Most recent paper

Metab Brain Dis. 2026 Jun 25;41(1):142. doi: 10.1007/s11011-026-01903-y.

ABSTRACT

This study longitudinally investigated LT's impact on cerebral function in MHE patients using rs-fMRI. Twenty patients underwent neuropsychological tests, clinical assessments and rs-fMRI before and one month after LT. Regional homogeneity (ReHo) and Granger causality analysis (GCA) were employed to evaluate alterations in local neural activity and effective connectivity before and after surgery. Pearson correlation analysis was conducted to examine the relationships between altered neural indices and clinical variables. After LT, ReHo in the left cuneus was significantly increased (p < 0.05). GCA revealed that the left cuneus exerted inhibitory effects on the bilateral superior frontal gyri, middle frontal gyri, right cingulate gyrus, and right precuneus, while the left cuneus experienced facilitatory effects from the right orbital middle frontal gyrus, left middle frontal gyrus, right middle occipital gyrus, and the cortex surrounding the right calcarine. The inhibitory connectivity from the left cuneus to the left middle frontal gyrus (r = 0.509, P = 0.022) and the facilitatory connectivity from the right middle occipital gyrus to the left cuneus (r = 0.468, P = 0.037) were positively correlated with improvements in liver function. These findings suggest LT-induced neural changes may underlie early cognitive recovery in MHE patients.

PMID:42348040 | DOI:10.1007/s11011-026-01903-y

Dev Psychobiol. 2026 Jul;68(4):e70179. doi: 10.1002/dev.70179.

ABSTRACT

Growing evidence in preclinical and clinical models suggests that prenatal cannabis exposure (PCE) is associated with changes in brain functioning and behavior. This observational longitudinal study examines these associations using biological measures of PCE in a sample of Black mother-infant dyads (N = 42), who have historically been underrepresented in developmental neuroimaging studies. Maternal urine samples collected during pregnancy (8-14 weeks of gestation) were assayed for 11-nor-9-carboxy-Δ9-tetrahydrocannabinol (COOH-THC) metabolites, providing a biologically verified measure of prenatal cannabis exposure. Newborns (57% female) completed a resting-state fMRI scan and were assessed using the NICU Network Neurobehavioral Scale at approximately 1 month postpartum. We performed voxelwise seed connectivity analyses using seeds in the bilateral hippocampus, insula, and caudate. We found that COOH-THC levels in early pregnancy were significantly associated with altered connectivity patterns in the hippocampus, insula, and caudate in infants. These functional connectivity patterns, however, were not correlated with indices of newborn neurobehavior. These preliminary results suggest that cannabis exposure early in pregnancy may impact neural connectivity shortly after birth, with effects that withstand the influence of co-occurring maternal psychosocial factors.

PMID:42347765 | DOI:10.1002/dev.70179

J Intell. 2026 Jun 1;14(6):94. doi: 10.3390/jintelligence14060094.

ABSTRACT

BACKGROUND: Trait creativity is linked to brain functional connectivity, but prior studies have focused on isolated networks, neglecting whole-brain architecture. Extraversion overlaps with creativity, yet its neural mechanisms remain unclear.

OBJECTIVE: Our objective was to investigate whether whole-brain functional network modularity (Q) mediates the relationship between extraversion and trait creativity.

METHODS: Forty-three healthy university students underwent resting-state fMRI and completed extraversion and creativity scales. Whole-brain functional networks were constructed using the AAL atlas. Modularity (Q) was computed from binary networks. Bivariate correlations and mediation analysis were performed.

RESULTS: Extraversion correlated positively with creativity (r = 0.38, p = .011) and modularity (r = 0.37, p = .014). Modularity correlated positively with creativity (r = 0.41, p = .007). Mediation analysis revealed a significant indirect effect of extraversion on creativity through modularity (ab = 0.113, 95% CI [0.005, 0.275]), with a non-significant direct effect.

