Examining relationships among NODDI indices of white matter structure in prefrontal cortical-thalamic-striatal circuitry and OCD symptomatology.

Obsessive-compulsive disorder is a psychiatric disorder characterized by intrusive thoughts and repetitive behaviors. There are two prominent features: Harm Avoidance (HA) and Incompleteness (INC). Previous resting-state studies reported abnormally elevated connectivity between prefrontal cortical (PFC) and subcortical regions (thalamus, striatum) in OCD participants. Yet, little is known about the white matter (WM) structural abnormalities in these connections. Using brain parcellation and segmentation, whole brain tractography, and Neurite Orientation Dispersion and Density Imaging (NODDI), we aimed to characterize WM structural abnormalities in OCD vs. healthy controls and determine the extent to which NODDI indices of these connections were associated with subthreshold-threshold HA, INC and overall OCD symptom severity across all participants. Four PFC regions were segmented: ventral medial (vmPFC), ventrolateral (vlPFC), dorsomedial (dmPFC), and dorsolateral (dlPFC). NODDI Neurite Density (NDI) and Orientation Dispersion (ODI) indices of WM structure were extracted from connections between these PFC regions and the thalamus (42 OCD, 44 healthy controls, mean age[SD] = 23.65[4.25]y, 63.9% female) and striatum (38 OCD, 41 healthy controls, mean age[SD] = 23.59[4.27]y, 64.5% female). Multivariate analyses of covariance revealed no between-group differences in these indices. Multivariate regression models revealed that greater NDI in vmPFC-thalamus, greater NDI and ODI in vmPFC-striatum, and greater NDI in dmPFC-thalamus connections were associated with greater INC severity (Q ≤ 0.032). These findings highlight the utility of NODDI in the examination of WM structure in OCD, provide valuable insights into specific WM alterations underlying dimensional INC, and can facilitate the development of customized treatments for OCD individuals with treatment-resistant symptoms.

Multilayer network analysis reveals instability of brain dynamics in untreated first-episode schizophrenia.

Although aberrant static functional brain network activity has been reported in schizophrenia, little is known about how the dynamics of neural function are altered in first-episode schizophrenia and are modulated by antipsychotic treatment. The baseline resting-state functional magnetic resonance imaging data were acquired from 122 first-episode drug-naïve schizophrenia patients and 128 healthy controls (HCs), and 44 patients were rescanned after 1-year of antipsychotic treatment. Multilayer network analysis was applied to calculate the network switching rates between brain states. Compared to HCs, schizophrenia patients at baseline showed significantly increased network switching rates. This effect was observed mainly in the sensorimotor (SMN) and dorsal attention networks (DAN), and in temporal and parietal regions at the nodal level. Switching rates were reduced after 1-year of antipsychotic treatment at the global level and in DAN. Switching rates at baseline at the global level and in the inferior parietal lobule were correlated with the treatment-related reduction of negative symptoms. These findings suggest that instability of functional network activity plays an important role in the pathophysiology of acute psychosis in early-stage schizophrenia. The normalization of network stability after antipsychotic medication suggests that this effect may represent a systems-level mechanism for their therapeutic efficacy.

Musical Sophistication and Multilingualism: Effects on Arcuate Fasciculus Characteristics.

The processing of auditory stimuli which are structured in time is thought to involve the arcuate fasciculus, the white matter tract which connects the temporal cortex and the inferior frontal gyrus. Research has indicated effects of both musical and language experience on the structural characteristics of the arcuate fasciculus. Here, we investigated in a sample of n = 84 young adults whether continuous conceptualizations of musical and multilingual experience related to structural characteristics of the arcuate fasciculus, measured using diffusion tensor imaging. Probabilistic tractography was used to identify the dorsal and ventral parts of the white matter tract. Linear regressions indicated that different aspects of musical sophistication related to the arcuate fasciculus' volume (emotional engagement with music), volumetric asymmetry (musical training and music perceptual abilities), and fractional anisotropy (music perceptual abilities). Our conceptualization of multilingual experience, accounting for participants' proficiency in reading, writing, understanding, and speaking different languages, was not related to the structural characteristics of the arcuate fasciculus. We discuss our results in the context of other research on hemispheric specializations and a dual-stream model of auditory processing.

