Most recent paper

Brain Behav. 2026 Apr;16(4):e71352. doi: 10.1002/brb3.71352.

ABSTRACT

BACKGROUND: Schizophrenia is a severe psychiatric disorder marked by specific cognitive and clinical disturbances, for which neuroimaging biomarkers remain elusive. Novel theoretical and computational frameworks, such as integrated information decomposition, offer promising approaches to provide interpretable biomarkers for neuroimaging alterations in schizophrenia, potentially capturing disruptions relevant to consciousness and self-experience.

METHODS: In this preliminary methodological exploration study, resting-state functional MRI (rsFMRI) data from 72 patients with schizophrenia and 74 healthy controls were retrieved and analyzed. Integrated information decomposition was leveraged to assess pairwise brain connectivity according to redundant, transferred, and synergistic components of information processing, as well as an overall metric of emergent consciousness/information integration: Φ. Clinical correlates with the Positive and Negative Syndrome Scale and the Wechsler Adult Intelligence Scale were assessed by partial Spearman correlations. Diagnostic accuracy was assessed through L1-regularized logistic regressions, after 5-fold cross-validation.

RESULTS: Redundancy was positively correlated with intelligence quotient (IQ) across both groups (rho = 0.187, p-value = 0.033). Within patients, information metrics were positively correlated with stereotyped thinking (min rho = 0.343, max p-value = 0.006) and preoccupation (min rho = 0.250, max p-value = 0.046). Positive symptoms were positively correlated with redundancy (min rho = 0.250, max p-value = 0.047). Promising diagnostic accuracy was reached with Φ (balanced accuracy = 64.38%, area under the curve = 70.89%), redundancy (balanced accuracy = 84.93%, area under the curve = 92.30%), and synergy (balanced accuracy = 65.75%, area under the curve = 70.93%).

CONCLUSIONS: These preliminary findings suggest that information metrics may offer clinically relevant, interpretable biomarkers for schizophrenia.

PMID:41913713 | DOI:10.1002/brb3.71352

Behav Brain Res. 2026 Mar 28:116181. doi: 10.1016/j.bbr.2026.116181. Online ahead of print.

ABSTRACT

BACKGROUND: Rumination is a transdiagnostic, persistent factor across many psychiatric conditions. Mapping its neural mechanisms may help differentiate ruminative profiles.

OBJECTIVE: To systematically review fMRI studies that evaluated rumination in psychiatric populations METHODS: We searched four databases (PubMed, EMBASE, Web of Science, Scopus) and included studies that integrated rumination measures with fMRI data.

RESULTS: Thirty-two articles met criteria; most were non-randomized (n = 31, 97%) and focused on depression (n = 24, 75%). Across disorders, clinical groups showed higher rumination than healthy controls, including in euthymic participants. In major depressive disorder, neural alterations implicated the default mode network, limbic and striatal regions, dorsolateral prefrontal cortex, and anterior cingulate cortex consistent with maladaptive ongoing processing. Neural signatures often persisted in remitted patients, suggesting possible trait markers of vulnerability. Intervention studies (n = 7) support using neuroimaging to track ruminative profiles and to inform more personalized interventions.

CONCLUSION: This review highlights the importance of examining rumination, here measured via trait questionnaires, state-induction paradigms, cognitive tasks, or resting-state fMRI, using more consistent conceptual and methodological approaches. Although rumination is transdiagnostic, implicated brain regions and networks may show disorder-specific patterns. Given heterogeneity in the literature, future work should prioritize controlled and interventional studies to clarify neural mechanisms and guide circuit-based, targeted treatments. PROSPERO REGISTRATION: #CRD532512.

PMID:41912094 | DOI:10.1016/j.bbr.2026.116181

Autism Res. 2026 Mar 30:e70241. doi: 10.1002/aur.70241. Online ahead of print.

