Altered brain regional homogeneity is associated with cognitive dysfunction in first-episode drug-naive major depressive disorder: A resting-state fMRI study

Data integration with Fusion Searchlight: Classifying brain states from resting-state fMRI

Resting-state fMRI captures spontaneous neural activity characterized by complex spatiotemporal dynamics. Various metrics, such as local and global brain connectivity and low-frequency amplitude fluctuations, quantify distinct aspects of these dynamics. However, these measures are typically analyzed independently, overlooking their interrelations and potentially limiting analytical sensitivity. Here, we introduce the Fusion Searchlight (FuSL) framework, which integrates complementary information from multiple resting-state fMRI metrics. We demonstrate that combining these metrics enhances the accuracy of pharmacological treatment prediction from rs-fMRI data, enabling the identification of additional brain regions affected by sedation with alprazolam. Furthermore, we leverage explainable AI to delineate the differential contributions of each metric, which additionally improves spatial specificity of the searchlight analysis. Moreover, this framework can be adapted to combine information across imaging modalities or experimental conditions, providing a versatile and interpretable tool for data fusion in neuroimaging.

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.

Aberrant resting-state voxel-mirrored homotopic connectivity in major depressive disorder with and without anxiety

OBJECTIVE

Prior researchers have identified distinct differences in functional connectivity neuroimaging characteristics among MDD patients. However, the auxiliary diagnosis and subtype differentiation roles of VMHC values in MDD patients have yet to be fully understood. We aim to explore the separating ability of VMHC values in patients with anxious MDD or with non-anxious MDD and HCs.

METHODS

We recruited 90 patients with anxious MDD, 69 patients with non-anxious MDD and 84 HCs. We collected a set of clinical variables included HAMD-17 scores, HAMA scores and rs-fMRI data. The data were analyzed combining difference analysis, SVM, correlation analysis and ROC analysis.

RESULTS

Relative to HCs, non-anxious MDD patients displayed significant lower VMHC values in the insula and PCG, and anxious MDD patients displayed a significant decrease in VMHC values in the cerebellum_crus2, STG, postCG, MFG and IFG. Compared with non-anxious MDD patients, the anxious MDD showed significant enhanced VMHC values in the PCG. The VMHC values in the insula and cerebellum_crus2 regions showed a better ability to discriminate HCs from patients with non-anxious MDD or with anxious MDD. The VMHC values in PCG showed a better ability to discriminate patients with anxious MDD and non-anxious MDD patients.

CONCLUSION

The VMHC values in the insula and cerebellum_crus2 regions could be served as imaging markers to differentiate HCs from patients with non-anxious MDD or with anxious MDD respectively. And the VMHC values in the PCG could be used to discriminate patients with anxious MDD from the non-anxious MDD patients.

An objective quantitative diagnosis of depression using a local-to-global multimodal fusion graph neural network

This study developed an artificial intelligence (AI) system using a local-global multimodal fusion graph neural network (LGMF-GNN) to address the challenge of diagnosing major depressive disorder (MDD), a complex disease influenced by social, psychological, and biological factors. Utilizing functional MRI, structural MRI, and electronic health records, the system offers an objective diagnostic method by integrating individual brain regions and population data. Tested across cohorts from China, Japan, and Russia with 1,182 healthy controls and 1,260 MDD patients from 24 institutions, it achieved a classification accuracy of 78.75%, an area under the receiver operating characteristic curve (AUROC) of 80.64%, and correctly identified MDD subtypes. The system further discovered distinct brain connectivity patterns in MDD, including reduced functional connectivity between the left gyrus rectus and right cerebellar lobule VIIB, and increased connectivity between the left Rolandic operculum and right hippocampus. Anatomically, MDD is associated with thickness changes of the gray and white matter interface, indicating potential neuropathological conditions or brain injuries.

The differential orbitofrontal activity and connectivity between atypical and typical major depressive disorder

OBJECTIVE

Atypical major depressive disorder (MDD) is a distinct subtype of MDD, characterized by increased appetite and/or weight gain, excessive sleep, leaden paralysis, and interpersonal rejection sensitivity. Delineating different neural circuits associated with atypical and typical MDD would better inform clinical personalized interventions.

METHODS

Using resting-state fMRI, we investigated the voxel-level regional homogeneity (ReHo) and functional connectivity (FC) in 55 patients with atypical MDD, 51 patients with typical MDD, and 49 healthy controls (HCs). Support vector machine (SVM) approaches were applied to examine the validity of the findings in distinguishing the two types of MDD.

RESULTS

Compared to patients with typical MDD and HCs, patients with atypical MDD had increased ReHo values in the right lateral orbitofrontal cortex (OFC) and enhanced FC between the right lateral OFC and right dorsolateral prefrontal cortex (dlPFC), and between the right striatum and left OFC. The ReHo in the right lateral OFC and the significant FCs found were significantly correlated with body mass index (BMI) in all groups of participants with MDD. The connectivity of the right striatum and left OFC was positively correlated with the retardation scores in the atypical MDD group. Using the ReHo of the right lateral OFC as a feature, we achieved 76.42% accuracy to differentiate atypical MDD from typical MDD.

CONCLUSION

Our findings show that atypical MDD might be associated with altered OFC activity and connectivity. Furthermore, our findings highlight the key role of lateral OFC in atypical MDD, which may provide valuable information for future personalized interventions.