CONCLUSIONS: Whole-brain network modularity statistically mediates the extraversion-creativity relationship. Higher extraversion is associated with increased modularity, which in turn is associated with higher creativity. These findings provide preliminary associative evidence for a brain network basis linking personality to trait creativity. The results reflect cross-sectional statistical patterns and require replication in larger, longitudinal samples.

PMID:42346709 | DOI:10.3390/jintelligence14060094

Imaging Neurosci (Camb). 2025 Dec 11;3:IMAG.a.1060. doi: 10.1162/IMAG.a.1060. eCollection 2025.

ABSTRACT

One of the major obstacles to the clinical application of resting-state functional magnetic resonance imaging (rs-fMRI) is the complex nature of its measurements, which limits interpretability. An approach to enhance the interpretability of the rs-fMRI metrics is to link them to more fundamental brain physiology, especially cerebral metabolism. Previous studies have established associations between glucose metabolism (CMRglu) and rs-fMRI measurements. In spite of this, oxidative metabolism (CMRO2) is more closely related to cerebral blood flow (CBF) and thus the blood-oxygenation level-dependent (BOLD) signal, and its relationship with CMRglu is complex. Additionally, most currently published rs-fMRI metrics are uncorrected for macrovascular contribution, which may obscure the neuronal contributions. In this study, we measured resting CMRO2 (along with the oxygen extraction fraction, OEF, and cerebral blood flow, CBF) using gas-free calibrated fMRI. We used linear mixed-effects (LME) models to examine associations between CMRO2 and various rs-fMRI metrics before and after macrovascular correction. We found that (1) significant associations existed between CMRO2 and multiple rs-fMRI metrics, with the strongest association found for the global functional density (gFCD) and the weakest for seed-based functional connectivity (FC); (2) associations with rs-fMRI metrics also varied for OEF and CBF; (3) significant sex differences were observed in the above associations; (4) the use of macrovascular correction substantially strengthened the goodness fit of all LME models examined. The latter improvement further validates the use of macrovascular correction in rs-fMRI. These results provide a framework for linking rs-fMRI metrics to fundamental brain physiology, thus improving interpretability of rs-fMRI measurements. This is the first study to formally link whole-brain MRI-based baseline CMRO2 and rs-fMRI metrics, and helps to push the envelope for rs-fMRI in future clinical applications.

PMID:42344994 | PMC:PMC13288501 | DOI:10.1162/IMAG.a.1060

Imaging Neurosci (Camb). 2025 Dec 5;3:IMAG.a.1044. doi: 10.1162/IMAG.a.1044. eCollection 2025.

ABSTRACT

Functional Magnetic Resonance Imaging (fMRI) is commonly used to localize brain regions activated during a task. Methods have been developed for constructing confidence regions of image excursion sets, allowing inference on brain regions exceeding non-zero activation thresholds. However, these methods have been limited to a single predefined threshold and brain volume data, overlooking more sensitive cortical surface analyses. We present an approach that constructs simultaneous confidence regions (SCRs) which are valid for all possible activation thresholds and are applicable to both volume and surface data. This approach is based on a recent method that constructs SCRs from simultaneous confidence bands (SCBs), obtained by using the bootstrap on 1D and 2D images. To extend this method to fMRI studies, we evaluate the validity of the bootstrap with fMRI data through extensive 2D simulations. Six bootstrap variants, including the nonparametric bootstrap and multiplier bootstrap, are compared. The Rademacher multiplier bootstrap-t performs the best, achieving a coverage rate close to the nominal level with sample sizes as low as 10. We further validate our approach using realistic noise simulations obtained by resampling resting-state 3D fMRI data, a technique that has become the gold standard in the field. Moreover, our implementation handles data of any dimension and is equipped with interactive visualization tools designed for fMRI analysis. We apply our approach to task fMRI volume data and surface data from the Human Connectome Project, showcasing the method's utility.

PMID:42344992 | PMC:PMC13288502 | DOI:10.1162/IMAG.a.1044

F1000Res. 2026 May 28;15:830. doi: 10.12688/f1000research.181680.1. eCollection 2026.