Thalamocortical Dysconnectivity in Treatment-Resistant Depression.

Thalamocortical connectivity is associated with cognitive and affective processing. The role of thalamocortical connectivity in the pathomechanism of treatment-resistant depression (TRD) remains unclear. This study included 48 patients with TRD and 48 healthy individuals. We investigated thalamocortical connectivity by performing resting-state functional MRI with the bilateral thalamus as the seed. In addition, patients with TRD were evaluated using the Montgomery-Åsberg Depression Rating Scale (MADRS). Compared with the healthy individuals, the patients with TRD exhibited increased functional connectivity (FC) of the thalamus with the insula and superior temporal cortex and reduced the FC of the thalamus with the anterior paracingulate cortex and cerebellum crus II. Our study may support the crucial role of thalamocortical dysconnectivity in the TRD pathomechanism. However, the small sample size may limit the statistical power. A future study with a large sample size of patients with TRD would be required to validate our findings.

Metabolic network connectivity disturbances in Parkinson's disease: a novel imaging biomarker.

The diagnosis of Parkinson's Disease (PD) presents ongoing challenges. Advances in imaging techniques like 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) have highlighted metabolic alterations in PD, yet the dynamic network interactions within the metabolic connectome remain elusive. To this end, we examined a dataset comprising 49 PD patients and 49 healthy controls. By employing a personalized metabolic connectome approach, we assessed both within- and between-network connectivities using Standard Uptake Value (SUV) and Jensen-Shannon Divergence Similarity Estimation (JSSE). A random forest algorithm was utilized to pinpoint key neuroimaging features differentiating PD from healthy states. Specifically, the results revealed heightened internetwork connectivity in PD, specifically within the somatomotor (SMN) and frontoparietal (FPN) networks, persisting after multiple comparison corrections (P < 0.05, Bonferroni adjusted for 10% and 20% sparsity). This altered connectivity effectively distinguished PD patients from healthy individuals. Notably, this study utilizes 18F-FDG PET imaging to map individual metabolic networks, revealing enhanced connectivity in the SMN and FPN among PD patients. This enhanced connectivity may serve as a promising imaging biomarker, offering a valuable asset for early PD detection.

Brain markers of subtraction and multiplication skills in childhood: task-based functional connectivity and individualized structural similarity.

Arithmetic, a high-order cognitive ability, show marked individual difference over development. Despite recent advancements in neuroimaging techniques have enabled the identification of brain markers for individual differences in high-order cognitive abilities, it remains largely unknown about the brain markers for arithmetic. This study used a data-driven connectome-based prediction model to identify brain markers of arithmetic skills from arithmetic-state functional connectivity and individualized structural similarity in 132 children aged 8 to 15 years. We found that both subtraction-state functional connectivity and individualized SS successfully predicted subtraction and multiplication skills but multiplication-state functional connectivity failed to predict either skill. Among the four successful prediction models, most predictive connections were located in frontal-parietal, default-mode, and secondary visual networks. Further computational lesion analyses revealed the essential structural role of frontal-parietal network in predicting subtraction and the essential functional roles of secondary visual, language, and ventral multimodal networks in predicting multiplication. Finally, a few shared nodes but largely nonoverlapping functional and structural connections were found to predict subtraction and multiplication skills. Altogether, our findings provide new insights into the brain markers of arithmetic skills in children and highlight the importance of studying different connectivity modalities and different arithmetic domains to advance our understanding of children's arithmetic skills.

Methylphenidate reduces spatial attentional bias by modulating fronto-striatal connectivity.

