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Overlapping symptoms between Alzheimers disease (AD), behavioral variant of frontotemporal dementia (bvFTD), and schizophrenia (SZ) can lead to misdiagnosis and delays in appropriate treatment, especially in cases of early-onset dementia. To determine the potential of brain signal variability as a diagnostic tool, we assessed the coefficient of variation of the BOLD signal (CVBOLD) in 234 participants spanning bvFTD (n = 53), AD (n = 17), SZ (n = 23), and controls (n = 141). All underwent functional and structural MRI scans. Data unveiled a notable increase in CVBOLD in bvFTD patients across both datasets (local and international, p

Resting state functional magnetic resonance imaging (rsfMRI) provides researchers and clinicians with a powerful tool to examine functional connectivity across large-scale brain networks, with ever-increasing applications to the study of neurological disorders, such as traumatic brain injury (TBI). While rsfMRI holds unparalleled promise in systems neurosciences, its acquisition and analytical methodology across research groups is variable, resulting in a literature that is challenging to integrate and interpret. The focus of this narrative review is to address the primary methodological issues including investigator decision points in the application of rsfMRI to study the consequences of TBI. As part of the ENIGMA Brain Injury working group, we have collaborated to identify a minimum set of recommendations that are designed to produce results that are reliable, harmonizable, and reproducible for the TBI imaging research community. Part one of this review provides the results of a literature search of current rsfMRI studies of TBI, highlighting key design considerations and data processing pipelines. Part two outlines seven data acquisition, processing, and analysis recommendations with the goal of maximizing study reliability and between-site comparability, while preserving investigator autonomy. Part three summarizes new directions and opportunities for future rsfMRI studies in TBI patients. The goal is to galvanize the TBI community to gain consensus for a set of rigorous and reproducible methods, and to increase analytical transparency and data sharing to address the reproducibility crisis in the field.

To investigate the microstructural integrity, tract volume analysis, and functional connectivity (FC) alterations of the left uncinate fasciculus (UF) in patients with amyotrophic lateral sclerosis (ALS) compared to healthy controls (HCs). Fourteen limb-onset ALS patients were recruited at baseline and ten at follow-up, along with 14 HCs. All participants underwent 3D T1-weighted, diffusion tensor imaging and kurtosis imaging (DTI/DKI), and resting-state functional MRI (rs-fMRI) using a 3 Tesla scanner with 64-channel coils. Eight metrics of diffusion, rs-FC of the left UF, and graph theory analyses were extracted. Statistical group comparisons and correlation analysis for significant diffusion metrics were also conducted. Significantly lower radial kurtosis (RK), mean kurtosis (MK), and higher DTI diffusivity metrics were observed in the left UF of ALS patients than in HCs. RK and MK were correlated with various cognitive scores, particularly executive function and visuospatial ability. The volume of the left UF was positively correlated only with RK and MK at follow-up. While rs-FC analysis did not reveal group differences, a negative functional link between the left UF and cerebellum was observed in HCs but not in patients. Graph theory analysis suggested decreased connectivity in baseline patients and potential compensatory effects during the follow-up. Our study reveals microstructural abnormalities and potential network changes in left UF. DKI metrics, especially RK and MK, may be more sensitive biomarkers than DTI metrics, particularly longitudinally. Diffusion changes appear to precede volume and functional connectivity alterations, suggesting diffusion as a potential early biomarker. [ABSTRACT FROM AUTHOR]

Restless Legs Syndrome (RLS) is a common neurological disorder currently diagnosed based on clinical features only, and characterized by a compulsive urge to move the legs triggered by rest or diminished arousal. This systematic review aimed at integrating all current brain magnetic resonance imaging (MRI) modalities for a convergent pathophysiological understanding of RLS phenomenology. We performed a MEDLINE (PubMed)-based systematic review for research articles in patients with primary RLS published in English from 2010 till November 2023. Studies meeting the inclusion criteria according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria were systematically assessed for quality using modality-specific checklists, bias using AXIS tool and a narrative synthesis of the results was conducted. A total of 49 studies (22 structural, 12 DTI, 7 iron-imaging, 4 spectroscopy with 10 datasets combining multiple approaches) involving 1273 patients (414 males) and 1333 healthy controls (478 males) met the eligibility criteria. Despite participant, technical/device-related and statistical heterogeneity, most agree that patients with primary RLS have structural and metabolite alterations, changes in multiple white matter tract architectures, and disrupted functional connectivity within multiple brain areas. Most of the studies (n = 43, 88 %) have a low-risk of bias on the AXIS scale. Scores on the modality-specific checklist ranged from 46 to 92 %, 70–93 % and 54–92 % for structural MRI, DTI and MRS Datasets, respectively. Notwithstanding the large heterogeneity in the methods employed, global connectivity alterations suggest the utility of casting RLS within a system-level perspective rather than viewing it as related to the dysfunction of a single or particular brain region. A holistic approach and its integration within the framework of molecular vulnerability and neurotransmitter alterations are warranted to disentangle the complex pathophysiology of RLS and to identify new therapeutic targets. • This paper systematically reviewed all studies on different brain MRI modalities in RLS. • Changes in white matter tract and functional connectivity within different areas in RLS. • RLS as a system-level network disorder rather than a deficit of single brain regions. • The limited number of studies and their heterogeneity prevent definitive conclusions. [ABSTRACT FROM AUTHOR]

Borderline personality disorder (BPD) and complex posttraumatic stress disorder (cPTSD) share clinical similarities, complicating diagnosis and treatment. Research on the neurobiology of BPD and monotraumatic PTSD has shown that a prefrontal-limbic imbalance in emotional and reward processing is a hallmark of both disorders, but studies examining this network in cPTSD are lacking. Therefore, this study aimed to directly compare neural processing of emotion and reward during decision making in cPTSD and BPD. Using functional magnetic resonance imaging, we measured neural activity in female patients (27 patients with cPTSD, 21 patients with BPD and 37 healthy controls) during a Desire-Reason Dilemma task featuring distracting fearful facial expressions. We found no differences in neural activation when comparing cPTSD and BPD. However, when grouping patients based on symptom severity instead on diagnosis, we found that increased symptoms of cPTSD were associated with increased activation of dorsolateral prefrontal cortex during reward rejection, whereas increased symptoms of BPD were associated with decreased activation in prefrontal and limbic regions during reward rejection with distracting negative emotional stimuli. This is the first study to investigate and compare emotional processing and reward-based decision making in cPTSD and BPD. Although we found no neural differences between disorders, we identified symptom-related neural patterns. Specifically, we found that elevated cPTSD symptoms were related to greater sensitivity to reward stimuli, whereas heightened BPD symptoms were related to increased susceptibility to emotional stimuli during goal-directed decision making. These findings enhance our understanding of neural pathomechanisms in trauma-related disorders. • First study to compare emotional processing and reward-based decision making in cPTSD and BPD. • Neural processing of rewards and emotions differs according to symptom severity rather than diagnostic status. • Symptoms of cPTSD are associated with increased cognitive control during reward rejection. • Symptoms of BPD are associated with increased emotional interference during inhibitory processing. [ABSTRACT FROM AUTHOR]

