Most recent paper

Front Neurosci. 2026 Sep 14;20:1891985. doi: 10.3389/fnins.2026.1891985. eCollection 2026.

ABSTRACT

EEG microstates are topographical patterns of EEG activity that offer a lens into the fast temporal dynamics of large-scale functional network activity and whole-brain functional organization. Microstates can capture temporal patterns of network configurations and transitions between these configurations at the millisecond scale. Although extensively studied in adults, microstates remain underutilized in developmental neuroscience, despite their potential for tracking significant developmental changes in brain network dynamics indicated by developmental fMRI studies. Extracting EEG microstates from developmental populations with relatively high artifact levels compared to adults remains a challenge due to the sensitivity of the method to such artifacts. Our tutorial provides a practical guide that walks the readers through the microstate analysis pipeline with a focus on special considerations for developmental data within the free, open-source software HAPPE (Harvard Automated Processing Pipeline for Electroencephalography) that is optimized for developmental artifacts. We first detail the conceptual foundations and current status of EEG microstates in developmental literature and then present a step-by-step tutorial on computing and interpreting microstates from resting-state and task-based EEG in developmental cohorts. All de-identified datasets used in the tutorial and the annotated microstate analysis code are freely available for public access at https://zenodo.org/records/17527065 and https://github.com/PINE-Lab/HAPPE/blob/master/3.%20generate/generateMicroStates.m. This article aims to make microstate computation more accessible, robust, and reproducible in developmental cognitive neuroscience.

PMID:42807752 | PMC:PMC13617483 | DOI:10.3389/fnins.2026.1891985

Neurorehabil Neural Repair. 2026 Sep 29:15459683261479722. doi: 10.1177/15459683261479722. Online ahead of print.

ABSTRACT

BACKGROUND: Recent studies have identified the right cerebellar Crus I (rCrus I) as a promising target for rTMS in improving language rehabilitation. However, it remains unclear whether continuous theta burst stimulation (cTBS) over the rCrus I improves language outcomes in patients with subacute post-stroke aphasia (PSA).

OBJECTIVE: To determine whether inhibitory cTBS over rCrus I improves language recovery in PSA and to explore underlying functional connectivity (FC) mechanisms.

METHODS: Fifty-one PSA patients were randomized to receive either real cTBS (n = 25) or sham stimulation (n = 26) over rCrus I (10 sessions, 2 weeks) combined with speech-language therapy (SLT). Language assessments (WAB-AQ, BNT, BDAE) and resting-state fMRI were conducted before and after the intervention.

RESULTS: Both groups showed significant language improvement post-intervention. No significant interaction was found for WAB-AQ (P = .058), but a significant interaction was observed for repetition (P = .034), favoring cTBS. Resting-state fMRI showed altered connectivity between rCrus I and right temporo-occipital regions, with FC changes negatively correlated with language gains in the cTBS group. Exploratory subgroup analyses identified 2 distinct FC response patterns (FC-increase and FC-decrease), indicating heterogeneous cerebello-cortical and intra-cerebellar connectivity modulation across participants.

CONCLUSIONS: Cerebellar cTBS did not confer a significant overall benefit on language recovery in PSA, but selectively improved repetition performance, suggesting domain-specific effects. Functional imaging indicated that rCrus I-centered connectivity changes were associated with behavioral outcomes, with marked inter-individual variability. These findings support a modulatory role of cerebellar cTBS on language networks, warranting further validation in larger, well-powered studies.

TRIAL REGISTRATION: This trial was registered under the China Clinical Trial Registry (Registration No. ChiCTR2100049828).

PMID:42806772 | DOI:10.1177/15459683261479722

Dev Neurobiol. 2026 Oct;86(4):e70068. doi: 10.1002/dneu.70068.

ABSTRACT

Cortical excitation-inhibition (E/I) balance regulates sensitive periods of plasticity and is critical for brain development. Yet, neuroimaging studies characterizing E/I dynamics in early childhood are rare. The Hurst exponent (H), derived from resting-state functional magnetic resonance imaging (rs-fMRI), provides a noninvasive proxy for E/I balance. We investigated age-related changes in H using longitudinal rs-fMRI from 55 typically developing children aged 1.5-5 years (78 sessions during natural sleep). Linear mixed-effects models revealed significant age-related increases in H, signifying greater inhibition or more balanced E/I, in three right-hemisphere regions: inferior frontal gyrus (IFG) pars opercularis and triangularis, and middle temporal pole. Whole-brain maps showed positive age effects across most cortical areas, though the most robust increases occurred in higher order association cortices rather than primary sensory regions, consistent with hierarchical network maturation. Higher H in right IFG opercular was associated with better expressive language skills and fewer behavioral/emotional problems, controlling for age and sex. These findings suggest that E/I balance maturation during toddlerhood and preschool years is most pronounced in regions supporting language development and cognitive control. Our results characterized normative developmental trajectories of H during an important neurodevelopmental window and its associations with emerging behavioral competencies, potentially informing future investigations of atypical E/I maturation in neurodevelopmental disorders.

