Resting-state Functional Connectivity Networks Research Articles

114. Association of Polygenic Risk for Bipolar Disorder With Resting-State Network Functional Connectivity in Youth

114. Association of Polygenic Risk for Bipolar Disorder With Resting-State Network Functional Connectivity in Youth

Decreased resting-state functional connectivity and brain network abnormalities in the prefrontal cortex of elderly patients with Parkinson's disease accompanied by depressive symptoms.

This study aimed to explore the brain network characteristics in elderly patients with Parkinson's disease (PD) with depressive symptoms. Thirty elderly PD patients with depressive symptoms (PD-D) and 26 matched PD patients without depressive symptoms (PD-NOD) were recruited based on HAMD-24 with a cut-off of 7. The resting-state functional connectivity (RSFC) was conducted by 53-channel functional near-infrared spectroscopy (fNIRS). There were no statistically significant differences in MMSE scores, disease duration, Hoehn-Yahr stage, daily levodopa equivalent dose, and MDS-UPDRS III between the two groups. However, compared to the PD-NOD group, the PD-D group showed significantly higher MDS-UPDRS II, HAMA-14, and HAMD-24. The interhemispheric FC strength and the FC strength between the left dorsolateral prefrontal cortex (DLPFC-L) and the left frontal polar area (FPA-L) was significantly lower in the PD-D group (FDR p < 0.05). As for graph theoretic metrics, the PD-D group had significantly lower degree centrality (aDc) and node efficiency (aNe) in the DLPFC-L and the FPA-L (FDR, p < 0.05), as well as decreased global efficiency (aEg). Pearson correlation analysis indicated moderate negative correlations between HAMD-24 scores and the interhemispheric FC strength, FC between DLPFC-L and FPA-L, aEg, aDc in FPA-L, aNe in DLPFC-L and FPA-L. In conclusion, PD-D patients show decreased integration and efficiency in their brain networks. Furthermore, RSFC between DLPFC-L and FPA-L regions is negatively correlated with depressive symptoms. These findings propose that targeting DLPFC-L and FPA-L regions via non-invasive brain stimulation may be a potential intervention for alleviating depressive symptoms in elderly PD patients.

Efficacy Assessment of Cerebral Perfusion Augmentation Through Functional Connectivity in an Acute Canine Stroke Model.

Ischemic stroke disrupts functional connectivity within the brain's resting-state networks (RSNs), impacting recovery. This study evaluates the effects of NEH (Norepinephrine and Hydralazine), a cerebral perfusion augmentation therapy, on RSN integrity in a hyper-acute canine stroke model. Fifteen adult purpose-bred mongrel canines, divided into treatment and control (natural history) groups, underwent endovascular induction of acute middle cerebral artery occlusion (MCAO). Post-occlusion, the treatment group received intra-arterial Norepinephrine (0.1-1.52 μg/kg/min, adjusted for 25-45 mmHg above baseline mean arterial pressure) and Hydralazine (20mg). Resting-state fMRI data were acquired with a 3.0 T scanner using a BOLD-sensitive EPI sequence (TR/TE=1400 ms/20ms, 2.5 mm slices, 300 temporal positions). Preprocessing included motion correction, spatial smoothing (2.5 mm FWHM), and high-pass filtering (0.01 Hz cutoff). Functional connectivity within RSNs were analyzed through group-level independent component analysis (ICA) and weighted whole-brain ROI-to-ROI connectome, pre-and post-MCAO. NEH therapy significantly maintained connectivity post-MCAO in the Higher-order Visual and Parietal RSNs, as evidenced by thresholded statistical mapping (TFCE p-corr > 0.95). However, this preservation was network-dependent, with no significant changes in the Primary Visual and Sensorimotor networks. NEH demonstrates potential as a proof-of-concept therapy for maintaining RSN functional connectivity following ischemic stroke, emphasizing the therapeutic promise of perfusion augmentation. These insights reinforce the role of functional connectivity as a measurable endpoint for stroke intervention efficacy, suggesting clinical translatability for patients with insufficient collateral circulation. NEH＝ Norepinephrine and Hydralazine; RSN＝ Resting-State Network; ICA = Independent Component Analysis; rsfMRI = resting-state Functional Magnetic Resonance Imaging; MCAO = Middle Cerebral Artery Occlusion; TFCE = Threshold-Free Cluster Enhancement.