Childhood neglect is associated with brain changes, yet the molecular mechanisms and behavioral relevance underlying such associations remain elusive. We calculated fractional amplitude of low-frequency fluctuations (fALFF) using resting-state functional MRI and tested their correlation with childhood neglect across a large sample of 510 healthy young adults. Then, we investigated the spatial relationships of the identified neural correlates of childhood neglect with gene expression, neurotransmitter, and behavioral domain atlases. We found that more severe childhood neglect was correlated with higher fALFF in the bilateral anterior cingulate cortex. Remarkably, the identified neural correlates of childhood neglect were spatially correlated with expression of gene categories primarily involving neuron, synapse, ion channel, cognitive and perceptual processes, and physiological response and regulation. Concurrently, there were significant associations between the neural correlates and specific neurotransmitter systems including serotonin and GABA. Finally, neural correlates of childhood neglect were associated with diverse behavioral domains implicating mental disorders, emotion, cognition, and sensory perception. The cross-sectional study design cannot unequivocally establish causality. Our findings may not only add to the current knowledge regarding the relationship between childhood neglect and mental health, but also have clinical implications for developing preventive strategies for individuals exposed to childhood neglect who are at risk for mental disorders. • Our work investigated neural correlates of childhood neglect and their molecular mechanisms and behavioral relevance. • More severe childhood neglect was correlated with higher fALFF in the bilateral anterior cingulate cortex. • The neural correlates of neglect were linked to specific gene category expressions, neurotransmitter systems, and behavior. • These findings may add to the current knowledge regarding the relationship between childhood neglect and mental health. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to investigate the specific manifestations and differences in brain network activity and functional connectivity between brain networks in patients with trigeminal neuralgia and migraine, aiming to reveal the neural basis of these two diseases. Background: Head and facial pain, including trigeminal neuralgia and migraine, is prevalent globally. However, the underlying neural mechanisms of these conditions remain unclear. Resting-state functional connectivity studies based on independent component analysis (ICA) may offer new insights into these diseases. Methods: The study involved 23 chronic migraine, 37 episodic migraine, 21 trigeminal neuralgia patients, and 33 age- and gender-matched controls. Resting-state functional magnetic resonance imaging was performed, and five sets of brain network components were extracted through ICA. Neuronal activity indicators were calculated for each participant's independent components, including amplitudes of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo). Functional connectivity was also assessed and compared among the four groups. Results: Trigeminal neuralgia patients showed reduced ALFF in the dorsal attention network versus episodic migraine patients and controls. Both trigeminal neuralgia and chronic migraine patients had decreased ReHo in this network. Migraine patients had weaker connectivity between the default mode and visual networks than controls. Trigeminal neuralgia patients also showed higher connectivity between the somatosensory motor and dorsal attention networks. Compared to episodic migraine, trigeminal neuralgia, and chronic migraine patients had increased connectivity between the visual and dorsal attention networks. Conclusion: The study provides evidence that long-term chronic head and facial pain may contribute to abnormalities in the activation and connectivity of the dorsal attention network. Compared to migraine patients, trigeminal neuralgia patients exhibit abnormal brain network connectivity, particularly within the somatomotor network, which may explain the presence of significant "trigger points." These findings offer new perspectives for understanding the characteristics of different head and facial pain subtypes. [ABSTRACT FROM AUTHOR]

Pilots are considered the final line of defense for aviation safety. Before becoming a pilot, an ab initio pilot must undergo systematic flight training. This study included 25 male flying cadets. Kendall’s coefficient of concordance was used to measure the regional homogeneity of the time series of a given voxel with its 26 nearest neighboring voxels. This operation was performed for all voxels to generate a regional homogeneity map for each participant based on Kendall’s coefficient of concordance. A partial correlation analysis was performed to examine the relationship between regional homogeneity maps and flight training hours. We found that the anterior cingulate cortex in the ab initio group was significantly positively correlated with flight hours. These results suggest a potential relationship between flight training experience and the functional properties of the anterior cingulate cortex. [ABSTRACT FROM AUTHOR]

Fibromyalgia (FM) and ankylosing spondylitis (AS) are both rheumatic diseases characterized by significant musculoskeletal pain. In this study, we investigated the differences of the resting-state network (RSN) connectivity and gray matter volume (GMV) between FM, AS and healthy controls (HCs). We recruited 38 FM patients, 82 AS patients and 61 HCs in this study. All the participants underwent resting-state functional MRI (rs-fMRI) scans in a GE 3.0T MR system. Independent component analysis (ICA) was conducted on the rs-fMRI data, and group differences of the rsFC between different resting-state networks were calculated using dual regression. We also conducted voxel-based morphometry (VBM) analysis to investigate the differences of the GMV in FM, AS and HCs. The rsFC between the dorsal default mode network (DDMN) and the body of left caudate nucleus was significantly decreased in FM patients in comparison to AS patients (87 voxels, p = 0.025). VBM analysis showed that the GMV of the left posterior lobe of cerebellum was significantly increased in FM patients compared with AS patients (88 voxels, p = 0.036). Neither ICA nor VBM analysis revealed significant differences of RSN connectivity or GMV between FM patients and HCs. The altered rsFC between DMN and the caudate nucleus suggested an aberrant cortico-striato-thalamo-cortical circuit in FM patients, indicating aberrant reward processing, with potential association with mood, motivation and cognitive functions. The increased GMV in the left posterior lobe of cerebellum indicated the participation of cerebellum in the abnormal pain processing in FM patients. [ABSTRACT FROM AUTHOR]

Neurofeedback (NF) has emerged as a promising avenue for demonstrating process-related neuroplasticity, enabling self-regulation of brain function. NF targeting the amygdala has drawn attention to therapeutic potential in psychiatry, by potentially harnessing emotion-regulation processes. However, not all individuals respond equally to NF training, possibly owing to varying self-regulation abilities. This underscores the importance of understanding the mechanisms behind successful neuromodulation (i.e. capacity). This study aimed to investigate the establishment and neural correlates of neuromodulation capacity using data from repeated sessions of amygdala electrical fingerprint (Amyg-EFP)-NF and post-training functional magnetic resonance imaging (fMRI)-NF sessions. Results from 97 participants (healthy controls and post-traumatic stress disorder and fibromyalgia patients) revealed increased Amyg-EFP neuromodulation capacity over training, associated with post-training amygdala-fMRI modulation capacity and improvements in alexithymia. Individual differenaces in this capacity were associated with pre-training amygdala reactivity and initial neuromodulation success. Additionally, amygdala downregulation during fMRI-NF co-modulated with other regions such as the posterior insula and parahippocampal gyrus. This combined modulation better explained EFP-modulation capacity and improvement in alexithymia than the amygdala modulation alone, suggesting the relevance of this broader network to gained capacity. These findings support a network-based approach for NF and highlight the need to consider individual differences in brain function and modulation capacity to optimize NF interventions. This article is part of the theme issue 'Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation'. [ABSTRACT FROM AUTHOR]

Human adolescence marks a crucial phase of extensive brain development, highly susceptible to environmental influences. Employing brain age estimation to assess individual brain aging, we categorized individuals (N = 7,435, aged 9–10 years old) from the Adolescent Brain and Cognitive Development (ABCD) cohort into groups exhibiting either accelerated or delayed brain maturation, where the accelerated group also displayed increased cognitive performance compared to their delayed counterparts. A 4-way multi-set canonical correlation analysis integrating three modalities of brain metrics (gray matter density, brain morphological measures, and functional network connectivity) with nine environmental factors unveiled a significant 4-way canonical correlation between linked patterns of neural features, air pollution, area crime, and population density. Correlations among the three brain modalities were notably strong (ranging from 0.65 to 0.77), linking reduced gray matter density in the middle temporal gyrus and precuneus to decreased volumes in the left medial orbitofrontal cortex paired with increased cortical thickness in the right supramarginal and bilateral occipital regions, as well as increased functional connectivity in occipital sub-regions. These specific brain characteristics were significantly more pronounced in the accelerated brain aging group compared to the delayed group. Additionally, these brain regions exhibited significant associations with air pollution, area crime, and population density, where lower air pollution and higher area crime and population density were correlated to brain variations more prominently in the accelerated brain aging group. [ABSTRACT FROM AUTHOR]

