Most recent paper

Sci Data. 2026 Feb 4. doi: 10.1038/s41597-026-06734-1. Online ahead of print.

ABSTRACT

We present a new dataset consisting of functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) collected from 39 healthy adults in their twenties to forties while performing cognitive tasks (visual oddball and N-back tasks) in addition to resting state. These tasks took place both inside and outside an MR scanner (i.e., simultaneous EEG-fMRI and EEG-only, respectively), enabling direct comparisons across the different recording environments. Moreover, a subset of the participants was in two different MRI scanners, allowing for traveling-subject analyses. In both scanners, we used EEG caps equipped with carbon wire loops to measure motion and ballistocardiogram artifacts for their subsequent removal from raw EEG signals, resulting in a dataset of superior quality compared to previous studies. All the raw data are publicly available for facilitating multimodal neuroimaging research.

PMID:41639123 | DOI:10.1038/s41597-026-06734-1

Neuroimage. 2026 Feb 2:121772. doi: 10.1016/j.neuroimage.2026.121772. Online ahead of print.

ABSTRACT

OBJECTIVES: Chronic ankle instability (CAI) is not only associated with those peripheral neuromuscular impairments but also with the functional changes in the supraspinal regions. Nevertheless, the characteristics of the cortical elements in CAI remain poorly understood. This study aimed to examine the dynamics of resting-state BOLD and ankle-related functional performance in recreational athletes with CAI, as well as explore the associations between neural fluctuations and ankle functional performance.

METHODS: This cross-sectional design study recruited 82 participants, comprising 41 active recreational athletes with CAI (CAI group) and 41 active recreational athletes without CAI (Control group). Data on joint position sense, one-leg standing balance, and resting-state fMRI were collected from both groups. A two-sample t-test was used to determine the difference in amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo) between the two groups. Linear regression analysis evaluated the associations between functional performance and dynamics of resting-state BOLD in the two groups.

RESULTS: Compared with control group, athletes with CAI had lower ALFF values in the bilateral supplementary motor area and reduced ReHo values in the right precentral gyrus and postcentral gyrus, while higher ALFF and ReHo values in the right cerebellum. Moreover, athletes with CAI had lower fALFF values in the left superior frontal gyrus and the right superior frontal gyrus than controls. The sway velocities of center of pressure in the one-leg standing with eyes closed condition were negatively associated with ALFF and ReHo values in the right cerebellum cluster.

CONCLUSIONS: Athletes with severely right-sided CAI had different neural fluctuations compared with controls. Elevated ALFF and ReHo values in the right cerebellum cluster were associated with balance control, suggesting that high ipsilateral cerebellar activity and homogeneity may compensate for balance control in athletes with CAI.

PMID:41638415 | DOI:10.1016/j.neuroimage.2026.121772

Neuroimage. 2026 Feb 2:121769. doi: 10.1016/j.neuroimage.2026.121769. Online ahead of print.

ABSTRACT

Sleep deprivation (SD) significantly impacts brain function, particularly through disruption of the glymphatic system, an essential mechanism for cerebral metabolic waste clearance dependent on cerebrospinal fluid (CSF) dynamics. Recent advances link CSF flow to global brain activity, measurable via global blood-oxygenation-level-dependent (gBOLD) signals. However, how gBOLD-CSF coupling changes during prolonged wakefulness remains unclear. Using resting-state functional magnetic resonance imaging (rs-fMRI), we investigated how 36-hour sleep deprivation affects gBOLD-CSF coupling in healthy participants. We observed a significant transient increase in gBOLD-CSF coupling strength as sleep deprivation progressed, peaking after approximately 30 hours of wakefulness. Importantly, changes in coupling strength correlated quantitatively with heightened subjective sleep pressure but not with vigilance performance. Furthermore, SD induced a temporary phase shift in CSF signal timing relative to gBOLD, indicating disrupted temporal coordination. These results suggest that SD triggers both a transient enhancement and a temporal instability in neuro-fluid coupling, reflecting a biphasic modulation of brain-CSF coupling linked to glymphatic-related dynamics. Our findings reveal novel compensatory adjustments within the glymphatic system during prolonged wakefulness, advancing our understanding of the physiological underpinnings linking sleep loss, metabolic clearance, and brain function, with potential implications for cognitive health and neurodegenerative disease risk.

