Disrupted interhemispheric coordination of sensory-motor networks and insula in major depressive disorder

Modulation of cerebellar homotopic connectivity by modified electroconvulsive therapy at rest: Study of first-episode, drug-naive adolescent major depressive disorder

Previous studies of brain function alterations that are associated with modified electroconvulsive therapy (MECT) for major depressive disorder (MDD) have yielded conflicting results because of variations in treatment durations, types of antidepressants, and disease course. Consequently, predicting the efficacy of MECT remains challenging. Thirty patients with first-episode, drug-naive adolescent MDD and 34 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging and neuropsychological tests. The patients received MECT and underwent scanning at two time points (baseline and posttreatment). Voxel-mirrored homotopic connectivity (VMHC), support vector machine (SVM), and support vector regression (SVR) analyses were employed to analyze the imaging data. Compared with HCs, patients at baseline exhibited greater VMHC in the cerebellum_2 and cerebellum_8. Following treatment, patients exhibited the restoration of normal VMHC values. Additionally, SVM and receiver operating characteristic curve analyses revealed that VMHC values in the cerebellum_2 could differentiate MDD patients from HCs with 73.85 % accuracy, 70.00% sensitivity, 79.41 % specificity, and an area under the curve of 0.7486. Furthermore, the SVR results indicated a significant association between predicted and actual symptomatic improvement based on the reduction ratio of Hamilton Depression Rating Scale-17 total scores (R2 = 0.5269, P < 0.0001). This study provides evidence that MECT modulates homotopic connectivity of the cerebellum_2 in first-episode, drug-naive adolescent MDD. Moreover, VMHC values in the cerebellum_2 may serve as a valuable neuroimaging biomarker for distinguishing MDD from HCs and potentially predicting early treatment response in MDD.

Differences in cognitive deficits and brain functional impairments between patients with first-episode and recurrent depression

BACKGROUND

Accumulating evidence shows that cognitive deficits are common in patients with major depressive disorder (MDD). However, the specific differences in cognitive impairment and brain functional alterations between first-episode depression (FED) and recurrent major depression (RMD) remain unclear, as do the relationships among these factors.

METHODS

A total of 43 RMD and 41 FED patients were included in this study. All the patients underwent examinations of resting-state functional magnetic resonance imaging (fMRI), event-related potential (ERP) measurements, and a series of standardised neuropsychological tests, including event-based (EBPM) and time-based (TBPM) prospective memory tasks, the Semantic Fluency Test (SFT), and the Continuous Performance Task-Identical Pairs (CPT-IP). Two-sample t-tests were used to compare cognitive functioning, ERP parameters, and brain functional indices between FED and RMD groups. Correlation analyses were performed to explore the associations between these variables.

RESULTS

Compared with FED patients, those with RMD displayed poorer CPT-IP performance, lower prospective memory (EBPM) scores, lower SFT performance, and prolonged P300 latency (all P < 0.05). Moreover, neuroimaging data analysis revealed increased regional neural activity in the right inferior temporal gyrus (ITG), alongside decreased interhemispheric functional connectivity in the bilateral ITG in RMD relative to FED. Correlation analyses indicated that these functional changes were significantly associated with the observed cognitive deficits.

CONCLUSION

Our data demonstrated more pronounced cognitive deficits and brain functional impairments in RMD relative to FED as well as their potential links. These findings not only elucidate the neural mechanisms underlying cognitive deficits in MDD, but also inform future treatment and prevention of cognitive dysfunction in patients suffering from MDD.

CLINICAL TRIAL NUMBER

Not applicable.