ABSTRACT

BACKGROUND: Obesity and type 2 diabetes mellitus (T2DM) are associated with accelerated brain atrophy, white matter microstructural disruption, and resting-state functional network dysconnectivity in elderly adults, driven by converging vascular, neuroinflammatory, and insulin-resistance mechanisms. Yoga is a recognized mind-body intervention with documented benefits for glycaemic control, vascular health, and neurocognitive function; however, no study has yet employed multimodal MR neuroimaging to systematically characterize these brain alterations in an elderly obese-diabetic population or to evaluate yoga-induced neuroplasticity within this cohort.

METHODS: This three-phase, prospective protocol will be conducted at Kasturba Hospital and the Center for Integrative Medicine and Research, Manipal Academy of Higher Education, Manipal, India. Phase 1 is a case-control study (n = 80; 40 obese-diabetic, 40 obese-non-diabetic; age 60-80 years) employing carotid Doppler ultrasonography, T1-weighted voxel-based morphometry and region-of-interest segmentation (SPM12/CAT12/AAL3), diffusion tensor imaging with ROI-based tractography (ExploreDTI), and resting-state fMRI (CONN toolbox), alongside the Eriksen Flanker and N-Back cognitive tasks. Phase 2 involves the systematic development and expert content-validation of a structured, AYUSH-compliant yoga module tailored for elderly obese-diabetic adults. Phase 3 applies the validated module in a 6-month pre-post intervention, with objective adherence monitoring via triaxial accelerometry and repeat of the full Phase 1 neuroimaging and cognitive battery.

DISCUSSION: This protocol addresses a critical gap in the yoga-neuroimaging literature by providing a multimodal, multi-phase framework to characterize neurovascular disease burden and evaluate structured yoga as a neurobiologically informed lifestyle intervention in a high-risk elderly population. Findings will inform AYUSH clinical guidelines, geriatric NCD prevention programs, and future randomized controlled trials.

PMID:42344431 | PMC:PMC13287981 | DOI:10.12688/f1000research.181680.1

Front Neurol. 2026 Jun 9;17:1797576. doi: 10.3389/fneur.2026.1797576. eCollection 2026.

ABSTRACT

BACKGROUND: Clinical diagnosis of prolonged disorders of consciousness (pDoC) relies primarily on behavioral scales, which lack sensitivity to covert cerebral cognitive activity and carry a risk of misdiagnosis. Few studies integrate structural and functional brain abnormalities to explore pDoC. The objective of this study was to employ resting-state functional magnetic resonance imaging (rs-fMRI) with diffusion tensor imaging (DTI) to delineate multimodal neuroimaging abnormalities in pDoC, clarify its neural mechanisms, and identify potential neuroimaging biomarkers.

METHODS: Eighteen patients with pDoC and 20 healthy controls (HCs) underwent rs-fMRI and DTI acquisition. Key metrics included fractional anisotropy (FA), amplitude of low-frequency fluctuations (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo), and functional connectivity (FC). Correlations between these metrics and Coma Recovery Scale-Revised (CRS-R) scores were analyzed.

RESULTS: Compared with HCs, pDoC patients exhibited reduced FA in the left anterior corona radiata (ACR-L) (p < 0.05), altered ALFF/fALFF/ReHo in prefrontal, cerebellar, and limbic regions, and disrupted FC within higher-order cortical networks. CRS-R scores positively correlated with ACR-L FA and prefrontal ReHo, and negatively correlated with cerebellar and limbic hyperactivity (p < 0.05).

CONCLUSION: Patients with pDoC demonstrate three simultaneous tiers of pathological co-alterations: extensive white matter structural disruption with peak significance in ACR-L; disintegration of higher-order cortical networks; patterns of hyperactivity and hyperconnectivity in the cerebellum, limbic system, and angular gyrus. Our findings provide a framework for understanding the pathophysiological mechanisms underlying consciousness impairment in pDoC. The neuroimaging biomarkers found in this study facilitate objective pDoC assessment and prognostic evaluation.

