Most recent paper

J Neurosci. 2025 Nov 17:e0577252025. doi: 10.1523/JNEUROSCI.0577-25.2025. Online ahead of print.

ABSTRACT

Sensorimotor and cognitive abilities undergo substantial changes throughout the human lifespan, but the corresponding changes in the functional properties of cortical networks remain poorly understood. This can be studied using temporal and spatial scales of functional magnetic resonance imaging (fMRI) signals, which provide a robust description of the topological structure and temporal dynamics of neural activity. For example, timescales of resting-state fMRI signals parsimoniously predict a significant amount of the individual variability in functional connectivity networks identified in adult human brains. In the present study, we quantified and compared temporal and spatial scales in resting-state fMRI data collected from 2,352 subjects of either sex between the ages of 5 and 100 in Developmental, Young Adult, and Aging datasets from the Human Connectome Project. For most cortical regions, we found that both temporal and spatial scales decreased with age throughout the lifespan, with the visual cortex and the limbic network consistently showing the largest and smallest scales, respectively. For some prefrontal regions, however, these two scales displayed non-monotonic trajectories and peaked around the same time during adolescence and decreased throughout the rest of the lifespan. We also found that cortical myelination increased monotonically throughout the lifespan, and its rate of change was significantly correlated with the changes in both temporal and spatial scales across different cortical regions in adulthood. These findings suggest that temporal and spatial scales in fMRI signals, as well as cortical myelination, are closely coordinated during both development and aging.Significance Statement Temporal and spatial scales of resting-state cortical activity in humans measured by fMRI largely decreased throughout the lifespan, except that for some regions in the prefrontal cortex they peaked similarly during adolescence. In addition, whereas cortical myelination consistently increased throughout the lifespan, its variation across different cortical networks and the rate of age-related changes were correlated with the dynamics of temporal and spatial scales of rs-fMRI activity, suggesting that the spatio-temporal scales of cortical activity and cortical myelination might be co-regulated during development and aging.

PMID:41249059 | DOI:10.1523/JNEUROSCI.0577-25.2025

Am J Physiol Regul Integr Comp Physiol. 2025 Nov 17. doi: 10.1152/ajpregu.00211.2025. Online ahead of print.

ABSTRACT

In preclinical models, the organum vasculosum of the lamina terminalis (OVLT) and subfornical organ (SFO) sense changes in serum sodium chloride (NaCl) concentration and mediate NaCl-induced changes in sympathetic nerve activity, vasopressin (AVP), thirst, and blood pressure (BP). In humans, brain imaging studies have shown that acute hypernatremia alters the activity or functional connectivity of the SFO and OVLT. However, no studies have investigated whether there are sex differences in central NaCl sensing in humans, which could underlie sex differences in neurohumoral responses to hypernatremia. Therefore, the purpose of this study was to test the hypothesis that acute relative hypernatremia would increase resting-state functional connectivity between NaCl-sensing brain regions and that these responses would be greater in men. Thirty-two young adults (17 men/15 women) underwent resting-state functional magnetic resonance imaging (fMRI) at baseline and during a 30-minute intravenous hypertonic saline infusion. We performed a seed-to-seed functional connectivity analysis. Despite similar increases in serum sodium, thirst, systolic BP, and plasma AVP between the sexes, there was a time*sex interaction (p<0.001) on SFO-OVLT functional connectivity, as SFO-OVLT functional connectivity increased in men during the late phase (15-30 minutes) of the hypertonic saline infusion (z-scores: baseline=0.21±0.20, late phase=0.29±0.21; p=0.04), but decreased in women (z-scores: baseline=0.27±0.17, late phase=0.15±0.18; p=0.004). Collectively, these results suggest that the functional coupling of the SFO and OVLT, which regulate sympathoexcitation and BP during acute hypernatremia, may be modulated by sex.

PMID:41247769 | DOI:10.1152/ajpregu.00211.2025

J Neurol. 2025 Nov 17;272(12):765. doi: 10.1007/s00415-025-13506-1.

ABSTRACT

OBJECTIVES: Cognitive decline in Parkinson's disease (PD) is closely associated with degeneration of the cholinergic system; however, the stage-dependent reorganization of cholinergic networks remains poorly understood. This study aimed to delineate alterations in cholinergic connectivity across the spectrum of cognitive impairment in PD patients.

METHODS: We enrolled 211 PD patients-classified as PD with normal cognition (PD-NC, n = 91), mild cognitive impairment (PD-MCI, n = 79), or dementia (PDD, n = 41)-and 71 healthy controls (HCs). Cholinergic functional networks were reconstructed by mapping predefined cholinergic subnetwork maps onto individual resting-state functional MRI data to derive subject-specific functional connectivity matrices. Graph theoretical measures were applied to quantify global and local topological characteristics. In addition, voxel-based morphometry (VBM) was used to assess group differences in cholinergic nuclei volumes. Furthermore, correlation and mediation analyses were conducted to explore the relationship between network disruption and cognitive performance.