Identifying Correlated Functional Brain Network Patterns Associated with Touch Discrimination in Survivors of Stroke Using Automated Machine Learning

Stroke recovery is multifaceted and complex. Machine learning approaches have potential to identify patterns of brain activity associated with clinical outcomes, providing new insights into recovery. We aim to use machine learning to characterise the contribution of and potential interaction between resting state functional connectivity networks in predicting touch discrimination outcomes in a well-phenotyped, but small, stroke cohort. We interrogated and compared a suite of automated machine learning approaches to identify patterns of brain activity associated with clinical outcomes. Using feature reduction, the identification of combined ‘golden features’, and five-fold cross-validation, two golden features patterns emerged. These golden features identified patterns of resting state connectivity involving interactive relationships: 1. The difference between right insula and right superior temporal lobe correlation and left cerebellum and vermis correlation; 2. The ratio between right inferior temporal lobe and left cerebellum correlation and left frontal inferior operculum and left supplementary motor area correlation. Our findings demonstrate evidence of the potential for automated machine learning to provide new insights into brain network patterns and their interactions associated with the prediction of quantitative touch discrimination outcomes, through the automated identification of robust associations and golden feature brain patterns, even in a small cohort of stroke survivors.

Parkinson's Disease Risk Variant rs9638616 is Non-Specifically Associated with Altered Brain Structure and Function.

A genome-wide association study (GWAS) variant associated with Parkinson's disease (PD) risk in Asians, rs9638616, was recently reported, and maps to WBSCR17/GALNT17, which is involved in synaptic transmission and neurite development. To test the association of the rs9638616 T allele with imaging-derived measures of brain microstructure and function. We analyzed 3-Tesla MRI and genotyping data from 116 early PD patients (aged 66.8±9.0 years; 39% female; disease duration 1.25±0.71 years) and 57 controls (aged 68.7±7.4 years; 54% female), of Chinese ethnicity. We performed voxelwise analyses for imaging-genetic association of rs9638616 T allele with white matter tract fractional anisotropy (FA), grey matter volume and resting-state network functional connectivity. The rs9638616 T allele was associated with widespread lower white matter FA (t = -1.75, p = 0.042) and lower functional connectivity of the supplementary motor area (SMA) (t = -5.05, p = 0.001), in both PD and control groups. Interaction analysis comparing the association of rs9638616 and FA between PD and controls was non-significant. These imaging-derived phenotypes mediated the association of rs9638616 to digit span (indirect effect: β= -0.21 [-0.42,-0.05], p = 0.031) and motor severity (indirect effect: β= 0.15 [0.04,0.26], p = 0.045). We have shown that a novel GWAS variant which is biologically linked to synaptic transmission is associated with white matter tract and functional connectivity dysfunction in the SMA, supported by changes in clinical motor scores. This provides pathophysiologic clues linking rs9638616 to PD risk and might contribute to future risk stratification models.

Multivariate association between psychosocial environment, behaviors, and brain functional networks in adolescent depression

BackgroundAdolescent depression shows high clinical heterogeneity. Brain functional networks serve as a powerful tool for investigating neural mechanisms underlying depression profiles. A key challenge is to characterize how variation in brain functional organization links to behavioral features and psychosocial environmental influences. MethodsWe recruited 80 adolescents with major depressive disorder (MDD) and 42 healthy controls (HCs). First, we estimated the differences in functional connectivity of resting-state networks (RSN) between the two groups. Then, we used sparse canonical correlation analysis to characterize patterns of associations between RSN connectivity and symptoms, cognition, and psychosocial environmental factors in MDD adolescents. Clustering analysis was applied to stratify patients into homogenous subtypes according to these brain-behavior-environment associations. ResultsMDD adolescents showed significantly hyperconnectivity between the ventral attention and cingulo-opercular networks compared with HCs. We identified one reliable pattern of covariation between RSN connectivity and clinical/environmental features in MDD adolescents. In this pattern, psychosocial factors, especially the interpersonal and family relationships, were major contributors to variation in connectivity of salience, cingulo-opercular, ventral attention, subcortical and somatosensory-motor networks. Based on this association, we categorized patients into two subgroups which showed different environment and symptoms characteristics, and distinct connectivity alterations. These differences were covered up when the patients were taken as a whole group. ConclusionThis study identified the environmental exposures associated with specific functional networks in MDD youths. Our findings emphasize the importance of the psychosocial context in assessing brain function alterations in adolescent depression and have the potential to promote targeted treatment and precise prevention.