PMID:41638414 | DOI:10.1016/j.neuroimage.2026.121769

Brain Lang. 2026 Feb 3;275:105720. doi: 10.1016/j.bandl.2026.105720. Online ahead of print.

ABSTRACT

Speech disorders are highly prevalent among patients with Parkinson's disease (PD). Although insights into the neural substrates of these disorders have been achieved since the introduction of functional magnetic resonance imaging (fMRI), the evidence has never been analyzed altogether. This review aims to summarize and discuss the findings from the two most common approaches of fMRI: task-based and resting-state. We grouped the evidence into four statements: (i) speech disorders in patients with PD are linked with functional changes in the speech production network (SPN), (ii) PD alters the SPN even before the onset of speech disorders, (iii) levodopa have a discrete effect on the SPN functioning, and (iv) speech therapy in patients with PD can induce changes on the activity of the SPN. Limitations of current evidence and future directions in the field are also discussed.

PMID:41638063 | DOI:10.1016/j.bandl.2026.105720

Neurobiol Aging. 2026 Feb 1;161:64-72. doi: 10.1016/j.neurobiolaging.2026.01.008. Online ahead of print.

ABSTRACT

Alzheimer's disease (AD) pathology disrupts functional brain connectivity long before symptoms emerge. African Americans face elevated AD risk, yet underlying mechanisms remain unclear. Genetic risk differs by ancestry: APOE-ε4 strongly predicts late-onset AD in European ancestry, whereas ABCA7 rs115550680 confers substantial risk in African ancestry. Yet, how these variants influence neural function in African Americans is unclear. The medial temporal lobe (MTL) is an early target of AD pathology and resting-state functional Magnetic Resonance Imaging (rs-fMRI) measures of dynamic network connectivity (hereafter "flexibility"), the brain's capacity to dynamically reconfigure connectivity, provide a sensitive metric of network adaptability, potentially preceding structural decline. However, comparative influence of APOE-ε4 and ABCA7 rs115550680 on MTL flexibility and subregional volumes in this population is unknown. 146 older African Americans (MeanAge=69.71 MeanSD=6.29) were genotyped for APOE-ε4 and ABCA7 rs115550680 via saliva samples. Rs-fMRI was used to calculate MTL flexibility and T1-weighted MRI quantified MTL subregional volumes. ANCOVAs controlled for age, sex, and education, and APOE-ε4 when ABCA7 rs115550680 was the predictor. ABCA7 rs115550680 risk allele carriers exhibited lower MTL flexibility than non-carriers (p = .042) and APOE-ε4 allele carriers (p = .030). They also showed hypertrophy in left anterior hippocampus (p = .049), bilateral entorhinal cortex (ERC) (right p = .048; left p = .020) compared to non-carriers, and greater left ERC volume than APOE-ε4 allele carriers (p = .027). APOE-ε4 or interaction effects were not significant (p > .05). These findings provide preliminary evidence that ABCA7 rs115550680 risk allele, but not APOE-ε4 allele, is linked to reduced MTL flexibility and subregional hypertrophy in older African Americans, suggesting ancestry-specific mechanisms of early AD risk.

PMID:41637763 | DOI:10.1016/j.neurobiolaging.2026.01.008

CNS Neurosci Ther. 2026 Feb;32(2):e70736. doi: 10.1002/cns.70736.

ABSTRACT

BACKGROUND: Neuroimaging studies frequently report aberrant spontaneous brain activity and functional connectivity within core functional networks, including the default mode network (DMN), frontoparietal network (FPN), and salience network (SN) in subclinical depression (SD). However, the dynamic coordination among these networks remains poorly understood, impeding comprehensive elucidation of the underlying neuropathology of SD.

METHODS: Resting-state functional magnetic resonance imaging (fMRI) data were collected from subjects with SD (n = 26) and healthy controls (HCs, n = 33). A preclustering-based co-activation pattern method was developed to investigate the dynamic patterns of network coordination. Finally, machine learning analysis was conducted to evaluate the potential of network dynamics for clinical diagnosis.

RESULTS: Subjects with SD exhibited decreased dwell time in the SN and increased transition frequency from the SN to DMN, which was positively correlated with depressive severity. Furthermore, an ensemble learning model based on SN-DMN dynamic features achieved a classification accuracy of 96.44% in distinguishing SD from HC.