PMID:42806655 | DOI:10.1002/dneu.70068

Brain Behav. 2026 Oct;16(10):e71798. doi: 10.1002/brb3.71798.

ABSTRACT

BACKGROUND: Speech impairment is common in Parkinson's disease (PD) and lacks effective clinical interventions due to poorly understood underlying mechanisms. Therefore, this study aimed to explore the relationship between altered brain functional networks and speech impairments in PD, identifying neural correlates of abnormal brain activity linked to PD-related speech disorders (SD).

METHODS: Baseline clinical characteristics, neurobehavioral assessments, and resting-state functional magnetic resonance imaging (rs-fMRI) data were collected from three groups: PD individuals with SD (PD-SD group), PD individuals without SD (PD-NON-SD group), and healthy controls (HC group). Independent component analysis (ICA) was performed to identify resting-state networks (RSNs) using the Group ICA of fMRI Toolbox (GIFT) implemented in MATLAB. Functional network connectivity (FNC) was subsequently quantified by calculating Pearson correlation coefficients between the extracted RSNs. One-way analysis of variance (ANOVA) was used to assess group differences in FNC, followed by post hoc pairwise comparisons for networks showing significant effects. Given the reported association between speech impairment and cognitive impairment in PD, correlation analyses were further performed to investigate the relationships between FNC alterations and clinical measures, including speech performance and cognitive function assessed by the Montreal Cognitive Assessment (MoCA).

RESULTS: Significant differences in FNC were observed between the left frontoparietal network (LFPN) and auditory network (AUN) across the three groups (p = 0.0280). In particular, the FNC between LFPN and AUN was significantly stronger in the PD-SD group compared to the PD-NON-SD group (p = 0.0221) and the HC group (p = 0.0047). Spearman correlation analysis revealed significant positive correlation between LFPN-AUN functional connectivity and Unified Parkinson's Disease Rating Scale part III (UPDRS-III) speech subscores (rs = 0.2624, p = 0.0466), as well as a significant negative correlation with MoCA scores (rs = -0.2847, p = 0.0249).

CONCLUSION: This study identifies disrupted functional connectivity between the LFPN and AUN in individuals with PD-SD. These findings suggest that altered integration of RSNs involved in motor, cognitive, and auditory processing may contribute to speech impairment in PD. Hyperconnectivity between LFPN and AUN may thus serve as a neural substrate for speech impairment in PD. Specifically, increased connectivity between the LFPN and AUN may represent a neural signature associated with speech dysfunction in PD. These results provide potential mechanistic insights and highlight candidate neural targets for future neuromodulation strategies aimed at improving speech function.

PMID:42806653 | DOI:10.1002/brb3.71798

World Neurosurg. 2026 Sep 28:125378. doi: 10.1016/j.wneu.2026.125378. Online ahead of print.

ABSTRACT

BACKGROUND: Resting-state functional MRI (rs-fMRI) provides a non-invasive method for assessing intrinsic connectivity changes associated with neurological recovery. This systematic review evaluated patterns of functional connectivity change after acquired brain injury (ABI), with a focus on network disruption, reorganisation, and recovery-related change.

METHODS: A systematic review was conducted according to PRISMA 2020 recommendations using a Population-Intervention-Outcome framework. PubMed, Scopus, Cochrane Library, and Google Scholar were searched for studies published between January 2010 and March 2026 examining rs-fMRI connectivity following ABI. Screening was performed independently by two reviewers, and eligible studies were appraised using Joanna Briggs Institute critical appraisal tools. Narrative synthesis was undertaken to evaluate connectivity disruption, compensatory reorganisation, and recovery-related network changes.

RESULTS: Twenty studies were included, predominantly involving stroke and traumatic brain injury populations. rs-fMRI identified alterations in functional connectivity, spontaneous activity, hub organisation, and network efficiency associated with motor, cognitive, behavioural, language, and consciousness outcomes. Only one included study directly evaluated functional connectivity following cranioplasty, providing limited evidence of recovery-related changes in default mode and whole-brain network organisation.

CONCLUSION: Resting-state fMRI demonstrates heterogeneous patterns of network disruption, reorganisation, and recovery-related connectivity change following ABI. These findings support the use of rs-fMRI as a research tool for characterising network-level recovery, while further prospective longitudinal studies using standardised imaging and outcome measures are needed to establish its clinical utility.

