Most recent paper

J Neurosci. 2026 Mar 9:e1846252026. doi: 10.1523/JNEUROSCI.1846-25.2026. Online ahead of print.

ABSTRACT

Congenital heart disease (CHD) affects approximately 1% of live births in the United States and is the most prevalent congenital disorder. Despite advances in neonatal cardiovascular surgery improving survival, neurodevelopmental impairments remain prevalent, impacting motor skills, social behavior, and executive function. Motor deficits and long-term challenges in emotional regulation and memory are particularly common. Recent research using resting-state functional MRI (rs-fMRI) has revealed disorganized brain networks in newborns with CHD. However, those few prior rs-fMRI studies examining the impact of CHD have relied on predefined brain parcellations to compare group-level connectivity, limiting the ability to capture spatial alterations in neonatal brain networks in CHD. Understanding these network-level changes is critical for elucidating mechanisms of neurodevelopmental impairment and identifying early biomarkers of risk. To address these gaps, our study introduces two conceptual advances: 1) a data-driven approach to investigate atypical brain network development in high-risk CHD and 2) the use of a population-sized, independent dataset of healthy newborns to derive a normative set of neonatal brain networks. By analyzing a large rs-fMRI of human newborns (N=448; 219 females and 229 males), we identify atypical brain activity in the sensorimotor and limbic networks of newborns with complex CHD. Notably, before cardiovascular surgery, these networks are split into left and right hemispheric subnetworks. Postoperatively, these components coalesce into a singular, symmetric pattern resembling networks observed in healthy neonates. Our study highlights the potential of rs-fMRI to detect subtle, early functional disruptions in CHD and may inform future biomarkers of neurodevelopmental risk.Significant Statement Congenital heart disease, the most common congenital disorder, affects 1% of live births and is associated with persistent neurodevelopmental impairments despite improved surgical survival. These deficits, including motor, socio-emotional, and cognitive challenges, may stem from early brain network disruptions. Prior resting-state fMRI studies in CHD relied on predefined parcellations, limiting detection of subtle spatial alterations. In this study, we used a data-driven approach and leveraged an independent normative dataset to define resting-state networks. Comparing CHD patients and healthy controls against these independently derived networks, we reveal atypical sensorimotor and limbic network organization preoperatively, which normalizes post-surgery. These findings highlight the potential of rs-fMRI to identify early biomarkers of neurodevelopmental risk and guide targeted interventions in this high-risk population.

PMID:41802866 | DOI:10.1523/JNEUROSCI.1846-25.2026

Neuropsychologia. 2026 Mar 7:109429. doi: 10.1016/j.neuropsychologia.2026.109429. Online ahead of print.

ABSTRACT

Valence bias (VB) refers to an individual's tendency to consistently interpret emotionally ambiguous stimuli as either positive or negative. As such bias may be closely linked to mental health outcomes such as anxiety and depression, investigating its underlying neural mechanisms hold important clinical relevance. Here, we obtained VB scores through a robust performance-based behavioral measure and sought to examine whether the whole-brain resting-state functional connectome could be leveraged to predict VB using connectome-based predictive modeling (CPM). Results highlighted a functional network model that could significantly predict individual VB. Specifically, our analyses revealed distributed patterns of connectivity in brain regions that support functions related to emotion regulation, cognitive control, and perceptual/emotional processing. These regions contained several key nodes - the amygdala, dorsal anterior cingulate cortex, and frontal operculum - that demonstrated predictive value for VB. Extending prior findings linking VB to functional brain organization, our findings demonstrated that VB can be predicted from large-scale functional brain regions using CPM, with several key nodes emerging as particularly influential, and further generalized these findings to a Korean adult sample. As VB reflects an individual's past experiences and interpretive tendencies, understanding the neural underpinnings of VB could assist in identifying potential neurobiological markers of vulnerability and resilience.

PMID:41802588 | DOI:10.1016/j.neuropsychologia.2026.109429

Behav Brain Res. 2026 Mar 7:116150. doi: 10.1016/j.bbr.2026.116150. Online ahead of print.

