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Background: Alzheimer's disease (AD) encompasses a spectrum that may progress from mild cognitive impairment (MCI) to full dementia, characterized by amyloid-beta and tau accumulation. Transcranial direct current stimulation (tDCS) is being investigated as a therapeutic option, but its efficacy in relation to individual genetic and biological risk factors remains underexplored. Objective: To evaluate the effects of a two-week anodal tDCS regimen on the left dorsolateral prefrontal cortex, focusing on functional connectivity changes in neural networks in MCI patients resulting from various possible underlying disorders, considering individual factors associated to AD such as amyloid-beta deposition, APOE ϵ4 allele, BDNF Val66Met polymorphism, and sex. Methods: In a single-arm prospective study, 63 patients with MCI, including both amyloid-PET positive and negative cases, received 10 sessions of tDCS. We assessed intra- and inter-network functional connectivity (FC) using fMRI and analyzed interactions between tDCS effects and individual factors associated to AD. Results: tDCS significantly enhanced intra-network FC within the Salience Network (SN) and inter-network FC between the Central Executive Network and SN, predominantly in APOE ϵ4 carriers. We also observed significant sex*tDCS interactions that benefited inter-network FC among females. Furthermore, the effects of multiple modifiers, particularly the interaction of the BDNF Val66Met polymorphism and sex, were evident, as demonstrated by increased intra-network FC of the SN in female Met non-carriers. Lastly, the effects of tDCS on FC did not differ between the group of 26 MCI patients with cerebral amyloid-beta deposition detected by flutemetamol PET and the group of 37 MCI patients without cerebral amyloid-beta deposition. Conclusions: The study highlights the importance of precision medicine in tDCS applications for MCI, suggesting that individual genetic and biological profiles significantly influence therapeutic outcomes. Tailoring interventions based on these profiles may optimize treatment efficacy in early stages of AD.

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BACKGROUND: Functional magnetic resonance imaging (fMRI) has not previously been used to localize the swallowing functional area in repetitive transcranial magnetic stimulation (rTMS) treatment for post-stroke dysphagia; Traditionally, the target area for rTMS is the hotspot, which is defined as the specific region of the brain identified as the optimal location for transcranial magnetic stimulation (TMS). This study aims to compare the network differences between the TMS hotspot and the saliva swallowing fMRI activation to determine the better rTMS treatment site and investigate changes in functional connectivity related to post-stroke dysphagia using resting-state fMRI. METHODS: Using an information-based approach, we conducted a single case study to explore neural functional connectivity in a patient with post-stroke dysphagia before, immediately after rTMS, and four weeks after rTMS intervention. 20 healthy participants underwent fMRI and TMS hotspot localization as a control group. Neural network alterations were assessed , and functional connections related to post-stroke dysphagia were examined using resting-state fMRI. RESULTS: Compared to the TMS-induced hotspots, the fMRI activation peaks were located significantly more posteriorly and exhibited stronger functional connectivity with bilateral postcentral gyri. Following rTMS treatment, this patient developed functional connection between the brainstem and the bilateral insula, caudate, anterior cingulate cortex, and cerebellum. CONCLUSION: The saliva swallowing fMRI activation peaks show more intense functional connectivity with bilateral postcentral gyri compared to the TMS hotspots. Activation peak-guided rTMS treatment improves swallowing function in post-stroke dysphagia. This study proposes a novel and potentially more efficacious therapeutic target for rTMS, expanding its therapeutic options for treating post-stroke dysphagia.