ABSTRACT

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition with atypical social communication as a core symptom. Variations in social information processing in individuals with ASD are associated with the social brain, which encompasses four specific subnetworks, that is, reward system, theory of mind network, mirror neuron system, and face perception network. However, the relationship between neural mechanisms of altered social functioning and modular integration of these subnetworks within the social brain remains unclear in ASD. With resting-state functional MRI (rs-fMRI) data from two large-scale datasets (ABIDE I and II), we computed the participation coefficient to explore the abnormal modular integration of the four subnetworks in 298 ASDs and 348 typically developing (TD) controls. Then, its associations with clinical symptoms, neurotransmitter systems, and transcriptional signatures were investigated. Additionally, the age effect on aberrant modular integration was estimated with linear regression models. Finally, we assessed the reproducibility of our results from a meta-perspective using other datasets. ASD participants exhibited increased integration of the reward system relative to TDs, which was correlated with Social Responsiveness Scale total score, the neurotransmitters such as 5HT1a and GABAa, and the disruption of the transcriptional signatures including cell proliferation and migration as well as tube and tissue morphogenesis. Additionally, the modular integration abnormality of the reward system was stable across development and replicated across datasets. We revealed a symptom-related, neurotransmitter- and transcriptional signature-associated, age-stable, and reproducible modular integration abnormality of the reward system in ASD. This hyper-integration was linked to reduced GABAa and serotonin receptor densities, providing neuroimaging and molecular evidence supporting the excitatory-inhibitory imbalance theory of ASD and insights into the mechanisms underlying social variations in ASD.

PMID:41912444 | DOI:10.1002/aur.70241

Behav Brain Res. 2026 Mar 28:116184. doi: 10.1016/j.bbr.2026.116184. Online ahead of print.

ABSTRACT

Extensive evidence has highlighted disrupted brain connectivity in schizophrenia, yet traditional node-centric approaches have provided only limited insights into its underlying neurobiology. To address this gap, we analyzed resting-state fMRI data from 52 first-episode schizophrenia patients and 51 matched healthy controls, applying an edge-centric framework to compute normalized entropy, which quantifies the diversity of edge community affiliations at each node. Compared with healthy control, patients with schizophrenia exhibited significantly reduced entropy in prefrontal and temporal regions, reflecting diminished network diversity. These alterations were further associated with transcriptomic profiles, with the most relevant genes enriched for synaptic signaling and neurodevelopmental processes. This study demonstrates aberrant edge-centric network dynamics in schizophrenia and their relations to schizophrenia-related molecular pathways, providing novel insights into the pathophysiology of the disorder.

PMID:41912092 | DOI:10.1016/j.bbr.2026.116184

Front Rehabil Sci. 2026 Mar 12;7:1758682. doi: 10.3389/fresc.2026.1758682. eCollection 2026.

ABSTRACT

INTRODUCTION: Plantar sensory input plays a key role in postural control. However, training protocols that solely amplify this bottom-up input have demonstrated inconsistent efficacy. We hypothesized that a top-down protocol using plantar sensations as a perceptual anchor and expanding the attentional scope from localized plantar sensations to a whole-body reference frame would yield greater improvements than sensory discrimination alone.

METHODS: Forty-eight healthy adults (N = 48) participated in a single 10-minute session of either Sensory Discrimination Only (SDO) or Sensory Discrimination with Expansion of Attentional Scope (SDE). The SDE protocol employs a brief therapeutic dialogue to facilitate this expansion. The Index of Postural Stability (IPS) was assessed at baseline (T0), immediately after the training (T1), and 30 min after (T2). Semi-structured interviews at T0/T1 were text-mined to quantify motor strategies. Resting-state functional magnetic resonance imaging (rs-fMRI) data were collected at T0/T1 for region-of-interest (ROI)-to-ROI connectivity analyses, focusing on major large-scale brain networks.

RESULTS: The SDE group demonstrated a significant IPS improvement (ΔIPS ≈ + 0.09, dz = 0.42) and maintained this improvement at 30 min (T0 vs. T2: dz = 0.32), whereas the SDO group demonstrated no change. Qualitative analyses of self-reported motor strategies in the SDE group indicated attentional expansion beyond a plantar perceptual anchor toward whole-body alignment, reflected by increased references to the shoulders while foot-related references remained common. In rs-fMRI, a cluster within attentional circuitry, including the salience and ventral attention networks, demonstrated a significant group × time interaction [threshold-free cluster enhancement [TFCE]/family-wise error [FWE]-corrected p < .05], characterized by reduced connectivity following SDE and a trend toward increased connectivity following SDO.

