Most recent paper

Neuroimage. 2025 Oct 1;321:121502. doi: 10.1016/j.neuroimage.2025.121502. Online ahead of print.

ABSTRACT

Resting-state functional MRI (fMRI) signals capture physiological processes, including systemic low-frequency oscillations (LFOs), respiration, and cardiac pulsations. These physiological oscillations-often treated as noise in functional connectivity analysis-reflect fundamental aspects of brain physiology and have recently been recognized as key drivers of brain waste clearance. However, these critical physiological signals are obscured in fMRI data due to slow sampling rates (typical repetition time (TR) > 0.8 s), which cause cardiac signal to alias into lower frequencies. To resolve physiological signals in fMRI datasets, we leveraged fast cross-slice sampling within each TR to hypersample the fMRI signal. A key novelty of this study is the development of a region-specific hypersampling approach, called HyPER (Hypersampling for Physiological signal Extraction in a Region-specific manner). HyPER enhances temporal resolution within coherently pulsating vascular and tissue compartments, including the major cerebral arteries, the superior sagittal sinus (SSS), gray matter (GM), and white matter (WM). This study is structured in three parts: (1) We developed and validated the HyPER approach using fast fMRI from a local dataset in four regions of interest: the major cerebral arteries, SSS, GM, and WM. (2) We applied this approach to the publicly available Human Connectome Project-Aging (HCP-A) dataset (ages 36-90 years), increasing the resolvable frequency by ninefold-from 0.625 Hz to 5.625 Hz-enabling clear separation of cardiac, respiration, and LFO oscillations. (3) We investigated how brain physiological pulsations change with age. Our findings revealed an age-related increase in cardiac and respiratory pulsations across all brain regions, likely reflecting an increased vessel stiffness and reduced dampening of high-frequency pulsations along the vascular network. In contrast, LFO pulsations generally declined with age, suggesting reduced vasomotion in the older brain. In summary, we demonstrated the feasibility and reliability of a region-specific hypersampling technique to resolve physiological pulsations in fMRI. This method can be broadly applied to existing fMRI datasets to uncover hidden physiological pulsations and advance our understanding of brain physiology and disease-related alterations.

PMID:41043798 | DOI:10.1016/j.neuroimage.2025.121502

Brain Res Bull. 2025 Oct 1:111563. doi: 10.1016/j.brainresbull.2025.111563. Online ahead of print.

ABSTRACT

This study explored the effects of 36-hour acute sleep deprivation on the functional connectivity of auditory-related brain regions in healthy young males, examining its associations with alertness and emotional states. Sixty participants were assessed before and after sleep deprivation using psychomotor vigilance tasks, sleepiness scales, mood scales, and resting-state fMRI. The findings indicated significant changes in the functional connectivity of auditory-related brain regions, involving multiple cognitive, emotional, and motor areas. Further correlation analysis revealed a complex relationship between auditory-related brain regions and alertness, sleepiness, and mood. This study provides new evidence on how sleep deprivation influences auditory-related brain function.

PMID:41043695 | DOI:10.1016/j.brainresbull.2025.111563

Biol Psychiatry. 2025 Oct 1:S0006-3223(25)01487-8. doi: 10.1016/j.biopsych.2025.09.012. Online ahead of print.

ABSTRACT

Functional magnetic resonance imaging (fMRI) data are often used to inform individual differences in cognitive, behavioral, and psychiatric phenotypes. These so-called "brain-behavior" association studies come in many flavors and are increasingly the focus of investigations utilizing large population neuroscience datasets. Still, many open questions surrounding the utility of task and resting state fMRI for modelling brain-behavior relationships remain, including the feasibility of conducting these investigations in developmental cohorts. With the growing availability of large neurodevelopmental datasets such as that provided by the Adolescent Brain Cognitive Development (ABCD) Study, we are now able to conduct well-powered analyses using large samples of longitudinal neuroimaging data collected from diverse populations of youth. Here we provide a high-level review of current controversies and challenges in this growing subfield of neuroscience, highlighting examples where task fMRI data and resting state fMRI data - either in isolation or combined - have yielded significant insights into brain-behavior associations. Challenges include issues related to measurement noise, appropriate estimation of effect sizes, and limits to generalizability due to insufficient diversity of samples. Innovative solutions involving advanced MRI data acquisition protocols, application of multivariate analysis methods, and more robust consideration of phenotypic complexity are reviewed. We propose that additional future directions for developmental cognitive neuroscience should include more reliable behavioral measures, multimodal neuroimaging brain-behavior studies, and greater consideration of environmental and other contextual influences on brain-behavior associations.