CONCLUSION: These findings underscore the potential of altered SN-DMN dynamics as candidates for future neuroimaging markers of SD and support a neurocognitive model whereby altered SN-DMN dynamic coordination makes subjects with SD more prone to internal directed attention biases, thereby contributing to self-related depressive symptoms like rumination.

PMID:41636698 | DOI:10.1002/cns.70736

Psychiatry Clin Neurosci. 2026 Feb 4. doi: 10.1111/pcn.70035. Online ahead of print.

ABSTRACT

AIM: To investigate abnormal patterns of intrinsic neural timescales (INT) in first-episode schizophrenia across different ages of onset, with a focus on differences in neural temporal-dynamic characteristics between early-onset and adult-onset patients.

METHODS: We collected resting-state fMRI data from 231 first-episode schizophrenia patients (early-onset, n = 122; adult-onset, n = 109) and 153 healthy controls (younger controls, n = 61; older controls, n = 92). INT was computed from the autocorrelation function of the fMRI signal. A two-way ANOVA tested the Diagnosis × Age-of-onset interaction. Further analyses included between-group comparisons, correlation analyses, and imaging transcriptomic analysis.

RESULTS: Fourteen region of interests (ROIs) showed significant interaction effects (P < 0.05/264), predominantly located within the default mode network (DMN, 9 ROIs), with additional involvement of sensorimotor, frontoparietal, memory retrieval, and dorsal attention networks. Group comparisons indicated that early-onset patients exhibited more widespread INT reductions across multiple regions relative to age-matched controls, whereas INT abnormalities in adult-onset patients were more restricted and primarily centered on the DMN. Interaction effects on INT were possibly associated with gene enrichment related to chemical synaptic transmission, glutamatergic signaling, and calcium/calmodulin-dependent kinase activity.

CONCLUSION: INT abnormalities in first-episode schizophrenia are dependent on age of onset: the early-onset subtype shows widespread shortening of timescales across multiple brain networks, suggesting broad neurodevelopmental compromise, whereas the adult-onset subtype exhibits more focal abnormalities centered on the DMN. These findings suggested that INT may serve as a potential neuroimaging biomarker for distinguishing onset-age subtypes, aiding precise stratification and mechanistic studies of schizophrenia.

PMID:41636398 | DOI:10.1111/pcn.70035

Nat Commun. 2026 Feb 3. doi: 10.1038/s41467-025-67398-w. Online ahead of print.

ABSTRACT

Human cognitive processing involves dynamic interactions across brain regions, evolving over time. Traditional neuroimaging analysis often overlooks this temporal aspect, limiting insights into how functional network connectivity (FNC) supports ongoing cognition and behaviour. Using sliding window analysis, we captured FNC changes during tasks, reflecting network reconfiguration in cognitive processes. We further determined behavioural relevance of time-varying FNC by relating network measurements with task performances and psychopathology. We found that several whole-brain FNC patterns, or states, persist across resting and task-based fMRI, with state occurrences fluctuating with the most prominent task stimuli. Regional FNC distinguishes specific task conditions, and time-varying FNC explains more variance in psychopathology symptoms compared to static connectivity. These findings highlight that cognitive tasks reshape regional and whole-brain connectivity. By considering the different FNC states, time-varying connectivity provides a more comprehensive representation of brain interactions and thus may represent a better neural proxy for cognition and behaviour.

PMID:41633990 | DOI:10.1038/s41467-025-67398-w

Brain Res Bull. 2026 Feb 1:111750. doi: 10.1016/j.brainresbull.2026.111750. Online ahead of print.

ABSTRACT

OBJECTIVE: The purpose of this research is to utilize resting-state functional magnetic resonance imaging (rs-fMRI), combined with sliding-window and cluster analysis methods. To identify alterations in functional connectivity (FC) patterns in patients with Parkinson's disease who exhibit olfactory dysfunction prior to the onset of motor symptoms, compared to healthy individuals.This method is intended to improve capabilities for the early detection of PD.

MATERIALS AND METHODS: We recruited fifteen individuals from three distinct groups: PD patients with no or mild olfactory dysfunction (PD-N/MH), those with severe olfactory dysfunction, and healthy controls (HC). We gathered and analyzed resting-state fMRI data to examine dynamic FC across these groups, subsequently conducting a thorough statistical evaluation.

RESULTS: Our cluster analysis identified two unique states of brain network connections across the groups. Notably, the subgroup with PD exhibited a more frequent occurrence and extended duration in state 1, along with reduced state transitions. Notably, the severity of olfactory dysfunction was significantly correlated with increased durations and frequencies in state 1 (P ＜0.05).

