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Neuroimage Clin. 2025 Nov 9;48:103907. doi: 10.1016/j.nicl.2025.103907. Online ahead of print.

ABSTRACT

BACKGROUND: Previous studies indicated that motor stroke is characterized by changes in the motor system's resting-state functional connectivity and functional topology. Furthermore, recent reports have shown that time-varying connectivity among motor areas is crucial for motor impairment and its recovery. Yet, it is unknown to what extent the topological organization of the motor network exhibits temporal dynamics that might be clinically relevant for the motor deficit after motor stroke.

OBJECTIVE: We combined a graph-theoretic approach and dynamic functional connectivity MRI to identify dynamic central motor nodes, that is motor areas whose time-varying topological properties are associated with motor impairment, and to characterize the dynamic interactions among regions of the motor system after stroke.

METHODS: Resting-state fMRI data were collected from a cohort of twenty acute right-hemispheric stroke patients (17 ischemic/3 hemorrhagic) exhibiting NIHSS scores ranging from 1 to 22 (mean=10.05; SD=5.58). Dynamic functional connectivity was estimated using a sliding window approach applied to regions of the motor network. Next, time-varying nodal betweenness centrality, defined as the portion of all shortest paths in the network involving such a node, was computed at each sliding window. Then, dynamic central motor nodes were characterized by correlating the amount of time that a given node exhibited high centrality (i.e., high centrality mode) with the degree of the upper limb impairment. Finally, the time-varying topological interactions within the motor network were investigated by characterizing its shortest paths.

RESULTS: A dynamic central motor node was identified in a region located within the ipsilesional primary cortex, namely the anterior wall of the ventral central sulcus (vCS). Specifically, severely impaired patients exhibited shorter stays in high centrality mode than less affected patients. Furthermore, upper limb impairment was associated with a dynamic network profile characterized by low functional connections among such a dynamic central motor node and a set of regions located in the central sulcus and supplementary motor area of the left hemisphere, as well as in the right cerebellum.

CONCLUSIONS: The current results indicate that acute motor stroke with upper limb impairment affects the time-varying topological properties of functional interactions within the motor network. Therefore, these findings may contribute to understanding motor deficits after stroke.

PMID:41240754 | DOI:10.1016/j.nicl.2025.103907

Alzheimers Res Ther. 2025 Nov 14;17(1):247. doi: 10.1186/s13195-025-01898-1.

ABSTRACT

BACKGROUND: Alzheimer's Disease Spectrum (ADS) progresses from preclinical stages to dementia, with dynamic functional connectivity (dFC) changes emerging early. This study aimed to investigate the dynamic changes in brain networks across different stages of ADS and their underlying molecular mechanisms.

METHODS: This cross-sectional study included 239 participants: 69 Healthy Controls (HC), 83 with Subjective Cognitive Decline (SCD), 56 with Mild Cognitive Impairment (MCI), and 31 with Alzheimer's disease (AD). All participants underwent neuropsychological testing and resting-state functional magnetic resonance imaging (rs-fMRI). Leading Eigenvector Dynamics Analysis (LEiDA), a data-driven method that captures time-resolved whole-brain dFC, was applied to identify transient brain states and calculated their occupancy rate, dwell time, and transition probabilities. Group differences in these dynamic metrics were assessed using a General Linear Model (GLM), and their correlations with cognitive performance were examined. To explore the molecular basis of significant dFC alterations, we performed gene-category enrichment analysis. This analysis integrated the spatial maps of altered brain states with regional gene expression data from the Allen Human Brain Atlas (AHBA), using spin permutations to ensure statistical robustness.

RESULTS: We identified ten recurring brain states and characterized how their transition patterns, stability, and frequency differed as a function of disease severity. Specifically, early disruptions appeared as altered transition probabilities between states, while later stages showed pronounced changes in the dwell time and occurrence rates of specific states, closely associated with cognitive decline. Notably, one brain state marked by synchronized activity in attention, salience, and default mode networks emerged as a critical hub linked to both cognitive deterioration and excitatory-inhibitory imbalance. Genes associated with this state were enriched in glycine-mediated synaptic pathways and expressed in both excitatory and inhibitory neurons, showing spatial and temporal patterns that extended from early development into late disease stages.

CONCLUSIONS: Our study uncovered the stage-dependent dFC changes and their molecular underpinnings of brain network dysfunction across the ADS.

PMID:41239516 | DOI:10.1186/s13195-025-01898-1

Commun Biol. 2025 Nov 14;8(1):1572. doi: 10.1038/s42003-025-09158-6.

ABSTRACT

Task-based functional magnetic resonance imaging (fMRI) reveals individual differences in neural correlates of cognition but faces scalability challenges due to cognitive demands, protocol variability, and limited task coverage in large datasets. Here, we propose DeepTaskGen, a deep-learning approach that synthesizes non-acquired task-based contrast maps from resting-state (rs-) fMRI. We validate this approach using the Human Connectome Project lifespan data, then generate 47 contrast maps from 7 different cognitive tasks for over 20,000 individuals from UK Biobank. DeepTaskGen outperforms several benchmarks in generating synthetic task-contrast maps, achieving superior reconstruction performance while retaining inter-individual variation essential for biomarker development. We further show comparable or superior predictive performance of synthetic maps relative to actual maps and rs-connectomes across diverse demographic, cognitive, and clinical variables. This approach facilitates the study of individual differences and the generation of task-related biomarkers by enabling the generation of arbitrary functional cognitive tasks from readily available rs-fMRI data.