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Previous research has shown that, in both laboratory and real-world contexts, punishment sensitivity is associated with lower risk-taking propensity. The neural underpinnings of the association between punishment sensitivity and risk-taking, however, remain largely unknown. To address this issue, we implemented resting-state functional connectivity (RSFC) and voxel-based morphometry (VBM) methodologies to investigate the neural basis of their relationship in the current study (N=594). The behavioral results confirmed a negative association between punishment sensitivity and risk-taking propensity, which supports the hypothesis. The VBM results demonstrated a positive correlation between punishment sensitivity and gray matter volume in the right orbitofrontal cortex (ROFC). Furthermore, the results of the RSFC analysis revealed that the functional connectivity between ROFC and the right medial temporal gyrus (RMTG) was positively associated with punishment sensitivity. Notably, mediation analysis demonstrated that punishment sensitivity acted as a complete mediator in the influence of ROFC-RMTG functional connectivity on risk-taking. These findings suggest that ROFC-RMTG functional connectivity may be the neural basis underlying the effect of punishment sensitivity on risk-taking propensity, which provides a new perspective for understanding the relationship between punishment sensitivity and risk-taking propensity.

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BACKGROUND: Bipolar disorder (BD) is a chronic psychiatric mood disorder that is solely diagnosed based on clinical symptoms. These symptoms often overlap with other psychiatric disorders. Efforts to use machine learning (ML) to create predictive models for BD based on data from brain imaging are expanding but have often been limited using only a single modality and the exclusion of the cerebellum, which may be relevant in BD. METHODS: In this study, we sought to improve ML classification of BD by combining information from structural, functional, and diffusion-weighted imaging. Participants (108 BD I, 78 control) with BD type I and matched controls were recruited into an imaging study. This dataset was randomly divided into training and testing sets. For each of the three modalities, a separate ML model was selected, trained, and then used to generate a prediction of the class of each test subject. Majority voting was used to combine results from the three models to make a final prediction of whether a subject had BD. An independent replication sample was used to evaluate the ability of the ML classification to generalize to data collected at other sites. RESULTS: Combining the three machine learning models through majority voting resulted in an accuracy of 89.5 % for classification of the test subjects as being in the BD or control group. Bootstrapping resulted in a 95 % confidence interval of 78.9 %-97.4 % for test accuracy. Performance was reduced when only using 2 of the 3 modalities. Analysis of feature importance revealed that the cerebellum and nodes of the emotional control network were among the most important regions for classification. The machine learning model performed at chance on the independent replication sample. CONCLUSION: BD I could be identified with high accuracy in our relatively small sample by combining structural, functional, and diffusion-weighted imaging data within a single site but not generalize well to an independent replication sample. Future studies using harmonized imaging protocols may facilitate generalization of ML models.

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BACKGROUND: While patients with major depressive disorder (MDD) and bipolar disorder (BD) exhibited default mode network (DMN) dysfunction revealed by aberrant resting-state functional connectivity (rsFC) patterns, previous findings have been inconsistent. Little is known about the similarities and differences in DMN rsFC between MDD and BD. METHODS: A voxel-wise meta-analysis of seed-based DMN rsFC studies on MDD or BD was performed using the Seed-based d Mapping software with permutation of subject images (SDM-PSI). Aberrant DMN rsFC in both disorders was investigated separately, followed by conjunction and between-disorder comparison analyses. Functional decoding was performed to implicate the psychophysiological underpinnings of derived brain abnormalities. RESULTS: Thirty-four studies comparing 1316 MDD patients with 1327 HC, and 22 studies comparing 1059 BD patients with 1396 HC were included. Compared to HC, MDD patients exhibited DMN hyperconnectivity with frontolimbic systems, and hypoconnectivity with temporal lobe and posterior cingulate cortex. BD patients displayed increased DMN connectivity with bilateral precuneus, and reduced connectivity with prefrontal cortex and middle temporal gyrus. No common patterns of DMN rsFC abnormalities were observed between MDD and BD. Compared to BD, MDD patients showed DMN hyperconnectivity with triangular part of the left inferior frontal gyrus and left fusiform gyrus. Functional decoding found that patterns of DMN rsFC alteration between MDD and BD were primarily related to action and perception domains. CONCLUSION: Distinct DMN dysfunction patterns in MDD and BD enhance current understanding of the neural substrates of mood disorders and may provide a potential biomarker for differentiation.