ABSTRACT

Although resting-state thought content and brain activity have been extensively studied, large-scale covariation between these domains remains poorly understood. In this study, we applied fully data-driven canonical correlation analysis (CCA) to resting-state fMRI and Amsterdam Resting-State Questionnaire (ARSQ) data from 1,616 healthy adults to investigate shared and sex-differentiated brain-behavior associations. For males, the first canonical correlation was 0.358 (p = 0.003, FDR-corrected p = 0.030), and for females, it was 0.331 (p < 0.001, FDR-corrected p < 0.001), with the first canonical variate explaining the largest proportion of covariance between ARSQ dimensions and network connectivity. Structure correlations revealed that "Sleepiness" was most strongly associated with Default Mode Network (DMN) connectivity in both sexes (male r = 0.764, p < 0.001; female r = 0.899, p < 0.001). Sex-differentiated patterns were observed in higher-order networks, including fronto-parietal, cingulo-opercular, and cerebellar networks. These results indicate a shared DMN-sleepiness coupling across sexes, alongside sex-specific associations in other large-scale networks. Our findings provide quantitative evidence for the neural embodiment of resting-state cognition and highlight the importance of considering both shared and sex-differentiated network in functional connectivity research.

PMID:41802498 | DOI:10.1016/j.bbr.2026.116150

Psychol Med. 2026 Mar 9;56:e69. doi: 10.1017/S0033291725102687.

ABSTRACT

BACKGROUND: Subthreshold depression (StD) is considered a prodromal stage of major depressive disorder (MDD). This study aims to investigate the neurobiological mechanisms of StD by analyzing functional connectivity (FC) and cognitive function in comparison to MDD.

METHODS: A total of 153 StD individuals, 188 MDD patients, and 110 healthy controls (HCs) were studied using resting-state functional magnetic resonance imaging (fMRI). Whole-brain FC was calculated using seeds from the default mode network (DMN), salience network (SN), executive control network, and affective network (AN). Cognitive function was assessed across seven domains.

RESULTS: StD showed only a deficit in social cognition, while MDD exhibited multidomain cognitive impairments compared to HCs. Both MDD and StD exhibited reduced FC between the right anterior insula (AI) and the left inferior frontal gyrus (IFG), and increased FC between the right subcallosal cingulate cortex and the left posterior cingulate cortex (PCC), key areas of the SN and AN, compared to HCs. MDD particularly showed decreased connectivity between the left PCC and the left middle temporal gyrus, and within the left PCC, while no abnormal FC of the DMN was found in StD. Altered AI-IFG FC was positively correlated with social cognition in StD.

CONCLUSIONS: Abnormal connectivity patterns of the SN and AN may contribute to the development of depressive symptoms in StD and MDD, while altered FC of the DMN may be involved in the onset of the disease. A social cognition deficit appeared first in StD, relating to the abnormal connectivity of the SN.

PMID:41800542 | DOI:10.1017/S0033291725102687

Front Neurosci. 2026 Feb 20;20:1761097. doi: 10.3389/fnins.2026.1761097. eCollection 2026.

ABSTRACT

BACKGROUND: Prolonged disorders of consciousness (pDOC), including vegetative/unresponsive wakefulness state (VS/UWS) and minimally conscious state (MCS), pose significant diagnostic and prognostic challenges. Multimodal neuroimaging has emerged as a promising tool to uncover neural biomarkers that reflect residual brain function and guide management. This pilot feasibility study aimed to preliminarily characterize metabolic, functional, and structural brain alterations in pDOC patients using simultaneous positron emission tomography/magnetic resonance (PET/MR) imaging, and to examine their tentative associations with clinical behavioral responsiveness.

METHODS: Eight pDOC patients and eight matched healthy controls underwent hybrid 18F-FDG PET/MR scanning. Resting-state fMRI, diffusion tensor imaging (DTI), and FDG-PET were processed to assess amplitude of low-frequency fluctuations (ALFF), fractional anisotropy (FA), and glucose metabolism, respectively. Group differences were analyzed, and correlations with Coma Recovery Scale-Revised (CRS-R) scores were evaluated. Multimodal integration was performed across imaging modalities.

RESULTS: Compared to controls, pDOC patients exhibited reduced ALFF and FDG uptake in the posterior cingulate cortex (PCC) and anterior cingulate cortex (ACC), with exploratory increased ALFF in the visual cortex inversely correlated with visual responsiveness. Functional connectivity analyses revealed attenuated intra- and inter-network connectivity in the DMN, SN, and DAN. FDG-PET identified metabolic hypofunction in the insula, frontal cortex, and cerebellum, while DTI demonstrated widespread white matter FA reductions. Multimodal correspondence revealed partially overlapping abnormalities in the PCC and occipital regions, highlighting candidate hubs that may be relevant to consciousness level and warrant further validation.

