Feed aggregator

Front Neurosci. 2025 Sep 24;19:1647538. doi: 10.3389/fnins.2025.1647538. eCollection 2025.

ABSTRACT

OBJECTIVE: This study utilized resting-state functional magnetic resonance imaging (fMRI) to examine changes in brain functional activity following acupuncture treatment for acute Bell's palsy (BP) and to investigate the potential central regulatory mechanisms involved.

METHODS: A total of 55 patients with acute Bell's facial paralysis (within 1-7 days of onset) were enrolled in the patient group, while 48 individuals without the condition were included as the healthy control group. The patient group received acupuncture therapy at EX-HN16 (Qianzheng), SJ17 (Yifeng), ST2 (Sibai), GB14 (Yangbai), EX-HN4 (Yuyao), SI18 (Quanliao), ST6 (Jiache), ST4 (Dicang), ST8 (Touwei), and bilateral LI4 (Hegu) points on the affected side. Each session lasted 30 min and was administered three times a week (Wednesday, Friday, and Sunday) until day 28 of the disease course. The patient group underwent fMRI scans, House-Brackmann (H-B) grading, Sunnybrook scale evaluation, and facial disability index (FDI) assessment both prior to the initial treatment and on the 28th day. The healthy group received a single fMRI scan after enrollment. MATLAB R2017 software was used to calculate the fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo) in patients before and after treatment, as well as in healthy controls.

RESULTS: Following treatment, the patient group showed significant improvements in H-B, Sunnybrook, and FDI scores compared to pretreatment levels (P < 0.05), with an overall effective rate of 96.4% (53/55). Prior to treatment, compared to healthy controls, patients exhibited decreased fALFF in the right posterior cingulate gyrus, increased fALFF in the right postcentral gyrus, left and right middle frontal gyri, and increased ReHo in the left precentral gyrus, right postcentral gyrus, and left middle occipital gyrus. After treatment, when compared to healthy controls, patients showed decreased fALFF in the left and right medial superior frontal gyri, and increased fALFF in the right postcentral gyrus, left precentral gyrus, and bilateral lingual gyri, and increased ReHo in the right precentral gyrus, bilateral transverse temporal gyri, right lingual gyrus, and right thalamus, and decreased ReHo in the right middle frontal gyrus. Relative to pretreatment values, patients displayed decreased fALFF in the left medial superior frontal gyrus and increased fALFF in the left precentral gyrus. Additionally, ReHo decreased the right and left medial superior frontal gyri, while it increased in the right inferior parietal angular gyrus, right precentral gyrus, and left superior parietal gyrus.

CONCLUSION: Acupuncture demonstrates a clear therapeutic effect on acute BP and contribute to clinical symptom improvement. Marked differences in brain functional activity were observed between patients and healthy individuals. The therapeutic effect of acupuncture may be linked to its ability to facilitate functional reorganization in brain regions associated with sensation, movement, and emotion.

CLINICAL TRIAL REGISTRATION: https://www.chictr.org.cn/searchproj.html? title=&officialname=&subjectid=&regstatus=&regno=ChiCTR2200065223& secondaryid=&applier=&studyleader=&createyear=&sponsor=&secsponsor= &sourceofspends=&studyailment=&studyailmentcode=&studytype=&study stage=&studydesign=&recruitmentstatus=&gender=&agreetosign=&measure= &country=&province=&city=&institution=&institutionlevel=&intercode=& ethicalcommitteesanction=&whetherpublic=&minstudyexecutetime=&maxstudy executetime=&btngo=btn, identifier ChiCTR2200065223.

PMID:41069516 | PMC:PMC12504244 | DOI:10.3389/fnins.2025.1647538

Nat Ment Health. 2025;3(10):1276-1290. doi: 10.1038/s44220-025-00503-6. Epub 2025 Sep 23.

ABSTRACT

Persisting symptoms after concussion (PSaC) represent a complex and poorly understood neuropsychiatric phenomenon with limited treatment options. Neural network dysfunction has been associated with PSaC, and neuromodulation, particularly repetitive transcranial magnetic stimulation, may be a promising intervention. However, neuroimaging findings have been inconsistent, limiting understanding of underlying network dysfunction. We aimed to identify a core neural network associated with PSaC and explore whether this network could yield candidate cortical targets for neuromodulation at the individual level. We hypothesized that differences in network disruption would be evident between individuals with high versus low symptom burden in PSaC. Here we show that a convergent multi-analytic approach combining symptom-activation maps generated from existing fMRI datasets, systematic review of resting-state fMRI studies of PSaC, and network-based meta-analysis of coordinates derived from these studies co-localize to the salience network in high symptom burden PSaC. Using Human Connectome Project data, we mapped this network to cortical regions that could serve as individualized targets for neuromodulation. This aligns with current clinical models of PSaC and may present a new direction for network-based therapy.