PMID:42805556 | DOI:10.1016/j.wneu.2026.125378

Epilepsy Behav. 2026 Sep 27;185:111301. doi: 10.1016/j.yebeh.2026.111301. Online ahead of print.

ABSTRACT

PURPOSE: Children with self-limited epilepsy with centrotemporal spikes (SeLECTS) and childhood absence epilepsy (CAE) often have favorable seizure outcomes, but cognitive inefficiencies may persist and affect school functioning. Whether choice reaction time (CRT) is related to somatomotor connectivity and thalamic or hippocampal volumes in these syndromes remains unclear.

METHODS: We performed an exploratory secondary analysis of public pediatric epilepsy neuroimaging data. After excluding one participant with SeLECTS because of FreeSurfer segmentation failure, the final structural and functional samples included 25 children with SeLECTS and 10 with CAE. CRT was the primary behavioral outcome. We tested whether SomMot connectivity-CRT coupling differed between syndromes and whether thalamic or hippocampal volumes were associated with CRT within the combined epilepsy sample.

RESULTS: The SomMot connectivity × syndrome interaction was nominally significant in the linear-age model (p = 0.039), yet was attenuated after quadratic age adjustment (p = 0.065). In the linear-age structural models, larger bilateral thalamic volumes were associated with shorter CRT within combined epilepsy sample, even after false discovery rate (FDR) correction. The estimates remained directionally consistent after quadratic age adjustment, yet no longer survived FDR correction.

CONCLUSION: Bilateral thalamic volumes were associated with CRT across combined epilepsy sample, while SomMot connectivity exhibited a candidate syndrome-dependent coupling pattern, suggesting complementary structural and functional correlates of reaction speed in pediatric epilepsy. Their sensitivity to age model specification warrants further validation in larger, age-balanced cohorts.

PMID:42801844 | DOI:10.1016/j.yebeh.2026.111301

Behav Brain Res. 2026 Sep 26:116502. doi: 10.1016/j.bbr.2026.116502. Online ahead of print.

ABSTRACT

Punishment sensitivity refers to an individual's tendency to perceive and respond to punishment and other negative outcomes. Delay discounting refers to that an individual tends to devalue the subjective worth of future rewards as the waiting time increases. Previous findings suggest that punishment sensitivity may be related to delay discounting, but direct evidence for this association and the neural mechanisms underlying this relationship remain unclear. To address this question, we combined behavioral measurements, voxel-based morphometry (VBM), resting-state fMRI, and mediation analysis to investigate their brain-behavior mechanisms. Behaviorally, punishment sensitivity negatively correlated with delay discounting. Furthermore, VBM analysis found that the gray matter volume (GMV) of the left dorsal medial prefrontal cortex (dmPFC_L) is positively associated with punishment sensitivity, and neuroimaging results revealed that the functional connectivity between the dmPFC_L and the right postcentral gyrus (PCG_R) was positively associated with punishment sensitivity. More critically, mediation analysis showed that this functional connectivity exhibited a partial mediation with a statistical suppressor effect in the association with delay discounting. These results suggest that the functional connectivity between the dmPFC_L and PCG_R may represent a neural correlate of this association, providing new insights and a neurobiological interpretation for this association.

PMID:42800541 | DOI:10.1016/j.bbr.2026.116502

Front Psychiatry. 2026 Sep 11;17:1883842. doi: 10.3389/fpsyt.2026.1883842. eCollection 2026.

ABSTRACT

BACKGROUND: Neuroimaging studies of internet gaming disorder (IGD) have primarily focused on reward-related and executive-control networks. However, sensory processing of addiction-related cues, particularly visual processing, may also contribute to IGD. Whether the intrinsic hierarchical organization of the visual system is altered remains unclear.

METHODS: The study included 35 individuals with IGD and 30 healthy controls (HCs), with an overall age range of 9-33 years. The sample was predominantly composed of adolescents. An a priori three-level visual hierarchy model comprising the primary visual cortex (V1), lingual gyrus, and lateral occipital cortex (LOC) was constructed. Functional connectivity (FC) was calculated for the V1-Lingual, Lingual-LOC, and V1-LOC pathways. A hierarchical integration index (HII), derived from V1-LOC and V1-Lingual connectivity, was calculated to assess long-range relative to local visual coupling. Group differences were assessed using MANCOVA with follow-up univariate analyses and FDR correction. Within the IGD group, associations between IAT scores and all visual hierarchical measures were examined using Pearson and covariate-adjusted partial correlations with FDR correction.