CONCLUSION: Simultaneous FDG-PET/MR was feasible in this pilot pDOC cohort and provided a convergent, multimodal assessment of metabolic-functional-structural alterations. The PCC and occipital visual cortices emerge as key regions linked to consciousness levels. Given the small sample size and cross-sectional design, these findings are preliminary, and warrant validation in larger longitudinal cohorts before clinical translation.

PMID:41799881 | PMC:PMC12963328 | DOI:10.3389/fnins.2026.1761097

Front Psychiatry. 2026 Feb 19;17:1775531. doi: 10.3389/fpsyt.2026.1775531. eCollection 2026.

ABSTRACT

BACKGROUND: Nonsuicidal self-injury (NSSI) is a complex behavior prevalent among adolescents, particularly females and those with depression. The DSM-5 introduced recommended diagnostic criteria for NSSI, yet many adolescents engaging in NSSI do not meet these standards. The neurobiological distinctions between adolescents with NSSI who fulfill the DSM-5 criteria (NSSI+) and those who do not (NSSI-) remain unclear.

METHODS: Sixty-three female depressive adolescents (40 NSSI+, 23 NSSI-) and 35 healthy controls (HCs) were included and underwent resting-state functional magnetic resonance imaging, diffusion tensor imaging and high-resolution T1-weighted imaging. We explored differences in brain structure-function interactions by applying structural-functional connectivity (SC-FC) coupling analysis using multimodal neuroimaging data. Partial Spearman's correlation analyses were used to identify association between SC-FC coupling and clinical features.

RESULTS: The NSSI+ group had notably distinct SC-FC coupling in task-positive network regions including decreased SC-FC coupling (greater decoupling) in the left dorsolateral superior frontal gyrus and increased coupling in the bilateral medial precuneus and right opercular inferior frontal gyrus, as compared to the NSSI- group. Moreover, the NSSI+ group displayed widespread coupling abnormalities across multiple networks compared to the HC group, while the NSSI- group only differed in the left dorsolateral superior frontal gyrus. Correlational analyses linked decoupling indices to several clinical features, particularly in the right subgenual anterior cingulate among the NSSI- participants.

CONCLUSIONS: These findings indicate that SC-FC coupling patterns distinguish NSSI subtypes in depressed female adolescents, with more severe NSSI associated with altered coupling in prefrontal, precuneus, and inferior frontal regions involved in executive control and attentional processing. The right subgenual anterior cingulate cortex-showing multiple clinical correlations-emerges as a potential target for early intervention of NSSI behavior. These findings highlight the utility of SC-FC coupling as a neural marker for NSSI subtyping and intervention planning.

PMID:41799811 | PMC:PMC12960618 | DOI:10.3389/fpsyt.2026.1775531

Front Psychiatry. 2026 Feb 20;17:1778601. doi: 10.3389/fpsyt.2026.1778601. eCollection 2026.

ABSTRACT

OBJECTIVE: To identify abnormal brain regions in patients with trigeminal neuralgia (TN) and screen for specific regions that can predict short-term recurrence after percutaneous radiofrequency ablation (RFT).

METHODS: Resting-state functional magnetic resonance imaging (rs-fMRI) was used to identify differential brain regions in TN patients. An individualized rs-fMRI approach was applied to screen for recurrence-related brain regions in patients undergoing RFT. Among these, regions with a 100% recurrence rate were classified as high-risk recurrence regions. Treatment outcomes and changes in these differential brain regions were observed postoperatively.

RESULTS: Thirty TN patients exhibited 19 differential brain regions. Four of these-Rolandic_Oper_L, Cerebellum_9_L, Lingual_R, and Calcarine_L-were newly identified as abnormal regions in TN. Among the 15 patients who underwent RFT, 15 potential recurrence-related regions were found. Six of these-contralateral Insula_L, Fusiform_L, Vermis_3, and Temporal_Sup_L; ipsilateral Cerebellum_3_R; and ipsilateral Fusiform_R (when involving V1 division pain)-were identified as high-risk recurrence regions. Follow-up scans confirmed that these recurrence-related differential brain regions were either eliminated or attenuated after surgery.

CONCLUSION: Patients with trigeminal neuralgia exhibit abnormalities in multiple brain regions. These findings demonstrate that individualized functional imaging biomarkers provide an effective framework for stratifying the risk of early postoperative recurrence. Specifically, abnormalities in the Insula_L, Fusiform_L, Cerebellum_3_R, Temporal_Sup_L, Vermis_3, and Fusiform_R can be defined as high-risk brain regions for predicting short-term recurrence after radiofrequency ablation.