CONCLUSIONS: In this proof-of-concept study, expanding attentional scope from a plantar perceptual anchor toward a whole-body reference frame was associated with immediate, group-level changes across measures. Postural stability improved, alongside changes in self-reported motor strategies and resting-state connectivity within attentional circuitry. Enhancing sensitivity to bottom-up plantar input remains fundamental; however, these findings suggest a potential next step-learning how to interpret and use plantar input as a whole-body reference signal for balance regulation. Confirmation in randomized and longitudinal studies, including evaluation in clinical populations, is warranted.

PMID:41908177 | PMC:PMC13018112 | DOI:10.3389/fresc.2026.1758682

J Alzheimers Dis. 2026 Mar 30:13872877261431317. doi: 10.1177/13872877261431317. Online ahead of print.

ABSTRACT

BackgroundAlzheimer's disease (AD) involves progressive cognitive decline associated with disrupted coordination and information exchange across brain regions. Cross-entropy can characterize inter-regional information flow, but its role in AD remains unexplored.ObjectiveTo evaluate cross-regional brain entropy (CRBEN) derived from resting-state fMRI in normal controls (NC), mild cognitive impairment (MCI), and AD, and to assess its potential as a biomarker of disease progression.MethodsResting-state fMRI data from 40 NC, 38 MCI, and 40 AD participants from ADNI 2/3 were preprocessed using SPM12 and FSL, including motion correction (FD < 0.5 mm). Mean time series were extracted from 300 regions of the seven-network Schaefer atlas. For each subject, a 300 × 300 CRBEN matrix was computed and decomposed using BrainSpace to obtain functional gradients, aligned via Procrustes analysis. Group differences were tested with two-sample t-tests controlling for age, sex, and education (Bonferroni-corrected, α = 0.05). Machine-learning classifiers were trained using gradient and demographic features, with robustness assessed by 1000 bootstrap resamples.ResultsCompared with NC, MCI showed reduced gradients in somatomotor, ventral-attention, and default-mode networks. AD showed further reductions versus MCI in somatomotor and default-mode networks, and versus NC in frontoparietal-control and default-mode networks (p < 0.05, corrected). Logistic regression achieved the highest accuracy (∼90%). Gradient flattening was prominent in temporal and occipital cortices, indicating reduced hierarchical organization.ConclusionsCRBEN gradients demonstrate progressive loss of network complexity across the AD continuum and may provide sensitive biomarkers of functional disintegration.

PMID:41906764 | DOI:10.1177/13872877261431317

Neurosci Biobehav Rev. 2026 Mar 27:106665. doi: 10.1016/j.neubiorev.2026.106665. Online ahead of print.

ABSTRACT

Olfactory dysfunction affects over 20% of the population. Despite progress in understanding its neural pathophysiology, research remains fragmented. This systematic review synthesizes evidence of brain structural and functional measures, and their association with clinical characteristics (e.g., etiology, duration) in patients with olfactory dysfunction. This may help to identify neural correlates and potential neuroimaging biomarkers of olfactory dysfunction's severity and progression. Following PRISMA guidelines, we screened 2374 papers and included 164 studies. Structural MRI studies consistently reported reduced olfactory bulb volume and/or sulcus depth, alongside gray matter reduction in the orbitofrontal cortex, hippocampus, insula, and amygdala in acquired olfactory dysfunction and paradoxical increases in congenital anosmia. Diffusion tensor imaging studies showed widespread white matter abnormalities, with prominent fractional anisotropy reductions. Resting-state fMRI demonstrated heterogeneous and global functional connectivity alterations. PET/SPECT studies generally reported reduced perfusion or hypometabolism in frontal regions, especially in the orbitofrontal regions. Dopamine transporter imaging showed more frequent dopaminergic deficits in Parkinson's and prodromal individuals with hyposmia. Electroencephalography studies, despite methodological heterogeneity, generally found prolonged latencies and reduced amplitudes in olfactory event-related potentials. Across techniques, these brain alterations often showed low-to-moderate correlations with olfactory function. Although etiological and methodological heterogeneity currently obstructs the identification of robust neuroimaging biomarkers of olfactory dysfunction's severity and progression, current evidence indicates that olfactory dysfunction involves widespread structural and functional alterations, mainly in olfaction-related areas, with the orbitofrontal cortex as a key area emerging across techniques. Large-scale, standardized studies are needed to enable stratified diagnosis and personalized prognosis.