RESULTS: V1-LOC connectivity was significantly reduced in the IGD group compared with HCs (HC: 0.364 ± 0.132; IGD: 0.130 ± 0.189; F(1,59) = 30.809; FDR-corrected p < 0.001; partial η2 = 0.343). V1-Lingual and Lingual-LOC connectivity did not show significant group differences, although their effect sizes were small-to-moderate (Cohen's d = 0.32 and 0.40, respectively). The HII was numerically lower in IGD but did not reach statistical significance (t = 1.90, p = 0.062; Cohen's d = 0.46). Within the IGD group, lower V1-LOC connectivity was associated with higher IAT scores (r = -0.479, FDR-corrected p = 0.016), and this association remained significant after controlling for age, sex, education, and mean FD (partial r = -0.447, FDR-corrected p = 0.048).

CONCLUSIONS: IGD is associated with altered long-range hierarchical connectivity within the visual system, particularly between early visual cortex and higher-order LOC. These findings provide a sensory-level perspective complementing reward- and control-centered accounts of IGD.

PMID:42798762 | PMC:PMC13613021 | DOI:10.3389/fpsyt.2026.1883842

Neurobiol Dis. 2026 Sep 25;230:107628. doi: 10.1016/j.nbd.2026.107628. Online ahead of print.

ABSTRACT

Acute basal ganglia ischemic stroke (BGIS) often leads to motor dysfunction, but the mechanisms of functional reorganization, particularly the underlying molecular basis, remain unclear. This study aimed to investigate the local and global functional reorganization patterns and their molecular correlates in acute BGIS. Resting-state fMRI data were acquired from 59 patients with acute BGIS and 35 age- and sex-matched healthy controls (HCs). Regional homogeneity (ReHo) and seed-based functional connectivity (FC) analyses were used to assess local and global brain connectivity, respectively. We identified a key classification feature using support vector machine (SVM) and logistic regression (LR) models combined with SHapley Additive exPlanations (SHAP) analysis, which was then spatially associated with Allen Human Brain Atlas (AHBA) transcriptomic data via partial least squares (PLS) regression, followed by functional enrichment analysis. Compared with HCs, BGIS patients demonstrated decreased ReHo in the bilateral precentral gyri, along with reduced interhemispheric FC between these two regions. The SVM and LR models effectively distinguished patients from HCs (AUCs = 0.877 and 0.868, respectively), with SHAP analysis identifying this reduced interhemispheric FC as the top discriminative feature. This key FC feature further showed a positive correlation with motor function. Genes spatially associated with this feature were enriched in synaptic function, ion transport, and energy metabolism. These findings highlight impaired interhemispheric FC between the bilateral precentral gyri and its associated transcriptomic signatures in acute BGIS, providing insights into the neurobiological basis of post-stroke motor dysfunction.

PMID:42790788 | DOI:10.1016/j.nbd.2026.107628

Int J Psychophysiol. 2026 Sep 25:113479. doi: 10.1016/j.ijpsycho.2026.113479. Online ahead of print.

ABSTRACT

Poor sleep quality is a prevalent issue linked to higher procrastination, which not only impairs academic and work functioning but also adversely affects mental and physical health. However, the psychological and neural basis underlying this association remain unclear. In this study, 1163 participants were initially assessed with self-report measures of sleep quality, procrastination, anxiety, and self-control and resting-state fMRI to examine the behavioral and neural correlates of the association between sleep quality and procrastination. After questionnaire and MRI quality control, 1079 participants were included in the final analyses. Elastic net regression revealed distinct functional connectivity patterns centered on the default mode network and prefrontal control regions, including the dorsolateral prefrontal cortex, medial prefrontal cortex, and anterior cingulate cortex, which significantly predicted poorer sleep quality. Furthermore, parallel mediation analyses indicated that anxiety and self-control statistically mediated the association between sleep quality and procrastination, and that composite brain network strength also showed an indirect association with procrastination involving these same behavioral pathways. Integrating these behavioral and neuroimaging findings, our results indicate that poor sleep quality is associated with atypical patterns of connectivity within prefrontal and default mode systems, which may be consistent with the proposed role of diminished psychological resources in emotion regulation and executive control. Guided by the conservation of resources model, this multi-level framework provides an integrated perspective on the psychological and neural basis of the relationship between sleep quality and procrastination, thereby providing potentially relevant directions for future intervention research.

PMID:42790747 | DOI:10.1016/j.ijpsycho.2026.113479

Brain Res Bull. 2026 Sep 25:112140. doi: 10.1016/j.brainresbull.2026.112140. Online ahead of print.