PMID:41799801 | PMC:PMC12964204 | DOI:10.3389/fpsyt.2026.1778601

Front Neurol. 2026 Feb 20;17:1738469. doi: 10.3389/fneur.2026.1738469. eCollection 2026.

ABSTRACT

Relapsing Multiple Sclerosis (RMS) is characterized by neuroinflammation and neurodegeneration, leading to disability. Ofatumumab (OFA), an anti-CD20 monoclonal antibody, has shown promise as a disease-modifying therapy. This study aimed to assess the neuroprotective effects of OFA in RMS using multimodal magnetic resonance imaging (MRI). We conducted a retrospective cohort study comparing 16 RMS patients receiving OFA for 1 year (Treatment Group, TG) with 8 treatment-naïve patients (No-Treatment Group, NTG). Participants underwent 3T MRI scans, including 3D T1-weighted, diffusion tensor imaging (DTI), and resting-state functional MRI (rs-fMRI). Clinical outcomes were measured using the Expanded Disability Status Scale (EDSS), timed 25-Foot Walk (T25FW), and cognitive assessments. Results showed significant improvements in motor function and anxiety in the TG, alongside increased white matter integrity and stable cognition. Notably, TG patients exhibited enhanced functional connectivity between the thalamus and cortex, as well as increased fractional anisotropy (FA) in key white matter tracts. In contrast, the NTG displayed gray matter atrophy. These preliminary findings suggest that OFA treatment may preserve brain structure and function in RMS, with potential neuroprotective effects mediated, through thalamocortical network modulation and white matter restoration.

PMID:41798819 | PMC:PMC12962950 | DOI:10.3389/fneur.2026.1738469

Int J Dev Neurosci. 2026 Apr;86(2):e70112. doi: 10.1002/jdn.70112.

ABSTRACT

Autism spectrum disorder (ASD) is one of the most prevalent developmental disorders. This study utilized 3-Tesla resting-state fMRI data analysed with the functional parcellation algorithm MOSI (modular analysis and similarity measurement) to investigate cortical functional organization in ASD. Sixty individuals with ASD and sixty healthy controls were selected from the Autism Brain Imaging Data Exchange (ABIDE), with no significant differences in age and gender distribution. The MOSI-derived metrics were compared using independent two-sample t-tests. The findings revealed a significant reduction in the functional volume of the left frontal lobe, a region critical for language, cognitive, and social processing. This reduction appears to be accompanied by compensatory expansion in other brain regions, suggesting a reallocation of neural resources that may contribute to ASD heterogeneity. These results support the notion of left frontal lobe developmental deviation (LFDD) as a parsimonious neural mechanism underlying key ASD features. The accountability of LFDD in various cognitive, symptomatic and behavioural characteristics of ASD is briefly discussed, along with its implications for male predominance and evolutionary relevance. Overall, the study provides a novel brain-based perspective on ASD, moving beyond traditional psychological models to offer a neurobiological explanation for its defining characteristics and possible underlying developmental origins.

PMID:41797657 | DOI:10.1002/jdn.70112

Neuropharmacology. 2026 Mar 6:110886. doi: 10.1016/j.neuropharm.2026.110886. Online ahead of print.

ABSTRACT

BACKGROUND: 5-Methoxy-N,N-dimethyltryptamine (5-MeO-DMT) is a potent serotonergic psychedelic with rapid therapeutic potential for depression and anxiety disorders. Despite growing clinical interest, the neurobiological mechanisms underlying 5-MeO-DMT's acute brain effects remain poorly understood, and potential sex differences in response have not been investigated. We conducted the first functional MRI study of 5-MeO-DMT in awake, drug-naïve rats using BOLD imaging.

METHODS: Male (n = 24) and female (n = 24) rats received I.P. injections of vehicle or 5-MeO-DMT (0.01, 0.1, or 1.0 mg/kg) during scanning sessions. BOLD signal changes and resting-state functional connectivity were assessed across 169 brain regions. Negative and positive BOLD volume activations were quantified during acute (1-10 min) and sustained (11-20 min) time windows post-injection, with sex-stratified analyses performed.

RESULTS: Females demonstrated markedly enhanced sensitivity to low-dose 5-MeO-DMT (0.1 mg/kg), exhibiting extensive negative BOLD responses that were largely absent in males at the same dose. The 1.0 mg/kg dose induced widespread negative BOLD responses across multiple brain regions in both sexes during the acute window (1-10 minutes post-injection), with effects substantially diminishing thereafter. Global functional connectivity was significantly reduced across all doses (p<0.0001), with regional specificity observed in hypothalamic and cerebellar networks. Temporal analysis revealed peak neurobiological effects within the first 10 minutes, consistent with 5-MeO-DMT's known rapid pharmacokinetics.