The medial prefrontal cortex (mPFC) has been implicated in the pathophysiology of social impairments, including social fear. However, the precise subcortical partners that mediate mPFC dysfunction on social fear behaviour have not been identified. Using a social fear conditioning paradigm, we induced robust social fear in mice and found that the lateral habenula (LHb) neurons and LHb-projecting mPFC neurons are activated synchronously during social fear expression. Moreover, optogenetic inhibition of the mPFC–LHb projection significantly reduced social fear responses. Importantly, consistent with animal studies, we observed an elevated prefrontal–habenular functional connectivity in subclinical individuals with higher social anxiety characterized by heightened social fear. These results unravel a crucial role of the prefrontal–habenular circuitry in social fear regulation and suggest that this pathway could serve as a potential target for the treatment of social fear symptoms often observed in many psychiatric disorders. [ABSTRACT FROM AUTHOR]

Motor fatigability emerges when challenging motor tasks must be maintained over an extended period of time. It is frequently observed in everyday life and affects patients as well as healthy individuals. Motor fatigability can be measured using simple tasks like finger tapping at maximum speed for 30 s. This typically results in a rapid decrease of tapping frequency, a phenomenon called motor slowing. In a previous study (Bächinger et al, eLife, 8 (September), https://doi.org/10.7554/eLife.46750, 2019), we showed that motor slowing goes hand in hand with a gradual increase in blood oxygen level dependent signal in the primary sensorimotor cortex (SM1), supplementary motor area (SMA), and dorsal premotor cortex (PMd). It is unclear what drives the activity increase in SM1 caused by motor slowing and whether motor fatigability affects the dynamic interactions between SM1, SMA, and PMd. Here, we performed dynamic causal modelling (DCM) on data of 24 healthy young participants collected during functional magnetic resonance imaging to answer this question. The regions of interest (ROI) were defined based on the peak activation within SM1, SMA, and PMd. The model space consisted of bilateral connections between all ROI, with intrinsic self-modulation as inhibitory, and driving inputs set to premotor areas. Our findings revealed that motor slowing was associated with a significant reduction in SM1 self-inhibition, as uncovered by testing the maximum à posteriori against 0 (t(23)=-4.51, p < 0.001). Additionally, the model revealed a significant decrease in the driving input to premotor areas (t(23) > 2.71, p < 0.05) suggesting that structures other than cortical motor areas may contribute to motor fatigability. [ABSTRACT FROM AUTHOR]

Background: Fatigue is commonly observed in pediatric multiple sclerosis (pedMS) patients, but its underlying mechanisms remain largely unexplored. We evaluated whether resting-state (RS) functional connectivity (FC) abnormalities in monoaminergic networks contributed to explain fatigue in pedMS. Methods: Fifty-five pedMS and twenty-three matched healthy controls (HC) underwent clinical and RS functional MRI assessment. Patients with Fatigue Severity Scale (FSS) score ≥ 4 were classified as fatigued (F). Patterns of dopamine-, noradrenaline- and serotonin-related RS FC were derived by constrained independent component analysis, using PET atlases for dopamine, noradrenaline, and serotonin transporters obtained in HCs' brain. Results: Compared to non-fatigued (NF)-pedMS patients and HC, F-pedMS patients (15/55, 27.3%) showed decreased dopamine-related RS FC in the right postcentral gyrus. They also showed decreased dopamine-related RS FC in the left insula vs. HC and increased dopamine-related RS FC in the left middle temporal gyrus and cerebellum (lobule VI) vs. NF patients. In the noradrenaline-related network, F-pedMS patients showed decreased RS FC in the left superior parietal lobule and increased RS FC in the right thalamus vs. HC and NF-pedMS. Compared to HC, F-pedMS patients also showed decreased RS FC in the right calcarine cortex and increased RS FC in the right middle frontal gyrus. In the serotonin-related network, F-pedMS patients showed decreased RS FC in the right angular gyrus and increased RS FC in the right postcentral gyrus vs. NF-pedMS patients. Discussion: In pedMS, fatigue is associated with specific monoaminergic network abnormalities, providing pathological markers for this bothersome symptom and putative targets for its treatment. [ABSTRACT FROM AUTHOR]

Background: Clinical evidence supports that swallowing function is correlated with cognition, but the neurobiological mechanism associated with cognitive impairment and dysphagia remains unclear. Objectives: To compare the brain activation patterns of the swallowing and the cognitive tasks and explore neural associations between swallowing and cognitive function via task‐related functional magnetic resonance imaging (fMRI). Methods: A total of 13 healthy older adults (aged > 60 years) were recruited. Participants underwent the clinical dementia rating (CDR) test and the Montreal Cognitive Assessment (MoCA). A block‐designed task‐related fMRI study was conducted where each participant completed both swallowing and cognitive tasks within a single session. During the swallowing task, participants swallowed 2 mL of thickened water, while the Stroop Colour Word Test (SCWT) served as the cognitive task. First‐level analysis of swallowing time‐series images utilised the general linear model (GLM) with Statistical Parametric Mapping (SPM), applying a voxel threshold of p < 0.001 for significance. Common activations in brain regions during swallowing and cognitive tasks were extracted at the group level, with significance set at p < 0.05, corrected for multiple comparisons using the false discovery rate (FDR), with a minimum cluster size of 20 voxels. Correlation analysis between behavioural measurements and imaging signals was also conducted. Results: Some regions were commonly activated in both task networks; these regions were the bilateral occipital lobe, cerebellum, lingual gyrus, fusiform, middle frontal gyrus, precentral and postcentral gyrus, right supramarginal and inferior parietal lobe. Most importantly, the average beta value of cognitive and swallowing tasks in these areas are both significantly negative related to the MoCA score. Furthermore, opposite signal changes were seen in the bilateral prefrontal lobes during the swallowing task, while positive activation in the bilateral prefrontal lobes was observed during the SCWT. Postcentral gyrus activation was more extensive than precentral gyrus activation in the swallowing task. Conclusion: The common activation of swallowing and cognitive tasks had multiple foci. The activity of cognitive and swallowing task in these areas is significantly negative correlated with the MoCA score. These findings may help to illustrate the association between dysphagia and cognitive impairment due to the common brain regions involved in cognition and swallowing and may provide a reference for further rehabilitation of dysphagia. Trial Registration: Clinical Trial: (Chinese Clinical Trial Registry): ChiCTR1900021795 [ABSTRACT FROM AUTHOR]

This study systematically reviews the available evidence on resting-state functional magnetic resonance imaging (rs-fMRI) related to neurological symptoms and cognitive declines in COVID-19 patients. We followed PRISMA guidelines and looked up the PubMed, and Scopus databases for articles search on COVID-19 patients with neurological impairments, and functional connectivity alteration using rs-fMRI technique. Articles published between January 1, 2020, and May 31, 2024, are included in this study. The Quality Assessment Tool for Observational Prospective and Cross-Sectional Studies from the National Heart, Lung, and Blood Institute (NHLBI) was used to assess the quality of papers. A total of 15 articles met the inclusion criteria. The result reveals that the most prevalent neurological impairment associated with COVID-19 was cognitive decline, encompassing issues in attention, memory, processing speed, executive functions, language, and visuospatial ability. The brain connectivity results reveal that two brain areas were functionally altered; the prefrontal cortex and parahippocampus. The functional connectivity mainly increased in the frontal, temporal, and anterior piriform cortex, and reduced in the cerebellum, superior orbitofrontal cortex, and middle temporal gyrus, which also correlated with cognitive decline. The findings of neurological symptoms indicate one study reported a Disorder of Consciousness (DoC), and four studies reported COVID-19 patients with olfactory dysfunction. The present study concludes that COVID-19 can alter brain functional connectivity and offers significant insight into how COVID-19 affects the neuronal foundation of cognitive decline and other neurological impairments. [ABSTRACT FROM AUTHOR]