Spatial attention bias reflects tendency to direct attention to specific side in space. This bias reflects asymmetric dopamine (DA) signaling in the striatum. Administration of DA agonists reduces spatial bias, yet the underlying mechanism is not yet clear. To address this, the current study tested whether methylphenidate (MPH; an indirect DA agonist) reduces orienting bias by modulating fronto-striatal connectivity. 54 adults with consistent bias completed the greyscales task which detects subtle biases during fMRI scanning under MPH (20 mg) or placebo, in a double-blind design. As hypothesized, MPH reduced bias by increasing orienting towards non-preferred hemispace, regardless of whether the initial bias was left or right. MPH-induced increases were found in activation of the medial superior frontal gyrus (mSFG: F[1;53] = 4.632, cluster-defining threshold of P < 0.05, minimal cluster size = 0, p_FWE = 0.036, η2 = 0.08) and its functional connectivity with the caudate (left caudate: F[1;53] = 12.664, p_FWE = 0.001, η2 = 0.192; right caudate: F[1;53] = 11.069, p_FWE = 0.002, η2 = 0.172), when orienting towards the non-preferred hemispace. MPH also reduced mSFG activation and fronto-striatal connectivity for the preferred hemispace. Results suggest modulation of frontal excitability due to increased caudate-mSFG functional connectivity. This mechanism may underlie the positive effect of dopaminergic agonists on abnormal patterns of directing attention in space.

White matter microstructure and functional connectivity in the brains of infants with Turner syndrome.

Turner syndrome, caused by complete or partial loss of an X-chromosome, is often accompanied by specific cognitive challenges. Magnetic resonance imaging studies of adults and children with Turner syndrome suggest these deficits reflect differences in anatomical and functional connectivity. However, no imaging studies have explored connectivity in infants with Turner syndrome. Consequently, it is unclear when in development connectivity differences emerge. To address this gap, we compared functional connectivity and white matter microstructure of 1-year-old infants with Turner syndrome to typically developing 1-year-old boys and girls. We examined functional connectivity between the right precentral gyrus and five regions that show reduced volume in 1-year old infants with Turner syndrome compared to controls and found no differences. However, exploratory analyses suggested infants with Turner syndrome have altered connectivity between right supramarginal gyrus and left insula and right putamen. To assess anatomical connectivity, we examined diffusivity indices along the superior longitudinal fasciculus and found no differences. However, an exploratory analysis of 46 additional white matter tracts revealed significant group differences in nine tracts. Results suggest that the first year of life is a window in which interventions might prevent connectivity differences observed at later ages, and by extension, some of the cognitive challenges associated with Turner syndrome.

Contracted functional connectivity profiles in autism.

OBJECTIVE: Autism spectrum disorder (ASD) is a neurodevelopmental condition that is associated with atypical brain network organization, with prior work suggesting differential connectivity alterations with respect to functional connection length. Here, we tested whether functional connectopathy in ASD specifically relates to disruptions in long- relative to short-range functional connections. Our approach combined functional connectomics with geodesic distance mapping, and we studied associations to macroscale networks, microarchitectural patterns, as well as socio-demographic and clinical phenotypes. METHODS: We studied 211 males from three sites of the ABIDE-I dataset comprising 103 participants with an ASD diagnosis (mean ± SD age = 20.8 ± 8.1 years) and 108 neurotypical controls (NT, 19.2 ± 7.2 years). For each participant, we computed cortex-wide connectivity distance (CD) measures by combining geodesic distance mapping with resting-state functional connectivity profiling. We compared CD between ASD and NT participants using surface-based linear models, and studied associations with age, symptom severity, and intelligence scores. We contextualized CD alterations relative to canonical networks and explored spatial associations with functional and microstructural cortical gradients as well as cytoarchitectonic cortical types. RESULTS: Compared to NT, ASD participants presented with widespread reductions in CD, generally indicating shorter average connection length and thus suggesting reduced long-range connectivity but increased short-range connections. Peak reductions were localized in transmodal systems (i.e., heteromodal and paralimbic regions in the prefrontal, temporal, and parietal and temporo-parieto-occipital cortex), and effect sizes correlated with the sensory-transmodal gradient of brain function. ASD-related CD reductions appeared consistent across inter-individual differences in age and symptom severity, and we observed a positive correlation of CD to IQ scores. LIMITATIONS: Despite rigorous harmonization across the three different acquisition sites, heterogeneity in autism poses a potential limitation to the generalizability of our results. Additionally, we focussed male participants, warranting future studies in more balanced cohorts. CONCLUSIONS: Our study showed reductions in CD as a relatively stable imaging phenotype of ASD that preferentially impacted paralimbic and heteromodal association systems. CD reductions in ASD corroborate previous reports of ASD-related imbalance between short-range overconnectivity and long-range underconnectivity.