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Background: The hypothalamus is a key hub of the neural circuits of motivated behavior. Alcohol misuse may lead to hypothalamic dysfunction. Here, we investigated how resting-state hypothalamic functional connectivities are altered in association with the severity of drinking and clinical comorbidities and how men and women differ in this association. Methods: We employed the data of the Human Connectome Project. A total of 870 subjects were included in data analyses. The severity of alcohol use was quantified for individual subjects with the first principal component (PC1) identified from principal component analyses of all drinking measures. Rule-breaking and intrusive scores were evaluated with the Achenbach Adult Self-Report Scale. We performed a whole-brain regression of hypothalamic connectivities on drinking PC1 in all subjects and men/women separately and evaluated the results at a corrected threshold. Results: Higher drinking PC1 was associated with greater hypothalamic connectivity with the paracentral lobule (PCL). Hypothalamic PCL connectivity was positively correlated with rule-breaking score in men (r=0.152, P=0.002) but not in women. In women but not men, hypothalamic connectivity with the left temporo-parietal junction (LTPJ) was negatively correlated with drinking PC1 (r=-0.246, P<0.001) and with intrusiveness score (r=-0.127, P=0.006). Mediation analyses showed that drinking PC1 mediated the relationship between hypothalamic PCL connectivity and rule-breaking score in men and between hypothalamic LTPJ connectivity and intrusiveness score bidirectionally in women. Conclusions: We characterized sex-specific hypothalamic connectivities in link with the severity of alcohol misuse and its comorbidities. These findings extend the literature by elucidating the potential impact of problem drinking on the motivation circuits.

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While the significance of obtaining restful sleep at night and maintaining daytime alertness is well recognized for human performance and overall well-being, substantial variations exist in the development of sleepiness during diurnal waking periods. Despite the established roles of the hypothalamus and striatum in sleep-wake regulation, the specific contributions of this neural circuit in regulating individual sleep homeostasis remain elusive. This study utilized resting-state functional magnetic resonance imaging (fMRI) and mathematical modeling to investigate the role of hypothalamus-striatum connectivity in subjective sleepiness variation in a cohort of 71 healthy adults under strictly controlled in-laboratory conditions. Mathematical modeling results revealed remarkable individual differences in subjective sleepiness accumulation patterns measured by the Karolinska Sleepiness Scale (KSS). Brain imaging data demonstrated that morning hypothalamic connectivity to the dorsal striatum significantly predicts the individual accumulation of subjective sleepiness from morning to evening, while no such correlation was observed for the hypothalamus-ventral striatum connectivity. These findings underscore the distinct roles of hypothalamic connectivity to the dorsal and ventral striatum in individual sleep homeostasis, suggesting that hypothalamus-dorsal striatum circuit may be a promising target for interventions mitigating excessive sleepiness and promoting alertness.

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The current study demonstrates that an individual's resting-state functional connectivity (RSFC) is a dependable biomarker for identifying differential patterns of cognitive and emotional functioning during late childhood. Using baseline RSFC data from the Adolescent Brain Cognitive Development (ABCD) study, which includes children aged 9-11, we identified four distinct RSFC subtypes. We introduce an integrated methodological pipeline for testing the reliability and importance of these subtypes. In the Identification phase, Leiden Community Detection defined RSFC subtypes, with their reproducibility confirmed through a split-sample technique in the Validation stage. The Evaluation phase showed that distinct cognitive and mental health profiles are associated with each subtype, with the Predictive phase indicating that subtypes better predict various cognitive and mental health characteristics than individual RSFC connections. The Replication stage employed bootstrapping and down-sampling methods to substantiate the reproducibility of these subtypes further. This work allows future explorations of developmental trajectories of these RSFC subtypes.