ABSTRACT

BACKGROUND: Hypertension is associated with brain remodeling and an increased risk of cognitive impairment. Although endocrine hormones play a central role in blood pressure regulation, how endocrine abnormalities are associated with brain network reorganization and cognitive function in hypertensive populations remains unclear. This study aimed to investigate whether renin-angiotensin-aldosterone system (RAAS) and hypothalamic-pituitary-adrenal (HPA) axis abnormalities are associated with distinct multimodal brain alterations and cognitive profiles in hypertension.

METHODS: In this cross-sectional study, 47 hypertensive adults underwent endocrine profiling, neuropsychological assessment, and resting-state functional MRI (rs-fMRI) and T1-weighted structural MRI on a 3.0T scanner. Image analyses included amplitude of Low-Frequency Fluctuations (ALFF), Voxel-based Morphometry (VBM), and hypothalamic seed-based Functional Connectivity (FC). Based on plasma levels of angiotensin II (Ang II), adrenocorticotropic hormone (ACTH), and aldosterone (ALD), patients were classified as endocrine-abnormal hypertension (EH; n = 20) or non-endocrine hypertension (NEH; n = 27). Group differences and endocrine-imaging associations were examined.

RESULTS: Compared with the NEH group, the EH group showed poorer performance on memory and language measures. The EH group also showed reduced ALFF in frontal regions and increased ALFF in the cerebellum, together with reduced gray matter volume in posterior cortical regions. Hypothalamic seed-to-voxel FC was reduced in the EH group with frontal, temporal, and occipital cortical regions and increased with cerebellar regions. In whole-sample analyses, hypothalamic-vermal connectivity was negatively associated with global cognition and language performance, cerebellar ALFF was negatively associated with episodic memory performance, and right superior frontal gyrus ALFF was negatively associated with circulating ALD levels.

CONCLUSIONS: Endocrine abnormalities in hypertension are associated with a distinct pattern of brain alterations characterized by prefrontal hypofunction, posterior cortical gray matter reductions, and altered hypothalamic-cortical and hypothalamic-cerebellar connectivity, accompanied by poorer performance on memory and language measures. These findings suggest that hypertensive patients with endocrine abnormalities may represent a subgroup with greater brain and cognitive vulnerability.

PMID:42790545 | DOI:10.1016/j.brainresbull.2026.112140

Sleep. 2026 Sep 25:zsag252. doi: 10.1093/sleep/zsag252. Online ahead of print.

ABSTRACT

STUDY OBJECTIVES: Comorbid insomnia and sleep apnea (COMISA) is a prevalent and clinically challenging phenotype, yet the neural substrates distinguishing it from isolated obstructive sleep apnea (OSA) remain elusive. We employed a multimodal graph theoretical approach to identify the structural and functional network patterns associated with the COMISA phenotype.

METHODS: We analyzed 124 male participants (45 controls, 58 OSA, and 21 COMISA). Structural covariance networks were derived from regional gray matter volume data, and functional networks from resting-state fMRI. Graph metrics-including strength, clustering coefficient (CC), efficiency, and closeness centrality (CloC)-were quantified for weighted, undirected networks to assess global and nodal topological properties.

RESULTS: Functional network analysis revealed significant global hyper-connectivity in both patient groups compared to controls. Crucially, COMISA demonstrated a distinct functional pattern compared to OSA, characterized by significantly elevated nodal metrics (CC and CloC) within thalamostriatal circuits, specifically involving the bilateral thalamus and putamen. Exploratory analyses across the cohort suggested possible positive associations between these nodal metrics and the severity of insomnia and depressive symptoms. In contrast, structural covariance networks showed no significant group differences, indicating a dissociation between the two modalities.

CONCLUSIONS: Our findings suggest that COMISA presents a distinct functional pattern, which is consistent with circuit-level dysregulation, specifically within the thalamostriatal axis. This subcortical pattern within arousal-modulating circuits offers a potential pathophysiological explanation for the clinical complexity and treatment resistance frequently observed in COMISA.

PMID:42789003 | DOI:10.1093/sleep/zsag252

Imaging Neurosci (Camb). 2026 Sep 23;4:IMAG.a.1334. doi: 10.1162/IMAG.a.1334. eCollection 2026.