Atypical effective connectivity from the frontal cortex to striatum in alcohol use disorder.

Alcohol use disorder (AUD) is a profound psychiatric condition marked by disrupted connectivity among distributed brain regions, indicating impaired functional integration. Previous connectome studies utilizing functional magnetic resonance imaging (fMRI) have predominantly focused on undirected functional connectivity, while the specific alterations in directed effective connectivity (EC) associated with AUD remain unclear. To address this issue, this study utilized multivariate pattern analysis (MVPA) and spectral dynamic causal modeling (DCM). We recruited 32 abstinent men with AUD and 30 healthy controls (HCs) men, and collected their resting-state fMRI data. A regional homogeneity (ReHo)-based MVPA method was employed to classify AUD and HC groups, as well as predict the severity of addiction in AUD individuals. The most informative brain regions identified by the MVPA were further investigated using spectral DCM. Our results indicated that the ReHo-based support vector classification (SVC) exhibits the highest accuracy in distinguishing individuals with AUD from HCs (classification accuracy: 98.57%). Additionally, our results demonstrated that ReHo-based support vector regression (SVR) could be utilized to predict the addiction severity (alcohol use disorders identification test, AUDIT, R2 = 0.38; Michigan alcoholism screening test, MAST, R2 = 0.29) of patients with AUD. The most informative brain regions for the prediction include left pre-SMA, right dACC, right LOFC, right putamen, and right NACC. These findings were validated in an independent data set (35 patients with AUD and 36 HCs, Classification accuracy: 91.67%; AUDIT, R2 = 0.17; MAST, R2 = 0.20). The results of spectral DCM analysis indicated that individuals with AUD exhibited decreased EC from the left pre-SMA to the right putamen, from the right dACC to the right putamen, and from the right LOFC to the right NACC compared to HCs. Moreover, the EC strength from the right NACC to left pre-SMA and from the right dACC to right putamen mediated the relationship between addiction severity (MAST scores) and behavioral measures (impulsive and compulsive scores). These findings provide crucial evidence for the underlying mechanism of impaired self-control, risk assessment, and impulsive and compulsive alcohol consumption in individuals with AUD, providing novel causal insights into both diagnosis and treatment.

Involvement of the cerebellum in structural connectivity enhancement in episodic migraine.

BACKGROUND: The pathophysiology of migraine remains poorly understood, yet a growing number of studies have shown structural connectivity disruptions across large-scale brain networks. Although both structural and functional changes have been found in the cerebellum of migraine patients, the cerebellum has barely been assessed in previous structural connectivity studies of migraine. Our objective is to investigate the structural connectivity of the entire brain, including the cerebellum, in individuals diagnosed with episodic migraine without aura during the interictal phase, compared with healthy controls. METHODS: To that end, 14 migraine patients and 15 healthy controls were recruited (all female), and diffusion-weighted and T1-weighted MRI data were acquired. The structural connectome was estimated for each participant based on two different whole-brain parcellations, including cortical and subcortical regions as well as the cerebellum. The structural connectivity patterns, as well as global and local graph theory metrics, were compared between patients and controls, for each of the two parcellations, using network-based statistics and a generalized linear model (GLM), respectively. We also compared the number of connectome streamlines within specific white matter tracts using a GLM. RESULTS: We found increased structural connectivity in migraine patients relative to healthy controls with a distinct involvement of cerebellar regions, using both parcellations. Specifically, the node degree of the posterior lobe of the cerebellum was greater in patients than in controls and patients presented a higher number of streamlines within the anterior limb of the internal capsule. Moreover, the connectomes of patients exhibited greater global efficiency and shorter characteristic path length, which correlated with the age onset of migraine. CONCLUSIONS: A distinctive pattern of heightened structural connectivity and enhanced global efficiency in migraine patients compared to controls was identified, which distinctively involves the cerebellum. These findings provide evidence for increased integration within structural brain networks in migraine and underscore the significance of the cerebellum in migraine pathophysiology.