PMID:41238730 | DOI:10.1038/s42003-025-09158-6

PLoS One. 2025 Nov 14;20(11):e0334165. doi: 10.1371/journal.pone.0334165. eCollection 2025.

ABSTRACT

While respiration is known to rhythmically modulate brain activity, how different breathing modes (nasal vs. oral) affect frequency-specific large-scale neural connectivity in humans remains unexplored. We used resting-state functional magnetic resonance imaging (fMRI) to examine how nasal and oral breathing modulate functional brain connectivity, focusing on blood oxygenation level-dependent (BOLD) fluctuations in the intermediate frequency band of 0.1-0.2 Hz in 20 healthy male participants. A fully data-driven ROI-based inference approach across 133 whole-brain ROIs revealed that nasal and oral breathing significantly activated the olfactory region and brainstem, respectively. Seed-based connectivity (SBC) analysis, using nonparametric permutation testing (10,000 iterations) and cluster-wise false discovery rate (FDR) thresholding (p-FDR < 0.05), based on these seeds, revealed distinct patterns of network engagement depending on breathing mode. Nasal breathing was associated with greater functional connectivity within higher-order brain networks, including the salience, somatosensory, default mode, and frontoparietal networks. Conversely, oral breathing increased connectivity centered on the brainstem, engaging subcortical regions involved in autonomic regulation and survival functions. Despite these differences, both conditions recruited stable respiratory core regions comprising the hippocampus, amygdala, and insula. These findings suggest a novel framework, the respiration-entrained brain oscillation network (REBON), defined by three operational criteria: (1) it is frequency-specific to the 0.1-0.2 Hz band (centered around ~0.16 Hz); (2) the activity of its principal regions, the olfactory region and brainstem, alternates in dominance depending on the mode of breathing; and (3) it includes a stable core of limbic and interoceptive structures, such as the hippocampus, amygdala, and insula. Understanding this network may have implications for future therapeutic strategies aimed at supporting cognitive functions, emotion regulation, and the integrity of large-scale brain networks in both clinical and wellness contexts; however, these translational implications require validation in future experimental studies.

PMID:41237075 | DOI:10.1371/journal.pone.0334165

Elife. 2025 Nov 14;14:RP105537. doi: 10.7554/eLife.105537.

ABSTRACT

Cognitive abilities are closely tied to mental health from early childhood. This study explores how neurobiological units of analysis of cognitive abilities-multimodal neuroimaging and polygenic scores (PGS)-represent this connection. Using data from over 11,000 children (ages 9-10) in the Adolescent Brain Cognitive Development (ABCD) Study, we applied multivariate models to predict cognitive abilities from mental health, neuroimaging, PGS, and environmental factors. Neuroimaging included 45 MRI-derived features (e.g. task/resting-state fMRI, structural MRI, diffusion imaging). Environmental factors encompassed socio-demographics (e.g. parental income/education), lifestyle (e.g. sleep, extracurricular activities), and developmental adverse events (e.g. parental use of alcohol/tobacco, pregnancy complications). Cognitive abilities were predicted by mental health (r = 0.36), neuroimaging (r = 0.54), PGS (r = 0.25), and environmental factors (r = 0.49). Commonality analyses showed that neuroimaging (66%) and PGS (21%) explained most of the cognitive-mental health link. Environmental factors accounted for 63% of the cognitive-mental health link, with neuroimaging and PGS explaining 58% and 21% of this environmental contribution, respectively. These patterns remained consistent over two years. Findings highlight the importance of neurobiological units of analysis for cognitive abilities in understanding the cognitive-mental health connection and its overlap with environmental factors.

PMID:41236810 | DOI:10.7554/eLife.105537

Brain Res Bull. 2025 Nov;232:111603. doi: 10.1016/j.brainresbull.2025.111603. Epub 2025 Oct 25.

ABSTRACT

BACKGROUND: Social anxiety disorder (SAD) is a prevalent psychiatric disorder, yet its underlying neural mechanisms remain unclear. Patients with SAD often show cognitive impairments associated with brain dysfunction. However, no study has examined the relationship between frequency-dependent brain activity and cognitive performance in SAD using resting-state functional magnetic resonance imaging (rs-fMRI) and neuropsychological assessments. In this study, we examined this association in patients with SAD using rs-fMRI.

METHODS: rs-fMRI data were collected from 27 patients with SAD and 40 healthy controls (HCs). Frequency-dependent alterations in fractional amplitude of low-frequency fluctuations (fALFF) were examined across typical (0.01-0.08 Hz), slow-5 (0.01-0.027 Hz), and slow-4 (0.027-0.073 Hz) bands to identify regions with abnormal spontaneous brain activity. Cognitive function was assessed using the Cambridge Neuropsychological Test Automated Battery. Correlations among abnormal brain activity, clinical symptoms, and cognitive functions were analyzed.