Altered resting-state functional connectivity and dynamic network properties in cognitive impairment: an independent component and dominant-coactivation pattern analyses study.

Cognitive impairment (CI) due to Alzheimer's disease (AD) encompasses a decline in cognitive abilities and can significantly impact an individual's quality of life. Early detection and intervention are crucial in managing CI, both in the preclinical and prodromal stages of AD prior to dementia. In this preliminary study, we investigated differences in resting-state functional connectivity and dynamic network properties between 23 individual with CI due to AD based on clinical assessment and 15 healthy controls (HC) using Independent Component Analysis (ICA) and Dominant-Coactivation Pattern (d-CAP) analysis. The cognitive status of the two groups was also compared, and correlations between cognitive scores and d-CAP switching probability were examined. Results showed comparable numbers of d-CAPs in the Default Mode Network (DMN), Executive Control Network (ECN), and Frontoparietal Network (FPN) between HC and CI groups. However, the Visual Network (VN) exhibited fewer d-CAPs in the CI group, suggesting altered dynamic properties of this network for the CI group. Additionally, ICA revealed significant connectivity differences for all networks. Spatial maps and effect size analyses indicated increased coactivation and more synchronized activity within the DMN in HC compared to CI. Furthermore, reduced switching probabilities were observed for the CI group in DMN, VN, and FPN networks, indicating less dynamic and flexible functional interactions. The findings highlight altered connectivity patterns within the DMN, VN, ECN, and FPN, suggesting the involvement of multiple functional networks in CI. Understanding these brain processes may contribute to developing targeted diagnostic and therapeutic strategies for CI due to AD.

Graph theoretical analysis and independent component analysis of diabetic optic neuropathy: A resting-state functional magnetic resonance imaging study.

This study aimed to investigate the resting-state functional connectivity and topologic characteristics of brain networks in patients with diabetic optic neuropathy (DON). Resting-state functional magnetic resonance imaging scans were performed on 23 patients and 41 healthy control (HC) subjects. We used independent component analysis and graph theoretical analysis to determine the topologic characteristics of the brain and as well as functional network connectivity (FNC) and topologic properties of brain networks. Compared with HCs, patients with DON showed altered global characteristics. At the nodal level, the DON group had fewer nodal degrees in the thalamus and insula, and a greater number in the right rolandic operculum, right postcentral gyrus, and right superior temporal gyrus. In the internetwork comparison, DON patients showed significantly increased FNC between the left frontoparietal network (FPN-L) and ventral attention network (VAN). Additionally, in the intranetwork comparison, connectivity between the left medial superior frontal gyrus (MSFG) of the default network (DMN) and left putamen of auditory network was decreased in the DON group. DON patients altered node properties and connectivity in the DMN, auditory network, FPN-L, and VAN. These results provide evidence of the involvement of specific brain networks in the pathophysiology of DON.

Sympathovagal quotient and resting-state functional connectivity of control networks are related to gut Ruminococcaceae abundance in healthy men

IntroductionHeart rate variability (HRV), brain resting-state functional connectivity (rsFC), and gut microbiota (GM) are three recognized indicators of health status, whose relationship has not been characterized. We aimed to identify the GM genera and families related to HRV and rsFC, the interaction effect of HRV and rsFC on GM taxa abundance, and the mediation effect of diet on these relationships. MethodsEighty-eight healthy, young Colombian men were included in this cross-sectional study. HRV metrics were extracted from 24-hour Holter monitoring data and the resting functional connectivity strength (FCS) of 15 networks were derived from functional magnetic resonance imaging. Gut microbiota composition was assessed using the sequences of the V3-V4 regions of the 16 S rRNA gene, and diet was evaluated using a food frequency questionnaire. Multivariate linear regression analyses were performed to evaluate the correlations between the independent variables (HRV metrics and FCS) and the dependent variables (GM taxa abundance or alpha diversity indexes). Mediation analyses were used to test the role of diet in the relationship between HRV and GM. ResultsThe sympathovagal quotient (SQ) and the FCS of control networks were positively correlated with the abundance of the gut Ruminococcaceae family and an unclassified Ruminococcaceae genus (Ruminococcaceae_unc). Additionally, the interaction between the FCS of the control network and SQ reduced the individual main effects on the Ruminococcaceae_unc abundance. Finally, reduced habitual fiber intake partially mediated the relationship between SQ and this genus. ConclusionTwo indicators of self-regulation, HRV and the rsFC of control networks, are related to the abundance of gut microbiota taxa in healthy men. However, only HRV is related to habitual dietary intake; thus, HRV could serve as a marker of food choice and GM composition in the future.

