect or suicidal thoughts. Major depressive disorder (MDD) is classified into various subtypes due to heterogeneous symptoms. Melancholic MDD has been considered one of the most common subtypes with special sleep features. However, the brain functional mechanisms in melancholic MDD with insomnia remain unclear.

MATERIALS AND METHODS

Melancholic MDD and healthy controls (HCs, n = 46) were recruited for the study. Patients were divided into patients with melancholic MDD with low insomnia (mMDD-LI, n = 23) and patients with melancholic MDD with high insomnia (mMDD-HI, n = 30), according to the sleep disturbance subscale of the 17-item Hamilton Depression Rating Scale. The dynamic amplitude of low-frequency fluctuation was employed to investigate the alterations of brain activity among the three groups. Then, the correlations between abnormal dALFF values of brain regions and the severity of symptoms were investigated.

RESULTS

Lower dALFF values were found in the mMDD-HI group in the right middle temporal gyrus (MTG)/superior temporal gyrus (STG) than in the mMDD-LI (p = 0.014) and HC groups (p < 0.001). Melancholic MDD groups showed decreased dALFF values than HC in the right middle occipital gyri (MOG)/superior occipital gyri (SOG), the right cuneus, the bilateral lingual gyrus, and the bilateral calcarine (p < 0.05). Lower dALFF values than HC in the left MOG/SOG and the left cuneus in melancholic MDD groups were found, but no significant difference was found between the mMDD-LI group and HC group (p = 0.079). Positive correlations between the dALFF values in the right MTG/STG and HAMD-SD scores (the sleep disturbance subscale of the HAMD-17) in the mMDD-HI group (r = 0.41, p = 0.042) were found. In the pooled melancholic MDD, the dALFF values in the right MOG/SOG and the right cuneus (r = 0.338, p = 0.019), the left MOG/SOG and the left cuneus (r = 0.299, p = 0.039), and the bilateral lingual gyrus and the bilateral calcarine (r = 0.288, p = 0.047) were positively correlated with adjusted HAMD scores.

CONCLUSION

The occipital cortex may be related to depressive symptoms in melancholic MDD. Importantly, the right MTG/STG may play a critical role in patients with melancholic MDD with more severe insomnia.

Baseline Clinical and Neuroimaging Biomarkers of Treatment Response to High-Frequency rTMS Over the Left DLPFC for Resistant Depression

BACKGROUND

Repetitive transcranial magnetic stimulation (rTMS) has proven to be an efficient treatment option for patients with treatment-resistant depression (TRD). However, the success rate of this method is still low, and the treatment outcome is unpredictable. The objective of this study was to explore clinical and structural neuroimaging factors as potential biomarkers of the efficacy of high-frequency (HF) rTMS (20 Hz) over the left dorso-lateral pre-frontal cortex (DLPFC).

METHODS

We analyzed the records of 131 patients with mood disorders who were treated with rTMS and were assessed at baseline at the end of the stimulation and at 1 month after the end of the treatment. The response is defined as a 50% decrease in the MADRS score between the first and the last assessment. Each of these patients underwent a T1 MRI scan of the brain, which was subsequently segmented with FreeSurfer. Whole-brain analyses [Query, Design, Estimate, Contrast (QDEC)] were conducted and corrected for multiple comparisons. Additionally, the responder status was also analyzed using binomial multivariate regression models. The explored variables were clinical and anatomical features of the rTMS target obtained from T1 MRI: target-scalp distance, DLPFC gray matter thickness, and various cortical measures of interest previously studied.

RESULTS

The results of a binomial multivariate regression model indicated that depression type (p = 0.025), gender (p = 0.010), and the severity of depression (p = 0.027) were found to be associated with response to rTMS. Additionally, the resistance stage showed a significant trend (p = 0.055). Whole-brain analyses on volume revealed that the average volume of the left part of the superior frontal and the caudal middle frontal regions is associated with the response status. Other MRI-based measures are not significantly associated with response to rTMS in our population.

CONCLUSION

In this study, we investigated the clinical and neuroimaging biomarkers associated with responsiveness to high-frequency rTMS over the left DLPFC in a large sample of patients with TRD. Women, patients with bipolar depressive disorder (BDD), and patients who are less resistant to HF rTMS respond better. Responders present a lower volume of the left part of the superior frontal gyrus and the caudal middle frontal gyrus. These findings support further investigation into the use of clinical variables and structural MRI as possible biomarkers of rTMS treatment response.