Purpose of Review: Population receptive field (pRF) modeling is an fMRI technique used to retinotopically map visual cortex, with pRF size characterizing the degree of spatial integration. In clinical populations, most pRF mapping research has focused on damage to visual system inputs. Herein, we highlight recent work using pRF modeling to study high-level visual dysfunctions. Recent Findings: Larger pRF sizes, indicating coarser spatial processing, were observed in homonymous visual field deficits, aging, and autism spectrum disorder. Smaller pRF sizes, indicating finer processing, were observed in Alzheimer's disease and schizophrenia. In posterior cortical atrophy, a unique pattern was found in which pRF size changes depended on eccentricity. Summary: Changes to pRF properties were observed in clinical populations, even in high-order impairments, explaining visual behavior. These pRF changes likely stem from altered interactions between brain regions. Furthermore, some studies suggested that pRF sizes change as part of cortical reorganization, and they can point towards future prognosis. [ABSTRACT FROM AUTHOR]

Patients with chronic migraine (CM) often exhibit structural and functional alterations in pain‐matrix regions, but it remains unclear how preventive treatment affects these changes. Therefore, this study aimed to investigate the structural and functional changes in pain‐matrix regions in CM patients after 6‐month treatment. A total of 24 patients with CM and 15 healthy controls were recruited for this study. Patients were divided into responder group (N = 9) and non‐responder group (N = 15). After completing the Migraine Disability Assessment (MIDAS) questionnaire, all patients underwent whole‐brain high‐resolution T1‐weighted images, diffusion‐weighted imaging, and resting‐state functional magnetic resonance imaging at baseline and 6‐month follow‐up. Whole brain gray matter volume and white matter diffusion indices were analyzed using voxel‐based analysis. Structural and functional connectivity analyses were performed to understand brain changes in patients after 6‐month preventive treatment. The responder group exhibited significantly higher MIDAS scores than the non‐responder group at baseline, but no significant difference between the two groups at follow‐up. No significant interval change was noted in gray matter volume, white matter diffusion indices, and structural connectivity in CM patients after 6‐month treatment. Nonetheless, the functional connectivity was significantly increased between occipital, temporal lobes and cerebellum, and was significantly decreased between parietal and temporal lobes after 6‐month preventive treatment. We concluded that resting‐state functional connectivity was suitable for investigating the preventive treatment effect on CM patients. [ABSTRACT FROM AUTHOR]

Functional connectivity (FC) refers to the activation correlation between different brain regions. FC networks as typically represented as graphs with brain regions of interest (ROIs) as nodes and functional correlation as edges. Graph neural networks (GNNs) are machine learning architectures used to analyze FC graphs. However, traditional GNNs are limited in their ability to characterize FC edge attributes because they typically emphasize the importance of ROI node-based brain activation data. Line GNNs convert the edges of the original graph to nodes in the transformed graph, thereby emphasizing the FC between brain regions. We hypothesize that line GNNs will outperform traditional GNNs in FC applications. We investigated the performance of two common GNN architectures (GraphSAGE and GCN) trained on line and traditional graphs predicting task-associated FC changes across two datasets. The first dataset was from the Human Connectome Project (HCP) with 205 participants, the second was a dataset with 12 participants. The HCP dataset detailed FC changes in participants during a story-listening task, while the second dataset included the FC changes in a different auditory language task. Our findings from the HCP dataset indicated that line GNNs achieved lower mean squared error compared to traditional GNNs, with the line GraphSAGE model outperforming the traditional GraphSAGE by 18% (p < 0.0001). When applying the same models to the second dataset, both line GNNs also showed statistically significant improvements over their traditional counterparts with little to no overfitting. We believe this shows that line GNN models demonstrate promising utility in FC studies. [ABSTRACT FROM AUTHOR]

Background: The spatial layout of large-scale functional brain networks exhibits considerable inter-individual variability, especially in the association cortex. Research has demonstrated a link between early socioeconomic status (SES) and variations in both brain structure and function, which are further associated with cognitive and mental health outcomes. However, the extent to which SES is associated with individual differences in personalized functional network topography during childhood remains largely unexplored. Methods: We used a machine learning approach—spatially regularized non-negative matrix factorization (NMF)—to delineate 17 personalized functional networks in children aged 9–10 years, utilizing high-quality functional MRI data from 6001 participants in the Adolescent Brain Cognitive Development study. Partial least square regression approach with repeated random twofold cross-validation was used to evaluate the association between the multivariate pattern of functional network topography and three SES factors, including family income-to-needs ratio, parental education, and neighborhood disadvantage. Results: We found that individual variations in personalized functional network topography aligned with the hierarchical sensorimotor-association axis across the cortex. Furthermore, we observed that functional network topography significantly predicted the three SES factors from unseen individuals. The associations between functional topography and SES factors were also hierarchically organized along the sensorimotor-association cortical axis, exhibiting stronger positive associations in the higher-order association cortex. Additionally, we have made the personalized functional networks publicly accessible. Conclusions: These results offer insights into how SES influences neurodevelopment through personalized functional neuroanatomy in childhood, highlighting the cortex-wide, hierarchically organized plasticity of the functional networks in response to diverse SES backgrounds. [ABSTRACT FROM AUTHOR]

Resting-state functional MRI (fMRI) has revealed functional changes at the cortical level in degenerative cervical myelopathy (DCM) patients. The aim of this study was to systematically integrate static and dynamic functional connectivity (FC) to unveil abnormalities of functional networks of DCM patients and to analyze the prognostic value of these abnormalities for patients using resting-state fMRI. In this study, we collected clinical data and fMRI data from 44 DCM patients and 39 healthy controls (HC). Independent component analysis (ICA) was performed to investigate the group differences of intra-network FC. Subsequently, both static and dynamic FC were calculated to investigate the inter-network FC alterations in DCM patients. k-means clustering was conducted to assess temporal properties for comparison between groups. Finally, the support vector machine (SVM) approach was performed to predict the prognosis of DCM patients based on static FC, dynamic FC, and fusion of these two metrics. Relative to HC, DCM patients exhibited lower intra-network FC and higher inter-network FC. DCM patients spent more time than HC in the state in which both patients and HC were characterized by strong inter-network FC. Both static and dynamic FC could successfully classify DCM patients with different surgical outcomes. The classification accuracy further improved after fusing the dynamic and static FC for model training. In conclusion, our findings provide valuable insights into the brain mechanisms underlying DCM neuropathology on the network level. [ABSTRACT FROM AUTHOR]

The neurobiological mechanism of borderline personality disorder (BPD) in adolescents remains unclear. The study aimed to assess the alterations in neural activity within prefrontal cortex in adolescents with BPD and investigate the relationship of prefrontal activity with emotional regulation and cognitive function. This study enrolled 50 adolescents aged 12–17 years with BPD and 21 gender and age-matched healthy control (HC) participants. Study assessment for each participant included a brain resting-state functional MRI (rs-fMRI), clinical assessment questionnaires such as Borderline Personality Features Scale (BPFS), Difficulties in Emotion Regulation Scale (DERS), Ottawa Self-Injury Inventory and Childhood Trauma Questionnaire (CTQ) and cognitive testing with Stroop Color-Word Test (SCWT). Fractional amplitude of low-frequency fluctuations (fALFF) and seed-based functional connectivity (FC) were obtained from rs-fMRI analysis. Correlation analysis was also performed to evaluate the associations of the neuroimaging metrics such as fALFF and FC with clinical assessment questionnaire and cognitive testing scores. Adolescents with BPD showed increased fALFF values in the right inferior frontal gyrus and decreased activity in the left middle frontal gyrus as compared to the HC group (p < 0.05, cluster size ≥ 100, FWE correction). In adolescents with BPD, increased fALFF in the right inferior frontal gyrus was related to the BPFS (emotional dysregulation), DERS-F (lacking of emotional regulation strategies) and Ottawa Self-Injury Inventory-4 C scores (internal emotional regulation function of self-injurious behavior). The reduced fALFF in the left middle frontal gyrus was associated with the SCWT-A (reading characters) and the SCWT-B (reading color) scores. Additionally, the fALFF values in the left middle frontal gyrus and the right inferior frontal gyrus were related to the CTQ-D (emotional neglect) (p < 0.05). The left middle frontal gyrus exhibited increased FC with the right hippocampus, left inferior temporal gyrus and right inferior frontal gyrus (voxel p < 0.001, cluster p < 0.05, FWE correction). The increased FC between the left middle frontal gyrus and the right hippocampus was related to the SCWT-C (cognitive flexibility) score. We observed diverging changes in intrinsic brain activity in prefrontal cortex, and neural compensatory changes to maintain function in adolescents with BPD. In addition, decreased neural function was closely associated with emotional dysregulation, while increased neural function as indicated by brain activity and FC was associated with cognitive dysfunction. These results indicated that alterations of intrinsic brain activity may be one of the underlying neurobiological markers for clinical symptoms in adolescents with BPD. [ABSTRACT FROM AUTHOR]

