Most recent paper

Front Neurosci. 2025 Jan 28;19:1472010. doi: 10.3389/fnins.2025.1472010. eCollection 2025.

ABSTRACT

INTRODUCTION: Type 2 diabetes mellitus (T2DM) accelerates brain aging and disrupts brain functional network connectivity, though the specific mechanisms remain unclear. This study aimed to investigate T2DM-driven alterations in brain functional network connectivity and topology.

METHODS: Eighty-five T2DM patients and 67 healthy controls (HCs) were included. All participants underwent clinical, neuropsychological, and laboratory tests, followed by MRI examinations, including resting-state functional magnetic resonance imaging (rs-fMRI) and three-dimensional high-resolution T1-weighted imaging (3D-T1WI) on a 3.0 T MRI scanner. Post-image preprocessing, brain functional networks were constructed using the Dosenbach atlas and analyzed with the DPABI-NET toolkit through graph theory.

RESULTS: In T2DM patients, functional connectivity within and between the default mode network (DMN), frontal parietal network (FPN), subcortical network (SCN), ventral attention network (VAN), somatosensory network (SMN), and visual network (VN) was significantly reduced compared to HCs. Conversely, two functional connections within the VN and between the DMN and SMN were significantly increased. Global network topology analysis showed an increased shortest path length and decreased clustering coefficient, global efficiency, and local efficiency in the T2DM group. MoCA scores were negatively correlated with the shortest path length and positively correlated with global and local efficiency in the T2DM group. Node network topology analysis indicated reduced clustering coefficient, degree centrality, eigenvector centrality, and nodal efficiency in multiple nodes in the T2DM group. MoCA scores positively correlated with clustering coefficient and nodal efficiency in the bilateral precentral gyrus in the T2DM group.

DISCUSSION: This study demonstrated significant abnormalities in connectivity and topology of large-scale brain functional networks in T2DM patients. These findings suggest that brain functional network connectivity and topology could serve as imaging biomarkers, providing insights into the underlying neuropathological processes associated with T2DM-related cognitive impairment.

PMID:39935840 | PMC:PMC11811103 | DOI:10.3389/fnins.2025.1472010

Brain Behav. 2025 Feb;15(2):e70321. doi: 10.1002/brb3.70321.

ABSTRACT

BACKGROUND: The thalamus plays a pivotal role in functional brain networks, yet its contribution to motor function recovery following stroke remains elusive. We aim to explore changes in thalamocortical functional connectivity poststroke and its correlation with motor function.

METHODS: Thirty-nine subacute ischemic stroke patients and 32 healthy individuals underwent resting-state functional magnetic resonance imaging (MRI). The Fugl-Meyer Assessment (FMA) was employed to evaluate upper and lower extremity motor function before and 1 year after stroke rehabilitation. The ipsilesional thalamus and contralesional thalamus were parceled into functional regions of interest (ROIs) based on connectivity with six cortical ROIs: prefrontal, motor, temporal, posterior parietal, somatosensory, and occipital cortex. Functional connectivity between each cortical ROI and its corresponding thalamic ROI was calculated and compared between groups. Differences identified in the ROI-to-ROI analysis were further investigated through seed-to-voxel whole-brain connectivity analyses to pinpoint thalamic dysconnectivity. Correlations with upper and lower extremity motor function were also analyzed.

RESULTS: Significant changes in thalamocortical functional connectivity were observed after stroke in ROI-to-ROI analysis, with bilateral somatosensory-thalamic connectivity decreased and ipsilesional temporal-thalamic and bilateral occipital-thalamic connectivity increased. Seed-to-voxel analysis localized ipsilesional thalamic hypoconnectivity to the ipsilesional rolandic operculum and ipsilesional precentral gyrus. Ipsilesional somatosensory-thalamic connectivity was positively correlated with baseline upper extremity FMA scores and negatively correlated with upper extremity motor function change rate at 1-year postdischarge.

CONCLUSIONS: This study provides new insights into the role of the thalamus in motor function recovery after stroke, offering preliminary evidence for its potential as a therapeutic target in poststroke rehabilitation.

PMID:39935146 | DOI:10.1002/brb3.70321

Brain Behav. 2025 Feb;15(2):e70323. doi: 10.1002/brb3.70323.

ABSTRACT

BACKGROUND AND AIMS: Adolescent major depressive disorder (MDD) is prevalent globally but often goes unnoticed due to differences in symptoms compared to adult criteria. Analyzing the brain from a network perspective provides new insights into higher-level brain functions and its pathophysiology. This study aimed to investigate changes in the topological organization of functional networks in adolescents with first-episode, treatment-naïve MDD.