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BACKGROUND: The prevalence of internalizing psychopathology rises precipitously from early to mid-adolescence, yet the underlying neural phenotypes that give rise to depression and anxiety during this developmental period remain unclear. METHODS: Youth from the Adolescent Brain and Cognitive DevelopmentSM Study (ages 9-10 years at baseline) with a resting-state fMRI scan and mental health data were eligible for inclusion. Internalizing subscale scores from the Brief Problem Monitor - Youth Form were combined across two years of follow-up to generate a cumulative measure of internalizing symptoms. The total sample (n = 6521) was split into a large discovery dataset and a smaller validation dataset. Brain-behavior associations of resting-state functional connectivity (RSFC) with internalizing symptoms were estimated in the discovery dataset. The weighted contributions of each functional connection were aggregated using multivariate statistics to generate a polyneuro risk score (PNRS). The predictive power of the PNRS was evaluated in the validation dataset. RESULTS: The PNRS explained 10.73% of the observed variance in internalizing symptom scores in the validation dataset. Model performance peaked when the top 2% functional connections identified in the discovery dataset (ranked by absolute ß-weight) were retained. The RSFC networks that were implicated most prominently were the default mode, dorsal attention, and cingulo-parietal networks. These findings were significant (p < 1*10-6) as accounted for by permutation testing (n = 7000). CONCLUSIONS: These results suggest that the neural phenotype associated with internalizing symptoms during adolescence is functionally distributed. The PNRS approach is a novel method for capturing relationships between RSFC and behavior.

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BACKGROUND: Physical activity combined with virtual reality and exergaming has emerged as a new technique to improve engagement and provide clinical benefit for gait and balance disorders in people with Parkinson's disease (PD). OBJECTIVE: To investigate the effects of a training protocol using a home-based exergaming system on brain volume and resting-state functional connectivity (rs-FC) in persons with PD. METHODS: A single blind randomized controlled trial was conducted in people with PD with gait and/or balance disorders. The experimental (active) group performed 18 training sessions at home by playing a custom-designed exergame with full body movements, standing in front of a RGB-D Kinect® motion sensor, while the control group played using the computer keyboard. Both groups received the same training program. Clinical scales, gait recordings, and brain MRI were performed before and after training. We assessed the effects of both training on both the grey matter volumes (GVM) and rs-FC, within and between groups. RESULTS: Twenty-three patients were enrolled and randomly assigned to either the active (n = 11) or control (n = 12) training groups. Comparing pre- to post-training, the active group showed significant improvements in gait and balance disorders, with decreased rs-FC between the sensorimotor, attentional and basal ganglia networks, but with an increase between the cerebellar and basal ganglia networks. In contrast, the control group showed no significant changes, and rs-FC significantly decreased in the mesolimbic and visuospatial cerebellar and basal ganglia networks. Post-training, the rs-FC was greater in the active relative to the control group between the basal ganglia, motor cortical and cerebellar areas, and bilaterally between the insula and the inferior temporal lobe. Conversely, rs FC was lower in the active relative to the control group between the pedunculopontine nucleus and cerebellar areas, between the temporal inferior lobes and the right thalamus, between the left putamen and dorsolateral prefrontal cortex, and within the default mode network. CONCLUSIONS: Full-body movement training using a customized exergame induced brain rs-FC changes within the sensorimotor, attentional and cerebellar networks in people with PD. Further research is needed to comprehensively understand the neurophysiological effects of such training approaches. Trial registration ClinicalTrials.gov NCT03560089.

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LSD is a hallucinogen with complex neurobiological and behavioral effects. Underlying these effects are changes in brain neuroplasticity. This is the first study to follow the developmental changes in brain structure and function following LSD exposure in periadolescence. We hypothesized LSD given during a time of heightened neuroplasticity, particularly in the forebrain, would affect cognitive and emotional behavior and the associated underlying neuroanatomy and neurocircuitry. Female and male mice were given vehicle, single or multiple treatments of 3.3 µg of LSD by oral gavage starting on postnatal day 51. Between postnatal days 90-120 mice were imaged and tested for cognitive and motor behavior. MRI data from voxel-based morphometry, diffusion weighted imaging, and BOLD resting state functional connectivity were registered to a mouse 3D MRI atlas with 139 brain regions providing site-specific differences in global brain structure and functional connectivity between experimental groups. Motor behavior and cognitive performance were unaffected by periadolescent exposure to LSD. Differences across experimental groups in brain volume for any of the 139 brain areas were few in number and not focused on any specific brain region. Multiple exposures to LSD significantly altered gray matter microarchitecture across much of the brain. These changes were primary associated with the thalamus, sensory and motor cortices, and basal ganglia. The forebrain olfactory system and prefrontal cortex and hindbrain cerebellum and brainstem were unaffected. The functional connectivity between forebrain white matter tracts and sensorimotor cortices and hippocampus was reduced with multidose LSD exposure. Does exposure to LSD in late adolescence have lasting effects on brain development? The bulk of our significant findings were seen through changes is DWI values across 74 brain areas in the multi-dose LSD group. The pronounced changes in indices of anisotropy across much of the brain would suggest altered gray matter microarchitecture and neuroplasticity. There was no evidence of LSD having consequential effects on cognitive or motor behavior when animal were evaluated as young adults 90-120 days of age. Neither were there any differences in the volume of specific brain areas between experimental conditions. The reduction in connectivity in forebrain white matter tracts with multidose LSD and consolidation around sensorimotor and hippocampal brain areas requires a battery of tests to understand the consequences of these changes on behavior.