PMID:41043534 | DOI:10.1016/j.biopsych.2025.09.012

medRxiv [Preprint]. 2025 Sep 25:2025.09.23.25336175. doi: 10.1101/2025.09.23.25336175.

ABSTRACT

Identifying robust neuroimaging biomarkers for Alzheimer's disease (AD) and mild cognitive impairment (MCI) is essential for early diagnosis and intervention. In this study, we introduce a novel, fully automated, guided dynamic functional connectivity (dFNC) framework to extract multiple dynamic measures for distinguishing MCI/AD from cognitively normal (CN) individuals. Resting-state fMRI data were used to extract subject-specific brain networks via spatially constrained independent component analysis (scICA), using a multi-objective optimization framework to ensure alignment with known functional networks while preserving individual variability. Using these components, dFNC was computed through a sliding-window approach. ICA was then applied to the concatenated dFNC matrices from the UK Biobank (UKBB) dataset to identify five canonical brain states, each representing a replicable, independent pattern of connectivity. These states served as biologically informed priors in a state-constrained ICA (St-cICA), which was applied to each subject in the combined OASIS-3 and ADNI datasets to guide individual-level decomposition and ensure interpretable connectivity states guided by state priors derived from the normative UKBB sample. St-cICA extracted subject-specific dFNC features and associated weighted timecourses. To characterize dFNC patterns, we computed metrics from the most strongly expressed (primary) state and introduce estimation of the second-most expressed (secondary) state at each timepoint, including dwell time, occupancy rate, and transition probabilities. Group comparisons using two-sample t-tests revealed widespread and significant alterations in AD/MCI compared to CN individuals. AD/MCI participants exhibited higher dwell times and increased self-transitions, indicating reduced neural flexibility and a tendency to remain in specific connectivity states. In contrast, CN individuals showed more diverse and recurrent transitions, reflecting greater adaptability. Secondary transitions revealed widespread selective switching in CN, whereas AD/MCI showed reduced cross-state engagement. A classification model trained on 6,960 dynamic features achieved strong performance in distinguishing AD/MCI from CN (mean AUC ≈ 0.85). These findings highlight the potential of guided dFNC as a biomarker framework for early-stage AD detection using resting-state fMRI.

PMID:41040719 | PMC:PMC12485992 | DOI:10.1101/2025.09.23.25336175

bioRxiv [Preprint]. 2025 Sep 25:2025.09.23.678044. doi: 10.1101/2025.09.23.678044.

ABSTRACT

Mouse models are an essential tool for understanding behavior and disease states in neuroscience research. While genetic and sex-specific effects have been reported in many neurodegenerative and psychiatric illnesses, these factors may also alter baseline neuroanatomical features of mice. This raises the question of whether the observed changes are related to the disease being studied (i.e., pathological differences) or if there are baseline strain or sex differences that may potentially predispose animals to different responses. Over the past decade, tremendous effort has been made in mapping neural architecture at various scales; however, the complex relationships including identifying genetic and sex-specific differences in brain structure and function remain understudied. To bridge this gap, we used C57BL/6J and DBA/2J mice, two of the most widely used inbred mouse strains in neuroscience research, to investigate strain and sex-specific features of the brain connectome in awake animals using magnetic resonance imaging (MRI). By combining resting-state fMRI and diffusion MRI, we found that the motor, sensory, limbic, and salience networks exhibit significant differences in both functional and structural domains between C57BL/6J and DBA/2J mice. Further, functional and structural properties of the brain were significantly correlated in both strains. Our results underscore the importance of considering these baseline differences when interpreting the brain-behavior interactions in mouse models of human disorders.

PMID:41040314 | PMC:PMC12485708 | DOI:10.1101/2025.09.23.678044

bioRxiv [Preprint]. 2025 Sep 25:2025.09.24.678309. doi: 10.1101/2025.09.24.678309.