METHOD: The study included 23 adolescents with depression and 27 matched healthy controls (HCs). Resting-state functional MRI (rs-fMRI) was conducted, and whole-brain functional networks were constructed. Graph theory analysis was used to evaluate network topological properties. A machine-learning multivariate diagnostic model was developed using network metrics associated with depression severity.

RESULTS: Both the MDD and HC groups displayed small-world topology, with male MDD patients showing reduced global clustering efficiency (Cp). The nodal Cp (NCp) and local efficiency (NLE) in the bilateral pallidum were significantly positively correlated with depression severity. In contrast, nodal efficiency (NE) in the left medial orbital superior frontal gyri (ORBsupmed) showed a negative correlation with disease severity. A machine-learning multivariate model using regional network topological features produced an AUROC of 0.71 (95% CI: 0.54-0.92) and an F1 score of 0.65, successfully differentiating adolescent MDD from HCs.

CONCLUSION: Our findings suggest disruptions in small-world topology in both global and local brain networks in adolescent depression. These abnormal nodal properties may serve as novel neural markers of the disorder.

PMID:39935140 | DOI:10.1002/brb3.70323

Brain Behav. 2025 Feb;15(2):e70314. doi: 10.1002/brb3.70314.

ABSTRACT

OBJECTIVE: We aimed to explore the alteration in topology and network properties in self-referential-related brain regions of individuals with depersonalization-derealization disorders (DPD), using evidence from resting-state functional magnetic resonance imaging (rs-fMRI).

METHODS: We first determined the regions of interest (ROIs) using Neurosynth, based on which we conducted an ROI-wise functional connectivity search to create a self-referential-related network and performed a topographical analysis. We then compared the analyzed properties from the rs-fMRI of disordered individuals to those of healthy controls to generate differential properties, based on which we conducted a machine learning-based disease diagnostic model.

RESULTS: The study found significant changes in connectivity between brain regions associated with self-referential processing in individuals with DPD compared to healthy controls. Correlation analysis showed negative correlations between "unreality of surroundings" and connectivity between the left inferior frontal gyrus (IFG) pars orbitalis and left insula and between "perceptual alterations" and connectivity between the left pregenual and subgenual anterior cingulate cortex (ACC). Graph theoretical analysis revealed increased local and global efficiency but decreased characteristic path length. The accuracy of the classification model was 0.885, and the area under the curve was 0.928.

CONCLUSIONS: Individuals with DPD showed alterations in brain topography and changes in network properties within self-referential-related brain regions; specifically, the changes in cortical midline structures and insula could be related to the underlying mechanism of DPD, highlighting potential targets for future research and therapeutic strategies.

PMID:39935045 | DOI:10.1002/brb3.70314

Sci Rep. 2025 Feb 11;15(1):5063. doi: 10.1038/s41598-024-82695-y.

ABSTRACT

Persistent genital arousal disorder (PGAD) is a rare disease causing high emotional distress eminently impacting the individual's quality of life. Experts in this field assume that the disease is caused by a multifaceted interplay of different etiologies which may share a common neurobiological basis. However, only one functional neuroimaging investigation exist, and a more in-depth comprehension of the neurobiological foundation is required. Therefore, this study aims to provide new insights into how the functional integration of brain regions may relate to PGAD. By using the functional magnetic resonance imaging (fMRI) technique, functional connectivity at rest (rs-FC) was compared between patients suffering PGAD (n = 26) and healthy controls (n = 26). Patients with PGAD showed different pattern in connectivity within brain structures putatively associated with the psychological and somatic dimensions of the disease including the right amygdala, left anterior cingulate cortex, right insula cortex, thalamic nuclei and prefrontal regions as seeds. The majority of these showed differences in brain connectivity pattern to the precuneus and prefrontal regions. The study offers preliminary insights into the characteristics and relevant neural mechanisms of PGAD. Nevertheless, since this study did not identify any peripheral correlates that would corroborate the interpretation of these findings, they were interpreted from a more theoretical perspective, thereby offering potential areas of focus for future research.

PMID:39934180 | DOI:10.1038/s41598-024-82695-y

Br J Anaesth. 2025 Feb 10:S0007-0912(25)00049-2. doi: 10.1016/j.bja.2024.12.036. Online ahead of print.

ABSTRACT

BACKGROUND: Ketamine, in doses suitable to induce anaesthesia in humans, gives rise to a unique state of unresponsiveness accompanied by vivid experiences and sensations, making it possible to disentangle the correlated but distinct concepts of conscious awareness and behavioural responsiveness. This distinction is often overlooked in the study of consciousness.

