Molecular basis underlying default mode network functional abnormalities in postpartum depression with and without anxiety.

Although Postpartum depression (PPD) and PPD with anxiety (PPD-A) have been well characterized as functional disruptions within or between multiple brain systems, however, how to quantitatively delineate brain functional system irregularity and the molecular basis of functional abnormalities in PPD and PPD-A remains unclear. Here, brain sample entropy (SampEn), resting-state functional connectivity (RSFC), transcriptomic and neurotransmitter density data were used to investigate brain functional system irregularity, functional connectivity abnormalities and associated molecular basis for PPD and PPD-A. PPD-A exhibited higher SampEn in medial prefrontal cortex (MPFC) and posterior cingulate cortex (PPC) than healthy postnatal women (HPW) and PPD while PPD showed lower SampEn in PPC compared to HPW and PPD-A. The functional connectivity analysis with MPFC and PPC as seed areas revealed decreased functional couplings between PCC and paracentral lobule and between MPFC and angular gyrus in PPD compared to both PPD-A and HPW. Moreover, abnormal SampEn and functional connectivity were associated with estrogenic level and clinical symptoms load. Importantly, spatial association analyses between functional changes and transcriptome and neurotransmitter density maps revealed that these functional changes were primarily associated with synaptic signaling, neuron projection, neurotransmitter level regulation, amino acid metabolism, cyclic adenosine monophosphate (cAMP) signaling pathways, and neurotransmitters of 5-hydroxytryptamine (5-HT), norepinephrine, glutamate, dopamine and so on. These results reveal abnormal brain entropy and functional connectivities primarily in default mode network (DMN) and link these changes to transcriptome and neurotransmitters to establish the molecular basis for PPD and PPD-A for the first time. Our findings highlight the important role of DMN in neuropathology of PPD and PPD-A.

Connectome-based model predicts individual differences in propensity to trust.

Trust constitutes a fundamental basis of human society and plays a pivotal role in almost every aspect of human relationships. Although enormous interest exists in determining the neuropsychological underpinnings of a person's propensity to trust utilizing task-based fMRI; however, little progress has been made in predicting its variations by task-free fMRI based on whole-brain resting-state functional connectivity (RSFC). Here, we combined a one-shot trust game with a connectome-based predictive modeling approach to predict propensity to trust from whole-brain RSFC. We demonstrated that individual variations in the propensity to trust were primarily predicted by RSFC rooted in the functional integration of distributed key nodes-caudate, amygdala, lateral prefrontal cortex, temporal-parietal junction, and the temporal pole-which are part of domain-general large-scale networks essential for the motivational, affective, and cognitive aspects of trust. We showed, further, that the identified brain-behavior associations were only evident for trust but not altruistic preferences and that propensity to trust (and its underlying neural underpinnings) were modulated according to the extent to which a person emphasizes general social preferences (i.e., horizontal collectivism) rather than general risk preferences (i.e., trait impulsiveness). In conclusion, the employed data-driven approach enables to predict propensity to trust from RSFC and highlights its potential use as an objective neuromarker of trust impairment in mental disorders.

Resting-State Functional Connectivity Underlying Costly Punishment: A Machine-Learning Approach.

A large number of studies have demonstrated costly punishment to unfair events across human societies. However, individuals exhibit a large heterogeneity in costly punishment decisions, whereas the neuropsychological substrates underlying the heterogeneity remain poorly understood. Here, we addressed this issue by applying a multivariate machine-learning approach to compare topological properties of resting-state brain networks as a potential neuromarker between individuals exhibiting different punishment propensities. A linear support vector machine classifier obtained an accuracy of 74.19% employing the features derived from resting-state brain networks to distinguish two groups of individuals with different punishment tendencies. Importantly, the most discriminative features that contributed to the classification were those regions frequently implicated in costly punishment decisions, including dorsal anterior cingulate cortex (dACC) and putamen (salience network), dorsomedial prefrontal cortex (dmPFC) and temporoparietal junction (mentalizing network), and lateral prefrontal cortex (central-executive network). These networks are previously implicated in encoding norm violation and intentions of others and integrating this information for punishment decisions. Our findings thus demonstrated that resting-state functional connectivity (RSFC) provides a promising neuromarker of social preferences, and bolster the assertion that human costly punishment behaviors emerge from interactions among multiple neural systems.

Alterations in gray matter volume due to unilateral hearing loss.

Although extensive research on neural plasticity resulting from hearing deprivation has been conducted, the direct influence of compromised audition on the auditory cortex and the potential impact of long durations of incomplete sensory stimulation on the adult cortex are still not fully understood. In this study, using voxel-based morphometry, we evaluated gray matter (GM) volume changes that may be associated with reduced hearing ability and the duration of hearing impairment in 42 unilateral hearing loss (UHL) patients with acoustic neuromas compared to 24 normal controls. We found significant GM volume increases in the somatosensory and motor systems and GM volume decreases in the auditory (i.e., Heschl's gyrus) and visual systems (i.e., the calcarine cortex) in UHL patients. The GM volume decreases in the primary auditory cortex (i.e., superior temporal gyrus and Heschl's gyrus) correlated with reduced hearing ability. Meanwhile, the GM volume decreases in structures involving high-level cognitive control functions (i.e., dorsolateral prefrontal cortex and anterior cingulate cortex) correlated positively with hearing loss duration. Our findings demonstrated that the severity and duration of UHL may contribute to the dissociated morphology of auditory and high-level neural structures, providing insight into the brain's plasticity related to chronic, persistent partial sensory loss.

[Investigation of satisfactory rate in patients with body dysmorphic disorder after cosmetic surgery].

OBJECTIVE: To explore the satisfactory rate in patients with body dysmorphic disorder (BDD) after cosmetic surgery. METHODS: We designed a questionnaire to investigate the postoperative satisfactory rate in patients with BDD and without BDD. RESULTS: There was significant difference in postoperative satisfactory rate between patients with BDD and without BDD. CONCLUSION: The patients with BDD have a lower satisfactory rate, which is even worse after repeated surgery.