PMID:41069366 | PMC:PMC12504115 | DOI:10.1038/s44220-025-00503-6

Brain Behav. 2025 Oct;15(10):e70947. doi: 10.1002/brb3.70947.

ABSTRACT

OBJECTIVE: This study aimed to assess the brain functional connectivity and its association with cognitive function in patients with chronic kidney disease (CKD) using resting-state functional magnetic resonance imaging (rs-fMRI).

METHODS: A total of 64 CKD patients were enrolled and divided into two groups based on their dependence on dialysis: dialysis-dependent CKD (DD-CKD) group (n = 38) and non-dialysis-dependent CKD (NDD-CKD) group (n = 26). A total of 43 healthy controls (NC) were also recruited and matched for age and sex. Cognitive function was evaluated using the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). MRI scans were conducted on a 3.0T Magnetom Skyra scanner equipped with a 32-channel phased array head coil. Data analysis was performed using the Data Processing Assistant for Resting-State fMRI (DPARSF) and Statistical Parametric Mapping (SPM) software.

RESULTS: Cognitive scores (MMSE and MoCA) were significantly lower in both CKD groups compared to healthy controls (p < 0.001), with DD-CKD patients exhibiting worse cognitive performance than NDD-CKD patients (p < 0.05). Laboratory parameters also differed: compared with DD-CKD, NDD-CKD patients had significantly lower levels of protein, creatinine, calcium, and phosphate (all p < 0.05). Network-based statistical analysis revealed reduced functional connectivity in both CKD groups relative to controls (p < 0.05). NDD-CKD patients showed disruptions mainly in the frontal-insular and occipital networks, whereas DD-CKD patients exhibited more extensive alterations involving frontoparietal, cingulate, and visual regions. Correlation analysis further showed that connectivity reductions in key regions-including the dorsolateral prefrontal cortex and parietal association areas-were negatively associated with renal function indicators such as serum creatinine and urea nitrogen (p < 0.05).

CONCLUSION: Resting-state fMRI effectively reflects alterations in brain functional connectivity in CKD patients and is associated with cognitive performance. Notably, DD-CKD patients showed more extensive network disruptions and more severe cognitive impairment.

PMID:41069337 | DOI:10.1002/brb3.70947

Psychol Med. 2025 Oct 10;55:e306. doi: 10.1017/S0033291725102006.

ABSTRACT

BACKGROUND: Schizophrenia progresses through high-risk, first-episode, and chronic stages, each associated with altered spontaneous brain activity. Resting state functional MRI studies highlight these changes, but inconsistencies persist, and the genetic basis remains unclear.

METHODS: A neuroimaging meta-analysis was conducted to assess spontaneous brain activity alterations in each schizophrenia stage. The largest available genome-wide association study (GWAS) summary statistics for schizophrenia (N = 53,386 cases, 77,258 controls) were used, followed by Hi-C-coupled multimarker analysis of genomic annotation (H-MAGMA) to identify schizophrenia-associated genes. Transcriptome-neuroimaging association and gene prioritization analyses were performed to identify genes consistently linked to brain activity alterations. Biological relevance was explored by functional enrichment.

RESULTS: Fifty-two studies met the inclusion criteria, covering the high-risk (Nhigh-risk = 409, Ncontrol = 475), first-episode (Ncase = 1842, Ncontrol = 1735), and chronic (Ncase = 1242, Ncontrol = 1300) stages. High-risk stage showed reduced brain activity in the right median cingulate and paracingulate gyri. First-episode stage revealed increased activity in the right putamen and decreased activity in the left gyrus rectus and right postcentral gyrus. Chronic stage showed heightened activity in the right inferior frontal gyrus and reduced activity in the superior occipital gyrus and right postcentral gyrus. Across all stages, 199 genes were consistently linked to brain activity changes, involved in biological processes such as nervous system development, synaptic transmission, and synaptic plasticity.

CONCLUSIONS: Brain activity alterations across schizophrenia stages and genes consistently associated with these changes highlight their potential as universal biomarkers and therapeutic targets for schizophrenia.

PMID:41069013 | DOI:10.1017/S0033291725102006

BMC Psychiatry. 2025 Oct 9;25(1):960. doi: 10.1186/s12888-025-07363-5.