METHODS: The mathematical framework of connectome harmonic decomposition (CHD) was used to view functional magnetic resonance imaging (fMRI) signals during ketamine-induced unresponsiveness as distributed patterns across spatial scales. The connectome harmonic signature of this particular state was mapped onto signatures of other states of consciousness for comparison.

RESULTS: An increased prevalence of fine-grained connectome harmonics was found in fMRI signals obtained during ketamine-induced unresponsiveness, indicating higher granularity. After statistical assessment, the ketamine sedation harmonic signature showed alignment with signatures of LSD-induced (fixed effect =0.0113 [0.0099, 0.0127], P<0.001) or ketamine-induced (fixed effect =0.0087 [0.0071, 0.0103], P<0.001) psychedelic states, and misalignment with signatures seen in unconscious individuals owing to propofol sedation (fixed effect =-0.0213 [-0.0245, -0.0181], P<0.001) or brain injury (fixed effect =-0.0205 [-0.0234, -0.0178], P<0.001).

CONCLUSIONS: The CHD framework, which only requires resting-state fMRI data and can be applied retrospectively, has the ability to track alterations in conscious awareness in the absence of behavioural responsiveness on a group level. This is possible because of ketamine's unique property of decoupling these two facets, and is important for consciousness and anaesthesia research.

PMID:39933965 | DOI:10.1016/j.bja.2024.12.036

Phys Life Rev. 2025 Feb 7;52:278-297. doi: 10.1016/j.plrev.2025.02.001. Online ahead of print.

ABSTRACT

Neural oscillations facilitate the functioning of the human brain in spatial and temporal dimensions at various frequencies. These oscillations feature a universal frequency architecture that is governed by brain anatomy, ensuring frequency specificity remains invariant across different measurement techniques. Initial magnetic resonance imaging (MRI) methodology constrained functional MRI (fMRI) investigations to a singular frequency range, thereby neglecting the frequency characteristics inherent in blood oxygen level-dependent oscillations. With advancements in MRI technology, it has become feasible to decode intricate brain activities via multi-band frequency analysis (MBFA). During the past decade, the utilization of MBFA in fMRI studies has surged, unveiling frequency-dependent characteristics of spontaneous slow oscillations (SSOs) believed to base dark energy in the brain. There remains a dearth of conclusive insights and hypotheses pertaining to the properties and functionalities of SSOs in distinct bands. We surveyed the SSO MBFA studies during the past 15 years to delineate the attributes of SSOs and enlighten their correlated functions. We further proposed a model to elucidate the hierarchical organization of multi-band SSOs by integrating their function, aimed at bridging theoretical gaps and guiding future MBFA research endeavors.

PMID:39933322 | DOI:10.1016/j.plrev.2025.02.001

J Headache Pain. 2025 Feb 10;26(1):29. doi: 10.1186/s10194-025-01969-6.

ABSTRACT

BACKGROUND: Changes in large-scale brain networks have been reported in migraine patients, but it remains unclear how these manifest in the various phases of the migraine cycle. Case-control fMRI studies spanning the entire migraine cycle are lacking, precluding a complete assessment of brain functional connectivity in migraine. Such studies are essential for understanding the inherent changes in the brain of migraine patients as well as transient changes along the cycle. Here, we leverage the concept of functional connectome (FC) fingerprinting, whereby individual subjects may be identified based on their FC, to investigate changes in FC and its stability across different phases of the migraine cycle.

METHODS: We employ a case-control longitudinal design to study a group of 10 patients with episodic menstrual or menstrual-related migraine without aura, in the 4 phases of their spontaneous migraine cycle (preictal, ictal, postictal, interictal), and a group of 14 healthy controls in corresponding phases of the menstrual cycle, using resting-state functional magnetic resonance imaging (fMRI). We propose a novel multilevel clinical connectome fingerprinting approach to analyse the FC identifiability not only within-subject, but also within-session and within-group.

RESULTS: This approach allowed us to obtain individual FC fingerprints by reconstructing the data using the first 19 principal components to maximize identifiability at all levels. We found decreased FC identifiability for patients in the preictal phase relative to controls, which increased with the progression of the attack and became comparable to controls in the interictal phase. Using Network-Based Statistic analysis, we found increased FC strength across several brain networks for patients in the ictal and postictal phases relative to controls.

CONCLUSION: Our novel multilevel clinical connectome fingerprinting approach captured FC variations along the migraine cycle in a case-control longitudinal study, bringing new insights into the cyclic nature of the disorder.