PMID:41905561 | DOI:10.1016/j.neubiorev.2026.106665

Biol Psychiatry Cogn Neurosci Neuroimaging. 2026 Mar 27:S2451-9022(26)00085-6. doi: 10.1016/j.bpsc.2026.03.012. Online ahead of print.

ABSTRACT

BACKGROUND: Addictive screen use (ASU), above and beyond screen time, has been linked to significant mental health risks. Yet, little is known about the neural risk factors that may associate with ASU. We examined two neurodevelopmental factors-cognitive control and reward-highlighted in substance use research and their links to ASU.

METHOD: We utilized resting-state and monetary incentive delay (MID) task fMRI data from the Adolescent Brain Cognitive Development (ABCD) Study® at baseline (Y0; ages 9-10) to predict addictive videogaming, addictive social media use, addictive phone use, and a composite measure of ASU at year two follow-up (Y2; ages 11-12). Cortical connectomic maturation was operationalized as distance from early-life and proximity to adult functional networks in an individual connectome to potentially index cognitive control development. This was supplemented by also assessing cognitive task performance. Nucleus Accumbens (NAc) activation in anticipation of reward in the MID task was used to assess reward processing.

RESULT: Above and beyond total screen time and attention problems, lower connectomic maturation at Y0 associated with Y2 higher ASU composite and addictive videogaming. Analyses including task performance indicated cortical maturation was associated with both ASU and task performance, but we did not find cognitive task performance to be directly related to ASU. Additionally, lower NAc anticipatory reward activation at Y0 was very weakly associated with higher Y2 ASU.

CONCLUSION: Delayed cortical network maturation and, to a lesser extent, lower anticipatory reward activation in 9-to-10-year-olds may be associated with addictive screen use in early adolescence, above-and-beyond parent-reported attention problems.

PMID:41905476 | DOI:10.1016/j.bpsc.2026.03.012

Ann Hematol. 2026 Mar 28;105(4):210. doi: 10.1007/s00277-026-06893-6.

ABSTRACT

This study aimed to assess alterations in functional connectivity (FC) within brain networks in children and adolescents with β-TM major and to explore the intrinsic relationship between network changes and cognitive impairment. This prospective study recruited 70 patients with β-TM and 64 healthy controls. Cognitive function assessments using Montreal Cognitive Assessment (MoCA) and Modified Mini-Mental State Examination (MMMSE), and hematological parameters were collected. Region of interest (ROI)-to-ROI connectivity analysis was conducted to investigate the whole brain FC within and between resting-state networks. Granger causality analysis was utilized to evaluate the effective interactions among them. Patients exhibited significant cognitive impairment compared to controls. Key hematological indicators, such as serum ferritin, were not found to be correlated with cognitive function. Rs-fMRI revealed extensive reductions in functional connectivity, accompanied by several enhancements. These FCs’ alterations significantly correlated with cognitive deficits. Granger causality analysis further indicated effective information flow from these FCs. This study showed significant correlation of cognitive impairment with aberrant FC in brain networks and hematological parameters in patients with β-TM. These results should advance our understanding of the neural mechanism underlying β-TM-related cognitive dysfunction and may serve as potential neuroimaging biomarkers for cognitive functioning in this population.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00277-026-06893-6.

PMID:41902954 | PMC:PMC13033005 | DOI:10.1007/s00277-026-06893-6

Mol Psychiatry. 2026 Mar 29. doi: 10.1038/s41380-026-03557-9. Online ahead of print.