ABSTRACT

BACKGROUND: Although abnormal amygdala functional connectivity (FC) has been reported in schizophrenia, most studies have treated the amygdala as a single structure. This study aimed to explore the association between amygdala subregional FC and anhedonia in patients with first-episode schizophrenia (FES).

METHODS: Resting-state functional magnetic resonance imaging (fMRI) was conducted in 31 FES patients (including 11 drug-naïve) and 33 matched healthy controls (HCs). Clinical symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS), and anhedonia was evaluated via the Snaith-Hamilton Pleasure Scale (SHAPS). Whole-brain FC analyses of amygdala subregions were performed, followed by group comparisons and correlation analyses with anhedonia scores.

RESULT: Compared to HCs, FES patients showed significantly reduced FC between specific amygdala subregions and cortical regions, particularly within the frontal, temporal, parietal, and limbic lobes (P < 0.05, GRF correction). Anhedonia severity was positively correlated with altered FC in the centromedial (CM) subregion of the amygdala (AMY_CM), especially with the supplementary motor area (SMA) and paracentral lobule (PLG). Notably, the association between right AMY_CM and right SMA FC and anhedonia remained significant after adjusting for clinical symptom severity (r = 0.46, P = 0.02).

CONCLUSIONS: FES patients exhibit disrupted FC between amygdala subregions and cortical areas, with specific patterns linked to anhedonia. These findings suggest that anhedonia may be associated with a potential neurobiological marker independent of general clinical symptoms and may be indicative of amygdala-cortical dysconnectivity in schizophrenia.

TRIAL REGISTRATION: Data used for this analysis came from case-control studies.

CLINICAL TRIAL NUMBER: not applicable. (April 2018 through March 2021).

PMID:41068675 | DOI:10.1186/s12888-025-07363-5

Brain Res Bull. 2025 Oct 7:111576. doi: 10.1016/j.brainresbull.2025.111576. Online ahead of print.

ABSTRACT

INTRODUCTION: The central mechanisms of intravesical electrical stimulation (IVES) were explored in a rat model of detrusor underactivity (DU) induced by bilateral pelvic nerve crush (bPNC). Resting-state functional magnetic resonance imaging (rs-fMRI) was used to evaluate regional homogeneity (ReHo) and functional connectivity (FC).

METHODS: Eighteen female Sprague-Dawley rats were randomly assigned to sham, bPNC, or IVES groups. The IVES group received 20-minute daily stimulations for 20 days after bPNC. Following treatment, rs-fMRI, cystometry, and immunofluorescence staining for ΔFosB (neuronal activity marker) and GAP43 (axonal plasticity marker) were performed.

RESULTS: Compared with bPNC rats, IVES significantly reduced maximum cystometric capacity and post-void residual volume, and increased detrusor pressure variation during voiding. The bPNC group had higher bladder capacity, increased filling-phase pressure variation, and lower voiding pressure than the sham group. Compared to sham and IVES rats, bPNC rats showed reduced ReHo in the right striatum and periaqueductal gray (PAG). FC between the right striatum and bilateral somatosensory cortex, and between the right PAG and left cerebellum, was weaker in bPNC rats. ΔFosB expression in the right striatum and PAG was higher in bPNC rats than in sham and IVES groups.

CONCLUSIONS: IVES may improve DU via modulation of neuronal activity in the right striatum and PAG and enhancing FC between the right striatum and somatosensory cortex, and between the right PAG and left cerebellum.

PMID:41067445 | DOI:10.1016/j.brainresbull.2025.111576

BMC Pediatr. 2025 Oct 9;25(1):790. doi: 10.1186/s12887-025-06196-1.

ABSTRACT

BACKGROUND: Attention deficit hyperactivity disorder (ADHD) is a common clinical developmental disorder. Aerobic exercise effectively improves the inhibition function of ADHD children, but its intervention mechanism is not clear yet. This study aimed to explore the brain mechanisms of aerobic exercise improving inhibitory function in children with ADHD.

METHODS: 20 school-age children with ADHD were studied. Before and after swimming exercise three times a week for 8 weeks, resting-state functional magnetic resonance imaging (rs-fMRI) and Flanker task tests were performed respectively. fMRI analysis focused on the right inferior frontal gyrus (rIFG), and the whole-brain functional connectivity (FC) was calculated based on rIFG. Paired t-test was used to analyze the FC value and the behavioral results of the Flanker task. And the correlations between the FC and the behavioral changes before and after swimming exercise were analyzed.