PMID:39930372 | DOI:10.1186/s10194-025-01969-6

Drug Alcohol Depend. 2025 Jan 30;268:112577. doi: 10.1016/j.drugalcdep.2025.112577. Online ahead of print.

ABSTRACT

INTRODUCTION: The salience network may be linked to addiction. Evidence suggests less salience network resting state functional connectivity (rsFC) from heavy alcohol use, but higher rsFC within and between brain networks from regular cannabis use. Given the rise in alcohol-cannabis co-use, the present study sought to elucidate rsFC between regions within the salience network and regions across the whole brain in individuals who use no drugs regularly, those who use alcohol only heavily, and those who co-use alcohol-cannabis.

METHODS: This is a secondary analysis of three clinical laboratory studies. A total of sixty individuals were classified into one of three groups based on their drug use: control (n = 16), heavy alcohol use only (n = 27), and heavy alcohol and regular cannabis co-use (n = 17). All participants completed resting state fMRI scans. Seed regions from the salience network were used to examine group differences in rsFC.

RESULTS: Main effects of group on rsFC emerged between the anterior cingulate cortex, left and right anterior insula, and left supramarginal gyrus seeds and regions associated with motor, sensory, visual, and executive control functioning (all ps < 0.05). Post-hoc analyses revealed less rsFC between alcohol-only and co-use groups as compared to controls (all ps < 0.05), but no differences between alcohol-only and co-use groups (all ps > 0.05).

CONCLUSIONS: This preliminary study suggests that co-using alcohol-cannabis may not be associated with any additive or contrasting effects on rsFC compared to using alcohol alone. Thus, in individuals who co-use alcohol-cannabis, alcohol may drive neural alterations associated with inhibitory control and substance craving.

PMID:39929057 | DOI:10.1016/j.drugalcdep.2025.112577

J Atten Disord. 2025 Feb 10:10870547251315230. doi: 10.1177/10870547251315230. Online ahead of print.

ABSTRACT

OBJECTIVE: ADHD and autism are complex and frequently co-occurring neurodevelopmental conditions with shared etiological and pathophysiological elements. In this paper, we attempt to differentiate these conditions among the young people in terms of intrinsic patterns of brain connectivity revealed during resting state using machine learning approaches. We had two key objectives: (a) to determine the extent to which ADHD and autism could be effectively distinguished via machine learning from one another on this basis and (b) to identify the brain networks differentially implicated in the two conditions.

METHOD: Data from two publicly available resting-state functional magnetic resonance imaging (fMRI) resources-Autism Brain Imaging Data Exchange (ABIDE) and the ADHD-200 Consortium-were analyzed. A total of 330 participants (65 females and 265 males; mean age = 11.6 years), comprising equal subgroups of 110 participants each for ADHD, autism, and healthy controls (HC), were selected from the data sets ensuring data quality and the exclusion of comorbidities. We identified region-to-region connectivity values, which were subsequently employed as inputs to the linear discriminant analysis algorithm.

RESULTS: Machine learning models provided strong differentiation between connectivity patterns in participants with ADHD and autism-with the highest accuracy of 85%. Predominantly frontoparietal network alterations in connectivity discriminate ADHD individuals from autism and neurotypical group. Networks contributing to discrimination of autistic individuals from neurotypical group were more heterogeneous. These included language, salience, and frontoparietal networks.

CONCLUSION: These results contribute to our understanding of the distinct neural signatures underlying ADHD and autism in terms of intrinsic patterns of brain connectivity. The high level of discriminability between ADHD and autism, highlights the potential role of brain based metrics in supporting differential diagnostics.

PMID:39927595 | DOI:10.1177/10870547251315230

J Pain Res. 2025 Feb 4;18:579-587. doi: 10.2147/JPR.S500924. eCollection 2025.

ABSTRACT

PURPOSE: The objective of this research is to delve into the central pathological mechanisms involved in the transformation from acute to chronic pain.

PATIENTS AND METHODS: This study enrolled 86 individuals with acute neck pain and 89 with chronic neck pain. Utilizing a 3.0T MR scanner, we obtained three-dimensional T1-weighted imaging (3D-T1WI) images and analyzed structural differences between the two groups with Freesurfer software to evaluate alterations in cortical thickness. Additionally, Blood Oxygen Level-Dependent functional Magnetic Resonance Imaging (BOLD-fMRI) images were acquired to assess intergroup differences in low-frequency amplitude using DPARSF software.