RESULTS: PD patients showed stage-dependent alterations in cholinergic network topology, with increased shortest path length (Lp) and global efficiency in the Ch1-3 pathway and reduced clustering coefficient, gamma, Lp, and sigma in the medial Ch4 pathway (p < 0.05). Regionally, right hippocampal nodal centrality (Ch1-3) and inferior occipital gyrus/local efficiency (Ch4 lateral capsular division) were reduced in PDD, while posterior orbital part of the right medial superior frontal gyrus (medial Ch4) degree centrality increased. Medial Ch4 topological brain metrics correlated with global cognition and key domains, whereas metrics of Ch4 lateral capsular division pathway related to visuospatial and language performance. Structurally, compared to HCs, Ch4 volume loss occurred in PD-NC and PD-MCI groups, while Ch5-6 atrophy was specific in PDD group. Mediation analysis confirmed that medial Ch4 Lp mediated the effect of disease stage on global cognition.

CONCLUSIONS: This study provides new insights into the stage-specific disruption of cholinergic network topology and structural atrophy in PD, demonstrating that Ch4 nucleus degeneration is critically associated with stage-dependent network dysfunction and domain-specific cognitive impairment, thereby offering cholinergic network biomarkers as potential tools for stratifying cognitive stages.

PMID:41247531 | DOI:10.1007/s00415-025-13506-1

Front Neurol. 2025 Oct 30;16:1660039. doi: 10.3389/fneur.2025.1660039. eCollection 2025.

ABSTRACT

BACKGROUND: Blepharospasm, characterized by involuntary contractions of the orbicularis oculi muscles, significantly impairs the quality of life. Its pathophysiology remains unclear. Inter-hemispheric cooperation is a prominent feature of the human brain. This study utilizes resting-state functional magnetic resonance imaging (rs-fMRI) to explore inter-hemispheric functional cooperation in blepharospasm patients by examining connectivity between functionally homotopic voxels (CFH), aiming to identify neural disruptions associated with the disorder.

METHODS: We recruited 30 patients with blepharospasm and 30 age-, sex-, and education-matched healthy controls. All participants underwent rs-fMRI scanning. CFH maps were generated for each participant to quantify inter-hemispheric connectivity at the voxel level. Group differences were assessed, and partial correlation analyses were performed in the patient group to examine the relationship between aberrant CFH values and clinical variables.

RESULTS: Compared to healthy controls, patients with blepharospasm showed significantly increased CFH in the left putamen and left precentral gyrus. However, these aberrant CFH values did not significantly correlate with clinical variables, including disease duration or total Jankovic Rating Scale (JRS) scores and its subscales.

CONCLUSIONS: This study identifies increased inter-hemispheric functional connectivity (FC) within key motor-related brain regions in blepharospasm. The observed hyperconnectivity in the putamen and precentral gyrus may reflect a compensatory neural mechanism to counteract motor dysfunction. These findings provide novel insights into the pathophysiology of blepharospasm and suggest that modulating inter-hemispheric communication may be a potential therapeutic target.

PMID:41245859 | PMC:PMC12611749 | DOI:10.3389/fneur.2025.1660039

Front Aging Neurosci. 2025 Oct 31;17:1682996. doi: 10.3389/fnagi.2025.1682996. eCollection 2025.

ABSTRACT

INTRODUCTION: Cognitive frailty, defined by the coexistence of mild cognitive impairment and physical frailty, imposes greater risk of negative health consequences than either condition alone. Cognitive intraindividual variability (IIV), which reflects the extent of fluctuation in cognitive performance, is an early indicator of impaired cognition and mobility. To extend current understanding of the underlying neural mechanisms of increased IIV due to cognitive frailty, this study investigated the association between brain networks, IIV, and mobility.

METHODS: A total of 38 community-dwelling cognitively frail/non-cognitively frail older adults (CF and non-CF; n = 17 and n = 21, respectively) underwent clinical assessments including the Trail Making Test, Stroop Test, Timed Up and Go test (TUG), and resting-state functional magnetic resonance imaging. Dispersion across executive tests was computed to ascertain IIV (IIV-dispersion). Analysis of covariance was used to determine group differences in IIV-dispersion and functional network connectivity adjusted for functional comorbidities. Moderation models were constructed to investigate the role of functional neural networks in the association between IIV-dispersion and TUG performance.

RESULTS: Compared to non-CF group, CF group exhibited greater IIV-dispersion (p = 0.042), lower within sensorimotor network (SMN) connectivity, and lower connectivity between the default mode network (DMN), fronto-executive network (FEN), and SMN (all p < 0.050). Further, regional DMN-FEN connectivity moderated the relationship between IIV-dispersion and TUG performance (R-sq = 0.427, p = 0.001) only among the CF.