RESULTS: Compared with HCs, patients with SAD showed lower mean fALFF (mfALFF) in the bilateral postcentral gyrus across the typical and slow-5 bands, but only in the left postcentral gyrus for the slow-4 band. While mfALFF was not significantly associated with clinical symptom severity, significant correlations were observed between mfALFF and cognitive functioning.

CONCLUSIONS: Our findings indicate that cognitive function in patients with SAD is associated with frequency-dependent abnormalities in spontaneous brain activity, particularly reduced mfALFF in the postcentral gyrus. Additionally, frequency-dependent neural markers may help identify and target cognitive dysfunction in SAD, with abnormal postcentral gyrus activity potentially contributing to understanding of its underlying neural mechanisms.

PMID:41236075 | DOI:10.1016/j.brainresbull.2025.111603

Brain Res Bull. 2025 Nov;232:111600. doi: 10.1016/j.brainresbull.2025.111600. Epub 2025 Oct 25.

ABSTRACT

BACKGROUND: Resting-state functional MRI (rs-fMRI), reflecting the functional connectivity in the brain, is a useful tool for investigating the functional alteration induced by neurological diseases. In animal studies, anesthesia is essential for the acquisition of rs-fMRI data to eliminate motion artifacts. However, the optimal anesthesia protocol for adolescent rats is rarely discussed. The aim of the current study is to propose a feasible anesthesia protocol combining isoflurane and dexmedetomidine for use in adolescent rats.

MATERIAL AND METHODS: The rs-fMRI data were acquired in ten adolescent rats (postnatal day 40) at 60 and 90 min after the bolus injection of the dexmedetomidine, respectively, to assess the different patterns of the resting-state networks. The subject-level independent component analysis (sICA) was performed to demonstrate the resting-state networks in the adolescent rats. The Z-scores, transformed from Pearson's correlation coefficients, were calculated to compare the difference of within-region functional connectivity between two time points. The functional connectivity matrix was demonstrated to show the interregional functional connectivity over the anesthesia protocol.

RESULTS: The respiratory rate of the adolescent rats returned to the baseline at around 35 min after the bolus injection, becoming stable at around 60 min. In the adolescent rats, the typical resting-state networks including the default mode network (DMN), sensory, and motor networks were observed, similar to that in adult ones under the same anesthesia protocol. The within-region functional connectivity was lower at 60 min compared to that at 90 min. The interregional functional connectivity showed the more specific network pattern at 90 min.

CONCLUSIONS: Our results demonstrated the feasibility of the anesthesia protocol with the combination of isoflurane and dexmedetomidine and highlighted its time-dependent and dosage effect in the adolescent rats.

PMID:41236072 | DOI:10.1016/j.brainresbull.2025.111600

Behav Brain Res. 2026 Feb 4;497:115895. doi: 10.1016/j.bbr.2025.115895. Epub 2025 Oct 24.

ABSTRACT

BACKGROUND AND OBJECTIVE: Attention-Deficit/Hyperactivity Disorder (ADHD) is a common neurodevelopmental condition characterized by inattention, hyperactivity, and impulsivity. Emerging evidence suggests that ADHD is linked to hypofunction of the prefrontal-parietal attention network, accompanied by compensatory hyperactivation in the cerebellum and brainstem. However, the underlying neural mechanisms remain insufficiently understood. In recent years, computerized cognitive training has gained attention as a promising non-pharmacological intervention for alleviating ADHD symptoms, though its mechanisms of action and effects on neural plasticity remain contentious. This study utilized longitudinal neuroimaging to investigate abnormal brain function in individuals with ADHD, assess the effects of personalized computerized cognitive training (PCCT) on core symptoms, and examine the relationship between functional brain changes and behavioral improvements.

MATERIALS AND METHODS: Sixteen children with ADHD (ADHD group) and sixteen age- and sex-matched healthy controls (HC group) were recruited. All participants underwent resting-state functional magnetic resonance imaging (rs-fMRI) within three days of clinical assessment. The fractional amplitude of low-frequency fluctuations (fALFF) was calculated to evaluate spontaneous neural activity. The ADHD group received a 16-week PCCT intervention consisting of interference inhibition, sustained inhibition, and dominant inhibition training, administered once per week for 60 min per session. Baseline differences in fALFF between the groups were examined, along with pre- and post-intervention changes in clinical scores and fALFF values within the ADHD group. Correlation analyses were conducted between changes in fALFF and behavioral measures.

