Most recent paper

Eur J Nucl Med Mol Imaging. 2026 Jul 6. doi: 10.1007/s00259-026-08053-4. Online ahead of print.

ABSTRACT

PURPOSE: Dopaminergic signalling and glucose metabolism have been implicated in autism spectrum disorder (ASD), yet in vivo evidence in the human brain remains largely unexplored. This study examined subcortical dopamine D2 receptor availability and glucose metabolism in ASD to assess their clinical relevance.

METHODS: In this dual-tracer PET/MR case-control study, 30 autistic and 30 neurotypical adults (age-, sex-, body mass index-, and IQ-matched) underwent [11C]raclopride PET to assess dopamine D2 receptor availability, [1⁸F]FDG PET to measure glucose metabolism and resting-state fMRI to evaluate functional connectivity.

RESULTS: Autistic individuals demonstrated increased D2 receptor availability in the thalamus, with additional increases in the nucleus accumbens and putamen among autistic males compared to neurotypical males. Glucose metabolism was elevated in the thalamus and globus pallidus in ASD relative to NT, and this pattern persisted within both autistic males and autistic females in sex‑stratified comparisons. Globus pallidus and thalamic glucose metabolism correlated positively with social and communication difficulties. Resting-state fMRI analyses revealed diagnosis- and sex-dependent correlations between thalamic D2 receptor availability and functional connectivity.

CONCLUSIONS: This study provides in vivo evidence of elevated subcortical D2R availability and glucose metabolism in autistic adults, a pattern observed across sexes. We also show that D2R availability is tightly linked to glucose metabolism and that D2R-functional connectivity coupling is altered in ASD, both relative to neurotypical adults and between autistic males and females. These findings highlight dopaminergic mechanisms as potential biomarkers and therapeutic targets in ASD.

PMID:42406073 | DOI:10.1007/s00259-026-08053-4

Neuromodulation. 2026 Jun 15:S1094-7159(26)00618-5. doi: 10.1016/j.neurom.2026.06.460. Online ahead of print.

ABSTRACT

OBJECTIVES: Transcranial focused ultrasound stimulation (TUS) is an emerging neuromodulatory technique capable of modulating cortical and subcortical brain regions with high spatial precision. However, its effects on large-scale functional brain networks and their temporal evolution remain incompletely understood. This study investigated whether brief theta burst TUS induces target-specific alterations in functional brain network topology over the first hour after stimulation.

MATERIALS AND METHODS: A total of 22 healthy participants were randomly assigned to receive TUS targeting either the right inferior frontal cortex (IFC) or the right thalamus. Resting-state functional magnetic resonance imaging was acquired at baseline and at three minutes post stimulation intervals spaced 15 minutes apart. Graph-theoretical analyses quantified four centrality metrics (strength, expected influence, betweenness, and closeness) across 86 brain regions. Global network organization was assessed using small-worldness.

RESULTS: IFC stimulation produced progressive reductions in regional network integration, initially affecting visual cortices and subsequently extending to right prefrontal and temporal regions, the insula, and the putamen, with peak effects occurring approximately 45 minutes post stimulation. IFC stimulation also increased global small-worldness, indicating a shift toward a more randomized network configuration. In contrast, thalamic stimulation resulted in a spatially circumscribed and temporally stable reduction in betweenness centrality within the left precuneus without widespread network alterations.

CONCLUSIONS: Brief theta burst TUS induces target-dependent and temporally evolving changes in large-scale functional brain organization. Cortical stimulation of the IFC produced distributed and progressive network reconfiguration, whereas thalamic stimulation yielded a focal and stable effect. These findings suggest that the magnitude and spatial extent of TUS-induced network modulation depend on the connectivity profile and topologic embedding of the stimulated structure.

PMID:42405921 | DOI:10.1016/j.neurom.2026.06.460

JIMD Rep. 2026 Jul 3;67(4):e70108. doi: 10.1002/jmd2.70108. eCollection 2026 Jul.