PMID:42344000 | PMC:PMC13286801 | DOI:10.3389/fneur.2026.1797576

Brain Res Bull. 2026 Jun 24:112022. doi: 10.1016/j.brainresbull.2026.112022. Online ahead of print.

ABSTRACT

BACKGROUND: To explore the functionally disordered regions and the directed effective-connectivity relationships among them in Internet Gaming Disorder (IGD), we adopted a meta-analysis-based Dynamic Causal Modeling approach.

METHODS: We first performed a meta-analysis of existing rs-fMRI literature using Anisotropic Effect Size Signature Differential Mapping (AES-SDM) to localize the consistent regions with functional changes, which were then defined as regions of interest (ROIs). Next, we collected resting-state fMRI data and IGD-related scale scores from 54 IGD patients and 46 healthy controls, extracted the neuronal time series (BOLD time series) and input them into spectral Dynamic Causal Modeling (spDCM), and characterized between-group changes in effective connectivity (EC) between the ROIs through Parametric Empirical Bayes (PEB) analysis.

RESULTS: In the IGD group, SFGdor_R showed reduced inhibitory effective connectivity with IFGopercular_L, IFGorb_L, and INS_R, and IFGorb_L also exhibited attenuated self-inhibition; in addition, an exploratory internally validated prediction analysis suggested that the IFGorb_L self-connection was associated with IAT severity.

CONCLUSIONS: These findings indicate altered frontal effective-connectivity patterns consistent with reduced top-down regulatory signaling, rather than definitive evidence of a causal biological mechanism. The internally validated prediction of IAT severity was exploratory, explained a modest proportion of variance, and requires confirmation in larger longitudinal studies with external validation.

PMID:42341846 | DOI:10.1016/j.brainresbull.2026.112022

Cereb Cortex. 2026 Jun 2;36(6):bhag077. doi: 10.1093/cercor/bhag077.

ABSTRACT

Adult brain regions differ in the intrinsic timescales (INT) over which they integrate information. This spatial organization appears to emerge gradually: infants' brain activity recorded during sleep with functional magnetic resonance imaging (fMRI) shows overall longer INT and a different spatial structure. However, since fMRI is sensitive to hemodynamic confounds and is affected by arousal state, these factors may have accounted for observed age-related differences. Here, we used electroencephalography (EEG) to investigate for the first time how INT develop in infancy in a longitudinal sample from 6 to 16-months-old (exploratory cohort, n = 45; validation cohort, n = 45) and adults (n = 10). Infants were awake and engaged in baseline visual protocol, and adults were recorded under comparable (and distinct) conditions. Infant intrinsic timescales shortened from 6 to 16-months but remained longer than those of adults at all ages. Finally, INT correlated with alpha lagged coherence, a metric of self-predictability and, to lesser extent, with alpha peak frequency, suggesting that alpha oscillatory activity may contribute to the emergence of INT. Identifying the mechanisms underlying longer INT early in infancy-a finding replicated across fMRI and EEG-is a crucial step toward understanding the neural computations that allow infants to extract and learn patterns from their environment.

PMID:42341187 | DOI:10.1093/cercor/bhag077

Cereb Cortex. 2026 Jun 2;36(6):bhag088. doi: 10.1093/cercor/bhag088.

ABSTRACT

The posterior superior temporal sulcus (pSTS) processes information from the eyes and the mouth that support social perception. To investigate the laterality of how these mechanisms function, we performed three experiments on lip and eye-gaze discrimination. In Experiment 1, participants (n = 18) performed lip-position and eye-gaze discrimination tasks in static facial expressions while transcranial magnetic stimulation (TMS) was delivered over the left and right pSTS. Results showed a double dissociation in which disruption of the left pSTS impaired the lip-position task, while disruption of the right pSTS impaired the eye-gaze matching task. In Experiment 2, participants (n = 16) performed a lip-reading task using dynamic video clips of a speaker while TMS was delivered over the left and right pSTS. Task performance was impaired when TMS was delivered over the left pSTS only. In Experiment 3, participants (n = 256) underwent resting-state functional magnetic resonance imaging. Results demonstrated that the left pSTS exhibited greater connectivity to language processing brain areas in the left hemisphere. In contrast, the right pSTS exhibited greater connectivity to visual areas specialized for face processing and spatial attention processing. Our study suggests that lip and eye-gaze discrimination are preferentially lateralized across the bilateral pSTS.