RESULTS: This study found that the brain regions with significant differences in rIFG-based FC values included rIFG, right inferior parietal lobule, and cerebellum posterior lobe. The response time after exercise was significantly shorter than that before exercise, while the accuracy after exercise was higher than before. And, the FC changes within rIFG were negatively correlated with the response time changes and positively correlated with the accuracy changes of the Flanker task.

CONCLUSION: This study suggests that the FC within rIFG and the FC between rIFG and right inferior parietal lobule are related to the improvement of inhibition function in ADHD children.

PMID:41068640 | DOI:10.1186/s12887-025-06196-1

AJNR Am J Neuroradiol. 2025 Oct 9:ajnr.A9030. doi: 10.3174/ajnr.A9030. Online ahead of print.

ABSTRACT

BACKGROUND AND PURPOSE: This study investigated dynamic cerebellar networks in post-stroke aphasia patients using resting-state fMRI. We examined intra-cerebellar and cerebellar-cortical dynamic functional connectivity quantified their temporal properties and graph-theoretical topology.

MATERIALS AND METHODS: Seventy-seven right-handed patients with post-stroke aphasia and 79 healthy controls underwent underwent 3T resting-state functional MRI. Dynamic cerebellar functional networks were constructed using the Seitzman-27 cerebellar atlas. A sliding-window approach (30 TR window, 1 TR step) was applied, followed by k-means clustering to identify distinct connectivity states. Graph-theoretical analyses were performed to quantify state-specific network topology. Variability of dynamic functional connectivity between cerebellar and cortical regions was calculated. Partial correlation analyses were conducted to examine relationships between dynamic network measures, lesion volume, and language and cognitive function.

RESULTS: Two cerebellar dynamic functional connectivity states were identified in post-stroke aphasia: a predominant segregated state (78.93%) with widespread reductions in connectivity and decreased clustering coefficient (d = -1.29), characteristic path length (d = -0.62), and Local Efficiency (d = -1.11), but higher Global Efficiency (d = 1.06); and a less frequent integrated state (21.07%) with enhanced connectivity and higher Clustering Coefficient (d = 0.57) and Characteristic Path Length (d = 0.70), but diminished Global Efficiency (d = -1.25) and small-worldness (d = -0.92), small-world index (d = -0.89). Post-stroke aphasia showed reduced variability of dynamic functional connectivity between cerebellar and cortical regions involved in language and cognition (Gaussian random field correction, voxel-level p < 0.001, cluster-level p < 0.05). Lesion volume negatively correlated with Aphasia Quotient, Repetition, Memory, Executive Function, and Attention (p < 0.05). State-specific network metrics and variability measures were associated with language and cognitive performance independently of lesion volume.

CONCLUSIONS: Post-stroke aphasia patients exhibited a segregated cerebellar state with reduced intra-cerebellar connectivity and efficiency, and an integrated state with enhanced connectivity and small-world properties, together with reduced variability in cerebellar-cortical connections to language-and cognition-related regions. These state-specific network alterations were linked to distinct behavioral domains independently of lesion volume, highlighting a dissociation between structural constraints and dynamic, lesion-independent plasticity.

ABBREVIATIONS: PSA = Post-Stroke Aphasia; DFC = Dynamic Functional Connectivity; FPN = Frontoparietal Network; DMN = Default Mode Network; SMN = Somatomotor Network; Eloc = Local Efficiency; Eg = Global Efficiency; Lp = Characteristic Path Length; DAN = Dorsal Attention Network; FDR = False Discovery Rate.

PMID:41067912 | DOI:10.3174/ajnr.A9030

J Cogn Neurosci. 2025 Oct 3:1-20. doi: 10.1162/JOCN.a.2396. Online ahead of print.

ABSTRACT

Complex cognition, such as creativity, relies on cognitive integration of various component processes (e.g., memory, attention, and imagery). Yet, current methods cannot fully capture how the brain integrates cognitive processes during complex tasks. Previous research suggests that communication between functionally dissimilar regions might underlie cognitive integration, allowing for complex cognition. Here, we provide a formal test of this notion using task-based fMRI (n = 28) to assess functional connectivity (FC) among sets of regions ("levels") varying in their functional dissimilarity (defined by differences in resting-state FC profiles) across five tasks hypothesized to vary in cognitive complexity. Each task involved conceptual association and/or idea generation. We found that as task complexity increased, task-FC between regions with greater functional dissimilarity also increased, and the strength of this linear trend positively predicted the relative complexity of tasks. Thus, more complex tasks recruited greater interactions between functionally dissimilar regions. Furthermore, this effect was primarily driven by the default mode and frontoparietal control networks, especially connector hubs within these networks. Task-FC at the highest functional dissimilarity levels was mostly related to metaphor production and bi-association (involving integrating two concepts), followed by generating novel object uses and uncommon association (involving expanding one concept), and was least related to common association (thus, this task was the least complex). Altogether, task-FC across functional dissimilarity levels robustly tracked the cognitive complexity of tasks, supporting the validity of this neural feature for measuring cognitive complexity in a continuous manner and for data-driven tests of theorized differences in task complexity.