ABSTRACT

In early-treated adults with phenylketonuria (PKU), the effects of elevated phenylalanine (Phe) on functional brain networks remain poorly understood. While subacute structural brain changes have been reported, their functional significance remains unclear. Executive and attentional functions have been shown to be particularly sensitive to metabolic control in PKU. In this double-blind, randomized, placebo-controlled crossover trial, we investigated the effects of a 4-week high-Phe period on resting-state functional connectivity using seed-based analyses of the dorsal attention and frontoparietal networks, which are critically involved in executive and attentional functions. Twenty-three adults with PKU (median age 35.3 years [IQR 12.0]; 43% female) were included. When baseline connectivity was considered, no significant differences in functional connectivity were observed between the Phe and placebo periods. Without baseline adjustment, exploratory analyses revealed increased functional connectivity of the right frontal eye field within the dorsal attention network with frontal regions. Changes in functional connectivity were neither associated with changes in metabolite concentrations nor in working memory, attention, or executive function. These findings suggest that subacute increases in Phe may induce subtle and potentially transient changes in functional brain networks, although their functional relevance and persistence over longer exposure periods remain unclear.

PMID:42404601 | PMC:PMC13330130 | DOI:10.1002/jmd2.70108

bioRxiv [Preprint]. 2026 Jun 28:2026.06.23.734045. doi: 10.64898/2026.06.23.734045.

ABSTRACT

This paper presents a framework for modelling the topography of whole-brain connectivity in resting-state functional MRI. The aim is to disentangle functional segregation, which manifests as abrupt changes in connectivity, from so-called gradients, i.e., smooth variations in connectivity across the brain. Our core assumption is that functional segregation leads to low-rank structure in the dense (point-to-point) connectome, whereas connectivity gradients imply a sparse and non-low-rank structure in the dense connectome. Our method thus decomposes the connectome into low-rank and sparse components, enabling the integration of local-nonlinear and global-linear embedding strategies. We show that this hybrid model approximates the empirical dense connectome more effectively than purely low-rank or purely gradient approaches. We also find that connectivity gradients derived from this model exhibit strong correspondence with task-based topographic maps. We hope that this approach can provide insight into the organisational principles of brain regions where gradients remain poorly characterised.

PMID:42395476 | PMC:PMC13320991 | DOI:10.64898/2026.06.23.734045

Res Sq [Preprint]. 2026 Jun 28:rs.3.rs-9557211. doi: 10.21203/rs.3.rs-9557211/v1.

ABSTRACT

Neuroimaging studies rarely test whether the variance structure is equivalent across population subgroups. Here, in 4,736 participants from the Adolescent Brain Cognitive Development (ABCD) cohort, we examine racialized heteroscedasticity (i.e., differences in variance across racialized groups) in neuroimaging and behavioral data and test how these differences in variance propagate into predictive modeling. Across neuroimaging modalities, behaviors, and predictive frameworks, variance differences exhibited consistent patterns, indicating that variance structure is a stable property across domains within the dataset. Simulation analyses demonstrated that such differences directly induce subgroup disparities in prediction error and reliability, even in the absence of mean differences. Across neuroimaging modalities, multiple measures demonstrated greater variance in Black participants, particularly in functional imaging modalities. Similar variance patterns were observed in behavioral measures, and predictive models exhibited greater residual dispersion and prediction variance in Black participants even when overall performance metrics were comparable. These findings position variance structure, rather than central tendency, as a critical determinant of model performance, generalizability, and reliability across diverse populations.

PMID:42396488 | PMC:PMC13321234 | DOI:10.21203/rs.3.rs-9557211/v1

Res Sq [Preprint]. 2026 Jun 25:rs.3.rs-9773701. doi: 10.21203/rs.3.rs-9773701/v1.

ABSTRACT

Major Depressive Disorder (MDD) involves large-scale brain network disruption at rest. Canonical zero-lag functional connectivity methods often miss temporal offsets (or "lags") in interactions. Lag-adjusted functional connectivity captures intrinsic neural timescales (INTs) and directional signaling, offering a more sensitive framework to characterize network-level alterations. Here, we applied the NeuroMark framework to resting-state scans from 235 MDD and 284 healthy controls, identifying 105 intrinsic connectivity networks (ICNs) and their time series. To enable sub-TR estimation, time series were upsampled to 100 ms resolution. Lag-adjusted connectivity was computed as the maximal cross-correlation for each ICN pair within a ±2s window sampled at 0.1s intervals. Group differences were assessed using a regression model. Significant differences emerged between groups (p<0.05). Specifically, MDD revealed hyperconnectivity in salience-sensorimotor and sensorimotor-temporoinsular networks, alongside hypoconnectivity in salience-higher cognitive temporal and frontal networks and temporoparietal-visual systems, indicating altered coordination among sensory, emotional, and cognitive processes. An exploration of the lags revealed a non-random bias in the temporal ordering of networks operating at different INTs. This was characterized by earlier relative cortical coupling in MDD, suggesting compressed inter-network timing. These findings underscore the utility of lag-adjusted approaches for detecting impaired neural coordination, beyond alterations in connectivity strength.