PMID:42341185 | DOI:10.1093/cercor/bhag088

Elife. 2026 Jun 24;15:RP110294. doi: 10.7554/eLife.110294.

ABSTRACT

Arousal fluctuates continuously during wakefulness, yet how these moment-to-moment variations shape large-scale functional connectivity (FC) remains unclear. Here, we combined 7T fMRI with concurrent pupillometry to quantify, for every functional connection, how time-varying FC covaries with spontaneous arousal in the awake human brain. Rather than exerting a uniform influence across the connectome, arousal organized FC into a low-dimensional set of seven connectivity communities, each defined by characteristic network compositions. These communities exhibited systematic hemispheric asymmetries, specifically identifying a 'left-hemisphere centripetal architecture' where the left hemisphere serves as a structural sink for the asymmetric convergence of arousal-modulated signals. Importantly, hemispheric asymmetry did not arise from global shifts in connectivity strength but instead reflected structured spatial heterogeneity embedded within community architecture. This modular and asymmetric organization was highly preserved during naturalistic movie watching, indicating that arousal-related modulation of FC reflects intrinsic principles that generalize across awake cognitive contexts. Together, these findings demonstrate that moment-to-moment arousal fluctuations shape large-scale FC through structured, hemispherically asymmetric network organization during wakefulness.

PMID:42339870 | DOI:10.7554/eLife.110294

Front Neurosci. 2026 Jun 8;20:1746322. doi: 10.3389/fnins.2026.1746322. eCollection 2026.

ABSTRACT

Narcolepsy type 1 (NT1) is characterized by profound sleep-wake state instability, pointing to a fundamental dysregulation of large-scale brain network dynamics. To elucidate this, we assessed whole-brain dynamic functional connectivity (dFC) stability using resting-state fMRI in 27 patients with NT1 and 25 matched healthy controls. Our analysis revealed a pattern of opposing alterations: patients exhibited significantly increased dFC stability within the bilateral somatomotor network (SMN), concurrent with decreased stability in the medial prefrontal default mode network (Default_PFCm). These opposing alterations were clinically relevant, as increased SMN stability correlated with poorer objective sleep efficiency, and decreased Default_PFCm stability was similarly associated with lower objective sleep efficiency. Here, we identify for the first time this coexisting neural signature of SMN hyper-stability and Default_PFCm instability in NT1. By simultaneously destabilizing higher-order cognitive networks and disinhibiting primary sensorimotor processing, orexin deficiency may contribute to a synergistic dysregulation that blurs sleep-wake boundaries. The divergence in dynamic network stability provides a novel systems-level framework for understanding state instability in NT1.

PMID:42338794 | PMC:PMC13284077 | DOI:10.3389/fnins.2026.1746322

Front Cognit. 2026 May 5;5:1767179. doi: 10.3389/fcogn.2026.1767179. eCollection 2026.

ABSTRACT

INTRODUCTION: There has been increasing attention to differences in function along the hippocampal long axis, with the posterior hippocampus proposed to have more variable signals that are well-suited to representing idiosyncratic details in memory, and the anterior hippocampus having less dynamic signals that are well-suited to integration. Whether long axis functional specialization persists into older age is not well-understood, despite known age-related declines in the level of detail in memories.

METHODS: We used a large database of resting state fMRI data (n = 337 humans of both sexes included) from across the adult lifespan (ages 18-88) to determine the degree of functional differentiation across the hippocampal posterior-anterior axis. Our first approach was to measure the correlation of signals within hippocampal subregions. Our second approach was to measure functional connectivity between hippocampal subregions and the rest of the brain. For both approaches, we tested how well functional differences along the hippocampal long axis accounted for individual and age differences in episodic memory.