PMID:41066703 | DOI:10.1162/JOCN.a.2396

Transl Psychiatry. 2025 Oct 6;15(1):356. doi: 10.1038/s41398-025-03584-0.

ABSTRACT

The multidimensional nature of schizophrenia requires a comprehensive exploration of the functional and structural brain networks. While prior research has provided valuable insights into these aspects, our study goes a step further to investigate the reconfiguration of the hierarchy of brain dynamics, which can help understand how brain regions interact and coordinate in schizophrenia. We applied an innovative thermodynamic framework, which allows for a quantification of the degree of functional hierarchical organisation by analysing resting state fMRI-data. Our findings reveal increased hierarchical organisation at the whole-brain level and within specific resting-state networks in individuals with schizophrenia, which correlated with negative symptoms, positive formal thought disorder and apathy. Moreover, using a machine learning approach, we showed that hierarchy measures allow a robust diagnostic separation between healthy controls and schizophrenia patients. Thus, our findings provide new insights into the nature of functional connectivity anomalies in schizophrenia, suggesting that they could be caused by the breakdown of the functional orchestration of brain dynamics.

PMID:41053029 | PMC:PMC12501247 | DOI:10.1038/s41398-025-03584-0

J Affect Disord. 2025 Oct 4;393(Pt A):120357. doi: 10.1016/j.jad.2025.120357. Online ahead of print.

ABSTRACT

BACKGROUND: Childhood trauma is a recognized risk factor for affective dysregulation and aggressive behavior in adolescents with Internet Gaming Disorder (IGD). However, the neurobiological pathways linking trauma to aggression in IGD remain poorly understood. This study aims to investigate how childhood trauma affects aggressive behavior in adolescents with IGD through specific neurobiological mechanisms.

METHOD: We recruited 111 adolescents categorized into IGD with childhood trauma (IGD-CT, n = 43), IGD without trauma (IGDN, n = 31), and healthy controls (HC, n = 37). Using resting-state fMRI, we computed amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) to compare spontaneous brain activity. Then we correlated the regional ALFF/fALFF with levels of childhood trauma (CTQ-SF score) and aggression. Finally, we conducted a mediation analysis to examine whether brain activity modulates the relationship between childhood trauma and aggression in youths with IGD.

RESULTS: The IGD-N group showed significantly lower fALFF compared with the IGD-CT group，they also had significant differences compared to the HC group. Furthermore, the mean fALFF in the left precuneus was positively correlated with CTQ-SF (r = 0.321, p = 0.008) and reactive aggression (RA; r = 0.396, p = 0.001) scores. Importantly, the mean fALFF in the left precuneus partially mediated the correlation between CTQ-SF and RA scores (effect proportion of 28.18 %).

CONCLUSION: Our study identifies the left precuneus as a critical neural region where childhood trauma uniquely impacts aggression in adolescents with IGD. The findings highlight the necessity for targeted interventions in IGD with trauma histories, providing potential avenues to reduce aggression in at-risk adolescents affected by both trauma and gaming addiction.

PMID:41052680 | DOI:10.1016/j.jad.2025.120357

Neuroimage Rep. 2025 Jul 8;5(3):100275. doi: 10.1016/j.ynirp.2025.100275. eCollection 2025 Sep.

ABSTRACT

BACKGROUND: Obsessive-compulsive disorder (OCD) is commonly treated with cognitive-behavioral therapy (CBT), yet many patients fail to achieve remission. Neuroimaging markers, such as pre-treatment functional and structural connectivity, may help elucidate OCD pathology and CBT mechanisms, and predict treatment outcomes. This study investigates the relationship between pre-treatment functional and structural connectivity and remission status in OCD patients following CBT.

METHODS: Thirty-three OCD patients underwent multimodal MRI, including resting-state fMRI to assess pre-treatment functional connectivity and diffusion tensor imaging (DTI) to evaluate white matter integrity. Functional connectivity multivariate pattern analysis (fc-MVPA) identified patterns linked to treatment outcomes. TRACULA, a probabilistic tractography technique, analyzed white matter tracts, focusing on diffusion metrics such as fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD). Analysis of covariance (ANCOVA) was used to examine group differences.