Frontostriatal salience network expansion in individuals in depression.

Decades of neuroimaging studies have shown modest differences in brain structure and connectivity in depression, hindering mechanistic insights or the identification of risk factors for disease onset1. Furthermore, whereas depression is episodic, few longitudinal neuroimaging studies exist, limiting understanding of mechanisms that drive mood-state transitions. The emerging field of precision functional mapping has used densely sampled longitudinal neuroimaging data to show behaviourally meaningful differences in brain network topography and connectivity between and in healthy individuals2-4, but this approach has not been applied in depression. Here, using precision functional mapping and several samples of deeply sampled individuals, we found that the frontostriatal salience network is expanded nearly twofold in the cortex of most individuals with depression. This effect was replicable in several samples and caused primarily by network border shifts, with three distinct modes of encroachment occurring in different individuals. Salience network expansion was stable over time, unaffected by mood state and detectable in children before the onset of depression later in adolescence. Longitudinal analyses of individuals scanned up to 62 times over 1.5 years identified connectivity changes in frontostriatal circuits that tracked fluctuations in specific symptoms and predicted future anhedonia symptoms. Together, these findings identify a trait-like brain network topology that may confer risk for depression and mood-state-dependent connectivity changes in frontostriatal circuits that predict the emergence and remission of depressive symptoms over time.

Morning resting hypothalamus-dorsal striatum connectivity predicts individual differences in diurnal sleepiness accumulation.

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.

Differential activation of lateral parabrachial nuclei and their limbic projections during head compared with body pain: A 7-Tesla functional magnetic resonance imaging study.

Pain is a complex experience that involves sensory, emotional, and motivational components. It has been suggested that pain arising from the head and orofacial regions evokes stronger emotional responses than pain from the body. Indeed, recent work in rodents reports different patterns of activation in ascending pain pathways during noxious stimulation of the skin of the face when compared to noxious stimulation of the body. Such differences may dictate different activation patterns in higher brain regions, specifically in those areas processing the affective component of pain. We aimed to use ultra-high field functional magnetic resonance imaging (fMRI at 7-Tesla) to determine whether noxious thermal stimuli applied to the surface of the face and body evoke differential activation patterns within the ascending pain pathway in awake humans (n=16). Compared to the body, noxious heat stimulation to the face evoked more widespread signal changes in prefrontal cortical regions and numerous brainstem and subcortical limbic areas. Moreover, facial pain evoked significantly different signal changes in the lateral parabrachial nucleus, substantia nigra, paraventricular hypothalamus, and paraventricular thalamus, to those evoked by body pain. These results are consistent with recent preclinical findings of differential activation in the brainstem and subcortical limbic nuclei and associated cortices during cutaneous pain of the face when compared with the body. The findings suggest one potential mechanism by which facial pain could evoke a greater emotional impact than that evoked by body pain.

Structure-function coupling in highly sampled individual brains.