The epileptogenic network in temporal lobe epilepsy (TLE) contains structures of the primary and secondary olfactory cortex such as the piriform and entorhinal cortex, the amygdala, and the hippocampus. Olfactory auras and olfactory dysfunction are relevant symptoms of TLE. This study aims to characterize olfactory function in TLE using olfactory testing and olfactory functional magnetic resonance imaging (fMRI). We prospectively enrolled 20 individuals with unilateral TLE (age 45 ± 20 years [mean ± SD], 65% female, 90% right‐handed) and 20 healthy individuals (age 33 ± 15 years [mean ± SD], 35% female, 90% right‐handed). In the TLE group, the presumed seizure onset zone was left‐sided in 75%; in 45% of the individuals with TLE limbic encephalitis was the presumed etiology; and 15% of the individuals with TLE reported olfactory auras. Olfactory function was assessed with a Screening Sniffin' Sticks Test (Burkhart, Wedel, Germany) during a pre‐assessment. During a pre‐testing, all individuals were asked to rate the intensity, valence, familiarity, and associated memory of five different odors (eugenol, vanillin, phenethyl alcohol, decanoic acid, valeric acid) and a control solution. During the fMRI experiment, all individuals repeatedly smelled eugenol (positively valenced odor), valeric acid (negatively valenced odor), and the control solution and were asked to rate odor intensity on a five‐point Likert scale. We acquired functional EPI sequences and structural images (T1, T2, FLAIR). Compared to healthy individuals, individuals with TLE rated the presented odors as more neutral (two‐sided Mann–Whitney U tests, FDR‐p < 0.05) and less familiar (two‐sided Mann–Whitney U tests, FDR‐p < 0.05). fMRI data analysis revealed a reduced response contrast in secondary olfactory areas (e.g., hippocampus) connected to the limbic system when comparing eugenol and valeric acid in individuals with TLE when compared with healthy individuals. However, no lateralization effect was obtained when calculating a lateralization index by the number of activated voxels in the olfactory system (two‐sided Mann–Whitney U test; U = 176.0; p = 0.525). TLE is characterized by olfactory dysfunction and associated with hypoactivation of secondary olfactory structures connected to the limbic system. These findings contribute to our understanding of the pathophysiology of TLE. This study was preregistered on OSF Registries (www.osf.io). [ABSTRACT FROM AUTHOR]

A growing number of publicly available human functional magnetic resonance imaging (fMRI) data sets use a 'deep' sampling approach, where many hours of data are acquired from a few individuals. We highlight an emerging approach within deep fMRI, which we refer to as 'intensive' fMRI: the creation of large-scale, publicly shared data sets that extensively sample cognitive phenomena to support the investigation of brain function at the single voxel level. We discuss key principles of intensive fMRI, its benefits and challenges, and practical considerations in creating intensive fMRI data sets. We discuss how intensive fMRI can advance scientific discovery in systems neuroscience, machine learning, and artificial intelligence. The rise of large, publicly shared functional magnetic resonance imaging (fMRI) data sets in human neuroscience has focused on acquiring either a few hours of data on many individuals ('wide' fMRI) or many hours of data on a few individuals ('deep' fMRI). In this opinion article, we highlight an emerging approach within deep fMRI, which we refer to as 'intensive' fMRI: one that strives for extensive sampling of cognitive phenomena to support computational modeling and detailed investigation of brain function at the single voxel level. We discuss the fundamental principles, trade-offs, and practical considerations of intensive fMRI. We also emphasize that intensive fMRI does not simply mean collecting more data: it requires careful design of experiments to enable a rich hypothesis space, optimizing data quality, and strategically curating public resources to maximize community impact. [ABSTRACT FROM AUTHOR]

It is known that abnormal functional connectivity (FC) in schizophrenia (SZ) is closely related to structural connectivity (SC). We speculate that indirect SC also have an impact on FC in SZ patients. Conventional single-layer network has limitations for studying the relationship between indirect SC and FC. Thus, this study constructed a multiplex network based on structural connectivity and functional connectivity (SC-FC). The SC-FC bandwidth and SC-FC cost are used to analyze the impact of indirect SC on FC. Moreover, this paper proposed mediation ability, mediation cost, mediated strength and mediated cost to quantify the effects of mediator nodes and mediated nodes on indirect SC. The results show that SZ patients exhibit lower SC-FC bandwidth and SC-FC cost compared to healthy controls (HC), which could be caused by the limbic and subcortical network (LSN), default mode network (DMN) and visual network (VN). The mediator and mediated nodes in indirect SC of SZ patients also showed diminished effects. These findings suggest that functional communication ability and cost in SZ patients are influenced by indirect SC. This study provides new perspectives for understanding the relationship between indirect SC and FC, and provides strong evidence for interpreting the physiological mechanisms of SZ patients. • Construction of multiplex network based on structural connectivity (SC) and functional connectivity (FC). • Using SC-FC bandwidth and SC-FC cost to analyze how indirect SC affects FC. • The SC-FC bandwidth and SC-FC cost of SZ patients were significantly reduced at whole-brain and module levels. • The role of nodes in affecting FC was quantified from mediator and mediated perspectives. • Results suggest that indirect SC in SZ patients results in reduced functional communication ability and cost. [ABSTRACT FROM AUTHOR]

Background: Vascular degeneration is an important cause of brain damage in aging. Assessing the functional properties of the cerebral vascular system may aid early diagnosis and prevention. Purpose: To investigate the relationships between potential vascular functional markers and vascular risks, brain parenchymal damage, and cognition. Study Type: Retrospective. Subjects: Two hundred two general community subjects (42–80 years, males/females: 127/75). Field Strength/Sequence: 3 T, spin echo T1W/T2W/FLAIR, resting‐state functional MRI with an echo‐planar sequence (rsfMRI), pseudo‐continuous arterial spin labeling (pCASL) with a three‐dimensional gradient‐spin echo sequence. Assessment: Cerebral blood flow (CBF) in gray matter calculated using pCASL, blood transit times calculated using rsfMRI, and the SD of internal carotid arteries signal (ICAstd) calculated using rsfMRI; visual assessment for lacunes; quantification of white matter hyperintensity volume; permutation test for quality control; collection of demographic and clinical data, Montreal Cognitive Assessment, Mini‐Mental State Examination. Statistical Tests: Kolmogorov–Smirnov test; Spearman rank correlation analysis; Multivariable linear regression analysis controlling for covariates; The level of statistical significance was set at P < 0.05. Results: Age was negatively associated with ICAstd (β = −0.180). Diabetes was associated with longer blood transit time from large arteries to capillary bed (β = 0.185, adjusted for age, sex, and intracranial volume). Larger ICAstd was associated with less presence of lacunes (odds ratio: 0.418, adjusted for age and sex). Higher gray matter CBF (β = 0.154) and larger ICAstd (β = 0.136) were associated with better MoCA scores (adjusted for age, sex, and education). Data Conclusion: Prolonged blood transit time, decreased ICAstd, and diminished CBF were associated with vascular dysfunction and cognitive impairment. They may serve as vascular functional markers in future studies. Evidence Level: 3 Technical Efficacy: Stage 3 [ABSTRACT FROM AUTHOR]