Dynamic changes of large-scale resting-state functional networks in major depressive disorder

Sliding window method is widely used to study the functional connectivity dynamics in brain networks. A key issue of this method is how to choose the window length and number of clusters across different window length. Here, we introduced a universal method to determine the optimal window length and number of clusters and applied it to study the dynamic functional network connectivity (FNC) in major depressive disorder (MDD). Specifically, we first extracted the resting-state networks (RSNs) in 27 medication-free MDD patients and 54 healthy controls using group independent component analysis (ICA), and constructed the dynamic FNC patterns for each subject in the window range of 10-80 repetition times (TRs) using sliding window method. Then, litekmeans algorithm was utilized to cluster the FNC patterns corresponding to each window length into 2-20 clusters. The optimal number of clusters was determined by voting method and the optimal window length was determined by identifying the most representative window length. Finally, 8 recurring FNC patterns regarded as FNC states were captured for further analyzing the dynamic attributes. Our results revealed that MDD patients showed increased mean dwell time and fraction of time spent in state #5, and the mean dwell time is correlated with depression symptom load. Additionally, compared with healthy controls, MDD patients had significantly reduced FNC within FPN in state #7. Our study reported a new approach to determine the optimal window length and number of clusters, which may facilitate the future study of the functional dynamics. These findings about MDD using dynamic FNC analyses provide new evidence to better understand the neuropathology of MDD.

Amplitude of low-frequency fluctuation (ALFF) alterations in adults with subthreshold depression after physical exercise: A resting-state fMRI study

BACKGROUND

Physical exercise has been proved to reduce the risk of major depression in Subthreshold depression (StD) individuals effectively, yet little is known about the spontaneous brain activity changes associated with physical exercise.

METHODS

A total of 70 adult subjects, including 38 StD and 32 healthy control (HC) subjects, underwent a resting-state functional magnetic resonance imaging (rs-fMRI) before and after eight-week aerobic exercise respectively. Then, the amplitude of low-frequency fluctuation (ALFF) alterations between the two groups were quantitatively analyzed.

RESULTS

Before exercise intervention, the rs-fMRI data showed increased ALFF of the right putamen in the StD group compared with HC group. After exercise intervention, there was no significant ALFF change observed between the StD and HC groups. The longitudinal ALFF differences from pre- to post- exercise intervention showed significantly decreased ALFF in the right middle and inferior occipital gyrus, right middle and inferior temporal gyrus, right fusiform gyrus (FG), while increased ALFF in the right middle cingulate, right superior parietal louble, right inferior parietal lobule (IPL) (inferior parietal gyrus and supramarginal gyrus), and bilateral precuneus in the StD group. As for HC group, the results showed that decreased ALFF in the right FG and right parahippocampus, while increased ALFF in the right precuneus, right middle cingulate, right supplementary motor area, right superior parietal lobule and right paracentral lobule in the HC group. No significant correlation between changes of ALFF and clinical scale scores in the StD group.

LIMITATIONS

The definitions of StD are varied in terms of different studies, the final sample size was relatively small, and the age range of the subjects in this study was narrow. Meanwhile, the exercise intervention trial was short-term.

CONCLUSIONS

These results further support the standpoint that physical exercise has the potential to reshape the abnormal patterns of spontaneous brain activity in adults with StD.

Resting-state connectivity studies as a marker of the acute and delayed effects of subanaesthetic ketamine administration in healthy and depressed individuals: A systematic review

Acute ketamine administration has been widely used in neuroimaging research to mimic psychosis-like symptoms. Within the last two decades, ketamine has also emerged as a potent, fast-acting antidepressant. The delayed effects of the drug, observed 2–48 h after a single infusion, are associated with marked improvements in depressive symptoms. At the systems’ level, several studies have investigated the acute ketamine effects on brain activity and connectivity; however, several questions remain unanswered around the brain changes that accompany the drug’s antidepressant effects and how these changes relate to the brain areas that appear with altered function and connectivity in depression. This review aims to address some of these questions by focusing on resting-state brain connectivity. We summarise the studies that have examined connectivity changes in treatment-naïve, depressed individuals and those studies that have looked at the acute and delayed effects of ketamine in healthy and depressed volunteers. We conclude that brain areas that are important for emotional regulation and reward processing appear with altered connectivity in depression whereas the default mode network presents with increased connectivity in depressed individuals compared to healthy controls. This finding, however, is not as prominent as the literature often assumes. Acute ketamine administration causes an increase in brain connectivity in healthy volunteers. The delayed effects of ketamine on brain connectivity vary in direction and appear to be consistent with the drug normalising the changes observed in depression. The limited number of studies however, as well as the different approaches for resting-state connectivity analysis make it very difficult to draw firm conclusions and highlight the importance of data sharing and larger future studies.