ABSTRACT

Dynamic coordination of metabolic demand across brain networks supports emerging cognitive abilities and may drive overall cognitive development, yet how these dynamics vary by sex and relate to cognition in late childhood remains unclear. Using resting-state fMRI from 2,000 healthy 9- to 11-year-olds in the ABCD study, we applied time-resolved dynamic time warping to quantify amplitude mismatches, a proxy of relative energy demand across brain intrinsic networks. Clustering revealed three recurring states: convergent (globally balanced), divergent (imbalanced), and mixed (intermediate). Females spent engaged more with the flexible mixed state, whereas males lingered longer in convergent and divergent states. Across the cohort, better performance on cognitive flexibility, processing speed, and long-term memory tasks correlated with greater overall time in the mixed state and with higher transition rates, but with shorter dwell in any single state. These findings indicate that neural flexibility, rather than prolonged stability, supports cognition during late childhood and that sex differences in dynamic energy coordination emerge well before adolescence.

PMID:41040180 | PMC:PMC12485794 | DOI:10.1101/2025.09.24.678309

BMC Psychiatry. 2025 Oct 2;25(1):924. doi: 10.1186/s12888-025-07351-9.

ABSTRACT

BACKGROUND: Thalamic structural and functional abnormalities in major depressive disorder (MDD) are linked to impairments in diverse cognitive and emotional functions via the thalamo-cortical circuit. Given the constraints of temporal and spatial factors on information exchange, investigating frequency-specific effective connectivity (EC) is essential for elucidating the abnormal mechanisms of spatiotemporal information communication in patients with MDD.

METHOD: We employed a large-scale, multicenter resting-state functional magnetic resonance imaging (fMRI) dataset comprising individuals with MDD and matched healthy controls. Frequency-specific EC between the thalamic subregions and cortical/subcortical regions was assessed using spectral Granger causality in four frequency bands: slow-5 (0.01–0.027 Hz), slow-4 (0.027–0.073 Hz), slow-3 (0.073–0.185 Hz), and a classic frequency range (0.01–0.08 Hz). Support vector regression (SVR) models were employed to evaluate the predictive value of altered EC for clinical symptom scores.

RESULTS: Individuals with MDD exhibited significant and frequency-dependent abnormalities in thalamocortical and thalamo-subcortical EC, with the most pronounced disruptions observed in the slow-5 band. These abnormalities originate from the specific thalamic subregions and extend to cortical and subcortical regions. Among the frequency bands analyzed, EC alterations in the slow-5 band showed the strongest association with clinical severity and yielded the highest predictive performance in SVR models.

CONCLUSIONS: Frequency-specific EC disruptions, particularly within the slow-5 band, may reflect fundamental spatiotemporal communication deficits in MDD. These findings highlight the slow-5 thalamocortical and thalamo-subcortical EC as a potential neurobiological marker for diagnosis and a target for treatment strategies in MDD.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12888-025-07351-9.

PMID:41039494 | PMC:PMC12490111 | DOI:10.1186/s12888-025-07351-9

Sci Rep. 2025 Oct 2;15(1):34415. doi: 10.1038/s41598-025-17431-1.

ABSTRACT

Executive function plays an important role throughout an individual's life, and current research has shown that physical activity is an effective way to promote the development of executive function. Further research into the mechanisms in the brain that promote executive function has focused on populations with diseases, and no consistent conclusions have been drawn for healthy populations. Moreover, the differential effects of different exercise doses and sample characteristics on executive function brain activation remain unclear. In this study, we used an activation likelihood estimation (ALE) meta-analysis integrating 20 task-based and resting-state functional magnetic resonance imaging (fMRI) studies to investigate the mechanisms in the brain underlying the effects of different exercise interventions on executive functions in healthy populations. The results showed that exercise interventions significantly altered brain activation patterns during cognitive tasks, particularly in the frontal, precuneus, thalamus and cingulate regions. We examined exercise interventions in various sub-groups, showing patterns of effects in different age groups, exercise types and exercise durations.

PMID:41039062 | PMC:PMC12491555 | DOI:10.1038/s41598-025-17431-1

Behav Brain Res. 2025 Sep 30:115859. doi: 10.1016/j.bbr.2025.115859. Online ahead of print.