RESULTS: Chronic neck pain patients exhibited increased cortical thickness in the left rostral middle frontal, left isthmus cingulate, left superior frontal, and right precuneus regions compared to those with acute neck pain. Low-frequency amplitude measures revealed decreased activity in the left dorsolateral superior frontal gyrus and left postcentral gyrus, among other areas, and increased activity in the right middle frontal gyrus and the opercular part of the right inferior frontal gyrus.

CONCLUSION: Our findings indicate that dysfunction and structural changes in the limbic system and prefrontal cortex may play a pivotal role in the progression from acute to chronic neck pain. These insights provide a significant new direction for understanding the central mechanisms underlying pain chronicity.

PMID:39926191 | PMC:PMC11806704 | DOI:10.2147/JPR.S500924

Front Hum Neurosci. 2025 Jan 24;19:1481474. doi: 10.3389/fnhum.2025.1481474. eCollection 2025.

ABSTRACT

INTRODUCTION: Mild-to-moderate traumatic brain injury (mmTBI) that lead to deficits in balance and gait are difficult to resolve through standard therapy protocols, and these deficits can severely impact a patient's quality of life. Recently, translingual neural stimulation (TLNS) has emerged as a potential therapy for mmTBI-related balance and gait deficits by inducing neuroplastic changes in the brain gray matter structure. However, it is still unclear how interactions within and between functional networks in brain are affected by TLNS. The current study aimed to extend our previous resting-state functional connectivity (RSFC) study investigating the effects of TLNS intervention on outcome measures related to gait and balance.

METHODS: An experimental PoNS device was utilized to deliver the TLNS. The 2-week TLNS intervention program, specifically stimulation during focused physical therapy focused on recovery of gait and balance, included twice-daily treatment in the laboratory and the same program at home during the intervening weekend. The resting-state fMRI datasets at pre- and post-interventions were collected by 3T MRI scanner with nine mmTBI patients. All participants also received both Sensory Organization Test (SOT) and Dynamic Gait Index (DGI) testing pre- and post-intervention as part of the behavioral assessment.

RESULTS: Compared to baseline, TLNS intervention led to statistically significant improvements in both the SOT [t (8) = 2.742, p = 0.028] and the DGI [t (8) = 2.855, p = 0.024] scores. Moreover, significant increases in intra- and inter-network RSFC were observed, particularly within the visual, default mode, dorsal attention, frontoparietal (FPN), and somatosensory (SMN) networks. Additionally, there were significant correlations between the SOT and inter-network FC [between FPN and SMN, r (9) = -0.784, p = 0.012] and between the DGI and intra-network FC [within SMN, r (9) = 0.728, p = 0.026].

DISCUSSION: These findings suggest that TLNS intervention is an effective in increasing somatosensory processing, vestibular-visual interaction, executive control and flexible shifting, and TLNS may be an effective approach to inducing brain network plasticity and may serve as a potential therapy for mmTBI-related gait and balance deficits.

PMID:39925723 | PMC:PMC11802553 | DOI:10.3389/fnhum.2025.1481474

Acta Radiol. 2025 Feb 9:2841851241310398. doi: 10.1177/02841851241310398. Online ahead of print.

ABSTRACT

BACKGROUND: Primary insomnia (PI) is one of the most common sleep disorders. Diagnosis of insomnia is mainly based on subjective sleep difficulties, and it is still necessary to find objective neurobiological markers.

PURPOSE: To investigate the functional connectivity (FC) of frontal hub regions important for PI.

MATERIAL AND METHODS: We enrolled 20 patients (5 men, 15 women) with PI and 20 controls (5 men, 15 women), matching age, sex. We used resting-state functional magnetic resonance imaging (fMRI) and voxel-mirrored homotopic connectivity (VMHC) to analyze the abnormal changes of FC in the frontal lobe of PI patients.

RESULTS: Compared to controls, abnormal FC regions were mainly concentrated in the superior frontal gyrus (L/R), middle frontal gyrus (L/R), and inferior frontal gyrus (L) of the orbital region and the inferior frontal gyrus of the opercular region (L) (P < 0.05). The VMHC results showed abnormal FC in the middle frontal gyrus of the orbital region (GFR correction, voxel P < 0.01, cluster P < 0.025) in PI patients. The FC between the orbitofrontal gyrus and the inferior frontal gyrus of the opercular region with the frontal gyrus of the medial orbital region demonstrated a significant correlation with the clinical scale (p < 0.05).

CONCLUSION: Our study identified abnormal FC, which was mainly located in the orbitofrontal gyrus and the inferior frontal gyrus of the opercular region, in the frontal lobe of patients with insomnia using resting-state fMRI. This is helpful to understand the abnormal neural activity mechanism of insomnia in the frontal lobe and provide a relatively accurate brain region basis for future prevention, diagnosis, and treatment.