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BACKGROUND: There is no diagnostic assessment procedure with moderate or strong evidence of use, and evidence for current means of treating prolonged disorders of consciousness (pDOC) is sparse. This may be related to the fact that the mechanisms of pDOC have not been studied deeply enough and are not clear enough. Therefore, the aim of this study was to explore the mechanism of pDOC using functional near-infrared spectroscopy (fNIRS) to provide a basis for the treatment of pDOC, as well as to explore preclinical markers for determining the arousal of pDOC patients. METHODS: Five minutes resting-state data were collected from 10 pDOC patients and 13healthy adults using fNIRS. Based on the concentrations of oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) in the time series, the resting-state cortical brain functional connectivity strengths of the two groups were calculated, and the functional connectivity strengths of homologous and heterologous brain networks were compared at the sensorimotor network (SEN), dorsal attention network (DAN), ventral attention network (VAN), default mode network (DMN), frontoparietal network (FPN), and visual network (VIS) levels. Univariate binary logistic regression analyses were performed on brain networks with statistically significant differences to identify brain networks associated with arousal in pDOC patients. The receiver operating characteristic (ROC) curves were further analyzed to determine the cut-off value of the relevant brain networks to provide clinical biomarkers for the prediction of arousal in pDOC patients. RESULTS: The results showed that the functional connectivity strengths of oxyhemoglobin (HbO)-based SEN∼SEN, VIS∼VIS, DAN∼DAN, DMN∼DMN, SEN∼VIS, SEN∼FPN, SEN∼DAN, SEN∼DMN, VIS∼FPN, VIS∼DAN, VIS∼DMN, HbR-based SEN∼SEN, and SEN∼DAN were significantly reduced in the pDOC group and were factors that could reflect the participants' state of consciousness. The cut-off value of resting-state functional connectivity strength calculated by ROC curve analysis can be used as a potential preclinical marker for predicting the arousal state of subjects. CONCLUSION: Resting-state functional connectivity strength of cortical networks is significantly reduced in pDOC patients. The cut-off values of resting-state functional connectivity strength are potential preclinical markers for predicting arousal in pDOC patients.