ABSTRACT

Social comparison is a crucial process for individuals engaging in social interactions. It exhibits a dual nature, capable of producing both positive and negative effects. Therefore, investigating the neural processing mechanisms underlying social comparison is of great significance. In this study, resting-state functional magnetic resonance imaging (rs-fMRI) was employed to analyze the functional connectivity of the default mode network (DMN) related to social comparison tendency. The results showed that stronger functional connectivity between the DMN and several cortical regions-including the supplementary motor area, inferior parietal lobule, cingulate gyrus, angular gyrus, calcarine sulcus, and superior frontal gyrus-was significantly correlated with higher levels of opinion comparison. In contrast, no significant correlation was found between ability comparison and DMN-based whole-brain functional connectivity. Furthermore, a dissociation between opinion and ability comparison was observed, and gender was identified as a moderating factor in the neural mechanisms of opinion comparison. These findings emphasize a unique relationship between opinion-based social comparison and DMN connectivity, offering novel neural insights into the processes underlying social comparison.

PMID:41038323 | DOI:10.1016/j.bbr.2025.115859

Biol Psychiatry Cogn Neurosci Neuroimaging. 2025 Sep 30:S2451-9022(25)00298-8. doi: 10.1016/j.bpsc.2025.09.020. Online ahead of print.

ABSTRACT

BACKGROUND: Abnormalities in the functional connectivity of large-scale brain networks, including the default mode (DMN), salience (SN), fronto-parietal (FPN), and limbic networks, have been implicated in repetitive negative thinking (RNT), a construct characterized by persistent and intrusive thoughts. However, the potential of these large-scale network abnormalities for predicting RNT in daily life remains underexplored.

METHODS: We leveraged the brain-based graph-theoretical predictive modeling (GPM) to predict daily-life RNT in 54 individuals. Functional MRI data were acquired during: (i) resting-state and (ii) an RNT-induced state. RNT severity and its momentary fluctuations were assessed using ecological momentary assessments (EMA).

RESULTS: The GPM identified key functional organizational properties of the DMN, FPN, and limbic networks that differentially predicted the severity and fluctuations of RNT and its specific clinical features (intrusiveness, repetitiveness, RNT-related anxiety). Specifically, the centrality of the medial prefrontal cortex (DMN) predicted EMA fluctuations of intrusiveness and severity of anxiety. Conversely, the strength and centrality of the orbitofrontal cortex (part of the limbic network) predicted EMA fluctuations of repetitiveness, and the segregation of the temporal pole (limbic network) predicted overall severity of RNT. Last, fluctuations in total RNT were predicted from the strength of the orbitofrontal cortex (limbic network) and segregation of the posterior mid-cingulate cortex (FPN). Notably, RNT was better predicted from daily-life prospective assessments than from lab-assessed clinical questionnaires.

CONCLUSIONS: These findings highlight the utility of the GPM for predicting the emergence of daily-life RNT and suggest specific network-level attributes (e.g., centrality, segregation) underlying RNT and its clinical features.

PMID:41038317 | DOI:10.1016/j.bpsc.2025.09.020

Cell Rep Med. 2025 Oct 1:102402. doi: 10.1016/j.xcrm.2025.102402. Online ahead of print.

ABSTRACT

Repetitive transcranial magnetic stimulation (rTMS) is approved for major depressive disorder (MDD), but it is limited by variable efficacy. Here, we examine antidepressant effects of our sequential dorsolateral prefrontal cortex (dlPFC)-dorsomedial prefrontal cortex (dmPFC) accelerated rTMS protocol, which includes a 4-day treatment with 4 sessions per day. At week 4, the Montgomery-Åsberg Depression Rating Scale (MADRS) reduction is significantly larger in the active group, and critical, significant differences were apparent on day 4. For active and sham-controlled groups, respectively, response rates are 57.69% and 23.08%, and remission rates are 38.46% and 15.38%. Of responders, over 85% remain in remission over 6 months. Resting-state fMRI shows dissociable symptom improvement associated with increased dlPFC-frontoparietal and decreased dmPFC-amygdalo-subcallosal cingulate functional connectivity. We highlight a cost-efficient generalizable rTMS approach targeting differential networks in MDD, which shows rapid and sustained antidepressant effects with a relatively small number of pulses and minimal treatment duration. The study is registered with ChiCTR (ChiCTR2100046042).

PMID:41038161 | DOI:10.1016/j.xcrm.2025.102402

JMIR Res Protoc. 2025 Oct 2;14:e77931. doi: 10.2196/77931.