CONCLUSION: To our knowledge, this is the first fMRI characterization of 5-MeO-DMT in any species, and it reveals a previously unreported sex difference in psychedelic response. The rapid onset and brief duration of peak effects align with 5-MeO-DMT's unique pharmacological profile and clinical reports.

PMID:41796937 | DOI:10.1016/j.neuropharm.2026.110886

Brain Res Bull. 2026 Mar 5:111815. doi: 10.1016/j.brainresbull.2026.111815. Online ahead of print.

ABSTRACT

Various Magnetic Resonance Imaging modalities were developed to explore the brain. Among them, functional MRI is of key importance for studying brain activity and its neural substrates. Recent works have pointed out that machine learning can use neuroimaging data to predict brain age. This approach is crucial not only for understanding the effects of aging but also for refining diagnostics because many chronic and neurodegenerative diseases appear as accelerated aging. Unfortunately, the prediction of brain age is particularly challenging for functional data due to the large dimension of the high-resolution connectomes usually derived to summarize the functional organization of the brain and their particular mathematical properties. In this work, we investigate the prediction of brain age from functional data on a large scale by creating a set of forty thousand functional connectomes via the processing of the resting-state fMRI scans of four cohort studies. This dataset is used to explore the ability of various connectome transformations and machine learning strategies to achieve accurate age predictions. We hope that our results will open the way for more reliable functional brain age measures.

PMID:41794271 | DOI:10.1016/j.brainresbull.2026.111815

J Clin Endocrinol Metab. 2026 Mar 7:dgag102. doi: 10.1210/clinem/dgag102. Online ahead of print.

ABSTRACT

CONTEXT: The developing brain is particularly vulnerable to glycemic extremes in early-onset type 1 diabetes (T1D). However, how treatment-specific modalities may influence long-term neurodevelopmental trajectories remains poorly understood.

OBJECTIVE: To characterize multimodal MRI neurodevelopmental profiles in pediatric T1D and evaluate treatment-related effects of Multiple Daily Injections (MDI) versus Continuous Subcutaneous Insulin Infusion (CSII) on brain structure, function, and test whether HbA1c-linked imaging features relate to executive-working-memory performance.

METHODS: Sixteen children with T1D (8 MDI, 8 CSII from diagnosis) and eight controls underwent structural MRI, diffusion MRI, and resting-state fMRI. Union Recursive Feature Elimination (U-RFE) selected gray-matter (GM), white-matter (WM), and functional connectivity (rs-FC) features discriminating groups; regression related selected features to long-term age-adjusted mean glycated hemoglobin (HbA1c). NEPSY-II Word List Interference (WI) was administered; control-referenced WI outcomes were examined versus HbA1c and HbA1c-associated structural features, including mediation.

RESULTS: Functional features outperformed structural features (balanced accuracy 0.83 vs 0.67). MDI showed reduced GM/WM integrity and disrupted fronto-temporal and subcortical connectivity versus CSII and controls. Right inferior frontal gyrus (IFG) volume correlated with HbA1c (r=0.71, p<0.05) and predicted HbA1c (β=0.28, p=0.015). Higher HbA1c related to poorer WI repetition (r=-0.60, p=0.013), and right IFG volume related to poorer WI repetition (r=-0.70, p=0.002). Mediation supported an indirect HbA1c effect via right IFG volume (a×b=-0.676; Sobel z=-1.765, one-tailed p=0.0388), explaining ∼64% of the total association. CSII had 30% lower hyperglycemia exposure than MDI and higher WI repetition mean ranks (11.19 vs 5.81; p=0.023).

CONCLUSIONS: Pediatric T1D is associated with multimodal neuroimaging alterations influenced by insulin treatment modality. CSII may confer neuroprotective benefits by improving metabolic control and preserving functional connectivity. Right IFG volume is a candidate imaging marker linking metabolic regulation to interference-sensitive executive-working-memory vulnerability.

PMID:41793758 | DOI:10.1210/clinem/dgag102

BMC Med. 2026 Mar 7. doi: 10.1186/s12916-026-04766-3. Online ahead of print.