RESULTS: Remission was associated with significantly higher pre-treatment resting-state functional connectivity between the occipital pole and lateral occipital cortex (height threshold: p < 0.001 uncorrected and cluster threshold: p < 0.05 cluster-size FDR corrected for multiple comparisons), suggesting a role in visual processing. Differences in white matter integrity were found in the corpus callosum rostrum, left acoustic radiation, right dorsal cingulum bundle, and right superior longitudinal fasciculus II, though these results were not corrected for multiple comparisons.

CONCLUSION: Enhanced pre-treatment functional connectivity in visual processing regions and specific white matter tracts may serve as biomarkers for remission in OCD following CBT. These findings could improve understanding of CBT's neural effects and guide personalized treatment strategies.

PMID:41050951 | PMC:PMC12489777 | DOI:10.1016/j.ynirp.2025.100275

Neuroimage Rep. 2025 Jun 28;5(3):100278. doi: 10.1016/j.ynirp.2025.100278. eCollection 2025 Sep.

ABSTRACT

Frontal lobe epilepsy (FLE), marked by recurrent seizures arising from the frontal lobes, can significantly impair cognitive and motor function, reducing quality of life. Recent studies suggest that epilepsies can involve functional networks throughout the brain that can be identified using resting-state functional magnetic resonance imaging (fMRI). In this study, we aimed to determine whether FLE is associated with a distinct functional network brain states. Using dynamic functional connectivity analysis in combination with k-means clustering, we investigated dynamic connectivity patterns of the somatomotor network (SMN) and default mode network (DMN) of ten right-hemisphere and six left-hemisphere FLE patients, as well as nine healthy controls. We found two distinct states of rest for both the SMN and DMN: a high connectivity state and a lower, more variable connectivity state that was often specific to individual patients. Both FLE groups showed reduced overall connectivity compared to controls, with the greatest differences emerging during the low connectivity state. Right FLE patients and controls exhibited relatively uniform reductions, whereas left FLE patients showed spatially specific disruptions, including reduced lateral-to-medial SMN connectivity and decreased connectivity in posterior and left-lateralized DMN regions. Our findings suggest that dynamic connectivity analysis can uncover the temporal complexity and patient-specific nature of brain network disruption in FLE, supporting the development of personalized diagnostic and treatment strategies. Further research with larger cohorts is necessary to validate these results and explore additional factors affecting brain functional connectivity.

PMID:41050945 | PMC:PMC12489773 | DOI:10.1016/j.ynirp.2025.100278

Neuroimage Rep. 2025 Jun 25;5(3):100276. doi: 10.1016/j.ynirp.2025.100276. eCollection 2025 Sep.

ABSTRACT

Functional Near-Infrared Spectroscopy (fNIRS) is an emerging neurotechnology that has several advantages over fMRI, but questions remain about factors that affect data quality and activity in stroke survivors. We examined the effect of protocol factors (Aim 1) and participant characteristics (Aim 2) on raw fNIRS signal quality and tested associations between quality control metrics and brain activity and connectivity (Aim 3) in a sample of 107 individuals with a history of left or right hemisphere stroke. Participants completed tasks that varied by cognitive and motor speech demands (from low to high): Resting State, Discourse Comprehension, and Picture Naming. Scalp-coupling indices, peak spectral power values, and number of bad channels from each task were extracted from the Quality Testing of Near Infrared Scans (QT-NIRS) toolbox (Montero-Hernandez and Pollonini, 2020) and used to index raw data quality. Data quality did not vary by session location or protocol experience, but all data quality metrics from Picture Naming were significantly lower than those from the other tasks. fNIRS signals were generally worse for Black women compared to Black men and White individuals regardless of gender. No significant associations between the raw fNIRS signal quality and Resting State functional connectivity were found. However, relative changes in Picture Naming hemoglobin concentrations were associated with scalp-coupling indices for certain channels. These results highlight the need for careful data preprocessing of already collected data and a systematic approach in future studies to mitigate inherent biases of optical instruments, thereby enhancing the inclusion of underrepresented groups in neuroscience research.

PMID:41050942 | PMC:PMC12489784 | DOI:10.1016/j.ynirp.2025.100276

Proc IEEE Int Symp Biomed Imaging. 2025 Apr;2025:10.1109/isbi60581.2025.10980810. doi: 10.1109/isbi60581.2025.10980810. Epub 2025 May 12.