PMID:39925044 | DOI:10.1177/02841851241310398

Brain Behav. 2025 Feb;15(2):e70302. doi: 10.1002/brb3.70302.

ABSTRACT

PURPOSE: The cerebellum's role extends beyond motor control, impacting various cognitive functions. A growing body of evidence supports the idea that the cerebellum optimizes performance across cognitive domains, suggesting critical connectivity with the neocortex. This study investigates how cerebellar transcranial direct current stimulation (tDCS) targeting the right Crus II region modulates functional brain connectivity.

METHOD: Using a within-subject design, 21 healthy participants underwent both sham and anodal cerebellar tDCS at 2 mA during 20 min of concurrent resting-state fMRI sessions. Data was preprocessed, and connectivity changes were examined using seed-to-voxel analysis. Given the potential impact of cerebellar dysfunctions on symptoms associated with autism spectrum disorders, we also assessed how individual autism quotient (AQ) scores might influence cerebellar functional connectivity. Moreover, electrical field simulations were computed for each participant to explore the effects of individual differences.

FINDINGS: Results indicated increased functional connectivity between the cerebellar Crus II and the right inferior frontal gyrus (IFG) during active tDCS compared to sham stimulation. The IFG (part of the Action Observation Network) plays a crucial role in understanding the actions and intentions of others, implicating the cerebellum in higher-order cognitive processes. In addition, linear mixed-effects models revealed an interaction between electric field strength and AQ scores, suggesting that functional connectivity changes are based on individual psychobiological differences.

CONCLUSION: Cerebellar tDCS significantly altered functional brain connectivity, particularly between the cerebellar Crus II and the IFG, both involved in social cognition. These findings contribute to our understanding of the cerebellum's role beyond motor control, highlighting its impact on cognitive and social processes and its potential for therapeutic applications, such as autism spectrum disorders.

PMID:39924992 | PMC:PMC11808187 | DOI:10.1002/brb3.70302

Mol Autism. 2025 Feb 8;16(1):8. doi: 10.1186/s13229-024-00631-3.

ABSTRACT

BACKGROUND: Brain signal variability (BSV) is an important understudied aspect of brain function linked to cognitive flexibility and adaptive behavior. Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by social communication difficulties and restricted and repetitive behaviors (RRBs). While atypical brain function has been identified in individuals with ASD using fMRI task-activation and functional connectivity approaches, little is known about age-related relationships with resting-state BSV and repetitive behaviors in ASD.

METHODS: We conducted a cross-sectional examination of resting-state BSV and its relationship with age and RRBs in a cohort of individuals with Autism Brain Imaging Data Exchange (n = 351) and typically developing (TD) individuals (n = 402) aged 5-50 years obtained from the Autism Brain Imaging Data Exchange. RRBs were assessed using the Autism Diagnostic Interview-Revised (ADI-RRB) scale. BSV was quantified using the root-mean-square successive difference (rMSSD) of the resting-state fMRI time series. We examined categorical group differences in rMSSD between ASD and TD groups, controlling for both linear and quadratic age. To identify dimensional relationships between age, group, and rMSSD, we utilized interaction regressors for group x age and group x quadratic age. Within a subset of individuals with ASD (269 subjects), we explored the relationship between rMSSD and ADI-RRB scores, both with and without age considerations. The relationship between rMSSD and ADI-RRB scores was further analyzed while accounting for linear and quadratic age. Additionally, we investigated the relationship between BSV, age, and ADI-RRB scores using interaction regressors for age x RRB and quadratic age x RRB.

RESULTS: When controlling for linear age effects, we observed significant group differences between individuals with ASD and TD individuals in the default-mode network (DMN) and visual network, with decreased BSV in ASD. Similarly, controlling for quadratic age effects revealed significant group differences in the DMN and visual network. In both cases, individuals with ASD showed decreased BSV compared with TD individuals in these brain regions. The group × age interaction demonstrated significant group differences in the DMN, and visual network brain areas, indicating that rMSSD was greater in older individuals compared with younger individuals in the ASD group, while rMSSD was greater in younger individuals compared with older individuals in the TD group. The group × quadratic age interaction showed significant differences in the brain regions included in DMN, with an inverted U-shaped rMSSD-age relationship in ASD (higher rMSSD in younger individuals that slightly increased into middle age before decreasing) and a U-shaped rMSSD-age relationship in TD (higher rMSSD in younger and older individuals compared with middle-aged individuals). When controlling for linear and quadratic age effects, we found a significant positive association between rMSSD and ADI-RRB scores in brain regions within the DMN, salience, and visual network. While no significant results were observed for the linear age × RRB interaction, a significant association between quadratic age and ADI-RRB scores emerged in the DMN, dorsal attention network, and sensorimotor network. Individuals with high ADI-RRB scores exhibited an inverted U-shaped relationship between rMSSD and age, with lower rMSSD levels observed in both younger and older individuals, and higher rMSSD in middle-aged individuals. Those with mid-range ADI-RRB scores displayed a weak inverted U-shaped rMSSD-age association. In contrast, individuals with low ADI-RRB scores showed a U-shaped rMSSD-age association, with higher rMSSD levels in younger and older individuals, but a lower rMSSD in middle-aged individuals.