PMID:42396482 | PMC:PMC13321241 | DOI:10.21203/rs.3.rs-9773701/v1

Eur J Nucl Med Mol Imaging. 2026 Jul 4. doi: 10.1007/s00259-026-08023-w. Online ahead of print.

ABSTRACT

AIM: To explore potential neuroimaging features derived from [18F]FDG PET/MRI imaging that may help characterize differences between adolescent with bipolar disorder (BD) and those with major depressive disorder (MDD).

MATERIALS AND METHODS: Patients were grouped based on the Hamilton Depression Scale (HAMD) and Hypomania Check List (HCL), and the severity of suicidal ideation and behavior was assessed. 14 BD and 14 MDD adolescent patients were enrolled. Simultaneous PET and MRI data (including 3D T1-weighted imaging, Diffusion Tensor Imaging (DTI), and resting-state functional MRI (fMRI)) were acquired. Functional connectivity (FC) and structural connectivity (SC) were derived from fMRI and DTI respectively. A multiple linear regression model was employed to predict FC from SC. SC-FC coupling was defined as Pearson correlation coefficient between predicted FC and original FC. Using cerebellar gray matter uptake as reference region, standardized uptake value ratio (SUVr) of each brain region was calculated as metabolic parameter.

RESULTS: Compared with the MDD group, the BD group showed significantly decreased SC-FC coupling and glucose metabolism in the thalamus. ‌In the BD group, SC-FC coupling in the paracentral lobule showed a significant positive correlation with metabolism (r = 0.70). In the MDD group, SC-FC coupling in cingulate gyrus showed a significant negative correlation with metabolism (r=-0.73). ‌In the BD group, SC-FC coupling in superior parietal lobule, postcentral gyrus, and precentral gyrus correlated significantly with HAMD, HCL, and suicide scores, respectively. In the MDD group, SC-FC coupling in precentral gyrus, orbital gyrus, and hippocampus showed the highest correlations with these clinical indicators. The middle temporal gyrus and parahippocampal gyrus were specifically associated with suicide scores in the BD group. ‌Notable intergroup differences between BD and MDD were thalamus (AUC = 0.86) and inferior temporal gyrus (AUC = 0.76), with SC-FC coupling features in these regions showing more prominent differences than metabolic features.

CONCLUSION: This study identifies the thalamus as a key region in adolescent BD. Differences in SC-FC coupling in thalamus and inferior temporal gyrus reflect notable exploratory features between adolescent BD and MDD patients, suggesting that SC-FC coupling parameters may represent potential neuroimaging signatures for differential diagnosis. The differences in correlations among SC-FC coupling, metabolism, and clinical parameters between the groups indicate distinct pathogenic mechanisms for BD and MDD.

PMID:42399489 | DOI:10.1007/s00259-026-08023-w

J Affect Disord. 2026 Jul 3:122212. doi: 10.1016/j.jad.2026.122212. Online ahead of print.

ABSTRACT

Although previous resting-state fMRI studies have revealed functional abnormalities in multiple brain regions of obsessive-compulsive disorder (OCD) patients, the underlying pathological mechanisms remain unclear. As the brain constitutes a complex dynamic system, capturing its dynamic features could advance our understanding of neural activity mechanisms. This study employed hidden Markov modeling (HMM) to investigate dynamic alterations in resting-state brain activity among OCD patients, offering a dynamic perspective on the disorder's pathophysiology. A total of 60 OCD patients and 57 healthy controls (HCs) were enrolled. The HMM was used to identify distinct brain states, characterizing their activation patterns. Temporal features of these states and differences in transition patterns between states were compared between the two groups. Compared to HCs, OCD patients spent significantly more time in the state characterized by mildly elevated global activation (p = 0.024, partial η2 = 0.070), while spending less time in the state characterized by high activation level in the auditory network (AUD) and salience network (SN), coupled with low activation level in default mode network (DMN) and frontoparietal network (FPN) (p = 0.030, partial η2 = 0.057). Additionally, OCD patients showed decreased switching rate (p = 0.025, partial η2 = 0.044) and particular difficulty transitioning from States 1, 2, and 5 into the state characterized by high SN and low DMN activation. These findings suggest altered dynamic patterns of brain network activity in OCD, characterized by abnormal temporal occupancy of specific brain states and reduced switching between states. These alterations may be related to salience network dysfunction and could contribute to our understanding of cognitive inflexibility in OCD from a dynamic perspective. However, further studies are needed to establish the specificity and clinical relevance of these findings.