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INTRODUCTION: Convergence Insufficiency (CI) is the most prevalent oculomotor dysfunction of binocular vision that negatively impacts quality of life when performing visual near tasks. Decreased resting-state functional connectivity (RSFC) is reported in the CI participants compared to binocularly normal control participants. Studies report that therapeutic interventions such as office-based vergence and accommodative therapy (OBVAT) can improve CI participants' clinical signs, visual symptoms, and task-related functional activity. However, longitudinal studies investigating the RSFC changes after such treatments in participants with CI have not been conducted. This study aimed to investigate the neural basis of OBVAT using RSFC in CI participants compared to the placebo treatment to understand how OBVAT improves visual function and symptoms. METHODS: A total of 51 CI participants between 18 and 35 years of age were included in the study and randomly allocated to receive either 12 one-hour sessions of OBVAT or placebo treatment for 6 to 8 weeks (1 to 2 sessions per week). Resting-state functional magnetic resonance imaging and clinical assessments were evaluated at baseline and outcome for each treatment group. Region of interest (ROI) analysis was conducted in nine ROIs of the oculomotor vergence network, including the following: cerebellar vermis (CV), frontal eye fields (FEF), supplementary eye fields (SEF), parietal eye fields (PEF), and primary visual cortices (V1). Paired t-tests assessed RSFC changes in each group. A linear regression analysis was conducted for significant ROI pairs in the group-level analysis for correlations with clinical measures. RESULTS: Paired t-test results showed increased RSFC in 10 ROI pairs after the OBVAT but not placebo treatment (p < 0.05, false discovery rate corrected). These ROI pairs included the following: Left (L)-SEF-Right (R)-V1, L-SEF-CV, R-SEF-R-PEF, R-SEF-L-V1, R-SEF-R-V1, R-SEF-CV, R-PEF-CV, L-V1-CV, R-V1-CV, and L-V1-R-V1. Significant correlations were observed between the RSFC strength of the R-SEF-R-PEF ROI pair and the following clinical visual function parameters: positive fusional vergence and near point of convergence (p < 0.05). CONCLUSION: OBVAT, but not placebo treatment, increased the RSFC in the ROIs of the oculomotor vergence network, which was correlated with the improvements in the clinical measures of the CI participants.

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OBJECTIVE: The amygdala joins the model of fear neurocircuitry for its subregional roles in processing and mediating panic. This study aims to explore the underlying neuromechanisms of temporal lobe epilepsy (TLE) patients with ictal panic (IP) by investigating the amygdala subregions functional connectivity (FC) alteration. METHODS: 18 TLE patients with IP (TLE-IP group), 23 TLE patients without IP (TLE-none-IP group) and 22 age- and sex- matched healthy controls (HC) were enrolled and required to take resting-state functional magnetic resonance imaging (rs-fMRI) scanning. The basolateral (BLA), centromedial (CMA), and superficial (SFA) amygdala subregions were extracted from Juelich histological atlas. The amygdala subregions-based FC was computed and compared among three groups. RESULTS: The TLE-IP group demonstrated stronger FC between the left BLA and right middle frontal gyrus (MFG) than the TLE-none-IP group and HC. Compared with the TLE-none-IP group and HC, the TLE-IP group showed increased FC between the right BLA and right postcentral gyrus. The FC between the left BLA/SFA and the orbital part of right MFG increased in the TLE-IP group. Furthermore, the TLE-IP group exhibited decreased FC between the left CMA and pons. Further analysis indicated altered FC between the amygdala subregions and the pons, precuneus and thalamus in the left-sided TLE-IP group, but the MFG, inferior parietal gyrus, supplementary motor area and cerebellum in the right-sided TLE-IP group. CONCLUSIONS: The present study revealed aberrant amygdala subregions-based FC in TLE patients with IP. These findings offer unique insights into the understanding of fear neurocircuitry in TLE patients with IP.

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AIMS: Previous neuroimaging research in alcohol use disorder (AUD) has found altered functional connectivity in the brain's salience, default mode, and central executive (CEN) networks (i.e. the triple network model), though their specific associations with AUD severity and heavy drinking remains unclear. This study utilized resting-state fMRI to examine functional connectivity in these networks and measures of alcohol misuse. METHODS: Seventy-six adult heavy drinkers completed a 7-min resting-state functional MRI scan during visual fixation. Linear regression models tested if connectivity in the three target networks was associated with past 12-month AUD symptoms and number of heavy drinking days in the past 30 days. Exploratory analyses examined correlations between connectivity clusters and impulsivity and psychopathology measures. RESULTS: Functional connectivity within the CEN network (right and left lateral prefrontal cortex [LPFC] seeds co-activating with 13 and 15 clusters, respectively) was significantly associated with AUD symptoms (right LPFC: ß = .337, p-FDR = .016; left LPFC: ß = .291, p-FDR = .028) but not heavy drinking (p-FDR > .749). Post-hoc tests revealed six clusters co-activating with the CEN network were associated with AUD symptoms-right middle frontal gyrus, right inferior parietal gyrus, left middle temporal gyrus, and left and right cerebellum. Neither the default mode nor the salience network was significantly associated with alcohol variables. Connectivity in the left LPFC was correlated with monetary delay discounting (r = .25, p = .03). CONCLUSIONS: These findings support previous associations between connectivity within the CEN network and AUD severity, providing additional specificity to the relevance of the triple network model to AUD.