RESULTS: 1.At baseline, the ADHD group showed significantly higher scores than the healthy control (HC) group in SNAP (hyperactivity/inattention rating scale), CPT (Continuous Performance Test), and MMFT (Memory Function Test) (P < 0.05). fALFF analysis revealed decreased fALFF values in the precuneus, angular gyrus, and postcentral gyrus, and increased fALFF values in the cerebellum and brainstem in the ADHD group (P < 0.05, GRF-corrected).2.Effects of PCCT: Following the intervention, the ADHD group demonstrated significant reductions in SNAP-IV, CPT, and MMFT scores (P < 0.05), along with improved performance in all three inhibitory control tasks. fALFF values increased in the precuneus and lingual gyrus and decreased in the cerebellum and hippocampus, indicating modulation of abnormal neural activity.3.Correlation Analysis: The fALFF value in the right cerebellar lobule IX was positively correlated with CPT scores (r = 0.715), and the fALFF value in the left hippocampus was also positively correlated with CPT scores (r = 0.642). In contrast, the fALFF value in the right superior temporal gyrus was negatively correlated with MMFT scores (r = -0.721). These findings suggest that the cerebellar-prefrontal circuit, hippocampus, and superior temporal gyrus play important roles in the regulation of cognitive functions in children with ADHD.

CONCLUSION: This study revealed widespread functional abnormalities in the brains of children with ADHD, characterized by inefficiencies in the prefrontal-parietal network and compensatory hyperactivation in the cerebellum and brainstem. PCCT effectively improved core ADHD symptoms and induced neuroplastic changes in specific brain regions, including reduced activity in the cerebellum and hippocampus and increased activity in the precuneus and lingual gyrus. Furthermore, fALFF changes in the cerebellar lobule IX, hippocampus, and superior temporal gyrus were closely associated with cognitive improvements, supporting the central role of the cerebellar-prefrontal circuitry in modulating executive functions in ADHD. These findings provide new evidence for neural compensation mechanisms and non-pharmacological treatment strategies for ADHD. Future studies may explore precision interventions targeting the cerebellar-prefrontal network, such as combining neuromodulation with cognitive training, to optimize long-term outcomes in ADHD.

PMID:41235972 | DOI:10.1016/j.bbr.2025.115895

Behav Brain Res. 2026 Feb 4;497:115890. doi: 10.1016/j.bbr.2025.115890. Epub 2025 Oct 24.

ABSTRACT

This study investigated the neural mechanisms underlying SPS and emotional reactivity from the perspective of large-scale brain networks. A sample of 62 Chinese university students (35 females) was recruited. SPS was measured using the Chinese version of the Highly Sensitive Person Scale (C-HSPS), and emotional reactivity was assessed with the revised Chinese version of the Emotional Reactivity Scale (ERS). Resting-state functional connectivity was examined using fMRI. Behavioral analyses revealed a significant positive correlation between SPS and emotional reactivity (r = 0.49, p < 0.01). Neuroimaging findings showed that SPS was significantly negatively correlated with the functional connectivity between the salience network (SN) and frontoparietal network (FPN) (r = -0.29, p < 0.05), and the SN-FPN connectivity was also significantly negatively correlated with emotional reactivity (r = -0.28, p < 0.05). Mediation analysis demonstrated that SPS mediated the relationship between SN-FPN connectivity and emotional reactivity, such that SN-FPN connectivity predicted emotional reactivity indirectly through SPS. These findings indicate significant associations among SPS, SN-FPN connectivity, and emotional reactivity. The reduced SN-FPN connectivity observed in individuals with high SPS may potentially endow high-SPS individuals with advantages in supportive environments but increases their vulnerability to emotional dysregulation in challenging situations. This study provides novel insights into the neural mechanisms underlying SPS.

PMID:41235970 | DOI:10.1016/j.bbr.2025.115890

Hum Brain Mapp. 2025 Nov;46(16):e70411. doi: 10.1002/hbm.70411.

ABSTRACT

Brain lateralization is considered evolutionarily adaptive. Impaired functional specialization is thought to cause abnormal lateralization in neurological disorders. However, the dynamic changes in brain laterality in Alzheimer's disease (AD) remain unclear. In this study, resting-state fMRI data and neuropsychological assessments from 109 participants (49 AD patients and 60 healthy controls [HC]) were used. Dynamic laterality time series were constructed by extracting the dynamic laterality index (DLI) within each sliding window. We assessed two key features: laterality reversal (LR), reflecting intra-hemispheric processing efficiency, and laterality fluctuation (LF), indicating inter-hemispheric communication. Group differences in dynamic laterality characteristics were analyzed using statistically rigorous methods, regressing out gender, age, years of education, and head movements. Spearman correlation analyses examined the relationship between laterality characteristics and cognitive performance. Our results showed that AD patients exhibited a more pronounced loss of left lateralization as well as stronger right lateralization, especially in the somatomotor network (SMN) and default mode network (DMN). Additionally, we observed decreased LR as well as increased LF with global trends in AD. These divergent changes disrupted the dynamical balance between intra- and inter-hemispheric information interaction. Notably, this imbalance depended on the degree of lateralization, and the higher order cognitive networks with high-level lateralization were more vulnerable. Importantly, the observed abnormal lateralization metrics were associated with worse cognitive impairment. Our study highlights a disruption of dynamic lateralization balance in higher order cortical networks in AD patients and reveals its potential role in the disease's pathophysiology.