PMID:42398672 | DOI:10.1016/j.jad.2026.122212

Res Sq [Preprint]. 2026 Jun 28:rs.3.rs-10021774. doi: 10.21203/rs.3.rs-10021774/v1.

ABSTRACT

Early-onset psychosis (EOP) is associated with marked cognitive impairment and poorer health-related and psychosocial outcomes compared to adult-onset illness, yet the neural mechanisms underlying these deficits during adolescence remain incompletely understood. Despite evidence implicating dorsolateral prefrontal cortex (dlPFC) dysfunction, the region's functional and structural correlates in youth with EOP are not well characterized. Adolescents with EOP (N=31) and healthy controls (HC; N=20) completed NIH Toolbox cognitive assessments and PROMIS self-reports. Prefrontal function was assessed using functional near-infrared spectroscopy (fNIRS) during a Stroop task and at rest. Multimodal MRI, including resting-state fMRI, diffusion tensor imaging, and structural imaging, was used to examine connectivity and morphology of prefrontal and fronto-cerebellar circuits. Adolescents with EOP exhibited poorer cognitive performance across executive functioning domains compared to HC. fNIRS revealed reduced right dlPFC activation on a cognitive control paradigm (p=0.007) and increased resting-state connectivity between right dlPFC and ventrolateral PFC (p=0.02). Furthermore, resting-state fMRI showed increased dlPFC-striatal connectivity and reduced connectivity with cerebellar Crus I/II (p-FDR<0.05). White matter integrity of the superior longitudinal fasciculus correlated with dlPFC activation during task performance. Structural analyses identified reduced frontal cortical thickness and decreased cerebellar Crus II volumes (p-FWE<0.05) in patients with EOP, with frontal morphology associating with cognitive measures. In summary, cognitive impairment in adolescents with EOP is associated with convergent abnormalities in dlPFC function, fronto-striatal connectivity, and fronto-cerebellar structure. These findings support a model of disrupted prefrontal circuit maturation in EOP and highlight multimodal imaging markers with potential relevance for early identification and targeted intervention.

PMID:42396496 | PMC:PMC13321269 | DOI:10.21203/rs.3.rs-10021774/v1

bioRxiv [Preprint]. 2026 Jun 24:2026.06.19.733190. doi: 10.64898/2026.06.19.733190.

ABSTRACT

Distinguishing healthy brain aging from early neurodegenerative disruption remains a major challenge in Alzheimer's disease. Here, we used resting-state fMRI from the Alzheimer's Disease Neuroimaging Initiative to model large-scale brain-state dynamics relative to a cognitively normal aging reference. A Hidden Markov Model trained exclusively on cognitively normal adults defined latent connectivity states, and a generalized additive model estimated an age-adjusted reference trajectory of transition entropy. Mild cognitive impairment and Alzheimer's disease showed progressively greater deviation from this reference, with the strongest disruption in Alzheimer's disease. A single absolute-deviation score retained much of the predictive information contained in higher-dimensional dynamic features, supporting its use as a compact and interpretable candidate biomarker of altered brain-state organization. These findings suggest that Alzheimer's disease is associated with measurable departure from healthy dynamic brain aging, providing an interpretable framework for future longitudinal and clinically validated studies.

PMID:42395576 | PMC:PMC13320867 | DOI:10.64898/2026.06.19.733190

bioRxiv [Preprint]. 2026 Jun 28:2026.06.25.734567. doi: 10.64898/2026.06.25.734567.