The relationship between regional homogeneity in resting-state functional magnetic resonance imaging and cognitive function in depressive disorders with migraine

Patients with depressive disorder with migraine (DDWM) are common, yet the neural mechanisms and brain function changes associated with this comorbidity remain partially understood. This study explores regional homogeneity (ReHo) abnormalities in resting-state functional magnetic resonance imaging (fMRI) and cognitive function in DDWM patients. We recruited 29 patients with DDWM, 34 patients with depressive disorder without migraine (DDWOM), and 43 matched healthy controls (HC). All participants underwent rs-fMRI scans, and imaging data were analyzed using ReHo. Cognitive function was assessed with the Repeatable Battery for the Assessment of Neuropsychological Status. We also employed support vector machine (SVM) analysis to evaluate whether abnormal ReHo values could distinguish DDWM. he DDWM group exhibited significantly lower ReHo values in the left cuneus and left calcarine compared to the DDWOM group. ReHo values in these regions were negatively correlated with pain scores on the Visual Analogue Scale (r = - 0.3628, p = 0.0001; r = - 0.3142, p = 0.001) and positively correlated with the List_Recall score on RBANS (r = 0.260, p = 0.007). SVM analysis indicated that the left cuneus ReHo value could distinguish DDWM from DDWOM with 78.09% accuracy, 87.66% sensitivity, and 74.33% specificity. The left cuneus and left calcarine are potential biomarkers for migraine symptoms in DDWM, with the left cuneus affecting cognitive function related to memory.

Phenomena of hypo- and hyperconnectivity in basal ganglia-thalamo-cortical circuits linked to major depression: a 7T fMRI study

Major depressive disorder (MDD) typically manifests itself in depressed affect, anhedonia, low energy, and additional symptoms. Despite its high global prevalence, its pathophysiology still gives rise to questions. Current research places alterations in functional connectivity among MDD's most promising biomarkers. However, given the heterogeneity of previous findings, the use of higher-resolution imaging techniques, like ultra-high field (UHF) fMRI (≥7 Tesla, 7T), may offer greater specificity in delineating fundamental impairments. In this study, 7T UHF fMRI scans were conducted on 31 MDD patients and 27 age-gender matched healthy controls to exploratorily contrast cerebral resting-state functional connectivity patterns between both groups. The CONN toolbox was used to generate functional network connectivity (FNC) analysis based on the region of interest (ROI)-to-ROI correlations in order to enable the identification of clusters of significantly different connections. Correction for multiple comparisons was implemented at the cluster level using a false discovery rate (FDR). The analysis revealed three significant clusters differentiating MDD patients and healthy controls. In Clusters 1 and 2, MDD patients exhibited between-network hypoconnectivity in basal ganglia-cortical pathways as well as hyperconnectivity in thalamo-cortical pathways, including several individual ROI-to-ROI connections. In Cluster 3, they showed increased occipital interhemispheric within-network connectivity. These findings suggest that alterations in basal ganglia-thalamo-cortical circuits play a substantial role in the pathophysiology of MDD. Furthermore, they indicate potential MDD-related deficits relating to a combination of perception (vision, audition, and somatosensation) as well as more complex functions, especially social-emotional processing, modulation, and regulation. It is anticipated that these findings might further inform more accurate clinical procedures for addressing MDD.

Differences of regional homogeneity and cognitive function between psychotic depression and drug-naïve schizophrenia

BACKGROUND

Psychotic depression (PD) and schizophrenia (SCZ) share overlapping symptoms yet differ in etiology, progression, and treatment approaches. Differentiating these disorders through symptom-based diagnosis is challenging, emphasizing the need for a clearer understanding of their distinct cognitive and neural mechanisms.

AIM

This study aims to compare cognitive impairments and brain functional activities in PD and SCZ to pinpoint distinguishing characteristics of each disorder.

METHODS

We evaluated cognitive function in 42 PD and 30 SCZ patients using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and resting-state functional magnetic resonance imaging (rs-fMRI). Regional homogeneity (ReHo) values were derived from rs-fMRI data, and group differences in RBANS scores were analyzed. Additionally, Pearson correlation analysis was performed to assess the relationship between cognitive domains and brain functional metrics.