ABSTRACT

BACKGROUND: Bipolar depression (BD-D) in adolescents and young adults is associated with disrupted neural circuits underlying affective regulation, particularly those involving the orbitofrontal cortex (OFC). Despite the promise of repetitive transcranial magnetic stimulation (rTMS) as a non-invasive intervention, effective targeting strategies that engage these dysfunctional circuits remain insufficiently explored. This study investigates the clinical efficacy of a novel rTMS protocol targeting the primary visual cortex (V1) node of the V1-OFC functional circuit in adolescents and young adults with BD-D.

METHODS: We conducted a double-blind randomized controlled trial. Fifty-two adolescents and young adults BD-D participants were randomized to active rTMS group (10 Hz, 100% RMT) or sham rTMS group (20% RMT) targeting the V1 region that exhibited the strongest functional connectivity with the OFC (MNI: - 12, - 81, 6). rTMS was administered over 3 weeks (5 sessions/week, 15 sessions in total), with all participants receiving adjunctive lurasidone (40-80 mg/day). The primary outcome was the change in depressive symptoms measured by the Montgomery-Åsberg Depression Rating Scale (MADRS) at baseline, week 3, and week 8. Secondary outcomes included HAMD-24, QIDS-SR, and HAMA. Resting-state fMRI was performed at baseline and after the 3-week intervention to examine changes in functional connectivity related to rTMS.

RESULTS: A total of 43 participants completed a 3-week intervention, and 37 completed the 8-week follow-up. Compared with the sham group, the active rTMS group showed significantly greater reductions in depressive symptoms. Between-group differences were significant on the primary outcome MADRS at week 8 (t(35) = - 3.595, pFDR < 0.01), with a parallel effect detected for the secondary outcome on the QIDS-SR (t(35) = - 3.653, pFDR < 0.01). HAMD-24 scores also differed significantly at week 3 (t(35) = - 3.921, pFDR < 0.01). No significant changes were found in anxiety symptoms. Resting-state fMRI indicated altered connectivity in the anterior cingulate cortex and right superior occipital gyrus, suggesting modulation of mood-related visual circuits. No severe adverse effects were reported in all participants.

CONCLUSIONS: The study preliminarily demonstrated that the navigated rTMS precisely targeting the V1-OFC circuit may be a safe and potentially effective intervention for adolescents and young adults with BD-D.

TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT05929183.

PMID:41792767 | DOI:10.1186/s12916-026-04766-3

Childs Nerv Syst. 2026 Mar 7;42(1):99. doi: 10.1007/s00381-026-07187-y.

ABSTRACT

BACKGROUND: Pediatric posterior fossa lesions are frequent, and surgery in this area often results in cerebellar injury. Despite improved surgical methods, the impact on brain functional networks and their role in motor and cognitive performance remain unclear. Existing research mainly involves adults or children who received additional therapies, obscuring the effects of isolated cerebellar damage. Evidence from pediatric functional neuroimaging after posterior fossa surgery is limited.

METHOD: In this cross-sectional study, we examined 12 postoperative children and 13 healthy peers using resting-state functional magnetic resonance imaging (rs-fMRI) and the CNS Vital Signs (CNS VS) computerized neurocognitive battery. The CNS VS battery provided age-adjusted standard scores across multiple cognitive domains as well as motor speed (MotSpd) and psychomotor speed (PsyMotSpd) indices.

RESULTS: Short-term postoperative results indicated that most cognitive domains assessed by CNS VS did not differ significantly between groups, whereas the patient group showed lower scores on MotSpd, PsyMotSpd, and the neurocognitive index (NCI). Brain imaging analyses revealed increased regional activity and altered seed-based functional connectivity in several cortical regions of the patient group relative to controls. Exploratory correlation analyses conducted across all participants showed that several of these imaging metrics were negatively associated with motor-related scores; however, one functional connectivity measure was positively associated with MotSpd.

CONCLUSION: These findings suggest that children following posterior fossa surgery exhibit measurable alterations in supratentorial brain network organization alongside relatively preserved cognitive performance but reduced motor-related scores on the CNS VS battery. The negative associations between certain imaging metrics and motor performance may reflect heterogeneous or inefficient network reorganization rather than a straightforward compensatory process. Further longitudinal and interventional studies are needed to clarify the functional significance of these network changes and to inform rehabilitation strategies.

PMID:41792257 | DOI:10.1007/s00381-026-07187-y

Transl Psychiatry. 2026 Mar 6. doi: 10.1038/s41398-026-03929-3. Online ahead of print.

