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Previous literature has established the presence of sex differences in behavioral inhibition as well as its neural substrates and related disease risk. However, there is limited evidence that speaks directly to the question of whether or not there are sex-dependent associations between behavioral inhibition and resting-state brain function and, if so, how they are modulated by the underlying molecular mechanisms. We computed functional connectivity density (FCD) using resting-state functional MRI data to examine their associations with behavioral inhibition ability measured using a Go/No-Go task across a large cohort of 510 healthy young adults. Then, we examined the spatial relationships of the FCD correlates of behavioral inhibition with gene expression and neurotransmitter atlases to explore their potential genetic architecture and neurochemical basis. A significant negative correlation between behavioral inhibition and FCD in the left superior parietal lobule was found in females but not males. Further spatial correlation analyses demonstrated that the identified neural correlates of behavioral inhibition were associated with expression of gene categories predominantly implicating essential components of the cerebral cortex (glial cell, neuron, axon, dendrite, and synapse) and ion channel activity, as well as were linked to the serotonergic system. Our findings may not only yield important insights into the molecular mechanisms underlying the female-specific neural substrates of behavioral inhibition, but also provide a critical context for understanding how biological sex might contribute to variation in behavioral inhibition and its related disease risk., Competing Interests: Declaration of Competing Interest The authors declare no conflict of interests., (Copyright © 2023. Published by Elsevier Inc.)

Previous research has demonstrated that serum lipid profile is associated with cognitive function as well as brain structure and function in middle-aged, elderly, and clinical populations. However, the nature and extent of lipids-brain-cognition relationships in young adulthood are largely unknown. In this study, 157 healthy young adults underwent resting-state functional MRI scans. Functional connectivity between and within 14 functional networks were calculated using independent component analysis. Peripheral venous blood samples were collected to measure serum lipids. Working memory was assessed using a 3-back task. Linear regression, correlation, and mediation analyses were conducted to test for potential associations between serum lipids, inter- and intranetwork functional connectivity, and working memory performance. We found that higher serum triglyceride (TG) level was correlated with stronger connectivity between left frontoparietal and ventral attention networks, between right frontoparietal and dorsal attention networks, between right frontoparietal and dorsal sensorimotor networks, between right frontoparietal and lateral visual networks, and between salience (SN) and ventral sensorimotor (vSMN) networks, as well as lower connectivity between posterior default mode and left frontoparietal networks, between left frontoparietal and medial visual networks, and between ventral attention and dorsal sensorimotor networks. In addition, higher SN-vSMN connectivity was related to lower 3-back accuracy. More importantly, the relationship between serum TG and 3-back accuracy was mediated by SN-vSMN connectivity. Our findings not only may expand existing knowledge regarding serum lipids-brain-cognition relations from the perspective of large-scale functional network organization but also may inform a translational conceptualization of how to improve cognitive function through regulating serum lipids., Competing Interests: The authors declare that there is no conflict of interest regarding the publication of this paper., (Copyright © 2020 Chunli Wang et al.)

Neuroimaging studies have linked inter-individual variability in the brain to individualized personality traits. However, only one or several aspects of personality have been effectively predicted based on brain imaging features. The objective of this study was to construct a reliable prediction model of personality in a large sample by using connectome-based predictive modeling (CPM), a recently developed machine learning approach. High-quality resting-state functional magnetic resonance imaging data of 810 healthy young participants from the Human Connectome Project dataset were used to construct large-scale brain networks. Personality traits of the five-factor model (FFM) were assessed by the NEO Five Factor Inventory. We found that CPM successfully and reliably predicted all the FFM personality factors (agreeableness, openness, conscientiousness and neuroticism) other than extraversion in novel individuals. At the neural level, we found that the personality-associated functional networks mainly included brain regions within default mode, frontoparietal executive control, visual and cerebellar systems. Although different feature selection thresholds and parcellation strategies did not significantly influence the prediction results, some findings lost significance after controlling for confounds including age, gender, intelligence and head motion. Our finding of robust personality prediction from an individual's unique functional connectome may help advance the translation of 'brain connectivity fingerprinting' into real-world personality psychological settings., (© The Author(s) 2020. Published by Oxford University Press.)

Neurovascular coupling reflects the close relationship between neuronal activity and cerebral blood flow (CBF), providing a new mechanistic insight into health and disease. Neuromyelitis optica (NMO) is an autoimmune inflammatory demyelinating disease of the central nervous system and shows cognitive decline-related brain gray matter abnormalities besides the damage of optic nerve and spinal cord. We aimed to investigate neurovascular coupling alteration and its clinical significance in NMO by using regional homogeneity (ReHo) to measure neuronal activity and CBF to measure vascular response. ReHo was calculated from functional MRI and CBF was computed from arterial spin labeling (ASL) in 56 patients with NMO and 63 healthy controls. Global neurovascular coupling was assessed by across-voxel CBF-ReHo correlations and regional neurovascular coupling was evaluated by CBF/ReHo ratio. Correlations between CBF/ReHo ratio and clinical variables were explored in patients with NMO. Global CBF-ReHo coupling was decreased in patients with NMO relative to healthy controls (p = .009). Patients with NMO showed decreased CBF/ReHo ratio (10.9%-17.3% reduction) in the parietal and occipital regions and increased CBF/ReHo ratio (8.0%-13.3% increase) in the insular, sensorimotor, temporal and prefrontal regions. Some of these abnormalities cannot be identified by a single CBF or ReHo analysis. Both abnormally decreased and increased CBF/ReHo ratios were correlated with more severe clinical impairments and cognitive decline in patients with NMO. These findings suggested that patients with NMO show abnormal neurovascular coupling, which is associated with disease severity and cognitive impairments., (© 2018 Wiley Periodicals, Inc.)