PMID:41235769 | DOI:10.1002/hbm.70411

Brain Commun. 2025 Oct 10;7(6):fcaf394. doi: 10.1093/braincomms/fcaf394. eCollection 2025.

ABSTRACT

Vascular cognitive impairment no dementia (VCIND) represents cognitive deficits due to vascular causes, without meeting the criteria for dementia. Cognitive training has emerged as a safe and effective intervention for VCIND, though its underlying mechanisms remain obscure. This study investigates how subcortical VCIND and computerized cognitive training affect brain functional lateralization of the fronto-parietal network (FPN), whose functions are notably influenced by both VCIND and cognitive training. In a randomized, active-controlled design for VCIND patients, we assessed the resting-state functional lateralization index (LI) of the FPN and conducted neuropsychological assessments in VCIND training and control groups (n = 30 per group) at baseline, after a 7-week intervention and at a 6-month follow-up. A healthy older group (n = 30) only provided baseline data. At baseline, VCIND patients showed an FPN lateralization pattern similar to that of healthy older adults. However, a stronger right-lateralized interhemispheric heterotopic LI in FPN correlated with better memory performance only in healthy adults. After the intervention, only the VCIND training group exhibited reduced lateralization in FPN, shifting to a bilateral interhemispheric LI, with stronger leftward changes correlating with improved executive and memory functions. Notably, these changes disappeared at the 6-month follow-up. These findings suggest that subcortical VCIND modifies the relationship between FPN lateralization and cognitive functions, rather than altering the lateralization pattern itself. Short-term computerized cognitive training facilitates executive and memory functions by promoting hemispherical reorganizing of FPN and functional compensation, although the benefits may diminish over time.

PMID:41234528 | PMC:PMC12607259 | DOI:10.1093/braincomms/fcaf394

Turk J Med Sci. 2025 Jul 26;55(5):1174-1187. doi: 10.55730/1300-0144.6072. eCollection 2025.

ABSTRACT

BACKGROUND/AIM: Exploratory methods in neuroimaging are gaining increasing attention for revealing functional connectivity structures across the entire brain. This study aims to contribute to the understanding of the functional mechanisms underlying dyslexia, along with the effects of specialized education for dyslexia treatment, by utilizing measures such as regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF), and fractional ALFF (fALFF).

MATERIALS AND METHODS: Resting-state functional magnetic resonance imaging data were collected from three groups of Turkish-speaking children aged 7-12: diagnosed with dyslexia for the first time (Dys, n = 19), children with dyslexia who received specialized education (EDys, n = 20), and healthy controls (HC, n = 27). In the study, brain activation in individuals with dyslexia was examined through resting-state analyses employing the ReHo, ALFF, and fALFF methods.

RESULTS: Significant reductions in ReHo and ALFF values were observed in brain regions associated with phonological processing and visuomotor integration in children with dyslexia. These findings indicate altered neural synchronization related to cognitive deficits in reading and language processing. Compared to HC, children with Dys showed significantly reduced ReHo and ALFF values in the left precuneus and middle frontal gyrus, while those EDys exhibited compensatory increases in calcarine and lingual gyri.

CONCLUSION: This study provides valuable insights into the resting-state neural connectivity of individuals with dyslexia, highlighting the impact of specialized educational programs in treating dyslexia. Our findings contribute to understanding the altered connectivity foundations of dyslexia compared to healthy children and support the development of educational interventions within this framework.

PMID:41234445 | PMC:PMC12611386 | DOI:10.55730/1300-0144.6072

Brain Res. 2025 Nov 11;1870:150044. doi: 10.1016/j.brainres.2025.150044. Online ahead of print.

ABSTRACT

BACKGROUND: Studies using repetitive transcranial magnetic stimulation (rTMS) frequently target non-motor brain areas to treat various conditions, including pain. However, whether and how non-motor rTMS affects neural activity is still debated in the scientific community.

OBJECTIVE: Characterize the local and global inhibitory effects of 2 non-motor rTMS protocols on brain activity.

METHODS: Participant's (n = 13) functional magnetic resonance imaging (fMRI) signal associated with a painful electrical paradigm was measured before and after 2 distinct low-frequency rTMS protocols (target: left superior temporal gyrus [STG]) with different intensities (conventional protocol: 90% resting motor threshold (rMT); individualized protocol: based on field-modeling). The target and the painful electrical paradigm were selected based on prior findings highlighting the role of the STG in pain memory. The size of activation clusters before and after the 2 rTMS protocols was compared using non-parametric tests. Field-modeling and state of the art white matter (WM) tractography were also used to document spatial effects of rTMS on brain activity.

RESULTS: rTMS targeting the STG significantly decreased BOLD activation in a widespread and long-lasting (∼ 10 min) manner, affecting both local (precentral gyrus, inferior parietal lobule and post central gyrus) and distant (inferior frontal gyrus, paracentral lobule, and insular gyrus and thalamus) brain areas for the conventional protocol. In contrast, no changes were observed for the individualized protocol. The distant rTMS effects observed in the left-hemisphere could be accounted for by structural connectivity, as revealed by tractography-based pathway analyses.