Alterations of resting-state functional network connectivity in patients with noise-induced hearing loss: A study based on independent component analysis.

Functional reorganization is a response to auditory deficits or deprivation, and less is known about the overall brain network alterations involving resting-state networks (RSNs) and multiple functional networks in patients with occupational noise-induced hearing loss (NIHL). So this study evaluated resting-state functional network connectivity (FNC) alterations in occupational NIHL using an independent component analysis (ICA). In total, 79 mild NIHL patients (MP), 32 relatively severe NIHL patients (RSP), and 84 age- and education- matched healthy controls (HC) were recruited. All subjects were tested using the Mini-mental State Examination scale, the tinnitus Handicap Inventory scale, the Hamilton Anxiety scale (HAMA) and scanned by T1-3DFSPGR, resting-state functional magnetic resonance imaging sequence in 3.0 T and analysed by the ICA. Seven RSNs were identified, compared with the HC, the MP showed increased FNC within the executive control network (ECN) and enhanced FNC within the default mode network (DMN) and the visual network (VN); compared with the HC, the RSP showed decreased FNC within the ECN and auditory network (AUN), DMN and VN; no significant changes in FNC were found in the MP compared with the RSP. Furthermore, the correlation analysis between the noise exposure time and hearing loss level, HAMA were both negative, and there were no significant correlations between the abnormal RSNs and the hearing level, noise exposure time and HAMA. These findings indicate that different degrees of NIHL involve different alterations in RSNs connectivity and may reveal the neural mechanisms related to emotion-related features and functional abnormalities following long-term NIHL.

Regional GABA levels modulate abnormal resting-state network functional connectivity and cognitive impairment in multiple sclerosis.

More evidence shows that changes in functional connectivity with regard to brain networks and neurometabolite levels correlated to cognitive impairment in multiple sclerosis. However, the neurological basis underlying the relationship among neurometabolite levels, functional connectivity, and cognitive impairment remains unclear. For this purpose, we used a combination of magnetic resonance spectroscopy and resting-state functional magnetic resonance imaging to study gamma-aminobutyric acid and glutamate concentrations in the posterior cingulate cortex, medial prefrontal cortex and left hippocampus, and inter-network functional connectivity in 29 relapsing-remitting multiple sclerosis patients and 34 matched healthy controls. Neuropsychological tests were used to evaluate the cognitive function. We found that relapsing-remitting multiple sclerosis patients demonstrated significantly reduced gamma-aminobutyric acid and glutamate concentrations and aberrant functional connectivity involving cognitive-related networks compared to healthy controls, and both alterations were associated with specific cognition decline. Moreover, mediation analyses indicated that decremented hippocampus gamma-aminobutyric acid levels in relapsing-remitting multiple sclerosis patients mediated the association between inter-network functional connectivity in various components of default mode network and verbal memory deficits. In summary, our findings shed new lights on the essential function of GABAergic system abnormalities in regulating network dysconnectivity and functional connectivity in relapsing-remitting multiple sclerosis patients, suggesting potential novel approach to treatment.

Effects of aripiprazole on resting-state functional connectivity of large-scale brain networks in first-episode drug-naïve schizophrenia patients

Aripiprazole modulates functional connectivity (FC) between several brain regions in first-episode schizophrenia patients, contributing to improvement in clinical symptoms. However, the effects of aripiprazole on abnormal connections among extensive brain networks in schizophrenia patients remain unclear. We aimed to investigate the effects of 12 weeks of aripiprazole treatment on the FC of large-scale brain networks. Forty-five first-episode drug-naïve schizophrenia patients and 45 healthy controls were recruited for this longitudinal study. Resting-state functional magnetic resonance imaging (fMRI) data were collected at baseline and after 12 weeks of aripiprazole treatment. The patients were classified into those in response (SCHr group) and non-response (SCHnr group) according to the improvement of clinical symptoms after 12-weeks treatment. The FC were evaluated for seven large-scale brain networks. In addition, correlation analysis was performed to investigate associations between changes FC of large-scale brain networks and clinical symptoms. Before aripiprazole treatment, schizophrenia patients showed decreased FC of extensive brain networks compared to healthy controls. The 12-week aripiprazole treatment significantly prevented the constantly decreased FC of subcortical network, default mode network and other brain networks in patients with SCHr, in association with the improvement of clinical symptoms. Taken together, these findings have revealed the effects of aripiprazole on FC in large-scale networks in schizophrenia patients, which could provide new insight on interpreting symptom improvement in SCH.