RESULTS

(1) The SCZ group showed significantly lower RBANS scores than the PD group across all cognitive domains, particularly in visuospatial/constructional ability and delayed memory (p < 0.05); (2) The SCZ group exhibited a significantly higher ReHo value in the left precuneus compared to the PD group (p < 0.05); (3) A negative correlation was observed between visuospatial construction, delayed memory scores, and the ReHo value of the left precuneus.

CONCLUSION

Cognitive impairment is more pronounced in SCZ than in PD, with marked deficits in visuospatial and memory domains. Enhanced left precuneus activity further differentiates SCZ from PD and correlates with cognitive impairments in both disorders, providing neuroimaging-based evidence to aid differential diagnosis and insights into cognitive dysfunction mechanisms, while also paving a clearer path for psychiatric research.

Temporal dynamic alterations of regional homogeneity in major depressive disorder: a study integrating machine learning

Previous studies have found alterations in the local regional homogeneity of brain activity in individuals diagnosed with major depressive disorder. However, many studies have failed to consider that even during resting states, brain activity is dynamic and time-varying. The lack of investigation into the dynamic regional homogeneity has hindered the discovery of biomarkers for depression. This study aimed to assess the utility of the dynamic regional homogeneity by a machine learning model (support vector machine). Sixty-five individuals with dynamic regional homogeneity and 57 healthy controls participated in resting-state functional magnetic resonance rescanning and scale estimating. The dynamic regional homogeneity and receiver operating characteristic curve methods were used for analysis of the imaging data. Relative to healthy controls, major depressive disorder patients displayed increased dynamic regional homogeneity values in the left precuneus and right postcentral gyrus. Additionally, receiver operating characteristic curve results of the dynamic regional homogeneity values in the left precuneus and right postcentral gyrus could distinguish major depressive disorder patients from healthy controls; furthermore, changes in the dynamic regional homogeneity were correlated with depression severity.

Potential correlations between abnormal homogeneity of default mode network and personality or lipid level in major depressive disorder

BACKGROUND

Default mode network (DMN) is one of the most recognized resting-state networks in major depressive disorder (MDD). However, the homogeneity of this network in MDD remains incompletely explored. Therefore, this study aims to determine whether there is abnormal network homogeneity (NH) of the DMN in MDD patients. At the same time, correlations between clinical variables and brain functional connectivity are examined.

METHODS

We enrolled 42 patients diagnosed with MDD and 42 HCs. A variety of clinical variables were collected, and data analysis was conducted using the NH and independent component analysis methods.

RESULTS

The study shows that MDD patients have higher NH values in the left superior medial prefrontal cortex (MPFC) and left posterior cingulate cortex (PCC) compared to HCs. Additionally, there is a positive correlation between NH values of the left superior MPFC and Eysenck Personality Questionnaire values. NH values of the left PCC are positively linked to CHOL levels, LDL levels, and utilization scores. However, these correlations lose significance after the Bonferroni correction.

CONCLUSION

Our findings indicate the presence of abnormal DMN homogeneity in MDD, underscoring the significance of DMN in the pathophysiology of MDD. Simultaneously, the study provides preliminary evidence for the correlation between clinical variables and brain functional connectivity.

Distinct resting-state effective connectivity of large-scale networks in first-episode and recurrent major depression disorder: evidence from the REST-meta-MDD consortium

Introduction

Previous studies have shown disrupted effective connectivity in the large-scale brain networks of individuals with major depressive disorder (MDD). However, it is unclear whether these changes differ between first-episode drug-naive MDD (FEDN-MDD) and recurrent MDD (R-MDD).

Methods

This study utilized resting-state fMRI data from 17 sites in the Chinese REST-meta-MDD project, consisting of 839 patients with MDD and 788 normal controls (NCs). All data was preprocessed using a standardized protocol. Then, we performed a granger causality analysis to calculate the effectivity connectivity (EC) within and between brain networks for each participant, and compared the differences between the groups.