ABSTRACT

Substantial asymmetries of motor dysfunction are evident in patients with Parkinson's disease (PD), the mechanisms of which remain largely unexplored. This study investigated how deep brain stimulation (DBS) targeting the globus pallidus interna (GPi) and subthalamic nucleus (STN) modulates characteristics of hemispheric lateralization in PD patients, with particular emphasis on motor asymmetries and hemispheric integration (via homotopic functional connectivity) and segregation (via hemispheric asymmetry in connectivity). Resting-state functional magnetic resonance imaging (fMRI) and Unified Parkinson's Disease Rating Scale (UPDRS) III scores were analyzed from 55 PD patients who underwent either bilateral GPi- or STN-DBS. Both targets produced significant improvements in motor function. Notably, stimulation effects on motor asymmetry depend on patients' baseline asymmetry direction (DBS OFF): STN-DBS consistently reduced asymmetry in the leftward-asymmetry patients, whereas GPi-DBS has stronger effects in rightward patients. In both cases, stimulation led to a more symmetric pattern. Beyond motor outcomes, motor gains were associated with changes in homotopic connectivity in the lateral occipital region, overlapping the extrastriate body area, suggesting a compensatory role of visual networks. These findings highlight the contribution of the visual networks to motor improvement and reveal target-dependent effects of DBS on both motor asymmetry and non-motor cognitive domains.

PMID:41904270 | DOI:10.1038/s41380-026-03557-9

Neurotherapeutics. 2026 Mar 27:e00893. doi: 10.1016/j.neurot.2026.e00893. Online ahead of print.

NO ABSTRACT

PMID:41904108 | DOI:10.1016/j.neurot.2026.e00893

J Neurophysiol. 2026 Mar 28. doi: 10.1152/jn.00597.2025. Online ahead of print.

ABSTRACT

Previous studies have documented neural network anomalies in posttraumatic stress disorder (PTSD) characterized by hypercorrelated interactions across brain areas, relative to controls. Here we evaluated and compared local, intra-area(s), interactions by computing crosscorrelations derived from prewhitened resting-state 3T fMRI BOLD time series within 84 brain regions (35 cortical areas and 7 subcortical nuclei per hemisphere) in 15 veterans with PTSD and 21 healthy controls. We found that intra-area correlations were significantly higher in PTSD, as compared to controls, indicating a restriction in local network flexibility. PTSD symptom severity was positively and significantly associated with increased local correlations, most prominently in frontal and limbic areas.

PMID:41902519 | DOI:10.1152/jn.00597.2025

Ideggyogy Sz. 2026 Mar 30;79(3-4):111-119. doi: 10.18071/isz.79.0111.

ABSTRACT

BACKGROUND AND PURPOSE: A central hypothesis to understand the pathophysiological background of psychosis is the modified and disconnected spontaneous activity between different brain regions. Studying patients experiencing first episode psychosis (FEP) is important, because the effects of long-term drug therapy and chronic disease processes are smaller and do not interfere with understanding the original brain processes. Resting state functional magnetic resonance imaging (rs-fMRI) provides a detailed working picture of the macroscopic connectivity structures of the brain. Furthermore, it is instrumental for understanding the biological processes of psychoses, and may have a role in the diagnosis. Studies to date provide evidence that disruption of brain networks is a fundamental factor in the development of psychosis.

METHODS: The aim of our study is to review the literature, with a particular focus on how rs-fMRI can be used to understand early psychosis as a neurodevelopmental disorder. In this narrative literature review, we used the search terms "first episode psychosis" and "resting state fMRI", and focused on the newer English language publications. Based on the search results, the studies were divided into two broad groups. First, we summarise the methods used to study functional connectivity. In the second half of the article, we discuss the analytical techniques that investigate regional brain activity.

RESULTS: FEP is characterized by decreased local network connectivity, while increase of global network connectivity is also observable. The majority of the papers have demonstrated the role of frontotemporal connections and thalamus. Studies examining regional homogeneity also support frontostriatal changes. Decreased activity has been measured in the ventromedial prefrontal cortex and dorsolateral prefrontal cortex. Several studies have described increased activity in the striatum and putamen. In addition, there has recently been an increasing focus on the cerebellum. Most studies have found hyperconnectivity between the cerebellum and the prefrontal cortex, the praecuneus and temporal regions, and in the cerebellar-thalamic-cortical circuit.

CONCLUSION: The reviewed studies support that rs-fMRI is an important tool in investigating FEP. However, the results are very heterogeneous, as a consequence of the different methods and analysis techniques. In the future, standardized protocols should help data collection and analysis to reduce heterogeneity.