ABSTRACT

BACKGROUND: Poststroke cognitive impairment (PSCI) is a chronic form of poststroke cognitive dysfunction that affects approximately one-third of the survivors of stroke. PSCI significantly increases the rates of mortality and functional disabilities, such as limitations in motor function, speech, and activities of daily living. Therefore, effective treatments are needed for patients with PSCI. Repetitive transcranial magnetic stimulation (rTMS) has been shown to exert beneficial behavioral effects in patients with PSCI. More importantly, a limited number of neuroimaging studies with small sample sizes have reported the beneficial effects of rTMS on brain plasticity and its reciprocal influence on cognitive and behavioral performance. Resting-state functional magnetic resonance imaging (rs-fMRI) has been widely used to study changes in brain activity, but there is no consensus regarding which brain regions play pivotal roles in rTMS for patients with PSCI.

OBJECTIVE: This study aims to explore the therapeutic effects of rTMS on changes in the brain activity of patients with PSCI, thereby providing robust evidence to elucidate its neuroimaging mechanisms.

METHODS: In this meta-analysis, we will systematically search the PubMed, Embase, Cochrane Library, Web of Science, China Biology Medicine, and China National Knowledge Infrastructure databases, VIP Chinese Science and Technology Periodical Database, and the China WanFang Database up to December 2024 to identify randomized controlled trials comparing active rTMS with sham stimulation conditions or conventional control conditions in patients with PSCI. The primary outcomes will include the amplitude of low-frequency fluctuation, fractional amplitude of low-frequency fluctuation, regional homogeneity, and functional connectivity across the whole brain. The secondary outcomes will include the Montreal Cognitive Assessment and Mini-Mental State Examination scores. Statistical analyses will be conducted via Review Manager (version 5.4), Seed-based d Mapping with Permutation of Subject Images (version 6.23), and Stata (version 18.0) software to assess study quality, evaluate the risk of bias, and analyze the outcome measures.

RESULTS: The study will offer a comprehensive analysis of the available evidence on the use of rTMS to improve cognitive impairment in patients with stroke based on rs-fMRI findings. The meta-analysis will be conducted from July 2024 to April 2026, following this predefined protocol. The process encompasses database searching and study screening (to be concluded by October 2025), data extraction and synthesis (to be completed by December 2025), and subsequent manuscript preparation and submission (anticipated by April 2026).

CONCLUSIONS: This meta-analysis will provide insights into the therapeutic potential of rTMS to improve cognitive impairment in patients with stroke. It will also highlight the strengths and limitations of the existing literature and suggest directions for future research. Ultimately, our study may aid future clinical decision-making concerning PSCI rehabilitation programs and provide evidence-based medical insights into the neuroimaging mechanisms of rTMS treatment for PSCI.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/77931.

PMID:41037808 | DOI:10.2196/77931

Imaging Neurosci (Camb). 2025 Sep 29;3:IMAG.a.907. doi: 10.1162/IMAG.a.907. eCollection 2025.

ABSTRACT

Both meditation and psychedelics are widely studied for their therapeutic potential in mental health. Recent research suggests potential synergies between mindfulness practice and psychedelics, though empirical studies have primarily focused on psilocybin. This study investigates the distinct and combined effects of mindfulness practice and an ayahuasca-inspired formulation containing N,N-dimethyltryptamine (DMT) and harmine on brain functional connectivity (FC), with implications for advancing clinical interventions. In this double-blind, placebo-controlled pharmaco-functional magnetic resonance imaging (fMRI) study, 40 meditation practitioners participated in a 3-day meditation retreat. They were randomized to receive either placebo or buccal DMT-harmine (120 mg each) and underwent fMRI scans 2 days before and after administration. Neural changes were assessed using multiple connectivity metrics, including within- and between-network connectivity, network and global connectivity, and cortical gradient analyses. Within-group changes showed that meditators in the placebo group exhibited increased network segregation across several resting-state networks, while the DMT-harmine group showed increased FC within the visual network (VIS) and between VIS and attention networks. Between-group differences similarly showed increased FC between VIS and the salience network (SAL) in the DMT-harmine group compared with placebo post-retreat. No evidence of prolonged cortical gradient disruption, which is characteristic of acute psychedelic action, was observed. This suggests a return to typical brain organization shortly after the experience. These findings reveal distinct neural mechanisms underlying meditation and psychedelic-augmented meditation. While meditation alone reduced FC between networks, DMT-harmine increased within- and between-network connectivity. Given the potential of meditation and psychedelics for improving mental health, further exploration of their synergistic potential in clinical contexts is warranted. This study advances the understanding of how psychedelics and mindfulness practice shape brain function, offering insights into their complementary roles in emotional and psychological well-being.