Several behavioral and neuroimaging markers could be used to predict eventual antidepressant medication (ADM) outcomes in patients with major depressive disorder (MDD). However, these predictors are either subjective or complex, which has limited their clinical use. Thus, we aimed to identify an objective and easy-to-get marker to predict early therapeutic efficacy. Forty-seven drug-naïve patients with MDD and 47 age-, gender- and education-matched healthy controls underwent resting-state functional magnetic resonance imaging (fMRI) scans. We calculated the variable coefficient (VC) of the global signal for each subject. Baseline Hamilton Rating Scale for Depression (HRSD) score and that after 2 weeks of ADM were assessed for patients. Although there was no difference in VC between patients with MDD and healthy controls, we found a significant positive correlation between the VC and the decline rate of HRSD scores in the patients. Compared with the non-responding depression (NRD) group, the treatment-responsive depression (TRD) group had a higher VC. Receiver operator characteristic curve analysis revealed that the VC exhibited a good ability to differentiate TRD from NRD. In addition, the linear and logistic regression analyses showed that the VC was a significant predictor of the decline rate of HRSD scores and the antidepressant treatment response. These findings suggest that variance of the global signal may serve as a useful marker to help clinicians find an appropriate drug for individuals with MDD at the earliest opportunity and then further to facilitate personalized therapy.

Objectives: According to aquaporin-4 antibody (AQP4-Ab), neuromyelitis optica (NMO) can be divided into seropositive and seronegative subgroups. The purpose of this study was to a) compare the distribution of spinal cord and brain magnetic resonance imaging (MRI) lesions between seropositive and seronegative NMO patients; b) explore occult brain damage in seropositive and seronegative NMO patients; and c) explore the contribution of visible lesions to occult grey and white matter damage in seropositive and seronegative NMO patients., Materials and Methods: Twenty-two AQP4-Ab seropositive and 14 seronegative NMO patients and 30 healthy controls were included in the study. Two neuroradiologists independently measured the brain lesion volume (BLV) and the length of spinal cord lesion (LSCL) and recorded the region of brain lesions. The normal-appearing grey matter volume (NAGM-GMV) and white matter fractional anisotropy (NAWM-FA) were calculated for each subject to evaluate occult brain damage., Results: The seropositive patients displayed more extensive damage in the spinal cord than the seronegative patients, and the seronegative group had a higher proportion of patients with brainstem lesions (28.57%) than the seropositive group (4.55%, P=0.064). Both NMO subgroups exhibited reduced NAGM-GMV and NAWM-FA compared with the healthy controls. NAGM-GMV was negatively correlated with LSCL in the seropositive group (r s =-0.444, P=0.044) and with BLV in the seronegative group (r s =-0.768, P=0.002). NAWM-FA was also negatively correlated with BLV in the seropositive group (r s =-0.682, P<0.001)., Conclusion: Our findings suggest that the occult brain damage in these two NMO subgroups may be due to different mechanisms, which need to be further clarified., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Background The field of microbiota-gut-brain research in animals has progressed, while the exact nature of gut microbiota-brain-cognition relationship in humans is not completely elucidated, likely due to small sample sizes and single neuroimaging modality utilized to delineate limited aspects of the brain. We aimed to comprehensively investigate such association in a large sample using multimodal MRI. Methods Fecal samples were collected from 157 healthy young adults and 16S sequencing was used to assess gut microbial diversity and enterotypes. Five brain imaging measures, including regional homogeneity (ReHo) and functional connectivity density (FCD) from resting-state functional MRI, cerebral blood flow (CBF) from arterial spin labeling, gray matter volume (GMV) from structural MRI, and fractional anisotropy (FA) from diffusion tensor imaging, were jointly analyzed with a data-driven multivariate fusion method. Cognition was evaluated by 3-back and digit span tasks. Results We found significant associations of gut microbial diversity with ReHo, FCD, CBF, and GMV within the frontoparietal, default mode and visual networks, as well as with FA in a distributed set of juxtacortical white matter regions. In addition, there were FCD, CBF, GMV, and FA differences between Prevotella- versus Bacteroides-enterotypes in females and between Prevotella- versus Ruminococcaceae-enterotypes in males. Moreover, the identified neuroimaging fusion biomarkers could mediate the associations between microbial diversity and cognition. Conclusions Our findings not only expand existing knowledge of the microbiota-gut-brain axis, but also have potential clinical and translational implications by exposing the gut microbiota as a promising treatment and prevention target for cognitive impairment and related brain disorders. • Gut microbiota-brain-cognition association was assessed using multimodal MRI. • Multimodal MRI measures were jointly analyzed with a multivariate fusion method. • Gut microbial diversity was correlated with multiple neuroimaging fusion measures. • There were differences in multiple neuroimaging fusion measures between enterotypes. • Fusion biomarkers mediated the relations between microbial diversity and cognition. [ABSTRACT FROM AUTHOR]