CONCLUSION: These observations underscore the significant relationship between state 1 connectivity patterns and olfactory impairment in PD patients. The discovery that PD patients with Parkinson's disease (PD) "linger" in the sparsely connected state 1 provides a dynamic functional correlate of the progressive pathology that initially affects olfaction. Dynamic functional connectivity analysis successfully distinguished PD patients from healthy controls even prior to the onset of motor symptoms, suggesting its potential as a neuroimaging biomarker for Parkinson's disease. Consequently, this method may facilitate early identification, timely intervention, and improved clinical management of PD by providing an early warning signal before motor symptom--based diagnosis, thereby potentially delaying disease progression and alleviating the burden on patients, families, and society.

PMID:41633431 | DOI:10.1016/j.brainresbull.2026.111750

Neuroimage. 2026 Feb 1:121758. doi: 10.1016/j.neuroimage.2026.121758. Online ahead of print.

ABSTRACT

Humans navigate in complex environments with abundant information. However, it is unclear how the human brain involves specific mechanisms to extract meaningful features from high-dimensional information to guide adaptive decision making. Here, we focused on investigating the causal role of the lateral frontopolar cortex (FPl), an area uniquely evolved in the human brain, in decomposing high-dimensional choice information. This was achieved via three experiments that collectively involved transcranial magnetic stimulation (TMS), resting-state functional magnetic resonance imaging (fMRI), task-based fMRI, and computational modelling. First, we found that disrupting FPl using TMS with a continuous theta-burst stimulation (cTBS) protocol impaired decision making with high-dimensional, but not low-dimensional, information. Second, we developed a computational model that arbitrates between a multi-feature decomposition mechanism and a simple heuristic. This model aided explaining that the FPl-TMS effect was attributed to diminished capabilities in multi-feature decomposition. Finally, fMRI data revealed stronger intrinsic FPl signals were related to greater tendency of employing multi-feature decomposition. Together, our results suggest a causal role of FPl in extracting decision-related features from high-dimensional information.

PMID:41633415 | DOI:10.1016/j.neuroimage.2026.121758

Sleep. 2026 Feb 3:zsag030. doi: 10.1093/sleep/zsag030. Online ahead of print.

ABSTRACT

STUDY OBJECTIVES: Sleep loss significantly disrupts cognitive and emotional functioning, yet the neural consequences of different types of sleep deprivation remain unclear.

METHODS: In a within-subject resting-state fMRI study, we examined how acute total sleep deprivation (TSD) and chronic sleep restriction (CSR) alter intrinsic functional brain organization in 28 healthy adults scanned under three conditions: rested wakefulness (RW), after one night of TSD, and after five nights of CSR.To quantify network-level disruption, we applied graph-theoretical analyses, including a novel within-subject adaptation of the Hub Disruption Index and Covariate-Constrained Manifold Learning (CCML), an unsupervised embedding technique sensitive to subject-level covariates. Moreover, we assessed subjective sleep quality, sleepiness, and circadian traits.

RESULTS: Both TSD and CSR were associated with a consistent reorganization of graph topology relative to RW. Furthermore, direct comparisons revealed that TSD and CSR affect different brain hubs. Regional changes in degree, closeness, and clustering coefficients were most prominent in subsystems of the default mode network, frontoparietal network, and cerebellum. These differences were also captured in CCML embeddings, supporting the hypothesis that acute and chronic sleep deprivation exert divergent effects on brain connectivity. Findings were robust across graph thresholds, brain atlases, and nodal metrics. Moreover, these results were further supported by subjective measures - sleepiness was associated with reduced network integration in RW, and circadian phenotype emerged as a key determinant of individual sensitivity to sleep loss.

CONCLUSIONS: Our results show that TSD and CSR induce divergent alterations in brain functional organization, offering new insights into their neural impact.

PMID:41631633 | DOI:10.1093/sleep/zsag030

Biol Psychiatry Glob Open Sci. 2025 Nov 29;6(2):100661. doi: 10.1016/j.bpsgos.2025.100661. eCollection 2026 Mar.

