Background The neural correlate of cognitive deficits in bipolar disorder (BD) is an issue that warrants further investigation. However, relatively few studies have examined the intrinsic functional connectivity (FC) underlying cognitive deficits involving sustained attention and executive function at both the region and network levels, as well as the different relationships between connectivity patterns and cognitive performance, in BD patients and healthy controls (HCs). Methods Patients with BD (n = 59) and HCs (n = 52) underwent structural and resting-state functional magnetic resonance imaging and completed the Wisconsin Card Sorting Test (WCST), the continuous performance test and a clinical assessment. A seed-based approach was used to evaluate the intrinsic FC alterations in three core neurocognitive networks (the default mode network [DMN], the central executive network [CEN] and the salience network [SN]). Finally, we examined the relationship between FC and cognitive performance by using linear regression analyses. Results Decreased FC was observed within the DMN, in the DMN-SN and DMN-CEN and increased FC was observed in the SN-CEN in BD. The alteration direction of regional FC was consistent with that of FC at the brain network level. Decreased FC between the left posterior cingulate cortex and right anterior cingulate cortex was associated with longer WCST completion time in BD patients (but not in HCs). Conclusions These findings emphasize the dominant role of the DMN in the psychopathology of BD and provide evidence that cognitive deficits in BD may be associated with aberrant FC between the anterior and posterior DMN.
Objective Bulimia nervosa (BN) is an eating disorder associated with the dysfunction of intrinsic brain networks. However, whether the network disruptions in BN patients manifest as dysconnectivity or imbalances of network modular segregation remains unclear. Method We collected data from 41 women with BN and 41 matched healthy control (HC) women. We performed graph theory analysis based on resting‐state functional magnetic resonance imaging (RS‐fMRI) data; then, we computed the participation coefficient (PC) among brain modules to characterize the modular segregation for the BN and HC groups. The number of intra‐ and inter‐modular connections was calculated to explain the PC changes. Additionally, we examined the potential associations of the measures mentioned above with clinical variables within the BN group. Results Compared with the HC group, the BN group showed significantly decreased PC in the fronto‐parietal network (FPN), cingulo‐opercular network (CON), and cerebellum (Cere). Additionally, the number of intra‐modular connections of the default mode network (DMN) and the number of the inter‐modular connections between the DMN and CON, FPN and Cere, and CON and Cere in the BN group were lower than those in the HC group. The nodal level analysis showed that the BN group had a decreased PC of the anterior prefrontal cortex (aPFC), dorsal frontal cortex (dFC), inferior parietal lobule (IPL), thalamus, and angular gyrus. Further, these metrics were significantly correlated with clinical variables in the BN group. Discussion These findings may provide novel insights to capture atypical topologies associated with pathophysiology mechanisms and clinical symptoms underlying BN.
Major depressive disorder (MDD) is associated with functional disturbances in subcortical regions. However, little is known about how the subcortical functional network relates to depressive symptom profile and treatment outcome. In this study, we aimed to investigate associations among subcortical connectivity, clinical symptoms and antidepressant response in MDD using multivariate methods. Data for the present study were derived from the Towards Neurobiology-based Diagnosis and Treatment of Affective Disorders (TNDTAD), which is a naturalistic prospective study of mood disorders (NCT03294525). Medication-free participants with MDD (n = 135) underwent a functional magnetic resonance imaging scan at baseline and completed posttreatment clinical assessment after 8 weeks of antidepressant monotherapy. We used partial least squares (PLS) analysis to explore associations between subcortical connectivity and symptom profile. Replication was undertaken in an independent sample (n = 74). We also investigated the association between the observed subcortical connectivity pattern and treatment outcome in the discovery sample. A distinctive subcortical connectivity pattern, critically involving dorsal striatum and thalamus, was associated with negative affect. This association was partly replicated in the independent sample. Lower composite functional connectivity score (reflecting the connectivity pattern) at baseline predicted greater symptom improvement after 8 weeks of antidepressant treatment. The emphasis here on the role of dorsal striatum and thalamus consolidates prior work of subcortical connectivity in MDD. The findings provide insight into the pathogenesis of MDD, linking subcortical functional connectivity with negative affect. However, while connectivity pattern significantly predicted treatment outcome, the low odds ratio suggests that finding predictive biomarkers for depression remains an aspiration.
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