Objectives: The objective of this study is to explore the functional connectivity (FC) of the cerebellum during the storage phase of micturition, through detecting spontaneous blood‐oxygen‐level dependent signal between the cerebellum and different brain regions using a high‐resolution 7 Tesla magnetic resonance imaging (MRI) scanner. Materials and Methods: We recruited healthy individuals with no reported history of neurological disease or lower urinary tract (LUT) symptoms. Participants were asked to drink 500 mL of water and then empty their bladders before entering the MRI scanner. They underwent a T1‐weighted anatomical scan, followed by an initial (8 min) empty bladder resting state functional MRI (rs‐fMRI) acquisition. Once subjects felt the desire to void, a second rs‐fMRI scan was obtained, this time with a full bladder state. We established a priori cerebellar regions of interest from the literature to perform seed‐to‐voxel analysis using nonparametric statistics based on the Threshold Free Cluster Enhancement method and utilized a voxel threshold of p < 0.05. Results: Twenty individuals (10 male and 10 female) with a median age of 25 years (IQR [3.5]) participated in the study. We placed 31 different 4‐mm spherical seeds throughout the cerebellum and assessed their FC with the remainder of the brain. Three of these (left cerebellar tonsil, right posterolateral lobe, right posterior lobe) showed significant differences in connectivity when comparing scans conducted with a full bladder to those with an empty bladder. Additionally, we observed sex differences in FC, with connectivity being higher in women during the empty bladder condition. Conclusion: Our initial findings reveal, for the first time, that the connectivity of the cerebellar network is modulated by bladder filling and is associated with LUT function. Unraveling the cerebellum's role in bladder function lays the foundation for a more comprehensive understanding of urinary pathologies affecting this area. [ABSTRACT FROM AUTHOR]

Background: There are increasing reports of the misuse of prescription psychostimulants for cognitive enhancement together with recreational cannabis. This raises a concern that chronic use of cannabis high in Δ9-THC may alter the sensitivity to amphetamines. In this exploratory study we hypothesized chronic exposure to Δ9-THC through vaporized cannabis would diminish the central nervous system (CNS) activity of Adderall. Methods: To address this issue we exposed male and female mice to inhaled vaporized cannabis (10.3% Δ9-THC) or placebo for 30 min each day for ten consecutive days. After 24 h, mice were imaged fully awake for changes in BOLD signal following an IP injection of Adderall (60 µg) during the scanning session. After a 2-week washout, without any cannabis or placebo exposure, mice were again imaged and challenged with Adderall during the scanning session. The data were registered to a mouse 3D MRI atlas with 134 brain regions providing sitespecific increases and decreases in global brain activity. Results: Mice exposed to cannabis when compared to placebo showed a decrease in brain activation to Adderall. The blunted Adderall response was characterized by a decrease in positive BOLD signal and increase in negative BOLD. The prefrontal cortex, accumbens, ventral pallidum, caudate/putamen, and thalamus were most affected. After a 2-week wash out there were no significant differences between the cannabis and placebo groups when challenged with Adderall. Summary: This exploratory study shows that short, daily exposures to inhaled cannabis, something equivalent to recreational use, affects the sensitivity to the psychostimulant Adderall. The reduced Adderall effect on brain activity, particularly circuitry associated with dopaminergic signaling raises concerns about escalation in psychostimulant use. [ABSTRACT FROM AUTHOR]

Goal: Structural brain graphs are conventionally limited to defining nodes as gray matter regions from an atlas, with edges reflecting the density of axonal projections between pairs of nodes. Here we explicitly model the entire set of voxels within a brain mask as nodes of high-resolution, subject-specific graphs. Methods: We define the strength of local voxel-to-voxel connections using diffusion tensors and orientation distribution functions derived from diffusion MRI data. We study the graphs' Laplacian spectral properties on data from the Human Connectome Project. We then assess the extent of inter-subject variability of the Laplacian eigenmodes via a procrustes validation scheme. Finally, we demonstrate the extent to which functional MRI data are shaped by the underlying anatomical structure via graph signal processing. Results: The graph Laplacian eigenmodes manifest highly resolved spatial profiles, reflecting distributed patterns that correspond to major white matter pathways. We show that the intrinsic dimensionality of the eigenspace of such high-resolution graphs is only a mere fraction of the graph dimensions. By projecting task and resting-state data on low-frequency graph Laplacian eigenmodes, we show that brain activity can be well approximated by a small subset of low-frequency components. Conclusions: The proposed graphs open new avenues in studying the brain, be it, by exploring their organisational properties via graph or spectral graph theory, or by treating them as the scaffold on which brain function is observed at the individual level.

Abstract Patients with chronic migraine (CM) often exhibit structural and functional alterations in pain‐matrix regions, but it remains unclear how preventive treatment affects these changes. Therefore, this study aimed to investigate the structural and functional changes in pain‐matrix regions in CM patients after 6‐month treatment. A total of 24 patients with CM and 15 healthy controls were recruited for this study. Patients were divided into responder group (N = 9) and non‐responder group (N = 15). After completing the Migraine Disability Assessment (MIDAS) questionnaire, all patients underwent whole‐brain high‐resolution T1‐weighted images, diffusion‐weighted imaging, and resting‐state functional magnetic resonance imaging at baseline and 6‐month follow‐up. Whole brain gray matter volume and white matter diffusion indices were analyzed using voxel‐based analysis. Structural and functional connectivity analyses were performed to understand brain changes in patients after 6‐month preventive treatment. The responder group exhibited significantly higher MIDAS scores than the non‐responder group at baseline, but no significant difference between the two groups at follow‐up. No significant interval change was noted in gray matter volume, white matter diffusion indices, and structural connectivity in CM patients after 6‐month treatment. Nonetheless, the functional connectivity was significantly increased between occipital, temporal lobes and cerebellum, and was significantly decreased between parietal and temporal lobes after 6‐month preventive treatment. We concluded that resting‐state functional connectivity was suitable for investigating the preventive treatment effect on CM patients.

Abstract Pilots are considered the final line of defense for aviation safety. Before becoming a pilot, an ab initio pilot must undergo systematic flight training. This study included 25 male flying cadets. Kendall’s coefficient of concordance was used to measure the regional homogeneity of the time series of a given voxel with its 26 nearest neighboring voxels. This operation was performed for all voxels to generate a regional homogeneity map for each participant based on Kendall’s coefficient of concordance. A partial correlation analysis was performed to examine the relationship between regional homogeneity maps and flight training hours. We found that the anterior cingulate cortex in the ab initio group was significantly positively correlated with flight hours. These results suggest a potential relationship between flight training experience and the functional properties of the anterior cingulate cortex.

Abstract Fibromyalgia (FM) and ankylosing spondylitis (AS) are both rheumatic diseases characterized by significant musculoskeletal pain. In this study, we investigated the differences of the resting-state network (RSN) connectivity and gray matter volume (GMV) between FM, AS and healthy controls (HCs). We recruited 38 FM patients, 82 AS patients and 61 HCs in this study. All the participants underwent resting-state functional MRI (rs-fMRI) scans in a GE 3.0T MR system. Independent component analysis (ICA) was conducted on the rs-fMRI data, and group differences of the rsFC between different resting-state networks were calculated using dual regression. We also conducted voxel-based morphometry (VBM) analysis to investigate the differences of the GMV in FM, AS and HCs. The rsFC between the dorsal default mode network (DDMN) and the body of left caudate nucleus was significantly decreased in FM patients in comparison to AS patients (87 voxels, p = 0.025). VBM analysis showed that the GMV of the left posterior lobe of cerebellum was significantly increased in FM patients compared with AS patients (88 voxels, p = 0.036). Neither ICA nor VBM analysis revealed significant differences of RSN connectivity or GMV between FM patients and HCs. The altered rsFC between DMN and the caudate nucleus suggested an aberrant cortico-striato-thalamo-cortical circuit in FM patients, indicating aberrant reward processing, with potential association with mood, motivation and cognitive functions. The increased GMV in the left posterior lobe of cerebellum indicated the participation of cerebellum in the abnormal pain processing in FM patients.