ABSTRACT

Primate brain function relies on distributed cortical networks. These networks are commonly identified through fMRI functional connectivity, defined as the spatial correlation of hemodynamic fluctuations measured at rest. To assess the contribution of distinct neuronal populations to fMRI functional connectivity, we obtained concurrent fMRI and dense single-unit recordings at rest in the macaque. Then, using standard waveform-based classification of action potential shape, we compared the activity of different neural subtypes to the local and brain-wide patterns of fMRI activity. Putative excitatory neurons were functionally intermixed, with approximately half having positive and half negative correlation with the local fMRI signal. By contrast, all putative inhibitory interneurons were positively correlated, with one subclass exhibiting brain-wide correlation that closely matched conventional seed-based functional connectivity. These findings indicate that, although excitatory projection neurons may underpin long-range network communication interneuron activity most closely matches the fMRI fluctuations at the heart of resting functional connectivity.

PMID:42395479 | PMC:PMC13321047 | DOI:10.64898/2026.06.25.734567

Front Neurol. 2026 Jun 18;17:1837032. doi: 10.3389/fneur.2026.1837032. eCollection 2026.

ABSTRACT

BACKGROUND: Herpes simplex virus (HSV) encephalitis is the most common sporadic viral encephalitis, frequently complicated by delirium. Intracranial pressure (ICP) elevation is a common feature, but its role in delirium via brain functional network disruption remains unclear. This study investigated whether surrogate marker of ICP burden (LP opening pressure) mediates delirium in HSV encephalitis by reducing degree centrality (DC), a measure of functional network hub integrity, in key brain regions.

METHODS: In a prospective two-center cohort study (December 2023-November 2025), 55 HSV encephalitis patients and 30 healthy controls underwent clinical assessments, ICP monitoring, and resting-state functional MRI (rs-fMRI). Delirium was evaluated using the Delirium Rating Scale (DRS; ≥12 indicating presence). DC was calculated from rs-fMRI data in regions of interest. Associations were analyzed via logistic regression, ANOVA, linear regression, and mediation models with bootstrapping.

RESULTS: Of 55 patients, 22 (40%) developed delirium. The delirium group had higher LP opening pressure (23.5 ± 4.8 vs. 15.5 ± 3.2 cmH₂O; p < 0.001), lower Glasgow Coma Scale scores, and worse outcomes. Elevated LP opening pressure (≥20 cmH₂O) increased delirium odds (OR 1.86; 95% CI 1.58-2.11; p < 0.001), amplified in subgroups with severe inflammation. DC was reduced in the delirium group in the right amygdala, right hippocampus, left insula, and left precuneus (all p < 0.05 vs. non-delirium and controls). LP opening pressure inversely correlated with DC in these regions (except left insula), and DC inversely correlated with DRS scores. Mediation analyses confirmed partial mediation by DC in the right amygdala (β = 0.129; 95% CI 0.079-0.158; p = 0.031), right hippocampus (β = 0.312; 95% CI 0.277-0.458; p = 0.002), and left precuneus (β = 0.275; 95% CI 0.187-0.398; p = 0.011).

CONCLUSION: Our exploratory findings suggest that LP opening pressure may be partially associated with delirium in HSV encephalitis through reduced degree centrality in limbic and default mode network hubs. As a preliminary investigation, these hypothesis-generating results highlight ICP management and DC as potential imaging biomarkers that warrant further validation in larger, longitudinal studies for delirium risk stratification and prevention.

PMID:42394934 | PMC:PMC13324997 | DOI:10.3389/fneur.2026.1837032

Eur J Phys Rehabil Med. 2026 Jun;62(3):245-253. doi: 10.23736/S1973-9087.26.09367-6.

ABSTRACT

BACKGROUND: Goal setting in stroke rehabilitation requires assessing patients' functional status, which involves both recovery and compensatory processes following stroke, underscoring the importance of identifying valid biomarkers. Functional connectivity measures derived from functional magnetic resonance imaging (fMRI) signals, which reflect underlying biological states, may offer value for characterizing functional status.

AIM: We tested whether functional connectivity correlates with functional status and discriminates post-stroke functional independence.

DESIGN: Observational study.

SETTING: Inpatient rehabilitation ward at Fujita Health University Hospital, Japan.

POPULATION: Fifty-eight patients with stroke.