RESULTS: Within the hippocampus, we found a more positive age slope (i.e., increasing similarity of signals) for the most posterior hippocampal region compared to the intermediate and anterior region, consistent with the posterior hippocampus losing some of its heterogeneous signaling in older age. Patterns of whole-brain connectivity showed significant differences in the age trajectories between hippocampal subregions for a number of target regions, including several frontal connections. Yet we did not find strong evidence that either within-hippocampal signals or differences in functional connectivity were associated with age-related episodic memory decline.

CONCLUSION: Age differences in hippocampal long axis functional organization were apparent during rest but were limited in how well they accounted for memory decline.

PMID:42338776 | PMC:PMC13271125 | DOI:10.3389/fcogn.2026.1767179

J Eat Disord. 2026 Jun 23. doi: 10.1186/s40337-026-01671-1. Online ahead of print.

ABSTRACT

BACKGROUND: Growing evidence indicates that bulimia nervosa (BN) is more likely driven by network-level dysfunctions rather than abnormalities in isolated brain regions. However, previous studies focusing on specific regions or connectivity features have led to a limited understanding of the complexity and integrality of network in BN. This study aimed to investigate large- and mesoscale network alterations in BN from the perspective of network segregation and integration.

METHODS: Using resting-state functional magnetic resonance imaging data from 85 BN patients and 71 healthy controls (HCs) matched for age, sex, and education, we applied a graph-theoretic framework to analyze functional network architecture in BN. Specifically, we examined group differences in within- and between-system functional connectivity (FC) as well as system segregation at both the whole-brain and system levels. Associations between network measures and clinical features were further explored.

RESULTS: Compared with HCs, BN patients exhibited whole-brain reduced within- and between-system FC accompanied by increased system segregation. At the system level, patients showed increased between-system FC of the default mode network (DMN), control network and ventral attention network, along with decreased DMN system segregation. The increased integration of DMN with other systems was associated with higher Beck Depression Inventory (BDI-21) scores in BN patients.

CONCLUSIONS: The neural mechanisms of BN involve an imbalance between network segregation and integration at both global and system levels, most pronounced within the DMN, whose alterations are associated with depression and disordered eating behavior. These findings may provide potential neural substrates for some core behavioral deficits in BN.

PMID:42337633 | DOI:10.1186/s40337-026-01671-1

Brain Topogr. 2026 Jun 23;39(5):71. doi: 10.1007/s10548-026-01228-0.

ABSTRACT

Brain aging is characterized by complex alterations in both anatomical structure and neural function. While the interdependence between structural connectivity (SC) and functional connectivity (FC) is well-established, the patterns of structural-functional coupling (SFC) during aging remain largely unexplored, despite being crucial for elucidating the neural mechanisms of age-related changes. Moreover, traditional resting-state fMRI studies have predominantly focused on linear correlations, often overlooking nonlinear causal interactions that may play a pivotal role in the aging brain. To address this, we employed a Nonlinear Granger Causality (NGC) model to investigate SFC at the whole-brain level. The study included 227 healthy participants, stratified into a young group (20-35 years, [Formula: see text]) and an older group (59-77 years, [Formula: see text]), with further subgrouping by sex. We analyzed SFC from both static and dynamic perspectives at regional and subnetwork levels. Our results demonstrated that the young group exhibited significantly stronger NGC-based SFC compared to the sex-matched older group. Additionally, males displayed a higher proportion of strong SFC connections than age-matched females. Notably, a widespread age-related decline in nonlinear causal coupling was observed across both regional and subnetwork scales, particularly within networks governing cognitive control and attention. Furthermore, dynamic analyses across sliding windows confirmed the persistence of these aging patterns throughout the scanning duration, despite increased temporal variability observed in the elderly. This study underscores the importance of incorporating nonlinear causal relationships into brain network research, as this approach offers deeper insights into the potential mechanisms underlying age-related cognitive decline and neurodegenerative processes.

PMID:42334649 | DOI:10.1007/s10548-026-01228-0

Acta Neurochir (Wien). 2026 Jun 23. doi: 10.1007/s00701-026-06926-z. Online ahead of print.