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Background: Generalized anxiety disorder (GAD) and social anxiety disorder (SAD) are distinguished by whether anxiety is limited to social situations. However, reports on the differences in brain functional networks between GAD and SAD are few. Our objective is to understand the pathogenesis of GAD and SAD by examining the differences in resting brain function between patients with GAD and SAD and healthy controls (HCs). Methods: This study included 21 patients with SAD, 17 patients with GAD, and 30 HCs. Participants underwent psychological assessments and resting-state functional magnetic resonance imaging. Whole-brain analyses were performed to compare resting-state functional connectivity (rsFC) among the groups. In addition, logistic regression analysis was conducted on the rsFC to identify significant differences between GAD and SAD. Results: Patients with SAD and GAD had significantly higher rsFC between the bilateral postcentral gyri and bilateral amygdalae/thalami than HCs. Compared with patients with SAD, those with GAD had significantly higher rsFC between the right nucleus accumbens and bilateral thalami and between the left nucleus accumbens and right thalamus. rsFC between the left nucleus accumbens and right thalamus positively correlated with state anxiety in patients with SAD and GAD, respectively. In addition, logistic regression analysis revealed that the right nucleus accumbens and the right thalamus connectivity could distinguish SAD from GAD. Conclusions: GAD and SAD were distinguished by the right nucleus accumbens and the right thalamus connectivity. Our findings offer insights into the disease-specific neural basis of SAD and GAD. Clinical Trial Registration Number: M10545. Impact Statement This study is the first to identify a resting state functional connectivity that distinguishes social anxiety disorder (SAD) from generalized anxiety disorder (GAD) and to clarify a common connectivity in both disorders. We found that the connectivity between the right nucleus accumbens and the right thalamus differentiated SAD from GAD. Furthermore, these rsFC differences suggest an underlying basis for fear overgeneralization. Our findings shed light on the pathophysiology of these conditions and could be used as a basis for further studies to improve outcomes for such patients.

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Genetic variations in single nucleotide polymorphisms (SNPs) within oxytocin pathway genes have been linked to social behavior and neurodevelopmental conditions. However, the neurobiological mechanisms underlying these associations remain elusive. In this study, we investigated the relationship between variations of 10 SNPs in oxytocin pathway genes and resting-state functional connectivity among 55 independent components using a large sample from the UK Biobank (N ≈ 30,000). Our findings revealed that individuals with the GG genotype at rs4813627 within the oxytocin structural gene (OXT) exhibited weaker resting-state functional connectivity in the corticostriatal circuit compared to those with the GA/AA genotypes. Empirical evidence has linked the GG genotype at OXT rs4813627 with a behavioral tendency of insensitivity to others. These results inform the neural mechanisms by which oxytocin-related genetic factors can influence social behavior.

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Obsessive-compulsive disorder (OCD) is characterized by intrusive thoughts and repetitive, compulsive behaviors, with childhood trauma recognized as a contributing factor to its pathophysiology. This study aimed to delineate brain functional aberrations in OCD patients and explore the association between these abnormalities and childhood trauma, to gain insights into the neural underpinnings of OCD. Forty-eight drug-naive OCD patients and forty-two healthy controls (HC) underwent resting-state functional magnetic resonance imaging and clinical assessments, including the Yale-Brown Obsessive Compulsive Scale (Y-BOCS) and Childhood Trauma Questionnaire-Short Form (CTQ-SF). Compared to HCs, OCD patients exhibited significantly decreased amplitude of low-frequency fluctuations (ALFF) in the right cerebellum, decreased regional homogeneity (ReHo) in the right cerebellum and right superior occipital lobes (FWE-corrected p < 0.05), which negatively correlated with Y-BOCS scores (p < 0.05). Furthermore, cerebellar ALFF negatively correlated with the CTQ emotional abuse subscale (r = - 0.514, p < 0.01). Mediation analysis revealed that cerebellar ALFF mediated the relationship between CTQ-emotional abuse and Y-BOCS (good model fit: R2 = 0.231, MSE = 14.311, F = 5.721, p < 0.01; direct effect, c' = 0.153, indirect effect, a*b = 0.191). Findings indicated abnormal spontaneous and regional cerebellar activity in OCD, suggesting childhood trauma impacts OCD symptoms through cerebellar neural remodeling, highlighting its importance for clinical treatment selection.