METHODS: Resting-state fMRI data were used to compute group-sparse inverse covariance matrices, which were negated to estimate partial correlations representing direct functional connectivity. Correlations between connectivity measures and functional independence measure (FIM) scores were examined. Principal component analysis (PCA) was applied to extract dominant connectivity features from connections associated with functional status. Connectivity-based discriminative performance was evaluated using receiver operating characteristic analysis.

RESULTS: Connectome mapping revealed significant positive correlations between total FIM scores and interhemispheric connectivity in homotopic perisylvian regions, including the insulae, superior temporal sulci and temporoparietal junctions. PCA extracted a major connectivity component whose strength demonstrated within-sample discrimination of functional independence. Lesions were predominantly located in subcortical regions.

CONCLUSIONS: The results support a significant association between homotopic functional connectivity within perisylvian, multifunctional regions located at the intersection of lobes and post-stroke daily functioning. Intrinsic interhemispheric functional connectivity, assessed using fMRI, may offer valuable insights into post-stroke functional status.

CLINICAL REHABILITATION IMPACT: These findings highlight a promising direction for developing connectivity-based rehabilitation strategies for stroke-related disability.

PMID:42394539 | DOI:10.23736/S1973-9087.26.09367-6

Transl Psychiatry. 2026 Jul 2. doi: 10.1038/s41398-026-04217-w. Online ahead of print.

ABSTRACT

Cerebellar hypermetabolism measured with FDG-PET is interpreted as maladaptive plasticity, while increased cerebellar functional connectivity reported in fMRI studies indicates a compensatory role. Using Alcohol Use Disorder (AUD) as a neurobiological model, the combination of PET and fMRI examinations can extend our understanding of cerebellar mechanisms underlying brain reorganization within the fronto-thalamo-cerebellar circuit (FCC) supporting executive functions. The aim of the present study was to investigate resting-state functional connectivity (rs-FC) of the cerebellum and to examine its relationship with cerebellar metabolism, thalamic grey matter volume (GM) as a key node of the FCC, and executive functioning. In AUD patients, stronger negative rs-FC was found between the cerebellar lobule VIII seed and voxels in the left superior frontal gyrus compared with HC. Path analysis conducted in AUD patients indicated that cerebellar hypermetabolism was positively related to fronto-cerebellar rs-FC, and that fronto-cerebellar rs-FC was positively related to inhibition performance. In this model, after controlling for thalamic GM abnormalities, cerebellar hypermetabolism negatively impacted inhibition performance through rs-FC. Cerebellar hypermetabolism disrupts negative fronto-cerebellar rs-FC, resulting in desynchronization within the fronto-cerebellar loop that compromises compensation for executive deficits. Cerebellar hypermetabolism may represent a biomarker of alcohol-related brain dysfunction, as an initial mechanism in the cascade linking fronto-cerebellar desynchronization and executive impairment.

PMID:42393033 | DOI:10.1038/s41398-026-04217-w

J Psychiatr Res. 2026 Jul 1;201:455-462. doi: 10.1016/j.jpsychires.2026.06.053. Online ahead of print.

ABSTRACT

BACKGROUND: Tourette syndrome (TS) shows substantial clinical heterogeneity, but the factors contributing to this variability remain unclear. Socioeconomic status (SES) may influence brain functional connectivity (FC) and symptom expression, yet its role in pediatric TS is still not well understood.

OBJECTIVE: To clarify the role of SES in modulating brain-behavior relationships in TS.

METHODS: Resting-state fMRI data were acquired from 67 children and adolescents with TS and 49 matched controls. FC was computed within and between seven predefined brain networks. We identified group differences in FC, examined associations between SES and clinical measures, and tested whether SES indicators (family income, parental education, and residential location) moderated FC-symptom relationships.

RESULTS: Compared with controls, children with TS showed significant alterations in FC, mainly characterized by increased connectivity involving somatomotor, frontoparietal control, default mode, attention, and limbic networks, and decreased connectivity within the right frontoparietal control network. Within the TS group, higher parental education was associated with greater premonitory urge severity. Moderation analyses showed that family income, parental education, and residential location moderated FC-premonitory urge associations; higher family income and parental education strengthened these associations, whereas rural residence weakened them.