ABSTRACT

The brain is never truly at rest. Even in the absence of external stimuli, the central nervous system continuously monitors and regulates visceral organs. However, it remains unclear to what extent this interoceptive signaling shapes the brain's resting state networks. Here, we tested the hypothesis that resting-state functional connectivity is actively sustained by visceral inputs. Using functional magnetic resonance imaging in 34 anesthetized rats, we identified a cohesive "interoception network" characterized by dense, reciprocal functional connectivity among the dorsal vagal complex, thalamus, hypothalamus, amygdala, insula, and cingulate cortex. The topology of this network was not static but dynamically coupled to the physiological state. Functional integration was robust in the digestive (fed) phase but significantly attenuated in the inter-digestive (fasted) phase. The network relied on the integrity of the vagus nerve. When vagal signaling was eliminated by bilateral cervical vagotomy, the network effectively disintegrated. These findings demonstrate that resting-state functional connectivity is not an intrinsic property of the isolated brain but an embodied phenomenon that relies on continuous neural signaling between the brain and viscera.

PMID:42787490 | PMC:PMC13602131 | DOI:10.1162/IMAG.a.1334

Curr Med Imaging. 2026 Sep 22. doi: 10.2174/0115734056480808260903070922. Online ahead of print.

ABSTRACT

INTRODUCTION: Although painful Temporomandibular Disorders (p-TMD) represent a common chronic pain condition, their central pathophysiology remains elusive. This work utilized multimodal resting-state functional MRI (rs-fMRI) to investigate functional brain alterations in patients with p-TMD.

METHODS: A total of 74 participants (41 p-TMD patients and 33 age- and gender-matched normal controls (NCs)) were enrolled in this case-control study. Each participant underwent both rs-fMRI and high-resolution structural imaging. We assessed multiple metrics, including Regional Homogeneity (ReHo), Amplitude of Low-Frequency Fluctuations (ALFF), Degree Centrality (DC), and further explored seed-based Functional Connectivity (FC). Intergroup differences were examined, and correlations between significant neuroimaging findings and clinical variables were assessed.

RESULTS: Relative to the NC group, p-TMD patients showed a specific increase in ReHo localized to the Left Postcentral Gyrus (L_PoG), with no concurrent changes in ALFF or DC in this region. This hyper-synchronous region demonstrated enhanced FC when the identified L_PoG cluster was used as the seed region in several brain regions, including the right caudate, left putamen, right postcentral gyrus, and right precentral gyrus. Notably, these altered ReHo and FC values showed no significant correlation with clinical variables.

DISCUSSION: The observed pattern of increased L_PoG ReHo in the absence of ALFF or DC changes suggests a highly localized enhancement of neuronal synchrony in the primary somatosensory cortex, rather than generalized hyperactivation or altered network hub status. The enhanced FC with the basal ganglia and contralateral sensorimotor cortex indicates aberrant integration of sensory and affective-motivational information. The lack of correlation with clinical measures suggests the brain alterations may better reflect stable disease traits than momentary pain states in p-TMD.

CONCLUSION: The current study identified L_PoG neuronal hypersynchrony and enhanced sensorimotor-motivational network coupling as central features of p- TMD, which may be a manifestation of pain-related neuroplasticity. Collectively, this study provides a neuroimaging basis for developing new biomarkers and suggests potential for future targeted neuromodulation strategies in p-TMD.

PMID:42786835 | DOI:10.2174/0115734056480808260903070922

Int J Neural Syst. 2026 Sep 25:2750015. doi: 10.1142/S0129065727500158. Online ahead of print.

ABSTRACT

Mental illness is becoming increasingly common in everyday life, affecting a growing number of people. Functional Magnetic Resonance Imaging (fMRI) is an effective technique for detecting mental disorders. Resting-state fMRI (rs-fMRI) analyses spontaneous low-frequency oscillations in the Blood Oxygen Level Dependent signal to examine the functional architecture of the brain. fMRI and rs-fMRI data processing contribute to mapping neural activity in specific brain regions, enabling accurate localization of cognitive functions and improving our understanding of Functional Connectivity and interactions among brain regions. This paper focuses on the use of Machine Learning and Deep Learning techniques for fMRI analysis to identify brain features that may be associated with Bipolar Disorder (BD) and Alzheimer's Disease (AD). The first step in the proposed approach is the preprocessing of fMRI and rs-fMRI data using two distinct methods: the first combines Statistical Parametric Mapping and the CONN toolbox for improved results, and the second focuses on the MELODIC software. The proposed approach begins with fMRI and rs-fMRI preprocessing using two pipelines: one integrating Statistical Parametric Mapping (SPM) with the CONN toolbox and another based on the MELODIC framework. The aim is to evaluate how preprocessing choices affect functional connectivity representations and classification performance when combined with classical Machine Learning (ML) methods, namely Support Vector Machines and Random Forests, and the Deep Learning (DL) model AlexNet. Given the altered brain connectivity patterns observed in Bipolar Disorder and Alzheimer's Disease, these methods are employed to assess preprocessing-learning interactions across both disorders. Experimental results emphasize that Connbox-SPM preprocessing combined with AlexNet yields the best results for both mental disorders, with Bipolar Disorder reporting 78.2% accuracy and AD achieving 82.4% accuracy.