ABSTRACT

BACKGROUND: Cognitive impairment following skull base meningioma resection remains poorly understood. This prospective study aimed to investigate the cognitive function alterations and resting-state fMRI (rs-fMRI) characteristics in patients undergoing extradural subtemporal approach meningioma resection.

METHODS: This study enrolled 23 right-handed primary petroclival meningioma patients from June 2024 to November 2024. Participants underwent cognitive assessments combined with rs-fMRI scans at three time points (Time1: one day before surgery; Time2: one week after surgery; and Time3: three months after surgery), utilizing comprehensive test scales including the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Symbol Digit Modalities Test (SDMT) and Trail Making Test (TMT-A & TMT-B). Alterations of low-frequency fluctuations (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo), and functional connectivity (FC) were calculated. Patient demographic characteristics, medical records, and neuroimaging data were systematically collected and analyzed. Independent samples t-tests, Mann-Whitney U tests, Fisher's exact tests and paired samples t-tests were used in statistical analysis.

RESULTS: 13 patients were in the non-dominant side (NDS) group, and 10 patients were in the dominant side (DS) group. There were no statistically significant differences in preoperative baseline (Time1) clinical characteristics and preoperative cognitive assessment outcomes between the two groups. Patients in the DS group showed marked decline in MMSE (mean Δ = -6.4 points, corrected p = 0.009), MoCA (mean Δ = -5.1 points, corrected p = 0.047), and SDMT scores (mean Δ = -17.8 points, corrected p = 0.003), along with prolonged TMT-A completion times (mean Δ = + 32.7 s, corrected p = 0.017) at Time2. Six patients (60%) showed significant cognitive decline, while four patients (40%) maintained cognitive performance stable. Patients in the NDS group showed no significant postoperative cognitive decline. The rs-fMRI analysis revealed three characteristic alterations in cognition impaired patients: decreased ALFF in left thalamus, reduced ReHo in left middle temporal gyrus and lowered fALFF in left middle frontal gyrus (all p < 0.05). Significant weakening of functional connectivity between these regions and cerebellar networks were observed, and they show marked improvement in parallel with cognitive recovery at three months postoperatively.

CONCLUSIONS: Patients undergoing dominant hemisphere extradural subtemporal approach for petroclival meningioma resection showed a propensity for transient postoperative declines in verbal memory, orientation, and executive function. These cognitive changes were associated with reduced spontaneous cortical activity and attenuated functional connectivity within cerebello-cortical and cerebello-subcortical networks. Both cognitive performance and these neural alterations demonstrated improvement at the three-month postoperative follow-up, these preliminary observations await further validation in larger independent cohorts.

PMID:42334641 | DOI:10.1007/s00701-026-06926-z

BMC Med Imaging. 2026 Jun 22. doi: 10.1186/s12880-026-02514-w. Online ahead of print.

ABSTRACT

BACKGROUND: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized primarily by social communication deficits and repetitive stereotyped behaviors. Its objective diagnosis has long relied on clinical scale assessments, lacking automated tools based on brain imaging.

METHOD: This study proposes an ASD auxiliary diagnostic framework integrating conditional generative adversarial network (conditional GAN, cGAN) data augmentation, multimodal feature fusion, and explainable deep learning, based on the ABIDE I/II multi-center public datasets. First, functional connectivity matrices of AAL-116 brain regions were extracted from resting-state functional magnetic resonance imaging (rs-fMRI), and cortical morphological features were derived from structural magnetic resonance imaging (sMRI). Multi-site scanning biases were corrected using the ComBat method. On this basis, minority class samples were augmented using class-conditional GAN, followed by multimodal information fusion via a dual-branch encoder and cross-attention mechanism, ultimately outputting classification decisions between ASD and typically developing (TD) subjects.