DISCUSSION: Greater IIV-dispersion due to cognitive frailty may be underpinned by large-scale altered functional connectivity across networks. However, localized reconfiguration of DMN-FEN connectivity may uniquely represent adaptive compensatory processes by which mobility is protected against the detrimental impact of greater IIV-dispersion secondary to cognitive frailty.

PMID:41245136 | PMC:PMC12615459 | DOI:10.3389/fnagi.2025.1682996

Hum Brain Mapp. 2025 Nov;46(16):e70413. doi: 10.1002/hbm.70413.

ABSTRACT

Macroscale brain modeling using neural mass models (NMMs) offers a framework for simulating human whole-brain dynamics. These models are pivotal for investigating the brain as a complex dynamic system, exploring phenomena like bifurcations, oscillatory patterns, and responses to stimuli. While connectome-based NMMs allow for the creation of personalized NMMs, their utility in capturing individual-specific neural characteristics remains underexplored, with current studies constrained by small sample sizes and computational inefficiencies. To address these limitations, we employed an algorithmically differentiable version of the reduced Wong Wang (RWW) model, enabling efficient optimization for large datasets. Applying this to resting-state fMRI data from 1444 samples, we optimized models with varying parameter complexities (n = 4, 658, and 23,875), which were derived from creating biologically plausible model variants. The optimized models achieved 4%, 19%, and 56% variance explanation in empirical functional connectivity (FC), respectively. Subject identification accuracy, based on simulated FC patterns, improved from < 1% (n = 4) to almost 100% (n = 23,875). Despite this precision, individual-level correlations between model parameters and attributes like age, gender, or intelligence quotient were small (effect sizes: η partial 2 ≤ 0.03 $$ {\eta}_{\mathrm{partial}}^2\le 0.03 $$ , standardized β ≤ 0.234 $$ \beta \le 0.234 $$ ). Machine learning analyses confirmed that these parameters lack the granularity to encode personal traits effectively. These findings suggest that, while current implementations of the RWW NMM can robustly replicate resting-state dynamics, the resulting parameters may lack the granularity required to map onto individual-specific behavioral metrics. This highlights a critical alignment problem: neural patterns and behavioral constructs such as intelligence may not correspond in a one-to-one fashion but instead represent higher-level abstractions. Bridging this gap will require the development of new tools capable of uncovering the underlying mapping manifolds, likely situated at the level of functional dynamics rather than isolated parameters. Future efforts should build on individual-level mechanistic modeling by exploring more expressive model classes and integrating richer sources of data, such as multimodal imaging or task-based paradigms, to better capture individual variability in both neural dynamics and behavioral traits. Such approaches may ultimately help to bridge the gap between model-based neural similarity and clinically meaningful personalization.

PMID:41243355 | DOI:10.1002/hbm.70413

J Affect Disord. 2025 Nov 13:120670. doi: 10.1016/j.jad.2025.120670. Online ahead of print.

ABSTRACT

BACKGROUND: Bipolar disorder (BD) carries high suicidality risk. While suicidal ideation (SI) correlates with evening chronotype, their joint neuroimaging mechanisms remain unclear. Unimodal MRI lacks sensitivity to detect coupled structural-functional abnormalities. We hypothesized BD patients with SI (BD-SI) would exhibit altered structural connectivity-functional connectivity (SC-FC) coupling versus BD patients without SI (BD-nSI) and healthy controls (HC), potentially correlating with chronotype.

METHODS: We recruited 138 BD-SI, 46 BD-nSI, and 280 HC. Resting-state functional MRI (rs-fMRI) and diffusion tensor imaging (DTI) data were acquired, and chronotype was assessed by Morningness-Eveningness Questionnaire (MEQ). Structural/functional connectivity and SC-FC coupling were compared across groups. Associations between SI, chronotype, and altered SC-FC coupling were examined in BD-SI group.

RESULTS: We found an altered functional connectivity (FC) network between 3 groups, involving the caudate nucleus, putamen, supplementary motor area, postcentral gyrus, inferior temporal gyrus and fusiform gyrus as important nodes. BD-SI patients demonstrated the most pronounced evening chronotype shift in MEQ total scores. BD-SI patients showed reduced SC-FC coupling in the triangular part of right inferior frontal gyrus (IFGtriang.R) compared to BD-nSI and HC, while both BD subgroups exhibited decreased coupling in the right olfactory cortex (OLF.R) relative to HC. The right amygdala (AMYG.R) displayed increased coupling in BD-SI versus BD-nSI, however, its nominal association with evening chronotype in BD-SI patients did not survive multiple comparisons correction.

CONCLUSION: Our study reveals changes in SC-FC coupling and a significant eveningness chronotype in BD-SI patients. This conjunction of physiological and clinical features warrants further investigation into chronotherapeutic strategies.

PMID:41241069 | DOI:10.1016/j.jad.2025.120670

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

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