North Korean defectors with PTSD and complex PTSD show alterations in default mode network resting-state functional connectivity.

North Korean defectors (NKDs) have often been exposed to traumatic events. However, there have been few studies of neural alterations in NKDs with post-traumatic stress disorder (PTSD) and complex PTSD (cPTSD). To investigate neural alterations in NKDs with PTSD and cPTSD, with a specific focus on alterations in resting-state functional connectivity networks, including the default mode network (DMN). Resting-state functional connectivity was assessed using brain functional magnetic resonance imaging in three groups of NKDs: without PTSD, with PTSD and with cPTSD. Statistical tests were performed, including region of interest (ROI)-to-ROI and ROI-to-voxel analysis, followed by post hoc correlation analysis. In the ROI-to-ROI analysis, differences in functional connectivity were found among the components of the DMN, as well as in the thalamus and the basal ganglia. Right hippocampus-left pallidum and right amygdala-left lingual gyrus connectivity differed between groups in the ROI-to-voxel analysis, as did connectivity involving the basal ganglia. The post hoc analysis revealed negative correlations between Coping and Adaptation Processing Scale (CAPS) score and left posterior cingulate cortex-right pallidum connectivity and between CAPS score and right putamen-left angular gyrus connectivity in the control group, which were not observed in other groups. The results suggest that there are alterations in the functional connectivity of the DMN and the limbic system in NKDs with PTSD and cPTSD, and that these alterations involve the basal ganglia. The lower correlations of CAPS score with right basal ganglia-DMN functional connectivity in patients compared with controls further implies that these connectivities are potential targets for treatment of PTSD and cPTSD.

Association between gene expression and altered resting-state functional networks in type 2 diabetes

BackgroundType 2 diabetes (T2DM) is a polygenic metabolic disorder that accelerates brain aging and harms cognitive function. The underlying mechanism of T2DM-related brain functional changes has not been clarified.MethodsResting-fMRI data were obtained from 99 T2DM and 109 healthy controls (HCs). Resting-state functional connectivity networks (RSNs) were separated using the Independent Component Analysis (ICA) method, and functional connectivity (FC) differences between T2DM patients and HCs within the RSNs were detected. A partial least squares (PLS) regression was used to test the relation between gene expression from Allen Human Brain Atlas (AHBA) and intergroup FC differences within RSNs. Then the FC differences-related gene sets were enriched to determine the biological processes and pathways related to T2DM brain FC changes.ResultThe T2DM patients showed significantly increased FC in the left middle occipital gyrus (MOG) of the precuneus network (PCUN) and the right MOG / right precuneus of the dorsal attention network (DAN). FC differences within the PCUN were linked with the expression of genes enriched in the potassium channel and TrkB-Rac1 signaling pathways and biological processes related to synaptic function.ConclusionThis study linked FC and molecular alterations related to T2DM and suggested that the T2DM-related brain FC changes may have a genetic basis. This study hoped to provide a unique perspective to understand the biological substrates of T2DM-related brain changes.

Individual resting-state network functional connectivity predicts treatment improvement of repetitive transcranial magnetic stimulation in major depressive disorder: A pilot study

The current pilot study aimed to exploratively investigate whether individual functional connectivity (FC) of the rTMS stimulation site with resting-state networks could predict the individual efficacy of rTMS treatment. We found that rTMS induced an increase of the FC between the stimulation site and the limbic network (LN) in healthy participants, and that this individualized FC was negatively correlated with the rTMS treatment improvement in MDD patients. Moreover, the LN successfully guided the personalized rTMS therapy. These findings highlighted the crucial role of the LN in understanding the mechanisms underlying rTMS treatment improvement, and the personalized therapy in MDD patients.

Altered Large-Scale Resting-State Functional Network Connectivity in Convergence Insufficiency Young Adults Compared With Binocularly Normal Controls.