PMID:41035622 | PMC:PMC12479382 | DOI:10.1162/IMAG.a.907

Neuroimage. 2025 Sep 29:121418. doi: 10.1016/j.neuroimage.2025.121418. Online ahead of print.

ABSTRACT

Scalp-recorded electroencephalography (EEG) is thought to be driven by both local and global oscillations dependent on the cognitive state and task of the individual. However, many EEG studies assume that the activity is local, especially when inverse modeling EEG activity. In this work, we show that a simple model of purely macroscopic connections derived from biologically plausible distributions of long-range axon delays can drive many of the traditional features of scalp-recorded EEG dynamics. All that is required is a simple linear model of time delays in a linear vector autoregressive framework with a few parameters. We make several simplifying modeling assumptions in the model: only long-range excitatory connections are included, local activity is treated as stochastic noise, and nonlinear synaptic dynamics are omitted. As a proof of concept, we restrict the model to five broad brain regions (frontal, parietal, occipital, temporal, thalamic) and model resting state EEG with no external input. We show how this simple connection model is derived from theoretical principles of synaptic activity. The model is able to replicate many features of real EEG data, including resting-state alpha power and coherence (8-13 Hz). We show that model parameters can also be informed by empirical work on structural connectivity, axon diameter estimation, and functional connectivity of fMRI BOLD measures. However, some features of the macroscopic simulations are not ideal as a model for all features of resting EEG, such as high coherence in low-frequencies in the simulation as opposed to real data. Overall, the results support the explanation of many classical EEG findings in terms of macroscopic network behavior as opposed to local activity.

PMID:41033379 | DOI:10.1016/j.neuroimage.2025.121418

IEEE Trans Neural Syst Rehabil Eng. 2025 Oct 1;PP. doi: 10.1109/TNSRE.2025.3616524. Online ahead of print.

ABSTRACT

Robotic-assisted therapy (RAT) represents a promising adjunctive rehabilitation technology, however, its underlying neuroplastic mechanisms remain incompletely characterized. We aimed to elucidate the neuroplastic reorganization induced by RAT that mediates motor functional improvements in stroke survivors. Thirteen stroke survivors in the RAT group and 13 demographically/clinically matched in the conventional rehabilitation therapy (CRT) group underwent a 4-week rehabilitation intervention. Motor function was assessed using the Fugl-Meyer Assessment upper and lower extremity subscale (FMA-UE, FMA-LE) and modified Barthel Index (MBI) at pre- and post-intervention timepoints. Concurrently, resting-state functional MRI (rs-fMRI) data were acquired for amplitude of low-frequency fluctuation (ALFF) computation and seed-based functional connectivity (FC) analysis. Repeated measures ANOVA showed significant Group × Time interactions for both FMA-UE and FMA-LE (F(1,24) = 4.913, p＜0.05; F(1,24) = 4.778, p＜ 0.05). All motor outcomes displayed strong main effects of Time (all p < 0.001). Post hoc simple effects tests revealed significant within group gains in FMA UE for both RAT and CRT and in FMA LE for RAT only, with no between group differences at any single time point. Neuroimaging showed that increases in ALFF within the ipsilesional precentral gyrus correlated with improvements in both FMA-UE and FMA-LE. Compared with CRT, RAT strengthened interhemispheric functional connectivity between the precentral and postcentral gyri and between the precentral and supramarginal gyri. Together, these findings indicate that RAT promotes motor recovery by up regulating activity in the ipsilesional motor cortex and enhancing cross hemispheric sensorimotor integration, providing the direct evidence for mechanism of post stroke neural restitution.

PMID:41032542 | DOI:10.1109/TNSRE.2025.3616524

J Pain Res. 2025 Sep 24;18:4975-4988. doi: 10.2147/JPR.S540502. eCollection 2025.