CONCLUSIONS: These exploratory findings suggest that, unlike the individualized protocol, conventional non-motor low-frequency rTMS protocol can induce widespread and long-lasting cortical inhibition via multiple pathways. These results open promising avenues for neurostimulation approaches targeting comparable effects in various clinical contexts. Additional research involving larger sample sizes is essential to validate these initial findings and confirm their broader applicability.

PMID:41232790 | DOI:10.1016/j.brainres.2025.150044

Neurology. 2025 Dec 9;105(11):e214385. doi: 10.1212/WNL.0000000000214385. Epub 2025 Nov 13.

ABSTRACT

BACKGROUND AND OBJECTIVES: Temporal lobe epilepsy (TLE) is a highly prevalent neurologic disorder, with 30%-50% of patients developing drug-resistant epilepsy. Pharmacoresistant seizures remodel critical arousal and respiratory networks, impairing autonomic function and chemoreception and putting patients at increased risk of adverse respiratory events and sudden unexpected death (SUDEP). Given that the bed nucleus of stria terminalis (BNST) serves as a key relay between brainstem respiratory nuclei and cortical arousal networks, we characterized interictal BNST connectivity alterations in patients with TLE.

METHODS: We conducted a case-control study of patients with drug-resistant TLE evaluated for epilepsy surgery at Vanderbilt University Medical Center, compared with healthy controls with no history of neurologic disease. Inclusion criteria for patients included clinical TLE diagnosis and age 18-65 years. Using resting-state fMRI (multiband factor = 3, repetition time [TR] = 1.3 seconds), we measured functional connectivity (FC) and effective connectivity through Granger causality (GC) between BNST and whole-brain cortical networks, and brainstem nuclei. Graph theoretical network metrics assessed BNST hub properties. Statistical analyses used multiple comparison corrections and age-corrected z-scores.

RESULTS: Thirty-seven patients with TLE (mean age 42.5 ± 12.1 years, 43.2% female) and 33 healthy controls (mean age 36.2 ± 12.0 years, 54.5% female) were studied. Patients demonstrated bilateral reductions in BNST connectivity and causal influence with the whole brain (FC: -2.31 ± 2.87, p = 0.0032; GC: -0.18 ± 0.08, p = 0.0025). While FC showed preserved BNST-brainstem connectivity, GC revealed ipsilateral disruptions in BNST influence over ventral tegmental area (0.023 ± 0.026, p = 0.0067), median raphe (-0.009 ± 0.029, p = 0.0038), and cuneiform nuclei (0.012 ± 0.062, p = 0.0153). Critical respiratory circuits showed divergent reorganization: dorsal raphe-parabrachial complex pathways exhibited 57.2% efferent reduction (p = 0.0028), with 204.6% compensatory afferent increase (p = 0.0020), while dorsal raphe-locus coeruleus circuits showed bilateral deterioration (66.2% reduction in dorsal raphe-locus coeruleus [DR→LC], p = 0.0015; 56.4% reduction in LC→DR, p = 0.0189). Graph analyses confirmed compromised BNST network integration bilaterally (p < 0.05).

DISCUSSION: Our findings reveal network reorganization in TLE that compromises autonomic and arousal circuit integrity, leading to failed respiratory-autonomic integration that may underlie respiratory vulnerability and increased SUDEP risk; however, we did not directly study SUDEP cases.

PMID:41232063 | DOI:10.1212/WNL.0000000000214385

Med Phys. 2025 Nov;52(11):e70138. doi: 10.1002/mp.70138.

ABSTRACT

BACKGROUND: Intersubject variation among patients with brain tumors complicates the template matching process for detecting the resting-state (rs) functional MRI (fMRI) language network when using independent component analysis (ICA).

PURPOSE: This study aimed to develop methods that use a probabilistic language atlas to incorporate intersubject variation in brain tumor patients into the template matching process.

METHODS: This retrospective study included 79 patients with brain tumors (average age, 50 ± 15 years) who underwent presurgical task-based (tb)-fMRI and rs-fMRI at clinical 3T scanners. At varying template generation thresholds (τ), binary and probabilistic templates were obtained from the language atlas. A binary template developed using healthy individuals and applied in published studies was tested as a control. Binary templates with goodness-of-fit (GOF) and probabilistic templates with weighted GOF (wGOF) or Jensen-Shannon distance (JSD) were used for template matching to recommend language networks from ICA. Dice coefficient and Pearson correlation with respect to tb-fMRI were assessed. Qualitative evaluation was performed by two neuroradiologists. Significant differences in Dice coefficients and Pearson correlations between different template matching methods, and significant differences between ratings were determined with the Wilcoxon signed-rank test, with p < 0.05 indicating statistical significance.

RESULTS: Compared to the control, recommendations from methods involving probabilistic language templates had significantly higher (p < 0.05) Dice coefficients across τ = 0% to τ = 35%. Pearson correlation results followed similar trends to those for Dice coefficient. Dice coefficients with the control were found to be 0.247 on average. Peak Dice coefficients with using wGOF and JSD for template matching were found to be 0.349 and 0.350, on average, respectively. Likert score results indicated significantly superior performance (p < 0.05) in identifying ICA components that contain the language network by using probabilistic language templates. 58 and 52 of 79 recommendations for the control were found to contain the language network (Likert scores ≥4) based on rater 1 and 2, respectively, which increased to 69-73 with template matching using wGOF and JSD.