ABSTRACT

Postoperative depression adversely influences breast cancer patients' clinical outcomes. Our prior study demonstrated that intraoperative esketamine ameliorated postoperative depression in breast cancer patients, yet the underlying neural mechanism remains incompletely understood. We performed a double-blind randomized controlled trial in 35 breast cancer patients with preoperative depressive symptoms, who were randomly given intraoperative esketamine 0.25 mg·kg⁻¹ (n = 18) or saline placebo (n = 17) over the initial 40 min of anesthesia. Resting-state functional magnetic resonance imaging data were collected at preoperative baseline and postoperative day 1 follow-up to calculate brain functional network measures. In contrast to no significant change in the placebo group, the esketamine group showed increased degree centrality of the left inferior frontal gyrus, opercular part from baseline to follow-up, which was related to improvement in depressive symptoms. Additionally, we found significant associations of baseline network measures at the global, nodal, and edge levels with short-term and long-term improvements in depressive symptoms following esketamine administration. These findings may not only provide novel insights into the neural mechanism by which esketamine exerts its antidepressant efficacy during the perioperative period, but also highlight the prospect of functional network measures as useful predictors of antidepressant response to esketamine in patients with breast cancer.

PMID:41792101 | DOI:10.1038/s41398-026-03929-3

Front Physiol. 2026 Feb 18;17:1750101. doi: 10.3389/fphys.2026.1750101. eCollection 2026.

ABSTRACT

INTRODUCTION: Cerebrospinal fluid (CSF) pulsations are linked to hemodynamics, with autonomic mechanisms, suggested to modulate slow-wave induced pulsations.

METHOD: To explore autonomic regulation's role in neurofluid flow, independent of sleep and neural activity, we hypothesized that modulating basal CO2 (altering vascular tone, cardiac activity and respiration) would highlight this link.

RESULTS: Using resting-state BOLD fMRI in neurofluid regions under different CO2 levels (capnic states), we found: 1) biomechanical modulation does not explain neurofluid dynamic variations across capnias; 2) beyond respiration, heart-rate variability independently drives low-frequency neurofluid flow, indicating autonomic control; 3) altered CO2 primarily affects neurofluid dynamics through the frequency (and not amplitude) of heart-rate and respiratory-volume variability.

DISCUSSION: These results suggest that both hyper- and hypocapnia disrupt how CSF responds to autonomic regulation, seen in deviations from normal cardiac and respiratory responses. Our work reveals neurofluid dynamics' sensitivity to CO2's frequency response, best explained by autonomic modulation. Modulating basal CO2 offers a new way to influence human neurofluid dynamics, independent of sleep or neuronal activity.

PMID:41788877 | PMC:PMC12956733 | DOI:10.3389/fphys.2026.1750101

Front Neurosci. 2026 Feb 18;20:1773151. doi: 10.3389/fnins.2026.1773151. eCollection 2026.

ABSTRACT

BACKGROUND AND PURPOSE: Awake mouse fMRI is a powerful tool for both neuroscience and translational research. To minimize head motion during scanning, habituation under physical restraint is commonly used. However, it remains unclear how stress levels and head motion evolve during habituation, particularly within the MRI environment.

METHODS: To address this, we repeatedly measured plasma corticosterone (CORT) levels in three groups of mice - controls, mice habituated outside the MRI magnet, and mice habituated within the fMRI environment - and acquired longitudinal resting-state fMRI data daily during an eight-day habituation period and again 15 days post-habituation at 15.2 T.

RESULTS: We found that CORT levels initially increased by approximately twofold and gradually decreased during habituation outside the magnet, whereas in mice habituated within the fMRI environment, CORT levels increased two- to fourfold and remained elevated throughout the habituation period. One week after habituation, CORT levels returned to baseline in both groups. Throughout all resting-state fMRI scanning sessions, head motion and functional connectivity remained stable, likely due to the well-designed restraint cradle that permitted paw movement.

CONCLUSION: These results suggest that, for our experimental setup, extending the number of habituation days does not further reduce stress in the MRI environment, provided that head motion remains within acceptable limits.

PMID:41788545 | PMC:PMC12956629 | DOI:10.3389/fnins.2026.1773151

Hum Brain Mapp. 2026 Mar;47(4):e70483. doi: 10.1002/hbm.70483.