ABSTRACT

Predicting the development of functional connectivity (FC) derived from resting-state functional MRI is pivotal for elucidating the intrinsic brain functional organization and modeling its dynamic development during infancy. Existing deep learning methods typically predict FC at a target timepoint from each available FC independently, yielding inconsistent predictions and overlooking longitudinal dependencies, which introduce ambiguity in practical applications. Furthermore, the scarcity and irregular distribution of longitudinal rs-fMRI data pose significant challenges in accurately predicting and delineating the trajectories of early brain functional development. To address these issues, we propose a novel Triplet Cycle-Consistent Masked Autoencoder (TC-MAE) for the trajectory prediction of the development of infant FC. Our TC-MAE has the capability to traverse FC over an extended period, extract unique individual characteristics, and predict target FC at any given age in infancy with longitudinal consistency. Extensive experiments on 368 longitudinal infant rs-fMRI scans demonstrate the superior performance of the proposed method in longitudinal FC prediction compared with state-of-the-art approaches.

PMID:41050556 | PMC:PMC12490125 | DOI:10.1109/isbi60581.2025.10980810

Proc IEEE Int Symp Biomed Imaging. 2025 Apr;2025:10.1109/isbi60581.2025.10981047. doi: 10.1109/isbi60581.2025.10981047. Epub 2025 May 12.

ABSTRACT

How to harmonize site effects is a fundamental challenge in modern multi-site neuroimaging studies. Although many statistical models and deep learning methods have been proposed to mitigate site effects while preserving biological characteristics, harmonization schemes for multi-site resting-state functional magnetic resonance imaging (rs-fMRI), particularly for functional connectivity (FC), remain undeveloped. Moreover, statistical models, though effective for region-level data, are inherently unsuitable for capturing complex, nonlinear mappings required for FC harmonization. To address these issues, we develop a novel, flexible deep learning method, Mamba-based Residual Generative adversarial network (MR-GAN), to harmonize multi-site functional connectivities. Our method leverages the Mamba Block, which has been proven effective in traditional visual tasks, to define FC-specified sequential patterns and integrate them with a multi-task residual GAN to harmonize multi-site FC data. Experiments on 939 infant rs-fMRI scans from four sites demonstrate the superior performance of the proposed method in harmonization compared to other approaches.

PMID:41050555 | PMC:PMC12490067 | DOI:10.1109/isbi60581.2025.10981047

Clin Transl Sci. 2025 Oct;18(10):e70372. doi: 10.1111/cts.70372.

ABSTRACT

Although extensive research has linked education to the Stroop effect, the neural mechanisms by which higher education influences Stroop performance in non-demented older adults remain unclear. This study investigated this relationship in 126 older adults from Qingdao, stratified into higher education (> 12 years) and non-higher education (≤ 12 years) groups. Demographic data and Stroop performance were collected using a 50-item Stroop Color-Word Test (SCWT), yielding measures of completion time, correct responses, score-time ratio (efficiency), and time interference score (TI). Resting-state fMRI (rs-fMRI) was performed, and neural activity was assessed via amplitude of low-frequency fluctuations (ALFF) to identify regions of interest (ROIs). Multivariable regression models examined associations between education and Stroop outcomes, followed by correlation analyses between ROIs and performance. Bootstrap mediation analysis (5000 resamples) tested whether ROIs mediated the education-Stroop relationship. Results showed that higher education was significantly associated with better Stroop performance-shorter completion time, higher efficiency, and lower TI-after full adjustment (all p < 0.05). Rs-fMRI revealed greater ALFF in the right frontal eye field (FEF), right dorsolateral prefrontal cortex (DLPFC), and left dorsal anterior cingulate cortex (dACC) in the higher education group. These regions correlated negatively with completion time and TI, and positively with efficiency. Mediation analyses confirmed that right FEF, right DLPFC, and the combined ROIs significantly mediated the effects of higher education on Stroop performance. In conclusion, higher education may enhance Stroop performance in non-demented older adults by modulating resting-state neural activity in key cognitive control regions.

PMID:41046460 | PMC:PMC12497356 | DOI:10.1111/cts.70372

Radiol Med. 2025 Oct 4. doi: 10.1007/s11547-025-02079-8. Online ahead of print.

ABSTRACT

PURPOSE: Rotator cuff injury (RCI) is a prevalent cause of shoulder disability, with emerging evidence implicating localized inflammatory cascades as key mediators of nociceptive signaling. Recent studies suggest that preoperative central sensitization induced by exposure to inflammation serves as a predictor of persistent pain following surgery at one-year follow-up. However, the underlying mechanism between peripheral inflammation, central pain processing, and postsurgical pain remains poorly characterized in RCI. Therefore, we aim to characterize pain-elicited brain responses and identify brain mediators of pain hypersensitivity in RCI patients.