To investigate the underlying resting-state functional connectivity (RSFC) of symptomatic convergence insufficiency (CI) compared with binocularly normal controls (BNC) using functional magnetic resonance imaging (fMRI) under The Convergence Insufficiency Neuro‑mechanism Adult Population Study (NCT03593031). A total of 101 participants were eligible for this study. After removing datasets with motion artifacts, 49 CI and 47 BNC resting-state functional magnetic resonance imaging datasets were analyzed. CI was diagnosed with the following signs: (1) receded near point of convergence of 6 cm or greater, (2) decreased positive fusional vergence of less than 15∆ or failing Sheard's criteria of twice the near phoria, (3) near phoria of at least 4∆ more exophoric compared with the distance phoria, and (4) symptoms using the Convergence Insufficiency Symptom Survey (score of ≥21). RSFC was assessed using a group-level independent components analysis and dual regression. A behavioral correlation analysis using linear regression method was performed between clinical measures and RSFC using the significant difference between the CI and BNC. On average, a decreased RSFC was observed within the frontoparietal network, default mode network and visual network in patients with CI, compared with the participants with BNC (P < 0.05, corrected for multiple comparisons). The default mode network RSFC strength was significantly correlated with the PFV, near point of convergence, and difference between the horizontal phoria at near compared with far (P < 0.05). Results support altered RSFC in patients with CI compared with participants with BNC and suggest that these differences in underlying neurophysiology may in part be in connection with the differences in optometric visual function used to diagnose CI.

The relationship between late (≥ 7 days) systemic dexamethasone and functional network connectivity in very preterm infants

BackgroundCurrent evidence shows that systemic dexamethasone administration starting after the first week of age reduces bronchopulmonary dysplasia for very preterm (VPT) infants, but its neurological effects remain obscure. Using resting-state functional magnetic resonance imaging (rs-fMRI), we assessed the changes in functional network connectivity (FNC) in very preterm infants treated with late systemic dexamethasone (≥7 days of age). MethodsVPT infants (GA ≤ 32 weeks) who needed to rely on mechanical ventilation for more than 7 days but fewer than 14 days to maintain vital signs were included in the study. The cohort was divided into two groups according to whether they were given systemic dexamethasone. In addition, 26 healthy term infants were recruited as controls. At term-equivalent age (TEA), rs-fMRI and 3D-T1 data from eligible infants were acquired with a 3.0-T MRI scanner. After the MRI data were preprocessed, group-level independent component analysis (ICA), a technique used for blind source separation, was used to identify the components of resting-state networks (RSNs). Then, the functional connectivity between components and RSNs was compared among different groups. Upon follow-up at 3 months of corrected age, the neurodevelopmental outcomes of enrolled infants were assessed with the Bayley Scales of Infant Development–Chinese Revision (BSID-CR), and the Motor Development Index (MDI) and Psychomotor Development Index (PDI) were measured. Finally, the correlations between resting-state FNC and BSID scores were analysed. ResultsUltimately, 59 infants were included in the final analysis, including 19 preterm infants who received dexamethasone, 20 who did not, and 20 healthy term infants as controls. Based on their data, 11 components were identified, belonging to 5 RSNs: the visual network (VN), the dorsal attention network (DAN), the auditory network (AN), the primary sensorimotor network (SMN), and the default-mode network (DMN). Compared with the term infants, the preterm infants showed significantly weakened functional connectivity between the DAN and VN, as well as the VN and AN (P < 0.05). Among preterm infants, those who were given dexamethasone showed significantly stronger functional connectivity between the DAN and VN, as well as the DMN and AN (P < 0.05), than those who were not. The correlation analysis demonstrated that the connectivity values between the DAN and VN and between the VN and AN were positively correlated with the MDI (r = 0.432, P＜0.001, and r = 0.479, P＜0.001, respectively) and the PDI (r = 0.436, P＜0.001 and r = 0.516, P＜0.001, respectively). ConclusionsOur investigation uncovers a noteworthy link between the administration of late systemic dexamethasone (≥7 days of age) in VPT infants and distinct improvements in FNC. Furthermore, the observed positive correlation between inter-network connectivity and scores on the BSID-CR implies a plausible neuroprotective aspect of this therapeutic approach in this specific group of children.

Testosterone and the Amygdala's Functional Connectivity in Women and Men.