Abstract Background The spatial layout of large-scale functional brain networks exhibits considerable inter-individual variability, especially in the association cortex. Research has demonstrated a link between early socioeconomic status (SES) and variations in both brain structure and function, which are further associated with cognitive and mental health outcomes. However, the extent to which SES is associated with individual differences in personalized functional network topography during childhood remains largely unexplored. Methods We used a machine learning approach—spatially regularized non-negative matrix factorization (NMF)—to delineate 17 personalized functional networks in children aged 9–10 years, utilizing high-quality functional MRI data from 6001 participants in the Adolescent Brain Cognitive Development study. Partial least square regression approach with repeated random twofold cross-validation was used to evaluate the association between the multivariate pattern of functional network topography and three SES factors, including family income-to-needs ratio, parental education, and neighborhood disadvantage. Results We found that individual variations in personalized functional network topography aligned with the hierarchical sensorimotor-association axis across the cortex. Furthermore, we observed that functional network topography significantly predicted the three SES factors from unseen individuals. The associations between functional topography and SES factors were also hierarchically organized along the sensorimotor-association cortical axis, exhibiting stronger positive associations in the higher-order association cortex. Additionally, we have made the personalized functional networks publicly accessible. Conclusions These results offer insights into how SES influences neurodevelopment through personalized functional neuroanatomy in childhood, highlighting the cortex-wide, hierarchically organized plasticity of the functional networks in response to diverse SES backgrounds.

Background: Non-specific chronic low back pain (CLBP) is a common painful condition and is responsible for different physical disorders. Despite alternative therapies, patients still suffer from persistent pain. Repetitive transcranial magnetic stimulation (rTMS) has provided much evidence of pain reduction, but results have not been examined deeply in CLBP symptoms.Objective: The analgesic effect of rTMS in non-specific CLBP patients was evaluated by the amplitude of low-frequency fluctuation (ALFF) analysis in resting-state fMRI.Material and Methods: In this experimental study, fifteen non-specific CLBP participants (46.87±10.89 years) received 20 Hz rTMS over the motor cortex. The pain intensity and brain functional scan were obtained during pre and post-stimulation for all participants. The ALFF maps of the brain in two scan sessions were identified and the percentage of pain reduction (PPR%) was determined using paired t-test. Also, correlation analysis was used to find a relationship between ALFFs and pain intensity.Results: Pain intensity was significantly reduced after induced-rTMS in non-specific CLBP (36.22%±13.28, P

Abstract Background Working memory (WM), a core component of executive functions, relies on a dedicated brain system that maintains and stores information in the short term. While extensive neuroimaging research has identified a distributed set of neural substrates relevant to WM, their underlying molecular mechanisms remain enigmatic. This study investigated the neural correlates of WM as well as their underlying molecular mechanisms. Results Our voxel-wise analyses of resting-state functional MRI data from 502 healthy young adults showed that better WM performance (higher accuracy and shorter reaction time of the 3-back task) was associated with lower functional connectivity density (FCD) in the left inferior temporal gyrus and higher FCD in the left anterior cingulate cortex. A combination of transcriptome-neuroimaging spatial correlation and the ensemble-based gene category enrichment analysis revealed that the identified neural correlates of WM were associated with expression of diverse gene categories involving important cortical components and their biological processes as well as sodium channels. Cross-region spatial correlation analyses demonstrated significant associations between the neural correlates of WM and a range of neurotransmitters including dopamine, glutamate, serotonin, and acetylcholine. Conclusions These findings may help to shed light on the molecular mechanisms underlying the neural correlates of WM.

Abstract Background The pathogenesis of intermittent exotropia (IXT) remains unclear. The study aims to investigate alterations of resting-state networks (RSNs) in IXT adult patients using resting-state functional magnetic resonance imaging (rs-fMRI) data to explore the potential neural mechanisms. Methods Twenty-six IXT adult patients and 22 age-, sex-, handedness-, and education-matched healthy controls (HCs) underwent fMRI scanning and ophthalmological examinations. Brain areas with significant functional connectivity (FC) differences between the IXT and HC groups were selected as regions of interest (ROI) and mean z-scores were calculated to control for individual differences. Results Compared with HCs, IXT patients exhibited altered FC in various brain regions within RSNs involved in binocular fusion, stereopsis, ocular movement, emotional processes and social cognition, including the default mode network (DMN), the dorsal attention network (DAN), the visual network (VN), the sensorimotor network (SMN), the executive control network (ECN), the frontoparietal network (FPN) and the auditory network (AN). The degree of exodeviation was positively correlated with FC value of left middle occipital gyrus (MOG) within the VN. Correspondingly, we found a negative correlation between the degree of exodeviation and the FC value of left angular gyrus (AG) within FPN (P

Yue He,1,&ast; Qianhan Liu,1,&ast; Yurong Zheng,1 Shengdan Liu,1 Mingling Yu,1 Changhe Ren,2 Guangxiang Chen1 1Department of Radiology, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, 646000, People’s Republic of China; 2Department of Pain, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, 646000, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Changhe Ren, Department of Pain, Affiliated Hospital of Southwest Medical University, No. 23 Tai Ping Street, Luzhou, Sichuan, 646000, People’s Republic of China, Tel +86 18982784626, Email riverrch@163.com Guangxiang Chen, Department of Radiology, Affiliated Hospital of Southwest Medical University, No. 23 Tai Ping Street, Luzhou, Sichuan, 646000, People’s Republic of China, Tel +86 18982409881, Email cgx23ly2002@163.comPurpose: Zoster-associated pain (ZAP) is frequently concomitant with psychiatric comorbidities. However, the underlying neuropathological mechanisms of ZAP with psychiatric comorbidities remain poorly understood.Patients and Methods: Rest-stating functional MRI (rs-fMRI) data from 41 ZAP patients without anxiety or depression (noA/D-ZAP), 11 ZAP patients with anxiety or depression (A/D-ZAP) and 29 healthy controls (HCs) were acquired. Degree centrality (DC) based on rs-fMRI was used to explore the node changes in the brain functional network in these subjects. Moreover, correlations and receiver operating characteristic curve analysis were performed.Results: One-way analysis of variance revealed abnormal DC values in the right middle frontal gyrus (MFG) and bilateral precuneus among the three groups. Compared with HCs, A/D-ZAP showed increased DC values in the bilateral pons, while noA/D-ZAP showed increased DC values in the right pons, left brainstem and rectal gyrus and decreased DC values in the right cingulate gyrus and bilateral precuneus. A/D-ZAP showed increased DC values in the left MFG and precentral gyrus (PG) compared with noA/D-ZAP. The DC value of the left pons in A/D-ZAP was positively correlated with the self-rating anxiety scale score. Areas under the curve of DC values in the left PG and MFG for distinguishing A/D-ZAP from the noA/D-ZAP group were 0.907 and 1.000, respectively.Conclusion: This study revealed the node differences in the brain functional network of ZAP patients with or without psychiatric comorbidities. In particular, abnormal DC values of the left MFG and PG may play an important role in the neuropathologic mechanism of the disease.Keywords: functional MRI, degree centrality, zoster-associated pain, anxiety, depression

Background: Working memory (WM), a core component of executive functions, relies on a dedicated brain system that maintains and stores information in the short term. While extensive neuroimaging research has identified a distributed set of neural substrates relevant to WM, their underlying molecular mechanisms remain enigmatic. This study investigated the neural correlates of WM as well as their underlying molecular mechanisms. Results: Our voxel-wise analyses of resting-state functional MRI data from 502 healthy young adults showed that better WM performance (higher accuracy and shorter reaction time of the 3-back task) was associated with lower functional connectivity density (FCD) in the left inferior temporal gyrus and higher FCD in the left anterior cingulate cortex. A combination of transcriptome-neuroimaging spatial correlation and the ensemble-based gene category enrichment analysis revealed that the identified neural correlates of WM were associated with expression of diverse gene categories involving important cortical components and their biological processes as well as sodium channels. Cross-region spatial correlation analyses demonstrated significant associations between the neural correlates of WM and a range of neurotransmitters including dopamine, glutamate, serotonin, and acetylcholine. Conclusions: These findings may help to shed light on the molecular mechanisms underlying the neural correlates of WM. [ABSTRACT FROM AUTHOR]