CONCLUSIONS: Socioeconomic context may contribute to variability in brain-symptom relationships in pediatric TS, particularly for premonitory urges rather than clinician-rated tic severity. These findings highlight the importance of considering socioeconomic context when interpreting neuroclinical heterogeneity in TS and may inform more context-sensitive clinical assessment and interpretation.

PMID:42391732 | DOI:10.1016/j.jpsychires.2026.06.053

J Pediatr Urol. 2026 Jun 9;22(5):106066. doi: 10.1016/j.jpurol.2026.106066. Online ahead of print.

ABSTRACT

INTRODUCTION: Nocturnal enuresis (NE) is a common neurodevelopmental condition, yet its underlying neural mechanisms remain unclear. This study leverages the large-scale Adolescent Brain Cognitive Development (ABCD) dataset to identify structural and functional brain correlates associated with active symptoms and the resolution of bedwetting.

METHODS: Using cross-sectional data from 3472 participants aged 9-10 years, children were categorized into three groups: active nocturnal enuresis (ANE, n = 225), history of nocturnal enuresis (HNE, n = 1171), and healthy control groups (CG, n = 2076). Multimodal neuroimaging protocol evaluated macrostructural properties via structural MRI (sMRI), microstructural white matter integrity via diffusion MRI (dMRI), and functional connectivity via resting-state fMRI (fMRI). Group differences were evaluated using linear models within an ANCOVA framework, adjusting for intracranial volume and handedness with False Discovery Rate (FDR) correction.

RESULTS: Compared to controls, the ANE group exhibited a significant volume deficit in the right caudate, decreased sulcal depth in the left insula, and lower internal correlation within the Cingulo-Opercular Network (CON). Conversely, the dry HNE group demonstrated significant structural adaptations, including bilaterally larger putamen volumes and increased right caudate volume compared to the ANE group. The HNE group also showed increased microstructural density (decreased mean diffusivity) in the bilateral hippocampus and an increased cortical surface area in the left insula. Both NE groups demonstrated persistently reduced functional coupling within the CON.

CONCLUSIONS: Nocturnal enuresis appears to be associated with a potential complex central signaling deficits. Reduced internal correlation within the CON across both active and former bedwetters indicates a potential for impairment in processing internal homeostatic bladder signals during sleep.

PMID:42391727 | DOI:10.1016/j.jpurol.2026.106066

Front Psychiatry. 2026 Jun 17;17:1846942. doi: 10.3389/fpsyt.2026.1846942. eCollection 2026.

ABSTRACT

BACKGROUND: This study examined the brain networks related to hyperactivity and impulsivity in children with Attention-Deficit/Hyperactivity Disorder (ADHD) and aimed to develop a resting-state functional connectivity marker that can predict symptom severity.

METHODS: A total of 44 children with ADHD (31 boys and 13 girls; mean age = 8.45 ± 1.52 years; range = 6-12 years) who met DSM-5 criteria were included. Resting-state fMRI data and clinical symptom scores were collected. Connectome-based predictive modeling (CPM) was used to predict hyperactivity-impulsivity symptoms based on whole-brain functional connectivity matrices. Symptoms were assessed using the SNAP-IV Parent and Teacher Rating Scales and the Conners Comprehensive Behavior Rating Scale. Model performance was tested with leave-one-out cross-validation and permutation testing.

RESULTS: The CPM model based on interregional functional connectivity successfully predicted hyperactivity-impulsivity symptoms (SNAP-IV parent and teacher ratings: r = 0.48, p = 0.001). The model also generalized well within the same dataset, as the selected functional connections significantly predicted hyperactivity-impulsivity scores on the Conners Parent Rating Scale (r = 0.49, p = 0.0009). Further analysis showed that stronger connectivity between the frontoparietal control network (FPN) and the dorsal attention network (DAN), and weaker connectivity between the FPN and the ventral attention network (VAN) and between the FPN and the somatomotor network (SMN), were related to symptom severity.

CONCLUSIONS: Whole-brain functional connectivity is associated with hyperactivity-impulsivity symptoms in children with ADHD. The findings highlight the key role of FPN-related networks in these symptoms and provide a neural correlate that, pending further validation, represents a preliminary candidate for a neuroimaging marker.

PMID:42389396 | PMC:PMC13318954 | DOI:10.3389/fpsyt.2026.1846942

Front Neurol. 2026 Jun 17;17:1868819. doi: 10.3389/fneur.2026.1868819. eCollection 2026.