CONCLUSIONS: The proposed application of probabilistic templates derived from a language tb-fMRI atlas of patients with brain tumors and probabilistic template matching methods can improve detection of rs-fMRI ICA language network in brain tumor patients.

PMID:41231662 | DOI:10.1002/mp.70138

Imaging Neurosci (Camb). 2025 Nov 10;3:IMAG.a.995. doi: 10.1162/IMAG.a.995. eCollection 2025.

ABSTRACT

The neural organization of cognitive control has been extensively studied using neuroimaging methods, but this organization is still not well understood. We argue that two factors may have contributed to this elusiveness. First, most previous research has relied on group-averaged results, which may provide a misleading representation of individual brains. Second, most fMRI studies study the brain only under a limited number of conditions, making it challenging to provide fine-grained distinctions in the functions associated with specific regions. Recent precision neuroimaging approaches have demonstrated substantial promise in furthering understanding of the human brain through repeated sampling of individual participants. However, most precision imaging work still relies on resting-state fMRI or a small number of tasks. In the present study, we demonstrate the utility of a novel dense imaging approach, which combines precision neuroimaging with an unusually large task battery. We demonstrate that patterns of neural activity associated with cognitive control tasks are significantly more similar within-person than between people, even after controlling for anatomical similarity, suggesting that these patterns are person-specific and reliable. In addition, we demonstrate that within-person and between-person similarity changes significantly across tasks, suggesting that some tasks may be more suited for exploring individual differences in cognitive control than others. Together, our findings highlight the potential value of a precision approach and the benefit of using a large number of tasks to further understanding of cognitive control.

PMID:41230411 | PMC:PMC12603659 | DOI:10.1162/IMAG.a.995

Front Neurol. 2025 Oct 28;16:1619226. doi: 10.3389/fneur.2025.1619226. eCollection 2025.

ABSTRACT

BACKGROUND: Unruptured cerebral arteriovenous malformations (AVMs) generally do not cause focal neurological deficits, prompting limited investigation into potential neurological changes associated with them.

PURPOSE: To determine whether AVMs exhibit combined functional and structural reorganization using resting-state functional MRI (rs-fMRI) and diffusion tensor imaging (DTI).

STUDY TYPE: Retrospective study.

POPULATION: 44 AVM patients who underwent both rs-fMRI and DTI examinations as well as an equal number of age- and sex-matched healthy controls.

SEQUENCE: Functional alterations were assessed using amplitude of low-frequency fluctuation (ALFF) analysis and functional connectivity networks, while fiber alterations were examined through fractional anisotropy (FA) analysis and tract-weighted functional connectivity (TW-FC) analysis.

ASSESSMENT: Functional alterations were evaluated by ALFF and functional connectivity networks, analyzed by neuroimaging specialists. Structural alterations were assessed through FA and TW-FC analysis, performed by experienced radiologists.

STATISTICAL TESTS: Independent two-sample t-test and the Mann- Whitney U test were used to analyze the continuous variables. Chi-squared test was used to test the categorical variables. We used permutation test with family-wise error correction while setting the statistical threshold of p < 0.05 at the cluster level. Two-tailed statistical significance was set at p < 0.05.

RESULTS: AVMs showed significant ALFF differences in 12 brain regions and altered functional connectivity networks compared to healthy controls (p < 0.05). Fiber connectivity and density were significantly reduced in AVM patients (p < 0.05). TW-FC analysis indicated significant differences across regions of interest (ROIs) between AVMs and healthy controls, suggesting integrated functional and structural reconfigurations (p < 0.05).

DATA CONCLUSION: The study reveals significant functional and structural changes in AVM patients, particularly in the visual network (VN) and sensorimotor network (SMN). These alterations suggest compensatory mechanisms that may offset functional deficits, providing insights into AVM pathophysiology and potential strategies for optimizing treatment to mitigate functional impairments and promote recovery.

PMID:41230380 | PMC:PMC12604527 | DOI:10.3389/fneur.2025.1619226

Dev Sci. 2026 Jan;29(1):e70093. doi: 10.1111/desc.70093.