Long‐term cognitive impairment is common in cardiac arrest survivors. Screening to identify patients at risk is recommended. Functional magnetic resonance brain imaging (fMRI) holds potential to contribute to prediction of cognitive outcomes. In this study, we investigated the possible value of early changes in resting‐state networks for predicting short and long‐term cognitive functioning of cardiac arrest survivors. We performed a prospective multicenter cohort study in cardiac arrest survivors in three Dutch hospitals. Resting‐state fMRI scans were acquired within a month after cardiac arrest. We primarily focused on functional connectivity within the default‐mode network (DMN) and salience network (SN), and additionally explored functional connectivity in seven other networks. Cognitive outcome was measured using the Montreal Cognitive Assessment (MoCA) during hospital admission and at 3 and 12 months, and by neuropsychological examination (NPE) at 12 months. We tested mixed effects models to evaluate the value of connectivity within the networks for predicting global cognitive outcomes at the three time points, and long‐term cognitive outcomes in the memory, attention, and executive functioning domains. We included 80 patients (age 60 ± 11 years, 72 (90%) male). MoCA scores increased significantly between hospital admission and 3 months (ΔMoCAhospital‐3M = 2.89, p < 0.01), but not between 3 and 12 months (ΔMoCA3M–12M = 0.38, p = 0.52). Connectivity within the DMN, SN, and dorsal attention network (DAN) was positively related to global cognitive functioning during hospital admission (βDMN = 0.85, p = 0.03; βSN = 1.48, p < 0.01; βDAN = 0.96, p = 0.01), but not at 3 and 12 months. Network connectivity was also unrelated to long‐term memory, attention, or executive functioning. Resting‐state functional connectivity in the DMN, SN, and DAN measured in the first month after cardiac arrest is related to short‐term global, but not long‐term global or domain‐specific cognitive performance of survivors. These results do not support the value of functional connectivity within these RSNs for prediction of long‐term cognitive performance after cardiac arrest. [ABSTRACT FROM AUTHOR]

Introduction: Schizophrenia is characterized by a loss of network features between cognition and reward sub-circuits (notably involving the mesolimbic system), and this loss may explain deficits in learning and cognition. Learning in schizophrenia has typically been studied with tasks that include reward related contingencies, but recent theoretical models have argued that a loss of network features should be seen even when learning without reward. We tested this model using a learning paradigm that required participants to learn without reward or feedback. We used a novel method for capturing higher order network features, to demonstrate that the mesolimbic system is heavily implicated in the loss of network features in schizophrenia, even when learning without reward. Methods: fMRI data (Siemens Verio 3T) were acquired in a group of schizophrenia patients and controls (n=78; 46 SCZ, 18 = Age = 50) while participants engaged in associative learning without reward-related contingencies. The task was divided into task-active conditions for encoding (of associations) and cued-retrieval (where the cue was to be used to retrieve the associated memoranda). No feedback was provided during retrieval. From the fMRI time series data, network features were defined as follows: First, for each condition of the task, we estimated 2nd order undirected functional connectivity for each participant (uFC, based on zero lag correlations between all pairs of regions). These conventional 2nd order features represent the task/condition evoked synchronization of activity between pairs of brain regions. Next, in each of the patient and control groups, the statistical relationship between all possible pairs of 2nd order features were computed. These higher order features represent the consistency between all possible pairs of 2nd order features in that group and embed within them the contributions of individual regions to such group structure. Results: From the identified inter-group differences (SCZ - HC) in higher order features, we quantified the respective contributions of individual brain regions. Two principal effects emerged: 1) SCZ were characterized by a massive loss of higher order features during multiple task conditions (encoding and retrieval of associations). 2) Nodes in the mesolimbic system were over-represented in the loss of higher order features in SCZ, and notably so during retrieval. Discussion: Our analytical goals were linked to a recent circuit-based integrative model which argued that synergy between learning and reward circuits is lost in schizophrenia. Themodel's notable prediction was that such a losswould be observed evenwhen patients learnedwithout reward. Our results provide substantial support for these predictions where we observed a loss of network features between the brain's sub-circuits for a) learning (including the hippocampus and prefrontal cortex) and b) reward processing (specifically constituents of the mesolimbic system that included the ventral tegmental area and the nucleus accumbens. Our findings motivate a renewed appraisal of the relationship between reward and cognition in schizophrenia and we discuss their relevance for putative behavioral interventions. [ABSTRACT FROM AUTHOR]

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) can provide corroborative data on neurophysiological alterations in Huntington's disease (HD). However, the alterations in EEG and fMRI resting-state functional connectivity (rsFC), as well as their interrelations, at different stages of HD remain insufficiently investigated. This study aimed to identify neurophysiological alterations in individuals with preclinical HD (preHD) and early manifest HD (EMHD) by analyzing EEG and fMRI rsFC and examining their interrelationships. We found significant differences in EEG power between preHD individuals and healthy controls (HC), with a decrease in power in a specific frequency range at the theta-alpha border and slow alpha activity. In EMHD patients, in addition to the decrease in power in the 7--9 Hz range, a reduction in power within the classic alpha band compared to HC was observed. The fMRI analysis revealed disrupted functional connectivity in various brain networks, particularly within frontal lobe, putamen-cortical, and cortico-cerebellar networks, in individuals with the HD mutation compared to HC. The analysis of the relationship between EEG and fMRI rsFC revealed an association between decreased alpha power, observed in individuals with EMHD, and increased connectivity in large-scale brain networks. These networks include putamen-cortical, DMN-related and cortico-hippocampal circuits. Overall, the findings suggest that EEG and fMRI provide valuable information for monitoring pathological processes during the development of HD. A decrease in inhibitory control within the putamen-cortical, DMN-related and cortico-hippocampal circuits, accompanied by a reduction in alpha and theta-alpha border oscillatory activity, could potentially contribute to cognitive decline in HD. [ABSTRACT FROM AUTHOR]

In recent years, functional magnetic resonance imaging (fMRI) has been widely utilized to diagnose neurological disease, by exploiting the region of interest (RoI) nodes as well as their connectivities in human brain. However, most of existing works only rely on either RoIs or connectivities, neglecting the potential for complementary information between them. To address this issue, we study how to discover the rich cross-view information in fMRI data of human brain. This paper presents a novel method for cross-view analysis of fMRI data of the human brain, called Cross-view transFormers (CvFormer). CvFormer employs RoI and connectivity encoder modules to generate two separate views of the human brain, represented as RoI and sub-connectivity tokens. Then, basic transformer modules can be used to process the RoI and sub-connectivity tokens, and cross-view modules integrate the complement information across two views. Furthermore, CvFormer uses a global token for each branch as a query to exchange information with other branches in cross-view modules, which only requires linear time for both computational and memory complexity instead of quadratic time. To enhance the robustness of the proposed CvFormer, we propose a two-stage strategy to train its parameters. To be specific, RoI and connectivity views can be firstly utilized as self-supervised information to pre-train the CvFormer by combining it with contrastive learning and then fused to finetune the CvFormer using label information. Experiment results on two public ABIDE and ADNI datasets can show clear improvements by the proposed CvFormer, which can validate its effectiveness and superiority. • Cross-view transformer is proposed to analyze multi-view fMRI data of human brain. • CvFormer considers diversity and complementary of cross-view information in brain. • A two-stage strategy with pre-training is used to train CvFormer for fMRI analysis. • Massive experimental show the effectiveness and superiority of the proposed CvFormer. [ABSTRACT FROM AUTHOR]