PMID:41902457 | DOI:10.18071/isz.79.0111

BMC Med. 2026 Mar 27. doi: 10.1186/s12916-026-04810-2. Online ahead of print.

ABSTRACT

BACKGROUND: The left inferior frontal gyrus (IFG) is implicated in both language and motor processes. Its functional reorganization post-stroke, particularly in motor dysfunction without aphasia, remains poorly understood. We investigated effective connectivity (EC) alterations of the left IFG and their neurochemical basis, and responsiveness to neuromodulation in subcortical stroke.

METHODS: Cross-sectional analysis included 32 left (LSS) and 27 right (RSS) stroke patients and 40 healthy controls (HCs). Seed-based EC of the left IFG was derived from resting-state fMRI and was compared between groups. Relationships between EC, neurotransmitter density, lesion-derived neurotransmitter indices, and Fugl-Meyer Assessment (FMA) scores were examined. Longitudinally, 30 patients received 14 sessions of cathodal-contralesional sensorimotor cortex (SMC), anodal-ipsilesional M1, or sham transcranial direct current stimulation (tDCS), synchronized with upper limb training. Pre-post FMA and EC changes were compared.

RESULTS: Both LSS and RSS groups showed increased EC from the left IFG to the right cerebellum posterior lobe (CPL) and superior frontal gyrus (SFG), whereas only LSS group showed decreased EC from the left CPL to the left IFG. EC from the left IFG to the right CPL positively correlated with FMA, while EC from the left CPL to the left IFG negatively correlated with FMA in LSS. These EC alterations were significantly associated with serotonergic, dopaminergic, and GABAergic neurotransmitter densities. Crucially, IFG-to-SFG connectivity mediated the relationship between lesion-derived neurotransmitter network damage and lower-limb motor deficits. Longitudinal intervention revealed that different tDCS protocols distinctively modulated the left IFG's EC, with the most robust changes induced by cathodal stimulation of the contralesional SMC.

CONCLUSIONS: Collectively, motor-related reorganization occurs in the left IFG post-stroke, characterized by altered EC patterns that are (1) correlated with motor performance, (2) underpinned by specific neurochemical systems, and (3) mediate post-stroke motor impairment. These reorganizations are plastic and respond specifically to targeted neuromodulation, highlighting the left IFG as a potential novel therapeutic target for motor recovery and informing personalized rehabilitation strategies.

TRIAL REGISTRATION: All data used in the present study were obtained from the research trials registered on ClinicalTrials.gov (NCT05648552; submitted 5 December 2022) and www.chictr.org.cn (ChiCTR2100044970; submitted 3 April 2021).

PMID:41896922 | DOI:10.1186/s12916-026-04810-2

Brain Imaging Behav. 2026 Mar 28;20(2):65. doi: 10.1007/s11682-026-01136-8.

ABSTRACT

Hypertension is increasingly recognized as a contributor to cognitive decline and altered brain function, with resting-state functional magnetic resonance imaging (rs-fMRI) offering a non-invasive method to assess spontaneous brain activity and connectivity. This study systematically reviewed and quantitatively synthesized rs-fMRI findings in hypertensive individuals compared to normotensive controls, and within hypertensive subgroups (cognitively normal vs. impaired). A systematic search of PubMed, Scopus, Web of Science, and Cochrane Library (January 2014-March 2024) identified 15 studies for qualitative synthesis, with 11 eligible for meta-analysis using random-effects models. Heterogeneity was assessed with the I2 statistic and bias via the Newcastle-Ottawa Scale. Results showed a moderate pooled effect size of d = 0.64 (95% CI: 0.39-0.89, I2 = 22.9%) for brain functional alterations, with consistent involvement of frontal, temporal, precuneus, cerebellar, and default mode network-related regions across individual studies. With larger effects in hypertensive versus normotensive individuals (d = 0.74, I2 = 39.5%), a moderate effect in cognitively impaired versus normal hypertensives (d = 0.56, I2 = 0%, n = 3), and a large effect for seed-based functional connectivity (d = 0.93, I2 = 0%, n = 2). Sensitivity analysis excluding high-effect studies (n = 2) confirmed robustness (d = 0.57, I2 = 19.7%). A Graphical Display of Study Heterogeneity (GOSH) plot of 1981 subsets, each with three or more studies, showed consistent effect sizes (d ≈ 0.5-0.7) and low-to-moderate heterogeneity (I2 = 0%-40%), supporting stability. Hypertension is significantly associated with altered brain function, particularly in memory and executive regions, suggesting rs-fMRI as a promising biomarker for early cognitive vulnerability detection.