PMID:42786613 | DOI:10.1142/S0129065727500158

Schizophrenia (Heidelb). 2026 Jul 29;12(1):76. doi: 10.1038/s41537-026-00789-0.

ABSTRACT

Previous studies have demonstrated widespread regional abnormalities in blood oxygen level-dependent (BOLD) amplitude of low frequency fluctuation (ALFF) in psychotic disorders. How regional ALFF is related to functional connectivity and behavior in psychotic illness, however, is poorly understood. Here we examined voxelwise ALFF across the brains of subjects with early psychosis (EP) vs. healthy controls (HCs) as well as its relationships to functional connectivity and task performance. Resting state fMRI data from 55 HCs and 109 participants with EP from the Human Connectome Project-Early Psychosis were analyzed. Our analytic strategy was to examine ALFF across the whole brain to determine what regions showed significant differences in the psychosis group and then determine how those regional abnormalities in ALFF were related to connectivity patterns with other brain areas. We then examined correlations between these measures and performance on task-relevant to the observed circuitry. Significantly lower ALFF was observed in the sensorimotor cortex in participants with EP vs. HC. Decreased sensorimotor ALFF in EP, furthermore, was associated with poor motor dexterity and cognitive function. Finally, in participants with EP, ALFF showed increased connectivity with the cerebellum, anterior cingulate, and insula. Our results suggest that spontaneous low-frequency blood oxygen level-dependent fluctuation amplitude is significantly lower in sensorimotor cortex in EP, and that this change is associated with poor motor skills and cognition. Hyperconnectivity within the observed circuits in participants with EP may indicate more widespread pathology with areas that show abnormally low levels of baseline BOLD fluctuation.

PMID:42786188 | DOI:10.1038/s41537-026-00789-0

Brain Res Bull. 2026 Sep 24:112141. doi: 10.1016/j.brainresbull.2026.112141. Online ahead of print.

ABSTRACT

BACKGROUND AND PURPOSE: Neuropsychological studies suggest that napping during night shifts may benefit nurses' brain functions and clinical performance. However, in vivo neuroimaging evidence remains scarce. This study aims to use resting-state functional magnetic resonance imaging (rs-fMRI) to investigate how night-shift napping modulates neural activity in nurses experiencing sleep deprivation (SD), addressing a critical gap in understanding the neurophysiological mechanisms underlying nap-induced recovery.

METHODS: rs-fMRI was administered to 24 nurses during three sessions: rested wakefulness (RW), SD, and napping (NAP). Within a biological day, RW represented normal sleep duration, SD indicated an absence of sleep, and NAP referred to naps lasting less than two hours during the night. Amplitude of low-frequency fluctuations (ALFF) analysis was performed to assess spontaneous neural activity and reflect brain function. One-way repeated measures analysis of variance, followed by post hoc paired t-tests, was used to examine ALFF differences.

RESULTS: A comparison between RW and SD revealed a significant SD-related reduction in ALFF, predominantly affecting the bilateral frontal and temporal cortices, insula, subcortical structures, and cerebellum, and a notable ALFF increase predominantly involving the bilateral occipital cortex, motor and sensory-related areas, parietal lobe, and several temporal regions (FWE-corrected P<0.05). When comparing RW with NAP sessions, the spatial extent of ALFF alterations was significantly reduced (FWE-corrected P<0.05). Additionally, comparison between SD and NAP sessions showed that NAP effectively mitigated the ALFF disturbances induced by SD.

CONCLUSION: Night-shift napping may serve as an effective strategy for restoring disturbed neural activity and thereby preserving cognitive and perceptual brain functions. These findings provide novel neuroimaging evidence supporting napping as a neuroprotective strategy for sleep-deprived nurses.

PMID:42785595 | DOI:10.1016/j.brainresbull.2026.112141

Neuroimage. 2026 Sep 24:122254. doi: 10.1016/j.neuroimage.2026.122254. Online ahead of print.