RESULTS: Experimental results demonstrate that, under stratified five-fold cross-validation, the proposed method achieved an AUC of 0.871 ± 0.016 and a balanced accuracy of 0.797 ± 0.012 on the full multimodal sample set, representing improvements of 13.2% and 9.2% over single sMRI and rs-fMRI modalities, respectively. Leave-one-site-out (LOSO) cross-validation yielded an average AUC of 0.783 ± 0.041, validating the model's cross-center generalization capability.

CONCLUSION: Explainability analysis based on Integrated Gradients revealed that the default mode network and social brain regions are key decision bases for distinguishing ASD from TD, highly consistent with existing neurobiological evidence.

CLINICAL TRIAL: Not applicable.

PMID:42332578 | DOI:10.1186/s12880-026-02514-w

J Invest Dermatol. 2026 Jun 22:S0022-202X(26)02624-2. doi: 10.1016/j.jid.2026.05.035. Online ahead of print.

NO ABSTRACT

PMID:42331309 | DOI:10.1016/j.jid.2026.05.035

Biol Psychiatry Cogn Neurosci Neuroimaging. 2026 Jun 22:S2451-9022(26)00179-5. doi: 10.1016/j.bpsc.2026.06.004. Online ahead of print.

ABSTRACT

BACKGROUND: Estradiol (E2) is associated with enhanced alcohol-related reward. Childhood maltreatment may potentiate its effects, particularly in women. There is a gap in the literature exploring the mechanistic effects of E on alcohol use and reward neurocircuitry, particularly in trauma-exposed women. We hypothesized that women would show an increase in alcohol use and craving immediately before ovulation, exacerbated by childhood maltreatment, and stronger effects of exogenous E2 on reward circuits.

METHODS: Participants were n=91 largely trauma-exposed, naturally cycling women characterized by low alcohol use and craving, recruited from the greater Atlanta area, enrolled in a randomized double-blind within-subjects crossover clinical trial of transdermal E2 as part of the Grady Trauma Project. Participants rated their alcohol use and craving nightly over the course of a full menstrual cycle, using ecological momentary assessment (1,765 responses). Interacting effects of childhood maltreatment and menstrual cycle phase on alcohol use and craving were modeled using zero-inflated Poisson regressions. A subset was then randomized to receive transdermal E2 or placebo during resting state fMRI and crossed over to the other condition on a subsequent cycle (n=49).

RESULTS: Findings supported a preovulatory increase in alcohol craving (β=0.63, p=0.03). An increase around ovulation was blunted in women with higher childhood maltreatment, among whom ovulatory alcohol craving decreased (β=-0.05, p=0.02). Exogenous E2 administration produced changes in resting-state functional connectivity between the VTA and insula among participants who exhibited cycle-dependent alcohol craving.

CONCLUSIONS: Findings suggest that the endogenous preovulatory E2 peak enhances alcohol craving, but that childhood maltreatment may blunt this effect. Neuroendocrine Risk for PTSD in Women, https://clinicaltrials.gov/study/NCT03973229, NCT03973229.

PMID:42331099 | DOI:10.1016/j.bpsc.2026.06.004

Neuron. 2026 Jun 22:S0896-6273(26)00412-5. doi: 10.1016/j.neuron.2026.05.020. Online ahead of print.

ABSTRACT

Precision functional mapping (PFM) enables the individual-level characterization of brain network organization but requires substantially more and higher-quality fMRI data than is standard. Despite the growing use of PFM, the objective criteria for data sufficiency and the quality needed to ensure interpretable and replicable individual-level results remain unclear. Here, we introduce the network similarity index (NSI), an objective measure of the extent to which functional connectivity (FC) patterns express the large-scale network structure required for PFM. The NSI captures low-spatial-frequency, coherent network organization and denoising fidelity, and it aligns closely with blinded expert assessments of PFM usability. The NSI also accounts for the variability in the rate at which FC becomes reliable across individuals. This NeuroResource provides an open source framework for NSI-based data quality evaluation and models linking NSI values with expert-judged PFM suitability. This framework can inform expected returns from additional data collection, thus enabling principled decisions about data sufficiency and replication in precision fMRI research.

PMID:42330956 | DOI:10.1016/j.neuron.2026.05.020