PMID:41896376 | DOI:10.1007/s11682-026-01136-8

Neuroimage. 2026 Mar 25:121887. doi: 10.1016/j.neuroimage.2026.121887. Online ahead of print.

ABSTRACT

Autonomic dysregulation characterizes neuropsychiatric and somatic disorders, often reflecting disrupted brain-heart communication mediated by the Central Autonomic Network (CAN). The CAN integrates visceral inputs and cortical control to maintain autonomic balance. Heart rate variability (HRV) provides peripheral index of CAN regulation, yet the causal dynamics underlying HRV-brain interactions remain poorly understood. We investigated effective connectivity (EC) within a core (C-CAN), extended (E CAN) and non-canonical CAN (N-CAN) to characterize bidirectional brain-heart dynamics at rest. Resting-state fMRI and photoplethysmography were acquired from 232 adults (164 females; mean age = 47.8 ± 18.9 years). PPG-derived HRV metrics (time, frequency, entropy) were extracted and EC was estimated via regression dynamic causal modeling across 100 brain regions, including 42 C-CAN nodes. Predictive modeling used cross-validated ridge regression and bidirectional interactions were modeled using HRV as a driving input. The E-CAN EC model best predicted entropy metrics (ApEn: r = 0.22, SampEn: r = 0.21). The C-CAN model improved predictive performance (SampEn: r = 0.27, ApEn: r = 0.23). Non-CAN EC aligned with E-CAN EC predictions (SampEn: r = 0.17). Analyses revealed HRV-driven influences on distributed cortical and subcortical regions. Our findings show that EC predicts HRV through integrative brain networks beyond canonical CAN nodes. Entropy-based HRV measures emerged as sensitive indicators of central influence on heart dynamics, while bottom up cardio-autonomic signals causally influenced key brain regions supporting neurovisceral integration. Collectively, these results highlight that the complexity of causal brain-heart interactions, reflected in HRV dynamics, mirrors the ROI-to-ROI connectivity patterns across canonical and extended CAN parcellations.

PMID:41895546 | DOI:10.1016/j.neuroimage.2026.121887

Hear Res. 2026 Mar 21;475:109622. doi: 10.1016/j.heares.2026.109622. Online ahead of print.

ABSTRACT

Magnetic resonance imaging (MRI) is a powerful and established tool to non-invasively probe the human auditory system. Varied blood oxygen level-dependent functional MRI (BOLD fMRI) acquisitions have been used to examine the functional roles of this system, but these acquisitions have substantial limitations, such as the need for specialized hardware and long acquisition times, and they typically rely on group averaging of activation patterns. In recent years, whole-brain multi-echo (ME) fMRI techniques have been used to reduce artifacts and scan times, map entire sensory systems, and improve sensitivity to neural activity in both resting-state and task fMRI data acquired at 3T. Combined with dense-sampling strategies, these ME techniques have facilitated "precision mapping" of neural activity in individual subjects. Thus, in this technical note we propose the use of a commonly available ME whole-brain acquisition and ME denoising approaches to examine the auditory system in both group and densely sampled single-subject datasets. Whole-brain and region-specific analyses were performed to identify auditory regions of activation. At the group level, auditory activation was identified bilaterally in cortical regions and unilaterally in cerebellar lobules VIIb/VIIIa with both analyses with ME data. Additionally, the region-specific analysis successfully identified unilateral activation in thalamic and brainstem regions. At the individual subject-level, precision mapping combined with ME denoising methods enhanced sensitivity, yielding bilateral activation in cortical, cerebellar, thalamic, and brainstem regions with both analyses. Lastly, we demonstrate the benefits of using multi-echo methods and a whole-brain precision mapping approach to better align an individual's functional response to their specific anatomy.