Structural connectivity (SC) between distant regions of the brain support synchronized function known as functional connectivity (FC) and give rise to the large-scale brain networks that enable cognition and behavior. Understanding how SC enables FC is important to understand how injuries to SC may alter brain function and cognition. Previous work evaluating whole-brain SC-FC relationships showed that SC explained FC well in unimodal visual and motor areas, but only weakly in association areas, suggesting a unimodal-heteromodal gradient organization of SC-FC coupling. However, this work was conducted in group-averaged SC/FC data. Thus, it could not account for inter-individual variability in the locations of cortical areas and white matter tracts. We evaluated the correspondence of SC and FC within three highly sampled healthy participants. For each participant, we collected 78 min of diffusion-weighted MRI for SC and 360 min of resting state fMRI for FC. We found that FC was best explained by SC in visual and motor systems, as well as in anterior and posterior cingulate regions. A unimodal-to-heteromodal gradient could not fully explain SC-FC coupling. We conclude that the SC-FC coupling of the anterior-posterior cingulate circuit is more similar to unimodal areas than to heteromodal areas.

Structural connectivity modifications following deep brain stimulation of the subcallosal cingulate and nucleus accumbens in severe anorexia nervosa.

PURPOSE: Anorexia nervosa (AN) is a mental health disorder characterized by significant weight loss and associated medical and psychological comorbidities. Conventional treatments for severe AN have shown limited effectiveness, leading to the exploration of novel interventional strategies, including deep brain stimulation (DBS). However, the neural mechanisms driving DBS interventions, particularly in psychiatric conditions, remain uncertain. This study aims to address this knowledge gap by examining changes in structural connectivity in patients with severe AN before and after DBS. METHODS: Sixteen participants, including eight patients with AN and eight controls, underwent baseline T1-weigthed and diffusion tensor imaging (DTI) acquisitions. Patients received DBS targeting either the subcallosal cingulate (DBS-SCC, N = 4) or the nucleus accumbens (DBS-NAcc, N = 4) based on psychiatric comorbidities and AN subtype. Post-DBS neuroimaging evaluation was conducted in four patients. Data analyses were performed to compare structural connectivity between patients and controls and to assess connectivity changes after DBS intervention. RESULTS: Baseline findings revealed that structural connectivity is significantly reduced in patients with AN compared to controls, mainly regarding callosal and subcallosal white matter (WM) tracts. Furthermore, pre- vs. post-DBS analyses in AN identified a specific increase after the intervention in two WM tracts: the anterior thalamic radiation and the superior longitudinal fasciculus-parietal bundle. CONCLUSIONS: This study supports that structural connectivity is highly compromised in severe AN. Moreover, this investigation preliminarily reveals that after DBS of the SCC and NAcc in severe AN, there are WM modifications. These microstructural plasticity adaptations may signify a mechanistic underpinning of DBS in this psychiatric disorder.

A novel method for sparse dynamic functional connectivity analysis from resting-state fMRI.

BACKGROUND: There is growing interest in understanding the dynamic functional connectivity (DFC) between distributed brain regions. However, it remains challenging to reliably estimate the temporal dynamics from resting-state functional magnetic resonance imaging (rs-fMRI) due to the limitations of current methods. NEW METHODS: We propose a new model called HDP-HSMM-BPCA for sparse DFC analysis of high-dimensional rs-fMRI data, which is a temporal extension of probabilistic principal component analysis using Bayesian nonparametric hidden semi-Markov model (HSMM). Specifically, we utilize a hierarchical Dirichlet process (HDP) prior to remove the parametric assumption of the HMM framework, overcoming the limitations of the standard HMM. An attractive superiority is its ability to automatically infer the state-specific latent space dimensionality within the Bayesian formulation. RESULTS: The experiment results of synthetic data show that our model outperforms the competitive models with relatively higher estimation accuracy. In addition, the proposed framework is applied to real rs-fMRI data to explore sparse DFC patterns. The findings indicate that there is a time-varying underlying structure and sparse DFC patterns in high-dimensional rs-fMRI data. COMPARISON WITH EXISTING METHODS: Compared with the existing DFC approaches based on HMM, our method overcomes the limitations of standard HMM. The observation model of HDP-HSMM-BPCA can discover the underlying temporal structure of rs-fMRI data. Furthermore, the relevant sparse DFC construction algorithm provides a scheme for estimating sparse DFC. CONCLUSION: We describe a new computational framework for sparse DFC analysis to discover the underlying temporal structure of rs-fMRI data, which will facilitate the study of brain functional connectivity.