CONCLUSION: These findings highlight age-related atypical BSV patterns in ASD and their association with repetitive behaviors, contributing to the growing literature on understanding alterations in functional brain maturation in ASD.

PMID:39923093 | PMC:PMC11806755 | DOI:10.1186/s13229-024-00631-3

Mult Scler Relat Disord. 2025 Jan 30;95:106270. doi: 10.1016/j.msard.2025.106270. Online ahead of print.

ABSTRACT

BACKGROUND: Altered brain network function is associated with cognitive impairment in multiple sclerosis (MS), but recent studies highlight a lack of consensus in the field. These differences may relate to the stage of MS, or different definitions for cognitive impairment.

OBJECTIVE: We investigated cognitive impairment and functional connectivity (FC) specifically in SPMS (secondary progressive MS) using resting-state functional MRI (rs-fMRI) and assessed the alterations in FC using two commonly used dichotomous criteria for cognitive impairment.

METHODS: 65 SPMS subjects from a British cohort underwent rs-fMRI at 3T, with independent component analysis of resting state networks. Cognitive impairment, assessed by neuropsychometry, was defined using a z-score of ≤ -1.96SD on ≥ 2 domains (-1.96SD group) or z-score of ≤ -1.5SD on ≥ 2 domains (-1.5SD group).

RESULTS: Cognitive impairment was, as expected, more prevalent in the -1.5SD (47 %) than -1.96SD criteria (30 %) group, despite similar demographics in both; mean age of 55 ± 7.1 years, disease duration 22 ± 9.6 years, median EDSS of 6.0 [range 4.0-6.5]. Adopting the -1.96SD criteria substantially increased the number of altered brain regions, with a 2.8 fold increase in regions showing decreased FC; including the ventral attentional and sensorimotor networks, and 1.5 fold increase in regions showing increased FC; including the precuneus and auditory networks.

CONCLUSIONS: The criteria chosen for cognitive impairment significantly impacts patterns of global FC change and may miss key network alterations, which could impact the efficacy of future therapeutic interventions highlighting the need for a consensus in the field. Agreed cut-offs for designating cognitive impairment could facilitate clinical management including monitoring disease activity, progression, and treatment efficacy.

PMID:39921989 | DOI:10.1016/j.msard.2025.106270

Parkinsonism Relat Disord. 2025 Jan 31;133:107315. doi: 10.1016/j.parkreldis.2025.107315. Online ahead of print.

ABSTRACT

PURPOSE: Craniocervical dystonia (CCD) is a large-scale network disorder that involves functional changes in multiple brain regions. However, the association between these functional changes and the underlying molecular mechanisms has not been explored.

OBJECTIVE: We aimed to characterize the molecular changes associated with the imaging-defined functional architecture of the brain in CCD.

METHODS: Resting-state functional magnetic resonance imaging (rs-fMRI) data were obtained from 146 patients with CCD and 137 healthy controls (HCs). Differences in the amplitude of low-frequency fluctuations (ALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo) were compared between groups. Transcriptomic data were obtained from the Allen Human Brain Atlas to identify the gene expression patterns underlying the affected functional architecture in CCD using partial least squares regression.

RESULTS: Compared to HCs, patients with CCD showed common functional alterations, mainly in the left middle occipital gyrus, right middle occipital gyrus, right calcarine, right precentral gyrus, and left postcentral gyrus. These functional alteration patterns were positively associated with 1763 genes (including five risk genes for dystonia) enriched for synaptic signaling, regulation of trans-synaptic signaling, and neuronal systems, while they were negatively associated with 2318 genes (including eight risk genes for dystonia), which were enriched for monoatomic cation transport, DNA damage response and neurodevelopment.

CONCLUSIONS: Our study reveals a genetic pathological mechanism explaining CCD-related brain functional changes.