Estimating Functional Connectivity by Integration of Inherent Brain Function Activity Pattern Priors

Brain functional connectivity (FC) has shown great potential in becoming biomarkers of brain status. However, the problem of accurately estimating FC from complex-noisy fMRI time series remains unsolved. Usually, a regularization function is more appropriate in fitting the real inherent properties of the brain function activity pattern, which can further limit noise interference to improve the accuracy of the estimated result. Recently, the neuroscientists widely suggested that the inherent brain function activity pattern indicates sparse, modular and overlapping topology. However, previous studies have never considered this factual characteristic. Thus, we propose a novel method by integration of these inherent brain function activity pattern priors to estimate FC. Extensive experiments on synthetic data demonstrate that our method can more accurately estimate the FC than previous. Then, we applied the estimated FC to predict the symptom severity of depressed patients, the symptom severity is related to subtle abnormal changes in the brain function activity, a more accurate FC can more effectively capture the subtle abnormal brain function activity changes. As results, our method better than others with a higher correlation coefficient of 0.4201. Moreover, the overlapping probability of each brain region can be further explored by the proposed method.

Altered Cortical-Striatal Network in Patients With Hemifacial Spasm

Objective: Hemifacial spasm (HFS) is a kind of motor disorder, and the striatum plays a significant role in motor function. The purpose of this study was to explore the alterations of the cortical-striatal network in HFS using resting-state functional magnetic resonance imaging (fMRI). Methods: The fMRI data of 30 adult patients with primary unilateral HFS (15 left-side and 15 right-side) and 30 healthy controls were collected. Six subregions of the striatum in each hemisphere were selected for functional connectivity (FC) analysis. One-sample t-test was used to analyze the intragroup FC of the HFS group and the control group. Two-sample t-test was used to compare the difference of FC between the two groups. The correlation between the abnormal FC and severity of HFS was evaluated by using the Spearman correlation analysis. Results: Compared with the controls, the striatal subregions had altered FC with motor and orbitofrontal cortex in patients with HFS. The altered FC between striatal subregions and motor cortex was correlated with the spasm severity in patients with HFS. Conclusion: The FC of the cortical-striatal network was altered in primary HFS, and these alterations were correlated with the severity of HFS. This study indicated that the cortical-striatal network may play different roles in the underlying pathological mechanism of HFS.

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.

Dysfunction of the anterior and intermediate hippocampal functional network in major depressive disorders across the adult lifespan

Accumulating evidence indicates that structural and functional abnormalities in hippocampal formation are linked to major depressive disorder (MDD). However, the resting-state functional connectivity (RSFC) of hippocampal subfields in MDD remains unclear. This cross-sectional study aimed to investigate the RSFC of hippocampal subfields in a large sample of MDD patients. The results revealed that patients with MDD showed lower RSFC between the right anterior hippocampus and the insula, and the RSFC was inversely correlated with anxiety symptoms of depression. Depressed patients also showed decreased RSFC between the bilateral intermediate hippocampus and left nucleus accumbens (NAcc), and the hippocampus-NAcc circuit was negatively correlated with core symptoms of depression. The functional connectivity between the right anterior hippocampus and left postcentral gyrus increased with ageing in MDD patients compared with healthy controls. These findings suggest that the functional network of hippocampal subfields may underlie anxiety and core depression symptoms.

Differentiation of Cerebellum-Type and Parkinson-Type of Multiple System Atrophy by Using Multimodal MRI Parameters

Recent studies have demonstrated the structural and functional changes in patients with multiple system atrophy (MSA). However, little is known about the different parameter changes of the most vulnerable regions in different types of MSA. In this study, we collected resting-state structure, perfusion, and patients with functional magnetic resonance imaging (fMRI) data of cerebellum-type of MSA (MSA-c) and Parkinson-type of MSA (MSA-p). First, by simultaneously using voxel-based morphology (VBM), arterial spin labeling (ASL), and amplitude of low-frequency fluctuation (ALFF), we analyzed the whole brain differences of structure, perfusion, and functional activation between patients with MSA-c and MSA-p. Second, we explored the relationships among structure, perfusion, function, and the clinical variables in patients with MSA. Finally, we extracted the MRI parameters of a specific region to separate the two groups and search for a sensitive imaging biomarker. As a result, compared with patients with MSA-p type, patients with MSA-c type showed decreased structure atrophy in several cerebella and vermis subregions, reduced perfusion in bilateral cerebellum_4_5 and vermis_4_5, and an decreased ALFF values in the right lingual gyrus (LG) and fusiform (FFG). Subsequent analyses revealed the close correlations among structure, perfusion, function, and clinical variables in both MSA-c and MSA-p. Finally, the receiver operating characteristic (ROC) analysis showed that the regional cerebral blood flow (rCBF) of bilateral cerebellum_4_5/vermis_4_5 could differentiate the two groups at a relatively high accuracy, yielding the sensitivity of 100%, specificity of 79.2%, and the area under the curve (AUC) value of 0.936. These findings have important implications for understanding the underlying neurobiology of different types of MSA and added the new evidence for the disrupted rCBF, structure, and function of MSA, which may provide the potential biomarker for accurately detecting different types of patients with MSA and new ideas for the treatment of different types of MSA in the future.