ABSTRACT

BACKGROUND: Intermittent rhythmic delta/theta activity (IRDA/IRTA) detected via electroencephalography (EEG) has been implicated in the pathophysiology of neuropsychiatric illnesses. Therefore, a combined EEG and functional magnetic resonance imaging (fMRI) approach was applied in a transdiagnostic group of patients with different causalities, i.e., autoimmune-mediated (in suspected autoimmune psychiatric syndromes [APS]) and primary psychiatric (borderline personality disorder [BPD]) causalities, as well as in healthy control (HC) participants, to characterize the brain regions functionally correlated with IRDA/IRTA.

METHODS: Overall, 135 EEG-fMRI datasets met the quality criteria, including 33 patients with suspected APS, 59 cases with BPD, and 43 HC participants. fMRI data were obtained using ultrafast MR encephalography and analyzed using AFNI. IRDA/IRTA events were separated from artifacts using independent component analysis and detected algorithmically. Brain regions (clusters) significantly correlated with IRDA/IRTA were first determined in all participants. Clusters occurring across all groups were classified as consensus areas. The groups were also analyzed individually, adding disease- or disorder-specific clusters not overlapping with the consensus areas.

RESULTS: Eleven consensus areas were identified across the 3 groups: 5 of them showed increased activity (Brodmann area [BA] 43-right [r], BA 2-left [l], BA 4-r, BA 18-r, BA 26/29/30-r), and 6 had reduced activity (BA 39-l, BA 10-l, BA 23-l, BA 19-l, BA 10-r, BA 18-l). The APS group showed 5 additional clusters, all with reduced activity (BAs 39-r, 1/3-r, 8-r, 4-l, 21-r). The BPD group showed one further cluster with increased activity (BA 17-l).

CONCLUSIONS: In this study, IRDA/IRTA-related brain activity changes across the groups were identified, with excitatory brain activity especially in fronto-centro-temporal brain areas with similarities to the salience network. Additional disease- or disorder-specific changes were discovered in APS and BPD.

PMID:41630827 | PMC:PMC12861157 | DOI:10.1016/j.bpsgos.2025.100661

Neuroimage Rep. 2026 Jan 23;6(1):100323. doi: 10.1016/j.ynirp.2026.100323. eCollection 2026 Mar.

ABSTRACT

Adverse childhood experiences are a risk factor for attachment disorders. While several neuroimaging studies have shown changes in functional networks in children who have experienced institutional care, the results are inconsistent. Furthermore, no research has been conducted on how structured residential care, such as Japan's small-group family-style care, influences attachment-related symptoms and functional connectivity. This study compared attachment-related symptoms (reactive attachment disorder [RAD] and disinhibited social engagement disorder [DSED] symptoms) between youth aged 9-18 years raised in Japanese small-group residential care (RC; n = 31) and those raised in birth families but not in RC (NRC; n = 37). Group differences in resting-state functional connectivity were also analyzed using multivariate pattern analysis (MVPA) on functional magnetic resonance imaging (fMRI) data. MVPA revealed group differences in whole-brain functional connectivity patterns from the right occipital pole and the left lingual gyrus (LLG). Functional connectivity between the LLG and the frontal medial cortex (FMC) was reduced in RC youth. LLG-FMC connectivity was positively correlated with RAD scores, while longer duration of stay in RC was negatively correlated with RAD symptoms. This study highlights caregiving environment's influence on attachment-related symptoms and functional connectivity, higher levels of RAD and DSED symptoms and reduced LLG-FMC functional connectivity in the RC group. However, this study further demonstrated not only the association between longer stays in family-like RC and the reduction of RAD symptoms but also changes in the connectivity. These findings suggest that stable, high-quality care may have the potential to mitigate adverse developmental outcomes.

PMID:41630788 | PMC:PMC12860606 | DOI:10.1016/j.ynirp.2026.100323

Eur J Neurosci. 2026 Feb;63(3):e70417. doi: 10.1111/ejn.70417.