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Progressive supranuclear palsy (PSP) is an atypical Parkinsonian syndrome characterized initially by falls and eye movement impairment. This multimodal imaging study aimed at eliciting structural and functional disease-specific brain alterations. T1-weighted and resting-state functional MRI were applied in multi-centric cohorts of PSP and matched healthy controls. Midbrain, cerebellum, and cerebellar peduncles showed severely low gray/white matter volume, whereas thinner cortical gray matter was observed in cingulate cortex, medial and temporal gyri, and insula. Eigenvector centrality analyses revealed regionally specific alterations. Multivariate pattern recognition classified patients correctly based on gray and white matter segmentations with up to 98 % accuracy. Highest accuracies were obtained when restricting feature selection to the midbrain. Eigenvector centrality indices yielded an accuracy around 70 % in this comparison; however, this result did not reach significance. In sum, the study reveals multimodal, widespread brain changes in addition to the well-known midbrain atrophy in PSP. Alterations in brain structure seem to be superior to eigenvector centrality parameters, in particular for prediction with machine learning approaches.

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BACKGROUND: Insomnia disorder (ID) is one of the most common sleep problems, usually accompanied by anxiety and depression symptoms. Functional magnetic resonance imaging (fMRI) study suggests that both poor sleep quality and negative emotion are linked to the dysregulation of brain network related to emotion processing in ID patients. Acupuncture therapy has been proven effective in improving sleep quality and mood of ID patients, but the involved neurobiological mechanism remains unclear. We aimed to investigate the modulation effect of acupuncture on resting-state functional connectivity (rsFC) of the emotional network (EN) in patients experiencing insomnia. METHODS: A total of 30 healthy controls (HCs) and 60 ID patients were enrolled in this study. Sixty ID patients were randomly assigned to real and sham acupuncture groups and attended resting-state fMRI scans before and after 4 weeks of acupuncture treatment. HCs completed an MRI/fMRI scan at baseline. The rsFC values within EN were calculated, and Hamilton Anxiety Scale (HAMA), Hamilton Depression Scale (HAMD), Pittsburgh Sleep Quality Index (PSQI), Hyperarousal Scale (HAS), and actigraphy data were collected for clinical efficacy evaluation. RESULTS: Resting-state FC analysis showed abnormalities in rsFC centered on the thalamus and dorsolateral prefrontal cortex within EN of ID patients compared to HCs. After real acupuncture treatment, rsFC of the anterior cingulate cortex, hippocampus, and amygdala were increased compared with the sham acupuncture group (p < 0.05, FDR corrected). In real acupuncture group, the rsFC value was decreased between left amygdala and left thalamus after 4 weeks of treatment compared with baseline. A trend of correlation was found that the increased rsFC value between the right amygdala and left hippocampus was positively correlated with the decreased HAMA scores across all ID patients, and the decreased left amygdala rsFC value with the left thalamus was negatively correlated with the increased sleep efficiency in the real acupuncture group. CONCLUSION: Our findings showed that real acupuncture could produce a positive effect on modulating rsFC within network related to emotion processing in ID patients, which may illustrate the central mechanism underlying acupuncture for insomnia in improving sleep quality and emotion regulation. TRIAL REGISTRATION: http://www.chictr.org.cn ., ChiCTR1800015282, 20/03/2018.

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