ABSTRACT

Cortical parcellation is fundamental to neuroscience, enabling the division of cerebral cortex into distinct, non-overlapping regions to support interpretation and comparison of complex neuroimaging data. Although extensive literature has investigated cortical parcellation and its connection to functional brain networks, the optimal spatial features for deriving parcellations from resting-state fMRI (rsfMRI) remain unclear. Traditional methods such as Independent Component Analysis (ICA) have been widely used to identify large-scale functional networks, while other approaches define disjoint cortical parcellations. However, bridging these perspectives through effective feature extraction remains an open challenge. To address this, we introduce Untamed, a novel framework that integrates unconstrained tensor decomposition using NASCAR to identify functional networks, with state-of-the-art graph node embedding to generate cortical parcellations. Our method produces near-homogeneous, spatially coherent regions aligned with large-scale functional networks, while avoiding strong assumptions like statistical independence required in ICA. Across multiple datasets, Untamed consistently demonstrates improved or comparable performance in functional connectivity homogeneity and task contrast alignment compared to existing atlases. The pipeline is fully automated, allowing for rapid adaptation to new datasets and the generation of custom parcellations. The atlases derived from the Genomics Superstruct Project (GSP) dataset, along with the code for generating customizable parcel numbers, are publicly available at https://untamed-atlas.github.io.

PMID:41787960 | DOI:10.1002/hbm.70483

Neuroscience. 2026 Mar 3:S0306-4522(26)00154-5. doi: 10.1016/j.neuroscience.2026.02.045. Online ahead of print.

ABSTRACT

Autonomic dysfunction is implicated in the manifestation of binge eating (BE) behaviors. Aberrant functional connectivity among brain regions involved in reward processing, affect regulation, and cognitive control have been the focus of resting state functional connectivity studies in BE. However, the influence of brain regions involved in central autonomic control and the relationship between autonomic balance and BE behavior remains unclear. The current study examines whether effective connectivity (EC) patterns in neural networks supporting the afore-mentioned cognitive processes moderates the relationship between heart rate variability (HRV), a physiological marker of autonomic balance, and BE behaviors. Resting-state fMRI data from 158 healthy adults (BE = 30; Control = 128) were analyzed using spectral dynamic causal modeling within a priori-defined eating regulation network. Leave-one-out cross-validation (LOOCV) assessed the predictive utility of EC patterns. Although 20 EC connections were associated with BE (posterior probability > 0.99), EC from the left posterior cingulate cortex to the hypothalamus predicted group membership above chance (AUC = 0.622, 95% CI [0.508, 0.731]). Approximate entropy was a significant predictor of binge eating behavior (ß = -6.625; p < 0.05) in a subset of 114 participants with usable photoplethysmography data (BE = 24; Control = 90). This relationship was significantly moderated by ventral tegmental area to hypothalamus EC (ß = -6.529; p < 0.05). These findings uncover novel directional connectivity patterns and identify brain-autonomic interactions that may underlie BE behavior, offering promising targets for future intervention strategies.

PMID:41786020 | DOI:10.1016/j.neuroscience.2026.02.045

J Affect Disord. 2026 Mar 3:121550. doi: 10.1016/j.jad.2026.121550. Online ahead of print.

ABSTRACT

This study explores the global signal topography of core and periphery brain networks in Major Depressive Disorder (MDD), Bipolar disorder (BD-Dep) and healthy controls (HC) using resting-state fMRI. In a sample of 140 depressed MDD and BD patients, and 70 HC, we observed a significant shift toward increased activity in the transmodal-core regions (e.g., default mode network, frontoparietal network) at the expense of unimodal-periphery regions (e.g., visual, sensory-motor cortices) in both depressed MDD and BD patients compared to HC. Whole brain machine learning analyses further demonstrated that altered global signal dynamics can effectively distinguish MDD and BD from HC (ACC = 79% and 77% respectively). Notably, we identified a significant negative correlation between global signal correlation in unimodal-periphery networks and depressive symptom severity. Additionally, in a smaller sample of BD during mania (N = 22) a distinct topographic pattern was observed, with increased global representation in the unimodal-periphery compared to depressive states, suggesting mood state-dependent shifts in network organization. To assess multivariate discriminability across diagnostic groups, a Partial Least Squares (PLS) analysis revealed that higher Core and related network activity (DMN, FPN) predicted diagnostic assignment to MDD and BD-Dep, whereas higher Periphery and related network (e.g., visual and sensory-motor networks) predicted assignment to BD-Man and HC. The Core-Periphery (C-) ratio emerged as the strongest predictor (VIP = 1.65). These results underscore the critical role of global signal topography in mood disorders, particularly the imbalance between core and peripheral brain networks, as a potential neurobiological marker for depressive states.

PMID:41785933 | DOI:10.1016/j.jad.2026.121550