PMID:39921933 | DOI:10.1016/j.parkreldis.2025.107315

Brain Struct Funct. 2025 Feb 8;230(2):39. doi: 10.1007/s00429-025-02899-4.

ABSTRACT

The influence of regional brain vasculature on resting-state fMRI BOLD signals is well documented. However, the role of brain vasculature is often overlooked in functional connectivity research. In the present report, utilizing publicly available whole-brain vasculature data in the mouse, we investigate the relationship between functional connectivity and brain vasculature. This is done by assessing interregional variations in vasculature through a novel metric termed vascular similarity. First, we identify features to describe the regional vasculature. Then, we employ multiple linear regression models to predict functional connectivity, incorporating vascular similarity alongside metrics from structural connectivity and spatial topology. Our findings reveal a significant correlation between functional connectivity strength and regional vasculature similarity, especially in anesthetized mice. We also show that multiple linear regression models of functional connectivity using standard predictors are improved by including vascular similarity. We perform this analysis at the cerebrum and whole-brain levels using data from both male and female mice. Our findings regarding the relation between functional connectivity and the underlying vascular anatomy may enhance our understanding of functional connectivity based on fMRI and provide insights into its disruption in neurological disorders.

PMID:39921726 | DOI:10.1007/s00429-025-02899-4

Neurobiol Dis. 2025 Feb 5:106816. doi: 10.1016/j.nbd.2025.106816. Online ahead of print.

ABSTRACT

Spinocerebellar ataxia type 3 (SCA3), a neurodegenerative disorder caused by excess CAG repeats in the ATXN3 gene, leads to progressive cerebellar ataxia and other symptoms. The results of previous studies suggest that trace element dysregulation contributes to neurodegenerative disorder onset. Here, we investigated the relationships of trace element dysregulation with CAG repeat length, clinical severity, and brain structural and functional connectivity in 45 patients with SCA3 and 44 healthy controls (HCs). Blood levels of lithium (Li), selenium (Se), and copper (Cu) were significantly lower in patients with SCA3 than in HCs; Li and Se levels were negatively correlated with CAG repeat length, especially in the manifest subgroup. Diffusion tensor imaging combined with resting-state functional magnetic resonance imaging revealed that Li levels were negatively correlated with fractional anisotropy in the white matter (WM) of bilateral frontal and parietal regions; tractography mapping showed disorder structural connectivity of Li-associated region nerve fiber pathways in patients with SCA3. Dynamic causal modeling analyses showed bidirectional causal connectivity from the inferior parietal lobule(IPL) to the cerebellum was significantly correlated with the blood level of Li in patients with SCA3. Time series correlation-based functional connectivity analysis revealed that the intrinsic connectivities of the bilateral dorsal premotor cortex(PMd) and IPL with local cerebellar regions were significantly weaker in patients with SCA3 than in HCs. Our results suggest that trace element dysregulation, especially Li deficiency, induces brain alterations and clinical manifestations in patients with SCA3; Li supplementation may be beneficial for WM or astrocytes in this patient population.

PMID:39921113 | DOI:10.1016/j.nbd.2025.106816

Prog Neuropsychopharmacol Biol Psychiatry. 2025 Feb 5:111283. doi: 10.1016/j.pnpbp.2025.111283. Online ahead of print.

ABSTRACT

Major depressive disorder (MDD) and bipolar disorder (BD) share various clinical behaviors and have confounded clinical diagnoses. Converging studies have suggested MDD and BD as disorders with abnormal communication among functional brain networks involved in mental activity and redirection. However, whether MDD and BD show disease-specific alterations in network information interaction remains unclear. This study collected resting-state functional MRI data of 98 patients with MDD, 55 patients with BD, and sex-, age-, and education-matched 95 healthy controls. Spectral dynamic causal model (spDCM) was used to investigate effective connectivities among three large-scale intrinsic functional networks including the default mode network (DMN), salience network (SN), and dorsal attention network (DAN). Effective connectivities showing disease-specific changes were then used as input features of support vector models to predict clinical symptoms and classify individuals with MDD and BD. Compared with healthy controls, both the MDD and BD groups showed increased DAN → SN connectivity. However, within-network connectivities of DMN and DAN showed opposite effects on the diseases. Notably, MDD and BD also showed different alterations on a connectivity loop of SN → DAN → DMN → SN, which could be used to predict the clinical symptom severity of either MDD or BD. Individuals with MDD and BD could be further classified by using connectivities showing opposite disease effects. Our findings reveal common and unique alterations of network interactions in MDD and BD, and further suggest disease-specific neuroimaging markers for clinical diagnosis.

PMID:39921029 | DOI:10.1016/j.pnpbp.2025.111283