ABSTRACT

Breast cancer is currently the most common malignant tumor, primarily affecting women, and it frequently leads to chronic pain that significantly impairs physical and mental health. Neuroimaging studies have demonstrated that breast cancer-related pain is associated with specific brain alterations, including changes in activation, connectivity, and structure of pain-processing regions. This review synthesizes findings on functional and structural brain changes related to chronic pain in breast cancer and compares them with non-cancer chronic pain patterns. By integrating recent evidence, it proposes a conceptual framework to advance the understanding of pain mechanisms and supports personalized pain management strategies to improve quality of life.

PMID:41030773 | PMC:PMC12477286 | DOI:10.2147/JPR.S540502

Brain Behav. 2025 Oct;15(10):e70899. doi: 10.1002/brb3.70899.

ABSTRACT

BACKGROUND: To explore the long-term efficacy and resting-state functional magnetic resonance imaging (fMRI) changes of lateral habenula nucleus (LHb) deep brain stimulation (DBS; LHb-DBS) for treatment-resistant bipolar disorder (TRBD).

METHODS: An 18-year-old woman with TRBD received bilateral LHb-DBS. We assessed changes in Hamilton Depression Scale-17 (HDRS-17), Bech-Rafaelsen Melancholia Scale (BRMS), Hamilton Anxiety Scale (HAMA), and Pittsburgh Sleep Quality Scale (PSQI) scores from preoperative baseline to postoperative continuous 24-month follow-up. Brain activity and resting-state functional connectivity (rsFC) were examined off-stimulation at 0.6 and 15 months post-LHb-DBS. Overall improvement and adverse events were analyzed.

RESULTS: Continuous 24-month follow-up showed average improvements from baseline of 65.33%, 54.90%, 63.33%, and 48.72% for HDRS-17, BRMS, HAMA, and PSQI scores, respectively. At the final follow-up, improvement was 96.00%, 88.24%, 84.85%, and 69.23%, respectively. Resting-state fMRI results revealed an increase in fractional amplitude of low-frequency fluctuations (fALFF) within the putamen, ventral tegmental area (VTA), and substantia nigra pars compacta (SNc) over 15 months of continuous bilateral LHb stimulation when DBS was off. From baseline to 15 months, fALFF in the putamen, VTA, and SNc increased by 1.68%, 6.36%, and 1.10%, respectively. Consistently reduction in rsFC was observed between the left nucleus accumbens (NAcc) and left hippocampus. Over the 15 months of continuous stimulation, rsFC decreased by 72% from baseline.

CONCLUSIONS: Long-term LHb-DBS can control symptoms and improve the quality of life in patients with TRBD. This may be attributed to an increase in fALFF in the putamen, VTA, and SNc, and a reduction in rsFC between the left NAcc and left hippocampus.

PMID:41030103 | PMC:PMC12484712 | DOI:10.1002/brb3.70899

BMC Psychiatry. 2025 Sep 30;25(1):895. doi: 10.1186/s12888-025-07331-z.

ABSTRACT

BACKGROUND: Non-suicidal self-injury (NSSI) addiction is prevalent among adolescents, but its underlying neural mechanisms remain unclear. This study aims to investigate the neural activity and functional connectivity characteristics associated with NSSI addiction using resting-state functional magnetic resonance imaging (rs-fMRI).

METHODS: A prospective collection of 62 adolescents was completed for this study, including 33 adolescents with self-injury behaviors and 29 age-, gender-, and education-matched healthy controls. The addiction component of the Ottawa Self-Injury Inventory (OSI) was used to assess the degree of NSSI addiction. Amplitude of low-frequency fluctuation (ALFF) analysis was employed to detect changes in local neural activity. Differential brain regions were considered regions of interests (ROIs). Whole-brain functional connectivity (FC) analysis based on ALFF was used to further explore potential changes in functional connections between ROIs and other brain areas in the NSSI group, and to analyze the relationship between these neural changes and addiction characteristics.

RESULTS: ALFF analysis revealed decreased ALFF values in the bilateral hippocampus and increased ALFF values in the right supplementary motor area of NSSI adolescents compared to healthy controls. Significantly reduced FC values was observed between the left hippocampus and the left precuneus, right middle temporal gyrus, and right inferior temporal gyrus, and between the right hippocampus and the right middle temporal gyrus. Additionally, increased FC values was observed between the left hippocampus and the left thalamus. Furthermore, ALFF values in the bilateral hippocampus were negatively correlated with the total score of addiction characteristics in NSSI adolescents.