ABSTRACT

Subjective tinnitus (ST) has been hypothesized to arise from large-scale network reorganization, but the affected circuits and their symptom scaling remain unclear. In a normal-hearing cohort (N = 114; 57 ST, 57 matched controls), we combined resting-state fMRI graph topology, ROI-to-ROI connectivity, voxel-based morphometry (VBM), and multivariate modelling using a harmonized 50-ROI parcellation from the CONN atlas, spanning 15 functional networks. Node-wise analyses (covarying age, sex, education, and motion; multiple-comparison control) showed selective, not global, reconfiguration: reduced integration centered on the left posterior parahippocampal gyrus (lower global efficiency and degree), increased segregation/clustering in inferior frontal and anterior insular hubs, longer path length in parahippocampal and frontal regions, and elevated local efficiency in the right amygdala. Network-based revealed hyperconnectivity in fronto-salience-language-cerebellar circuits and hypoconnectivity across default mode and dorsal attention/temporo-parietal pathways. Symptom coupling was convergent and dissociable: Higher tinnitus severity/duration tracked reduced integration in medial visual/limbic regions with increased integration/degree in right frontal-temporal opercular nodes, whereas higher anxiety related to increased integration/clustering in subcallosal, cerebellar, and occipito-limbic territories alongside decreases in putamen. VBM demonstrated widespread white-matter reductions (inferior frontal, temporal pole, insula, inferior temporal gyrus, and putamen) with more focal gray-matter effects, and a multivariate GLM confirmed a robust omnibus group difference. These multimodal, symptom-linked signatures provide strong evidence that ST reflects targeted network reorganization reduced medial temporal/visual-limbic integration accompanied by increased local specialization within salience and control hubs and yield actionable circuit markers for patient stratification and mechanism-guided treatment targeting.

PMID:41630178 | DOI:10.1111/ejn.70417

BMC Med. 2026 Feb 2. doi: 10.1186/s12916-026-04668-4. Online ahead of print.

ABSTRACT

BACKGROUND: Household cannabis use is a risk factor for adolescents' mental health problems. However, little is known about the association of the cessation and psychological impairments in affected adolescents. This study examined the associations of household cannabis cessation and adolescents' mental health outcomes and potential pathways.

METHODS: This cohort study used data from the Adolescent Brain Cognitive Development study and included adolescents aged 10-13 years with household cannabis use within 12 months at wave 2. Household cannabis cessation was defined as the absence of cannabis use by household members (excluding the adolescent participant) at wave 3 among households that reported use at wave 2. Internalizing and externalizing problems were assessed using the Child Behavior Checklist, and psychotic-like experiences (PLEs) were evaluated using the Prodromal Questionnaire-Brief Child Version. Family conflict and sleep problems were assessed using the Family Environment subscale and the Sleep Disturbance Scale for Children, respectively. Demographic and psychometric confounders were balanced with propensity score matching (PSM). Linear regression was applied to investigate the associations between cessation and mental health outcomes. Mediation analyses of family conflict and adolescent sleep problems were performed. We further considered the influence of genetic predisposition to cannabis use disorder (CUD) and examined whether brain connectivity patterns, measured by resting-state fMRI, modified the relationships.

RESULTS: Of the 1426 adolescents exposed to household cannabis within 12 months, 438 (30.7%) were no longer exposed by wave 3. After PSM, cessation was associated with lower levels of internalizing and externalizing problems, and PLEs (mean ratios, 0.84-0.86, all P < 0.02), adjusting for baseline scores. The associations persisted after additionally adjusting for the adolescents' polygenic risk for CUD among White participants. Family conflict and sleep problems mediated the associations of cessation with internalizing (proportion mediated, 6.8% and 25.8%, respectively) and externalizing symptoms (14.3% and 24.8%, respectively). Adolescents with weaker connections between cingulo-parietal and dorsal attention networks showed stronger associations between cessation and PLEs.

CONCLUSIONS: Household cannabis cessation was linked to a lower level of adolescent mental health problems at follow-up. These findings suggest that interventions aimed at reducing or eliminating household cannabis exposure may be beneficial for youth well-being.

PMID:41629925 | DOI:10.1186/s12916-026-04668-4

PLoS One. 2026 Feb 2;21(2):e0340899. doi: 10.1371/journal.pone.0340899. eCollection 2026.

ABSTRACT

The clinical diagnosis of fibromyalgia (FM), a syndrome characterized by generalized pain, is challenging due to its unknown etiology and frequent comorbidity with other diseases. As a noninvasive modality, functional magnetic resonance imaging has been extensively employed in investigating the pathogenesis of FM. This study proposes a novel diagnostic approach utilizing resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging (DTI) combined with a machine learning algorithm with the objective of enhancing the clinical diagnostic efficiency of FM. Two-sample t tests revealed differences between FM patients and healthy controls in rs-fMRI and DTI corresponding to brain image indices, mainly in the temporal lobe and frontal lobe. In addition, an effective diagnostic classification model was developed based on the single variable feature selection method by applying a support vector and random forest classifier combined with different brain image indicators. Our study demonstrated that the integration of DTI features with a support vector machine model yields superior diagnostic outcomes.