PMID:41895044 | DOI:10.1016/j.heares.2026.109622

J Psychiatr Res. 2026 Mar 25;198:133-141. doi: 10.1016/j.jpsychires.2026.03.026. Online ahead of print.

ABSTRACT

Hypomania, a diagnostic phase of bipolar disorder (BD), has garnered considerable research attention regarding its underlying neurobiological mechanisms, which remain inadequately understood. This cross-sectional observational study aimed to investigate the neurobiological correlates of hypomania by examining local brain activity and functional connectivity (FC) through resting-state functional magnetic resonance imaging (rs-fMRI) analyses. The results revealed abnormal local brain activity in the anterior orbital gyrus (OFCant) and superior frontal gyrus (SFG) in patients with hypomania. Additionally, FC analysis demonstrated disrupted connectivity between the right OFCant (R OFCant) and both the right putamen (R PUT) and right insula (R INS). Notably, these altered connectivity patterns showed significant correlations with clinical symptom severity. Collectively, these findings provide preliminary neuroimaging evidence for the neurobiological basis of hypomania, warranting replication and validation in larger and independent cohorts.

PMID:41894926 | DOI:10.1016/j.jpsychires.2026.03.026

Neuroimage. 2026 Mar 25:121888. doi: 10.1016/j.neuroimage.2026.121888. Online ahead of print.

ABSTRACT

The Default Mode Network (DMN) is a large-scale intrinsic brain network critically involved in internally oriented cognition, including autobiographical memory. Core DMN regions such as the hippocampus and medial prefrontal cortex are central to memory retrieval, schema construction and self-referential processing. Individuals with Highly Superior Autobiographical Memory (HSAM) provide a unique model to investigate the neural mechanisms underlying exceptional memory ability. However, the intrinsic functional connectivity and temporal dynamics of the DMN in HSAM remain largely unexplored. To provide new insight into the baseline network mechanisms that supports HSAM irrespective of memory retrieval, in this study we examined both static and dynamic features of DMN functional architecture in 12 HSAM individuals and 31 matched controls during resting-state fMRI. Using a multilevel analytical framework encompassing link-level, node-level, and whole-network level measures, we characterized connectivity strength, temporal variability, and co-activation dynamics within the DMN. HSAM individuals showed enhanced and more temporally stable functional connectivity among memory-related, schema-related, and self-referential DMN regions, including the hippocampus, temporal pole, and ventromedial prefrontal cortex. These findings suggest that HSAM is associated with a more integrated and stable DMN organization, potentially supporting continuous memory replay and the consolidation of autobiographical experiences. This enhanced DMN coherence may represent a neural signature of HSAM.

PMID:41895550 | DOI:10.1016/j.neuroimage.2026.121888

Neuroimage. 2026 Mar 25:121883. doi: 10.1016/j.neuroimage.2026.121883. Online ahead of print.

ABSTRACT

Dexterous hand motor behavior emerges from coordinated interactions within a distributed brain network. While task-related neural dynamics have been investigated, recent fMRI studies showed that also spontaneous - i.e. non-task related - brain connectivity can predict task-specific performance. Still, it remains unclear whether spontaneous functional connectivity reflects also the encoding of general aspects of hand motor control. Here, we applied connectome-based predictive modelling (CPM) to resting-state functional connectivity (rs-FC) from the Human Connectome Project (HCP) to predict performance in hand motor tasks. We identified a "core" hand motor network whose intrinsic connectivity predicted not only task-specific measures (dexterity and strength) but generalised its prediction across different effectors and tasks. This "core" model also generalized its predictions to an independent dataset (external validation), including different behavioral measures and rs-fMRI data. In addition, transcranial magnetic stimulation (TMS) over inferior parietal cortex selectively impacted the core model's predictive power in a time-dependent manner, consistent with the known neurophysiological effects of the stimulation protocol. Together, these findings demonstrate that spontaneous brain activity encodes behaviorally relevant information about hand motor control, spanning both low-level features and higher-order representations. By linking spontaneous brain activity to behavioural motor outcomes, our findings pave the way for better understanding how spontaneous connectivity alterations might underlie motor dysfunction in neurological disorders.

PMID:41895547 | DOI:10.1016/j.neuroimage.2026.121883