MATERIALS AND METHODS: Utilizing a case-control design, twenty-eight patients with right/bilateral RCI and twenty healthy controls underwent functional MRI during pressure noxious stimuli, with pain intensity quantified via the visual analog scale. Comprehensive analyses of preoperative resting-state fMRI, serum cytokine profiles, and postoperative neuroimaging were conducted in RCI patients.

RESULTS: We found significantly higher level of pain sensitivity and IL-6 concentrations in RCI patients compared to controls. RCI patients exhibited higher activation within the left primary somatosensory cortex (S1), which mediated the relationship between IL-6 levels and pain sensitivity. Notably, preoperative S1 amplitude of low-frequency fluctuations (ALFF) exhibited a strong positive correlation with IL-6 concentrations (r = 0.62) and served as a robust predictor of postoperative pain reduction. These findings establish left S1 hyperactivation as a neuroplastic hub integrating peripheral inflammatory signaling (IL-6 elevation) and central pain sensitization in RCI.

CONCLUSION: The observed preoperative associations between S1 function, cytokine profiles, and postoperative pain resolution provide translational evidence for S1 as a predictive biomarker of pain chronification risk.

PMID:41045353 | DOI:10.1007/s11547-025-02079-8

Eur J Neurosci. 2025 Oct;62(7):e70271. doi: 10.1111/ejn.70271.

ABSTRACT

Depressive symptoms are commonly observed in stress-related psychiatric disorders, such as major depressive disorder (MDD) and posttraumatic stress disorder (PTSD). To date, emerging evidence from behavior and psychology suggests the possibility of underlying neurobiological mechanisms in transdiagnostic depression. This study aims to identify predictive signatures of depression severity across MDD and PTSD using a whole-brain connectivity machine learning analysis based on resting-state functional magnetic resonance imaging (rs-fMRI). Patients with MDD (n = 84) and PTSD (n = 65), all medication-free at the time of enrollment, underwent rs-fMRI scans along with a battery of clinical assessments. Using a multivariate machine learning approach, we applied sparse connectome predictive modeling to identify a functional connectivity signature that predicts individual depression severity, as assessed by Hamilton Depression Rating Scale-17 items. The cross-validated model explained 42% of the variance in depression severity across MDD and PTSD. The identified connectome signature predominantly involved regions in the fronto-limbic circuit (e.g., middle frontal gyrus and temporal pole), subcortical areas (e.g., hippocampal, caudate, and brainstem), and the cerebellum. Our findings highlight diffuse whole-brain dysfunction patterns associated with depressive symptom severity, emphasizing the importance of transdiagnostic research in understanding the neurobiological mechanisms underlying key clinical features across disorders.

PMID:41045096 | DOI:10.1111/ejn.70271

J Neurochem. 2025 Oct;169(10):e70217. doi: 10.1111/jnc.70217.

ABSTRACT

Brain's high energy demands require abundant production of ATP from glucose oxidation, mandating coupling between neural activity and nutrient supply. Understanding how neural activity augments blood flow (CBF) to support metabolism of glucose (CMRglc) and oxygen (CMRO2) can help unravel mysteries of neurovascular and neurometabolic couplings underlying functional MRI (fMRI) with blood oxygenation level-dependent (BOLD) contrast. Key to this enigma is oxygen extraction fraction (OEF). Fundamentally, OEF is defined by flow-metabolism (i.e., CBF-CMRO2) coupling generating mitochondrial ATP to signify limits of hypoxia and ischemia. However, to fully account for observed CBF-CMRO2 coupling, the OEF must include a term for oxygen diffusivity (DO2) that is regulated by rheological properties of blood. BOLD contrast depends on intravoxel spin dephasing of tissue water protons due to paramagnetic fields generated by deoxyhemoglobin. During augmented neural activity, if CBF increases more than CMRO2, then deoxyhemoglobin (paramagnetic) is replaced by perfusing oxyhemoglobin (diamagnetic) to increase BOLD signal. Calibrated fMRI converts BOLD contrast into OEF according to the deoxyhemoglobin dilution model. Agreement across these OEF models (i.e., OEF trifecta) authenticates calibrated fMRI, both gas-based and gas-free methods. CMRO2 by gas-free calibrated fMRI easily and reproducibly tracks neural activity, while combining it with CMRglc can also reveal aerobic glycolysis. In summary, there is translational potential of gas-free calibrated fMRI for metabolic imaging in the resting and stimulated brain, from neurodegeneration to neurological disorders.

PMID:41044817 | DOI:10.1111/jnc.70217