Disruption of human brain connectivity networks in patients with cervical spondylotic myelopathy

Background

Brain functional plasticity and reorganization in patients with cervical spondylotic myelopathy (CSM) is increasingly being explored and validated. However, specific topological alterations in functional networks and their role in CSM brain functional reorganization remain unclear. This study investigates the topological architecture of intrinsic brain functional networks in CSM patients using graph theory.

Methods

Functional MRI was conducted on 67 CSM patients and 60 healthy controls (HCs). The topological organization of the whole-brain functional network was then calculated using theoretical graph analysis. The difference in categorical variables between groups was compared using a chi-squared test, while that between continuous variables was evaluated using a two-sample t-test. Nonparametric permutation tests were used to compare network measures between the two groups.

Results

Small-world architecture in functional brain networks were identified in both CSM patients and HCs. Compared with HCs, CSM patients showed a decreased area under the curve (AUC) of the characteristic path length (FDR q=0.040), clustering coefficient (FDR q=0.037), and normalized characteristic path length (FDR q=0.038) of the network. In contrast, there was an increased AUC of normalized clustering coefficient (FDR q=0.014), small-worldness (FDR q=0.009), and global network efficiency (FDR q=0.027) of the network. In local brain regions, nodal topological properties revealed group differences which were predominantly in the default-mode network (DMN), left postcentral gyrus, bilateral putamen, lingual gyrus, and posterior cingulate gyrus.

Conclusions

This study reported altered functional topological organization in CSM patients. Decreased nodal centralities in the visual cortex and sensory-motor regions may indicate sensory-motor dysfunction and blurred vision. Furthermore, increased nodal centralities in the cerebellum may be compensatory for sensory-motor dysfunction in CSM, while the increased DMN may indicate increased psychological processing in CSM patients.

Effects of prenatal opioid exposure on functional networks in infancy

Prenatal opioid exposure has been linked to altered neurodevelopment and visual problems such as strabismus and nystagmus. The neural substrate underlying these alterations is unclear. Resting-state functional connectivity MRI (rsfMRI) is an advanced and well-established technique to evaluate brain networks. Few studies have examined the effects of prenatal opioid exposure on resting-state network connectivity in infancy. In this pilot study, we characterized network connectivity in opioid-exposed infants (n = 19) and controls (n = 20) between 4–8 weeks of age using both a whole-brain connectomic approach and a seed-based approach. Prenatal opioid exposure was associated with differences in distribution of betweenness centrality and connection length, with positive connections unique to each group significantly longer than common connections. The unique connections in the opioid-exposed group were more often inter-network connections while unique connections in controls and connections common to both groups were more often intra-network. The opioid-exposed group had smaller network volumes particularly in the primary visual network, but similar network strength as controls. Network topologies as determined by dice similarity index were different between groups, particularly in visual and executive control networks. These results may provide insight into the neural basis for the developmental and visual problems associated with prenatal opioid exposure.

Shared and distinct homotopic connectivity changes in melancholic and non-melancholic depression

OBJECTIVE

Previous studies have revealed different neuroimaging features between melancholic and non-melancholic major depressive disorder (MDD). However, homotopic connectivity of melancholic and non-melancholic MDD remains unknown. The present study aimed to explore common and distinct homotopic connectivity patterns of melancholic and non-melancholic MDD and their associations with clinical characteristics.

METHODS

Sixty-four patients with MDD and thirty-two healthy controls were scanned by resting-state functional magnetic resonance imaging (fMRI). Voxel-mirrored homotopic connectivity (VMHC) and pattern classification were applied to analyze the imaging data.

RESULTS

Relative to healthy controls, melancholic patients displayed decreased VMHC in the fusiform gyrus, posterior cingulate cortex (PCC), superior occipital gyrus (SOG), postcentral gyrus and precentral/postcentral gyrus, and non-melancholic patients displayed decreased VMHC in the PCC. Compared with non-melancholic patients, melancholic patients displayed reduced VMHC in the precentral gyrus and precentral/postcentral gyrus. Support vector machine (SVM) results exhibited VMHC in the precentral gyrus could distinguish melancholic patients from non-melancholic patients with more than 0.6 for specificity, sensitivity and accuracy.

CONCLUSION

The study demonstrated common and distinct homotopic connectivity patterns in melancholic and non-melancholic patients. Decreased VMHC in the PCC may be a state-related change for depression, and reduced VMHC in the precentral gyrus and postcentral gyrus may be a distinctive neurobiological feature for melancholic MDD. VMHC in precentral gyrus might be served as potential imaging markers to discriminate melancholic patients from non-melancholic MDD.