The amygdala contains androgen receptors and is involved in various affective and social functions. An interaction between testosterone and the amygdala's functioning is likely. We investigated the amygdala's resting-state functional connectivity (rsFC) network in association with testosterone in 94 healthy young adult women and men (final data available for analysis from 42 women and 39 men). Across the whole sample, testosterone was positively associated with the rsFC between the right amygdala and the right middle occipital gyrus, and it further predicted lower agreeableness scores. Significant sex differences appeared for testosterone and the functional connectivity between the right amygdala and the right superior frontal gyrus (SFG), showing higher testosterone levels with lower connectivity in women. Sex further predicted the openness and agreeableness scores. Our results show that testosterone modulates the rsFC between brain areas involved in affective processing and executive functions. The data indicate that the cognitive control of the amygdala via the frontal cortex is dependent on the testosterone levels in a sex-specific manner. Testosterone seems to express sex-specific patterns (1) in networks processing affect and cognition, and (2) in the frontal down-regulation of the amygdala. The sex-specific coupling between the amygdala and the frontal cortex in interaction with the hormone levels may drive sex-specific differences in a variety of behavioral phenomena that are further associated with psychiatric illnesses that show sex-specific prevalence rates.

Neural Representation of Collective Self-esteem in Resting-state Functional Connectivity and its Validation in Task-dependent Modality.

Collective self-esteem (CSE) is an important personality variable, defined as self-worth derived from membership in social groups. A study explored the neural basis of CSE using a task-based functional magnetic resonance imaging (fMRI) paradigm; however, task-independent neural basis of CSE remains to be explored, and whether the CSE neural basis of resting-state fMRI is consistent with that of task-based fMRI is unclear. We built support vector regression (SVR) models to predict CSE scores using topological metrics measured in the resting-state functional connectivity network (RSFC) as features. Then, to test the reliability of the SVR analysis, the activation pattern of the identified brain regions from SVR analysis was used as features to distinguish collective self-worth from other conditions by multivariate pattern classification in task-based fMRI dataset. SVR analysis results showed that leverage centrality successfully decoded the individual differences in CSE. The ventromedial prefrontal cortex, anterior cingulate cortex, posterior cingulate gyrus, precuneus, orbitofrontal cortex, posterior insula, postcentral gyrus, inferior parietal lobule, temporoparietal junction, and inferior frontal gyrus, which are involved in self-referential processing, affective processing, and social cognition networks, participated in this prediction. Multivariate pattern classification analysis found that the activation pattern of the identified regions from the SVR analysis successfully distinguished collective self-worth from relational self-worth, personal self-worth and semantic control. Our findings revealed CSE neural basis in the whole-brain RSFC network, and established the concordance between leverage centrality and the activation pattern (evoked during collective self-worth task) of the identified regions in terms of representing CSE.

Abnormal functional connectivity in radiologically isolated syndrome: A resting-state fMRI study

Background: Radiologically isolated syndrome (RIS) patients might have psychiatric and cognitive deficits, which suggests an involvement of major resting-state functional networks. Notwithstanding, very little is known about the neural networks involved in RIS. Objective: To examine functional connectivity differences between RIS and healthy controls using resting-state functional magnetic resonance imaging (fMRI). Methods: Resting-state fMRI data in 25 RIS patients and 28 healthy controls were analyzed using an independent component analysis; in addition, seed-based correlation analysis was used to obtain more information about specific differences in the functional connectivity of resting-state networks. Participants also underwent neuropsychological testing. Results: RIS patients did not differ from the healthy controls regarding age, sex, and years of education. However, in memory (verbal and visuospatial) and executive functions, RIS patients’ cognitive performance was significantly worse than the healthy controls. In addition, fluid intelligence was also affected. Twelve out of 25 (48%) RIS patients failed at least one cognitive test, and six (24.0%) had cognitive impairment. Compared to healthy controls, RIS patients showed higher functional connectivity between the default mode network and the right middle and superior frontal gyri and between the central executive network and the right thalamus (pFDR < 0.05; corrected). In addition, the seed-based correlation analysis revealed that RIS patients presented higher functional connectivity between the posterior cingulate cortex, an important hub in neural networks, and the right precuneus. Conclusion: RIS patients had abnormal brain connectivity in major resting-state neural networks and worse performance in neurocognitive tests. This entity should be considered not an “incidental finding” but an exclusively non-motor (neurocognitive) variant of multiple sclerosis.