CONCLUSIONS: This study highlights reduced local neural activity and functional connectivity in the bilateral hippocampus of NSSI adolescents, and demonstrates that these alterations are associated with heightened addictive features in self-injuring individuals.

TRIAL REGISTRATION: A study of positive psychological group interventions in adolescents with non-suicidal self-injury (registration date: 03/01/2024; registration number: ChiCTR2400079412).

PMID:41029257 | PMC:PMC12486709 | DOI:10.1186/s12888-025-07331-z

Addict Behav. 2025 Sep 12;172:108494. doi: 10.1016/j.addbeh.2025.108494. Online ahead of print.

ABSTRACT

BACKGROUND: Patients with internet gaming disorder (IGD) suffer from an imbalance of over-integrated and weakly dissociated functional brain networks. Approach bias modification training (ApBMt) has been used to correct patients' automatic approach biases to addictive stimuli; however, research exploring changes in brain network topology is limited.

METHODS: Seventy subjects were randomly assigned to the approach-avoidance task (AAT) group or the sham-AAT group, and 57 subjects (AAT, 30; sham-AAT, 27) completed the entire procedure, which included pretests, AAT/sham-AAT interventions, and posttests. Behavioral and resting-state fMRI data were collected before and after the tests. This study aimed to investigate the effects of ApBMt on topological changes in resting functional brain networks in patients with IGD and explore the relationship between these network changes and behavioral indicators of addiction severity.

RESULTS: Repeated-measures ANOVA of the behavioral data showed that the AAT group had significant score reductions after ApBMt. Imaging data revealed significant decreases in brain network over-integration and increases in segregation of the fronto-parietal network (FPN) and the cingulo-opercular network (CON). Additionally, a positive correlation was found between the post-pre difference in DSM-5 scores and the post-pre difference in nodal efficiency (Ne) in the anterior prefrontal cortex (aPFC).

CONCLUSIONS: The findings of this study demonstrate that ApBMt effectively reduces the severity of IGD, along with associated changes in brain network topology, such as enhanced segregation and decreased over-integration. However, it is important to highlight that the neurobiological changes observed are correlated with the reduction in IGD severity, but causality cannot be established. Further research is necessary to better understand the clinical potential of ApBMt in treating IGD, either as a stand-alone intervention or in combination with other therapeutic approaches.

PMID:41027144 | DOI:10.1016/j.addbeh.2025.108494

J Sick Cell Dis. 2025 Sep 18;2(1):yoaf031. doi: 10.1093/jscdis/yoaf031. eCollection 2025.

ABSTRACT

BACKGROUND: Adults with sickle cell disease (SCD) often experience cognitive deficits and chronic pain, but the cerebral mechanisms underlying these symptoms remain unclear. Elevated cerebral blood flow (CBF) is a compensatory response to anemia, yet its impact on brain function and perception is not well understood.

OBJECTIVE: To examine alterations in cerebral perfusion and resting-state brain function in adults with SCD and their associations with cognition and pain sensitivity.

METHODS: Seven adults with SCD and 3 healthy controls underwent arterial spin labeling (ASL) and resting-state functional MRI (rs-fMRI). Metrics included global/regional CBF, resting-state functional connectivity (rsFC), and amplitude of low-frequency fluctuations (ALFF). Participants completed NIH Toolbox fluid cognition tests and the Pain Sensitivity Questionnaire (PSQ).

RESULTS: SCD patients exhibited significantly higher global CBF (72.1 vs. 47.2 mL/100g/min; P = .04), reduced cortical zALFF (P = .0013), and elevated white-matter zALFF (P = .0023). They also showed resting-state network hyperconnectivity, with diminished anti-correlations between the default mode and salience networks. SCD participants scored lower on processing speed (P = .02) and reported higher pain sensitivity (PSQ total, P = .0040). Higher CBF was associated with slower cognitive performance but not directly with pain sensitivity. Exploratory mediation models suggested that altered brain activity may partially mediate this relationship.

CONCLUSIONS: Adults with SCD demonstrate cerebral hyperperfusion, disrupted functional connectivity, and altered spontaneous brain activity, which may contribute to cognitive slowing and heightened pain sensitivity. These findings highlight the need for further research into brain-targeted therapies in SCD.

PMID:41024864 | PMC:PMC12476913 | DOI:10.1093/jscdis/yoaf031