ABSTRACT

Creativity constitutes an essential component of higher-order cognitive abilities in humans. Functional magnetic resonance imaging (fMRI) investigations have increasingly delineated the neural correlates underlying creative processes. Nevertheless, the structural architecture of the brain provides the foundational substrate for these functions, and variations in morphology can substantially influence cognitive capabilities. To date, systematic reviews and quantitative syntheses specifically targeting the structural correlates of creativity remain sparse. Consequently, this study utilized activation likelihood estimation (ALE) to perform a meta-analysis aimed at identifying consistent gray matter regions implicated in creative cognition. This was complemented by subsequent task-based meta-analytic connectivity modeling (MACM) and resting-state functional connectivity (RSFC) analyses. The ALE meta-analysis, encompassing 25 structural studies, revealed a convergent anatomical framework involving the superior frontal gyrus (SFG), middle frontal gyrus (MFG), paracentral lobule (PCL), and cingulate gyrus (CG). Additionally, MACM analyses uncovered co-activation networks linking these regions with both the default mode network (DMN) and executive control network (ECN). Further RSFC evaluations corroborated these findings, confirming the previously identified couplings within DMN and ECN, while additionally highlighting significant engagement of the salience network (SN) and sensorimotor network (SMN) related to creativity. These insights support the triple-network hypothesis of creativity, emphasizing particularly the novel role of the SMN, and provide crucial neuroimaging evidence that enriches our understanding of the cognitive mechanisms facilitating creativity.

PMID:42785491 | DOI:10.1016/j.neuroimage.2026.122254

Neuroimage. 2026 Sep 24:122258. doi: 10.1016/j.neuroimage.2026.122258. Online ahead of print.

ABSTRACT

The anterior cingulate cortex (ACC) coordinates internally oriented, salience-related and control processes, and hence may be involved in addictive behaviours. Its role in internet gaming disorder (IGD) remains unclear. We therefore seek to determine whether ACC-related circuits show convergent alterations across complementary levels of functional organisation in IGD. Resting-state functional magnetic resonance imaging (fMRI) data from 45 participants endorsing at least five DSM-5 IGD criteria and 45 matched healthy controls were analysed using all four atlas-defined ACC subregions as seeds to account for the functional heterogeneity of the ACC. We first mapped static functional connectivity differences. Next, we tested whether the implicated pathways showed altered temporal variability using sliding-window dynamic functional connectivity, characterised recurring seed-to-parcel connectivity states, and estimated directed effective connectivity using spectral dynamic causal modelling with parametric empirical Bayes. Compared with healthy controls, individuals with IGD showed reduced static connectivity between the dorsal ACC and two left precuneus clusters, and between the subgenual ACC and a posterior medial calcarine/precuneus cluster. Primary dynamic analyses revealed reduced variability in dorsal ACC connectivity with the left inferior frontal gyrus and left medial superior frontal gyrus, increased variability in subgenual ACC connectivity with the left precuneus/cuneus, and greater occupancy of a ventral attention/default mode-dominant connectivity state. Spectral dynamic causal modelling indicated weaker directed influence from the subgenual ACC to the posterior medial node and from this node to the left inferior frontal gyrus. Together, these findings delineate multilevel alterations in ACC-related posterior medial and frontal control circuitry in IGD, suggesting disrupted coordination across static, dynamic, state-based, and directed dimensions of intrinsic brain organisation.

PMID:42785489 | DOI:10.1016/j.neuroimage.2026.122258

J Affect Disord. 2026 Sep 24:122534. doi: 10.1016/j.jad.2026.122534. Online ahead of print.

ABSTRACT

BACKGROUND: Delusions constitute a cross-diagnostic core symptom of schizophrenia spectrum disorders and correlate with poor functional outcomes. Despite much recent effort successfully mapping neuropsychiatric symptoms to specific brain networks, investigations focusing on network localization of delusions are still scarce.

METHODS: We initially conducted a systematic review of 44 published neuroimaging studies to identify brain regions exhibiting structural and functional alterations associated with delusions. By applying functional connectivity network mapping to normative functional connectomes derived from two independent resting-state fMRI datasets, we mapped these affected brain regions to three delusion networks.

RESULTS: The delusion morphology and task-induced activation abnormality networks were both broadly distributed and had some spatial similarities. In addition to their shared spatial overlap with the ventral attention and somatomotor networks, the delusion morphology abnormality network showed greater spatial overlap with the frontoparietal and dorsal attention networks, while the task-induced activation abnormality network overlapped more extensively with the subcortical and limbic networks. Concurrently, the delusion resting-state activity abnormality network showed the greatest spatial overlap with the default network. In addition, the right opercular part of the inferior frontal gyrus, the right anterior agranular insula complex, and the right anterior portion of the superior temporal gyrus exhibited functional connectivity profiles with the highest spatial similarity to these delusion network probability maps and were therefore considered potential neuromodulation targets.

CONCLUSIONS: Aside from elucidating the neurobiological mechanism underlying delusions from a network perspective, our findings potentially inform the development of reliable biomarkers and targeted treatments for delusions.

PMID:42785384 | DOI:10.1016/j.jad.2026.122534