PMID:41628150 | DOI:10.1371/journal.pone.0340899

IBRO Neurosci Rep. 2026 Jan 15;20:139-147. doi: 10.1016/j.ibneur.2026.01.005. eCollection 2026 Jun.

ABSTRACT

BACKGROUND: An increasing number of neuroimaging studies have consistently indicated that the locus coeruleus is associated with cognitive impairment in the early stages of Alzheimer's disease, and the locus coeruleus plays a critical role in cognition, including memory encoding, consolidation, and retrieval.

OBJECTIVE: To investigate whether and how acupuncture modulates the functional connectivity patterns of the locus coeruleus, and offer a new perspective on the mechanism through which acupuncture exerts its efficacy.

METHODS: Resting-state functional magnetic resonance imaging (fMRI) data were collected from 50 patients with amnestic cognitive impairment (aMCI) before and after verum or sham acupuncture. Seed-based whole-brain functional connectivity (FC) was calculated and compared to explore the changing patterns of the locus coeruleus in aMCI patients following acupuncture.

RESULTS: Increased FCs were observed between the left locus coeruleus and the left inferior parietal lobule, and between the right locus coeruleus and the right posterior cerebellum in aMCI patients after verum acupuncture. Further analyses revealed a correlation between FC of the left locus coeruleus and the left inferior parietal lobule before acupuncture and improvement in immediate recall in aMCI patients.

CONCLUSIONS: These results suggest that acupuncture could enhance FC between the locus coeruleus and the inferior parietal lobule/the posterior cerebellum. These functional alterations appear to be linked to the efficacy of acupuncture, particularly in ameliorating memory deficits.

PMID:41626073 | PMC:PMC12856631 | DOI:10.1016/j.ibneur.2026.01.005

Front Psychiatry. 2026 Jan 16;16:1722172. doi: 10.3389/fpsyt.2025.1722172. eCollection 2025.

ABSTRACT

BACKGROUND: Mild cognitive impairment (MCI) is a precursor state of Alzheimer's disease (AD) and has attracted attention, but why amnestic mild cognitive impairment (aMCI) is more likely to progress to AD than non-amnestic mild cognitive impairment (naMCI) is unclear. The present study of aMCI compares differences in intra- and inter-network functional connectivity (FC) across multiple networks in naMCI and further correlates FC with cognitive assessment scores to assess their ability to predict AD progression.

METHODS: Resting-state functional magnetic resonance imaging (rs-fMRI) was performed in 30 naMCI and 40 aMCI cases, and 12 resting-state networks (RSNs) were identified by independent component analysis (ICA). Two-sample t-tests were performed to detect intra-network FC differences, and functional network connectivity (FNC) was calculated to compare inter-network FC differences. Subsequently, Pearson or Spearman correlation analyses were used to explore the correlation between altered FC and cognitive assessment scores.

RESULTS: The aMCI compared to the naMCI differed within the (Default mode network) DMN, (Dorsal attention network) DAN, (Sensorimotor system) SMN, and (Salience network) SN networks (corrected for FWEc, P< 0.05), and inter-network differences in DAN-DMN, DMN-SN, SN-SMN (corrected for FWEc, P<0.05).

CONCLUSION: aMCI contrasts naMCI with widespread intra- and inter-static FNC differences, mainly involving the DMN, DAN, SMN, and SN. these network interactions provide a powerful method for assessing and predicting why aMCI is more likely to progress to AD, and contribute to our understanding of the neurological mechanisms underlying the pathological process of AD.

PMID:41625622 | PMC:PMC12855511 | DOI:10.3389/fpsyt.2025.1722172

Front Psychiatry. 2026 Jan 15;16:1704170. doi: 10.3389/fpsyt.2025.1704170. eCollection 2025.

ABSTRACT

BACKGROUND: Autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) are highly comorbid. The neural basis of this comorbidity remains unclear. We compared brain structural-functional coupling (SC-FC coupling) across ASD subgroups and typically developing (TD) controls to parse the neurobiological heterogeneity of ASD.

METHODS: We analyzed T1-weighted and resting-state fMRI data from 331 participants from ABIDE II (130 ASD [39 ASD+ADHD, 91 ASD-only] and 201 TD). For each participant, we extracted multivariate structural features from T1-weighted images to construct an individual structural covariance network. SC-FC coupling for each brain region was quantified by correlating its observed functional connectivity profile with the profile predicted from individual structural features via linear regression.

