Distinct MRI-based functional and structural connectivity for antidepressant response prediction in major depressive disorder.

OBJECTIVE: Emerging studies have identified treatment-related connectome predictors in major depressive disorder (MDD). However, quantifying treatment-responsive patterns in structural connectivity (SC) and functional connectivity (FC) simultaneously remains underexplored. We aimed to evaluate whether spatial distributions of FC and SC associated treatment responses are shared or unique. METHODS: Diffusion tensor imaging and resting-state functional magnetic resonance imaging were collected from 210 patients with MDD at baseline. We separately developed connectome-based prediction models (CPM) to predict reduction of depressive severity after 6-week monotherapy based on structural, functional, and combined connectomes, then validated them on the external dataset. We identified the predictive SC and FC from CPM with high occurrence frequencies during the cross-validation. RESULTS: Structural connectomes (r = 0.2857, p < 0.0001), functional connectomes (r = 0.2057, p = 0.0025), and their combined CPM (r = 0.4, p < 0.0001) can significantly predict a reduction of depressive severity. We didn't find shared connectivity between predictive FC and SC. Specifically, the most predictive FC stemmed from the default mode network, while predictive SC was mainly characterized by within-network SC of fronto-limbic networks. CONCLUSIONS: These distinct patterns suggest that SC and FC capture unique connectivity concerning the antidepressant response. SIGNIFICANCE: Our findings provide comprehensive insights into the neurophysiology of antidepressants response.

Neuroanatomical and functional substrates of the hypomanic personality trait and its prediction on aggression

Hypomanic personality manifests a close link with several psychiatric disorders and its abnormality is a risk indicator for developing bipolar disorders. We systematically investigated the potential neuroanatomical and functional substrates underlying hypomanic personality trait (HPT) and its sub-dimensions (i.e., Social Vitality, Mood Volatility, and Excitement) combined with structural and functional imaging data as well as their corresponding brain networks in a large non-clinical sample across two studies (n = 464). Behaviorally, HPT, specifically Mood Volatility and Excitement, was positively associated with aggressive behaviors in both studies. Structurally, sex-specific morphological characteristics were further observed in the motor and top-down control networks especially for Mood Volatility, although HPT was generally positively associated with grey matter volumes (GMVs) in the prefrontal, temporal, visual, and limbic systems. Functionally, brain activations related to immediate or delayed losses were found to predict individual variability in HPT, specifically Social Vitality and Excitement, on the motor and prefrontal-parietal cortices. Topologically, connectome-based prediction model analysis further revealed the predictive role of individual-level morphological and resting-state functional connectivity on HPT and its sub-dimensions, although it did not reveal any links with general brain topological properties. GMVs in the temporal, limbic (e.g., amygdala), and visual cortices mediated the effects of HPT on behavioral aggression. These findings suggest that the imbalance between motor and control circuits may be critical for HPT and provide novel insights into the neuroanatomical, functional, and topological mechanisms underlying the specific temperament and its impacts on aggression. (AU)

Neuroanatomical and functional substrates of the hypomanic personality trait and its prediction on aggression.

Hypomanic personality manifests a close link with several psychiatric disorders and its abnormality is a risk indicator for developing bipolar disorders. We systematically investigated the potential neuroanatomical and functional substrates underlying hypomanic personality trait (HPT) and its sub-dimensions (i.e., Social Vitality, Mood Volatility, and Excitement) combined with structural and functional imaging data as well as their corresponding brain networks in a large non-clinical sample across two studies (n = 464). Behaviorally, HPT, specifically Mood Volatility and Excitement, was positively associated with aggressive behaviors in both studies. Structurally, sex-specific morphological characteristics were further observed in the motor and top-down control networks especially for Mood Volatility, although HPT was generally positively associated with grey matter volumes (GMVs) in the prefrontal, temporal, visual, and limbic systems. Functionally, brain activations related to immediate or delayed losses were found to predict individual variability in HPT, specifically Social Vitality and Excitement, on the motor and prefrontal-parietal cortices. Topologically, connectome-based prediction model analysis further revealed the predictive role of individual-level morphological and resting-state functional connectivity on HPT and its sub-dimensions, although it did not reveal any links with general brain topological properties. GMVs in the temporal, limbic (e.g., amygdala), and visual cortices mediated the effects of HPT on behavioral aggression. These findings suggest that the imbalance between motor and control circuits may be critical for HPT and provide novel insights into the neuroanatomical, functional, and topological mechanisms underlying the specific temperament and its impacts on aggression.