ABSTRACT

OBJECTIVE: To determine whether high-frequency rTMS of the left angular gyrus improves behavioral signs of consciousness in prolonged disorders of consciousness (pDoC) and to identify network mechanisms and predictors of response.

METHODS: In a randomized, double-blind, sham-controlled crossover trial, patients with pDoC received 3 weeks of 20-Hz rTMS over the left angular gyrus and 3 weeks of sham stimulation in counterbalanced order, separated by a 1-week washout. Consciousness was evaluated using the Coma Recovery Scale-Revised (CRS-R). Resting-state fMRI was acquired at baseline and after each period to quantify network-level changes. Explainable machine-learning models related stimulation-induced network changes and baseline features to behavioral improvement.

RESULTS: Forty patients completed the trial. Behavioral improvement occurred more frequently during active than sham stimulation (p < 0.05), predominantly in visual, motor, and auditory domains. Explainable analyses indicated that post-rTMS recovery within the default mode network (DMN) and the subcortical network (SCN) best characterized responders (random forest AUC = 0.861). Stronger baseline within-DMN functional connectivity predicted greater likelihood of improvement (support vector machine AUC = 0.972).

CONCLUSION: Left angular gyrus rTMS improved consciousness-related behaviors in a subset of pDoC patients, potentially mediated by DMN-SCN network reconfiguration; patients with stronger baseline within-DMN connectivity were more likely to benefit.

CLINICAL TRIAL REGISTRATION: https://www.chictr.org.cn/index.html, identifier ChiCTR2300069980.

PMID:42388696 | PMC:PMC13318575 | DOI:10.3389/fneur.2026.1868819

Neuroimage. 2026 Jul 1:122085. doi: 10.1016/j.neuroimage.2026.122085. Online ahead of print.

ABSTRACT

Resting state functional magnetic resonance imaging (rs-fMRI) is a widely used imaging modality that can capture spontaneous neural activity of the brain. The human brain is a complex system, and emerging evidence suggests that the complexity of neural activity may serve as an index of its information processing capacity. In this study, we used multiscale sample entropy (MSE) to analyze the complexity of rs-fMRI time series from 504 healthy subjects aged 6 to 85 years. We constructed global and regional trajectories of the brain's functional complexity across the lifespan and examined its correlation with executive function. We observed a nonlinear trajectory of fMRI-complexity, with a peak occurring at 23 years of age (95% CI: 21.27,26.38 years). Males reached the peak complexity at 26 years (95% CI: 19.95, 33.14 years), whereas females peaked at 23 years (95% CI 20.16, 29.18 years). Significant correlations were found between complexity and Number-Letter Switching of the Trail Making Test in the parietal and medial temporal lobes, while Inhibition and Inhibition/Switching of the Color Word Interference Test showed significant negative correlations with rs-fMRI complexity in the lateral and medial frontal cortex. These results provide insight into the behavior of fMRI-complexity across lifespan stages and highlight its association with executive function. As a non-invasive biomarker, fMRI-complexity may offer a novel approach to understanding the brain's information processing capacity and its deficits in illness.

PMID:42386108 | DOI:10.1016/j.neuroimage.2026.122085

Neuroimage. 2026 Jul 1:122100. doi: 10.1016/j.neuroimage.2026.122100. Online ahead of print.

ABSTRACT

Schizophrenia (SZ) is a severe psychiatric disorder with heterogeneous symptoms. It often entails alterations in brain networks, conventionally probed by functional connectivity using resting-state data. This study investigated task-related alterations in brain organization, including the functional connectivity gradient and infra-slow sequential organization, during auditory tasks in individuals with SZ. Functional connectivity gradient analysis showed disrupted functional hierarchical organization in SZ. Sequential organization represented significant differences in phase shifts between SZ and healthy controls (HC) over the somatomotor, parietal, and supracallosal anterior cingulate cortex. Decoding analyses reliably classified SZ from HC using phase shift values. Particularly, phase shifts in the postcentral gyrus correlated with clinical courses. These findings indicate that SZ is characterized by abnormal hierarchical organization and infra-slow propagation during auditory processing.

PMID:42386106 | DOI:10.1016/j.neuroimage.2026.122100