Results

Our findings revealed that R-MDD exhibited increased EC in the fronto-parietal network (FPN) and decreased EC in the cerebellum network, while FEDN-MDD demonstrated increased EC from the sensorimotor network (SMN) to the FPN compared with the NCs. Importantly, the two MDD subgroups displayed significant differences in EC within the FPN and between the SMN and visual network. Moreover, the EC from the cingulo-opercular network to the SMN showed a significant negative correlation with the Hamilton Rating Scale for Depression (HAMD) score in the FEDN-MDD group.

Conclusion

These findings suggest that first-episode and recurrent MDD have distinct effects on the effective connectivity in large-scale brain networks, which could be potential neural mechanisms underlying their different clinical manifestations.

Abnormal voxel-mirrored homotopic connectivity in first-episode major depressive disorder using fMRI: a machine learning approach

Objective

To explore the interhemispheric information synergy ability of the brain in major depressive disorder (MDD) patients by applying the voxel-mirrored homotopic connectivity (VMHC) method and further explore the potential clinical diagnostic value of VMHC metric by a machine learning approach.

Methods

52 healthy controls and 48 first-episode MDD patients were recruited in the study. We performed neuropsychological tests and resting-state fMRI scanning on all subjects. The VMHC values of the symmetrical interhemispheric voxels in the whole brain were calculated. The VMHC alterations were compared between two groups, and the relationship between VMHC values and clinical variables was analyzed. Then, abnormal brain regions were selected as features to conduct the classification model by using the support vector machine (SVM) approach.

Results

Compared to the healthy controls, MDD patients exhibited decreased VMHC values in the bilateral middle frontal gyrus, fusiform gyrus, medial superior frontal gyrus and precentral gyrus. Furthermore, the VMHC value of the bilateral fusiform gyrus was positively correlated with the total Hamilton Depression Scale (HAMD). Moreover, SVM analysis displayed that a combination of all clusters demonstrated the highest area under the curve (AUC) of 0.87 with accuracy, sensitivity, and specificity values of 86.17%, 76.74%, and 94.12%, respectively.

Conclusion

MDD patients had reduced functional connectivity in the bilateral middle frontal gyrus, fusiform gyrus, medial superior frontal gyrus and precentral gyrus, which may be related to depressive symptoms. The abnormality in these brain regions could represent potential imaging markers to distinguish MDD patients from healthy controls.

Deviant spontaneous neural activity as a potential early-response predictor for therapeutic interventions in patients with schizophrenia

Objective

Previous studies have established significant differences in the neuroimaging characteristics between healthy controls (HCs) and patients with schizophrenia (SCZ). However, the relationship between homotopic connectivity and clinical features in patients with SCZ is not yet fully understood. Furthermore, there are currently no established neuroimaging biomarkers available for the diagnosis of SCZ or for predicting early treatment response. The aim of this study is to investigate the association between regional homogeneity and specific clinical features in SCZ patients.

Methods

We conducted a longitudinal investigation involving 56 patients with SCZ and 51 HCs. The SCZ patients underwent a 3-month antipsychotic treatment. Resting-state functional magnetic resonance imaging (fMRI), regional homogeneity (ReHo), support vector machine (SVM), and support vector regression (SVR) were used for data acquisition and analysis.

Results

In comparison to HCs, individuals with SCZ demonstrated reduced ReHo values in the right postcentral/precentral gyrus, left postcentral/inferior parietal gyrus, left middle/inferior occipital gyrus, and right middle temporal/inferior occipital gyrus, and increased ReHo values in the right putamen. It is noteworthy that there was decreased ReHo values in the right inferior parietal gyrus after treatment compared to baseline data.

Conclusion

The observed decrease in ReHo values in the sensorimotor network and increase in ReHo values in the right putamen may represent distinctive neurobiological characteristics of patients with SCZ, as well as a potential neuroimaging biomarker for distinguishing between patients with SCZ and HCs. Furthermore, ReHo values in the sensorimotor network and right putamen may serve as predictive indicators for early treatment response in patients with SCZ.