Provincial and connector qualities of somatosensory brain network hubs in bipolar disorder.

Brain network hubs are highly connected brain regions serving as important relay stations for information integration. Recent studies have linked mental disorders to impaired hub function. Provincial hubs mainly integrate information within their own brain network, while connector hubs share information between different brain networks. This study used a novel time-varying analysis to investigate whether hubs aberrantly follow the trajectory of other brain networks than their own. The aim was to characterize brain hub functioning in clinically remitted bipolar patients. We analyzed resting-state functional magnetic resonance imaging data from 96 euthymic individuals with bipolar disorder and 61 healthy control individuals. We characterized different hub qualities within the somatomotor network. We found that the somatomotor network comprised mainly provincial hubs in healthy controls. Conversely, in bipolar disorder patients, hubs in the primary somatosensory cortex displayed weaker provincial and stronger connector hub function. Furthermore, hubs in bipolar disorder showed weaker allegiances with their own brain network and followed the trajectories of the limbic, salience, dorsal attention, and frontoparietal network. We suggest that these hub aberrancies contribute to previously shown functional connectivity alterations in bipolar disorder and may thus constitute the neural substrate to persistently impaired sensory integration despite clinical remission.

The macroscale routing mechanism of structural brain connectivity related to body mass index.

Understanding the brain's mechanisms in individuals with obesity is important for managing body weight. Prior neuroimaging studies extensively investigated alterations in brain structure and function related to body mass index (BMI). However, how the network communication among the large-scale brain networks differs across BMI is underinvestigated. This study used diffusion magnetic resonance imaging of 290 young adults to identify links between BMI and brain network mechanisms. Navigation efficiency, a measure of network routing, was calculated from the structural connectivity computed using diffusion tractography. The sensory and frontoparietal networks indicated positive associations between navigation efficiency and BMI. The neurotransmitter association analysis identified that serotonergic and dopaminergic receptors, as well as opioid and norepinephrine systems, were related to BMI-related alterations in navigation efficiency. The transcriptomic analysis found that genes associated with network routing across BMI overlapped with genes enriched in excitatory and inhibitory neurons, specifically, gene enrichments related to synaptic transmission and neuron projection. Our findings suggest a valuable insight into understanding BMI-related alterations in brain network routing mechanisms and the potential underlying cellular biology, which might be used as a foundation for BMI-based weight management.

Altered static brain activity and functional connectivity after heat stroke.

This study aimed to investigate the alteration of brain function based on resting-state functional MRI in patients after heat stroke. This study included 10 cases of patients after heat stroke and 10 cases of healthy controls. Abnormal brain function was calculated using amplitude of low-frequency fluctuations (ALFF) and degree centrality analysis, as well as functional connectivity analysis based on regions of interest (ROI). Correlation analyses were performed to evaluate the association between brain function changes and clinical scales. Combining ALFF and degree centrality results, the decreased brain regions included the left cuneus and the right angular gyrus, while the increased brain regions included the right cerebellar_Crus1. Using the left cuneus with significant differences in ALFF and degree centrality as ROI, the functional connectivity results revealed decreased brain regions including bilateral lingual gyrus, bilateral postcentral cingulate gyrus, and left precentral gyrus. The degree centrality value of the right cerebellar_Crus1 was positively correlated with glasgow coma scale (GCS) scores ( r  = 0.726, P  = 0.027), and the functional connectivity value of the right posterior cingulate gyrus was positively correlated with GCS scores ( r  = 0.717, P  = 0.030). Heat stroke patients exhibit abnormal activity in multiple brain regions, which has important clinical significance for evaluating the severity of the disease.