ABSTRACT

Developmental dyslexia (DD) is a prevalent neurodevelopmental disorder that significantly affects academic learning and social development. Although numerous brain regions have been implicated in DD under both task-based and resting-state conditions, dysfunctions in large-scale functional coordination across brain systems in DD remains poorly understood. Using AES-SDM, we conducted a meta-analysis of seed-based whole-brain functional connectivity (FC) studies, including 12 task-based studies with 226 dyslexics and 232 age-matched controls, and 7 resting-state studies with 120 dyslexics and 145 controls. Results revealed consistently reduced FC between the left inferior frontal gyrus (IFG) and the left fusiform gyrus (FFG) in dyslexics compared with age-matched controls across both task and resting states, suggesting a core neural pathway underlying DD. In addition, task-specific abnormalities were identified, including hypoconnectivity between the left IFG and the right cerebellum, and hyperconnectivity between the left IFG and the bilateral angular gyrus (AG), anterior cingulate cortex (ACC), and left thalamus. By contrast, resting-state analyses identified additional hypoconnectivity between the left FFG and the posterior cingulate cortex (PCC). Together, these findings suggest that DD is associated with widespread disruption in functional integration across the brain, shedding new light on its neural mechanisms of DD and pointing to potential connectivity-based biomarkers for diagnosis. SUMMARY: Dyslexics exhibited consistent hypoconnectivity between the left inferior frontal gyrus and the left fusiform gyrus across both task and resting conditions. Under the task condition, dyslexics showed specific hypoconnectivity between the left inferior frontal gyrus and the right cerebellum, and hyperconnectivity with the bilateral angular gyrus, anterior cingulate cortex, and left thalamus. Under the resting condition, dyslexics showed specific hypoconnectivity between the left fusiform gyrus and the posterior cingulate cortex.

PMID:41229151 | DOI:10.1111/desc.70093

BMC Neurol. 2025 Nov 12;25(1):464. doi: 10.1186/s12883-025-04485-x.

ABSTRACT

BACKGROUND: Cognitive dysfunction has been reported in patients with glaucoma, but the underlying neural mechanisms remain unclear. This study aimed to explore functional connectivity (FC) alterations in hippocampal subregions in primary angle-closure glaucoma (PACG) patients with cognitive impairment.

METHOD: This study included forty-four PACG patients with cognitive dysfunction, and forty-six healthy controls (HCs). Participants underwent 3D high-resolution T1 structural imaging and BOLD fMRI scanning. Seven hippocampal subregions were selected as seed regions to explore changes in FC between the bilateral hippocampal subregions (Cornu Ammonis 1, Cornu Ammonis 2, Cornu Ammonis 3, Dentate gyrus, Entorhinal cortex, HATA, Subiculu) and the whole brain in PACG patients with cognitive dysfunction.

RESULTS: Compared with the HCs group, the PACG group showed decreased FC between multiple hippocampal subregions and the cerebellum, precentral gyrus, postcentral gyrus, supplementary motor area, supramarginal gyrus, inferior frontal gyrus, opercular part, lenticular nucleus, pallidum, rolandic operculum, inferior parietal, supramarginal, and angular gyri. However, increased FC was found between the bilateral hippocampal subregions and the calcarine fissure and surrounding cortex, lingual gyrus, anterior cingulate, and paracingulate gyri. We also found that FC between hippocampal subregions and some brain regions were associated with visual acuity, average cup-to-disc ratio, and retinal nerve fibre layer thickness.

CONCLUSION: These findings reveal widespread hippocampal FC alterations involving the cerebellum, sensorimotor, default mode, and visual network (VN) in PACG patients with cognitive dysfunction, contributing to a better understanding of the underlying neural mechanisms.

PMID:41225363 | DOI:10.1186/s12883-025-04485-x

Neurotherapeutics. 2025 Nov 11:e00790. doi: 10.1016/j.neurot.2025.e00790. Online ahead of print.

ABSTRACT

Racemic (R,S)-ketamine exerts rapid antidepressant effects, and growing evidence suggests its R-isomer may offer sustained efficacy with fewer side effects. However, the neurobiological mechanisms underlying (R)-ketamine's action in the human brain are largely unknown. To address this, we acquired resting-state fMRI data from 32 healthy volunteers 24 ​h before and after intranasal administration of (R)-ketamine (n ​= ​24) or placebo (n ​= ​8). We primarily assessed changes in long-range functional synchrony using degree centrality (DC) and elucidated the sources of these changes with functional connectivity (FC) analysis. (R)-ketamine significantly decreased DC in a key cognitive-motor integration hub: the supplementary motor area/middle cingulate cortex (SMA/MCC, cluster-corrected P ​< ​0.05). Critically, the reduction of DC was absent under the placebo condition, yielding a significant group-by-time interaction (P ​= ​0.01). The reduction in long-range synchrony of the SMA/MCC was primarily driven by attenuated FC with both the dorsal medial prefrontal cortex/dorsal anterior cingulate cortex (dMPFC/dACC) and the cerebellum, and was spatially correlated with serotonin, norepinephrine, and acetylcholine neurotransmitter profiles. More importantly, the clinical relevance of the neuroimaging phenotypes was established in an independent Major Depressive Disorder (MDD) cohort, where FC between the SMA/MCC and dMPFC/dACC significantly correlated with depressive symptom severity (HAMD score, P ​= ​0.019). This study provides novel, system-level evidence that intranasal (R)-ketamine modulates specific human brain networks by attenuating long-range synchrony in the SMA/MCC. The link between the neuroimaging phenotype, depression-relevant neurotransmitter profiles, and clinical symptom severity may offer a plausible therapeutic mechanism of (R)-ketamine.

PMID:41224612 | DOI:10.1016/j.neurot.2025.e00790