RESULTS: Compared to TD individuals, the ASD group showed altered SC-FC coupling in networks critical for social cognition, emotion, sensory processing, and cognitive control: the default mode network (DMN), limbic system (LimN), somatomotor network (SMN), and frontoparietal network (FPN). Crucially, distinct patterns emerged between ASD subgroups. The ASD-only group had stronger coupling in the left inferior temporal gyrus (ITG.L). The ASD+ADHD group showed increased coupling in specific cerebellar regions: the right cerebellar lobule IX (Cerebellum_9_R) and right cerebellum Crus II (Cerebellum_Crus2_R).

CONCLUSIONS: Our findings demonstrate both shared and subtype-specific alterations in SC-FC coupling in ASD. Comparing ASD subgroups clarifies that comorbid ADHD is associated with unique neural pathways, particularly involving cerebellar integration for attentional processes. Measuring SC-FC coupling offers a valuable approach for disentangling the heterogeneity in ASD and may aid in developing targeted interventions.

PMID:41625611 | PMC:PMC12852334 | DOI:10.3389/fpsyt.2025.1704170

Neuroimage Rep. 2026 Jan 20;6(1):100321. doi: 10.1016/j.ynirp.2026.100321. eCollection 2026 Mar.

ABSTRACT

OBJECTIVE: SNAP-25, a synaptic vesicle docking protein, carries a polymorphism (rs3746544) in its 3'-UTR region that is associated with ADHD, yet its functional mechanism remains unknown. The purpose of this study is to evaluate the impact of synaptosomal-associated protein 25 (SNAP-25) gene MnlI polymorphism (rs3746544) on spontaneous brain activity in children with attention deficit hyperactivity disorder (ADHD), employing the fractional amplitude of low-frequency fluctuation (fALFF) analysis of resting-state functional Magnetic Resonance Imaging (rs-fMRI) data, to explore its potential neurobiological mechanisms and neuroimaging biomarkers.

METHODS: This study enrolled 56 boys with ADHD (aged 8-10 years) and 21 age-matched healthy boys as healthy controls (HCs). According to the SNAP-25 MnlI genotype, ADHD patients were divided into two groups: the TT homozygote group (TT group, n = 36) and the G-allele carrier group (TG group, n = 20). Rs-fMRI data were acquired and analyzed using fALFF to measure spontaneous brain activity.One-sample t-tests were performed to calculate fALFF maps for each group, setting the threshold as a cluster greater than 20 voxels, with P < 0.01 after AlphaSim correction. Two-sample t-tests were performed to calculate the differences in fALFF values among the TT, TG, and HCs groups, with age as a covariate. A cluster of greater than 20 voxels, with P < 0.01 after AlphaSim correction, was considered to have statistically significant differences. Assessed the Working Memory Index (WMI) using the Wechsler Intelligence Scale for Children-IV (WISC-IV) in children with ADHD from the TT and TG groups.

RESULTS: One-sample t-tests revealed that children with ADHD group (both TT and TG group) exhibited significantly lower fALFF values in the default mode network (DMN) and parieto-occipital cortex compared to HCs, while showing increased fALFF located in the posterior cerebellar lobe; Two-sample t-tests demonstrated that: (a) Compared to HCs, the ADHD group (both TT and TG group) showed widespread reductions of fALFF values across multiple brain regions, including the posterior cingulate cortex and precuneus. The TG group showed more pronounced decreases when compared with the TT group. (b) In comparison to the TG group, the TT group exhibited higher fALFF values in higher-order cognitive regions, such as the right superior frontal gyrus and left medial frontal gyrus, but lower fALFF values in the posterior cerebellar lobe and posterior cingulate cortex. The TT group had significantly higher WMI compared to the TG group (t = 2.098, P < 0.05).

CONCLUSIONS: The SNAP-25 gene MnlI polymorphism has an impact on spontaneous brain activity in children with ADHD, as measured by fALFF. This study reveals the potential mechanisms from the perspective of brain networks, demonstrates how ADHD genotypes affect neural function, and provides a new approach for clinical decision-making and efficacy monitoring.

PMID:41624630 | PMC:PMC12856436 | DOI:10.1016/j.ynirp.2026.100321