Most recent paper

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

Tomography. 2026 Mar 2;12(3):30. doi: 10.3390/tomography12030030.

ABSTRACT

BACKGROUND: In temporal lobe epilepsy (TLE), locally reduced glucose metabolism (i.e., hypometabolism) is indicative of the epileptogenic onset zone (EZ). Here, we investigate the potential value of resting-state fMRI (rs-fMRI) for localizing the EZ with fluorodeoxyglucose positron emission tomography (FDG-PET) as ground truth.

METHODS: Twelve PET-positive patients (34.1 ± 13.1 y; 5 females) with unilateral drug-resistant TLE were included. FDG-PET and rs-fMRI were acquired simultaneously at a hybrid 3T PET-MR scanner. Hypometabolic regions were identified on the FDG-PET images by a nuclear medicine expert. The FDG-PET images were compared with a clinical FDG-PET control dataset with normal glucose uptake distribution. The output z-score maps were thresholded at z < -2 to produce a binary mask of the significantly hypometabolic regions. The hypometabolism masks were mirrored onto the contralateral hemisphere for the asymmetry comparison. Regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF), and fractional ALFF (fALFF) were calculated from the rs-fMRI in conventional (0.01-0.1 Hz) and slow-3 (0.073-0.198 Hz) frequency bands. Asymmetry indices (AIs) were calculated using the ipsilateral and contralateral hypometabolic masks in the PET-positive subjects and assessed via the one-sample Wilcoxon test and Spearman correlation coefficients.

RESULTS: The AIs of conventional fALFF were significantly lower in the hypometabolic zone (p < 0.05). A significant negative correlation was found between the AIs of FDG-PET and fALFF in the slow-3 band (r = -0.62; p < 0.05).

CONCLUSIONS: Conventional and slow-3 band fALFF showed a potential to mimic the FDG-PET findings in terms of EZ localization. Further research with extended cohorts and histopathological validation is required to determine the clinical value.

PMID:41893825 | DOI:10.3390/tomography12030030

Brain Sci. 2026 Mar 19;16(3):327. doi: 10.3390/brainsci16030327.

ABSTRACT

Background/Objectives: Young adulthood is a critical developmental period during which lifestyle behaviors may shape intrinsic brain network dynamics that support cognition. This pilot longitudinal intervention study examined whether variability in physical activity and sedentary behavior during an 8-week exercise and/or cognitive intervention protocol was associated with changes in intrinsic brain dynamics and cognitive and mood outcomes in undergraduate young adults. Methods: Participants (n = 32) completed resting-state functional magnetic resonance imaging (rs-fMRI) at baseline (T1) and post-intervention (T2). Dynamic functional network connectivity (dFNC) was estimated from 53 intrinsic connectivity networks derived using spatially constrained independent component analysis (ICA). Ten recurring dynamic connectivity states were identified and individualized using constrained dynamic double functional independent primitives (c-ddFIPs). State occupancy and dynamic convergence and divergence metrics were computed to characterize network flexibility. Results: Greater moderate-to-vigorous physical activity was modestly but consistently associated with increased occupancy of integrative higher-order states, particularly States 6 and 7, and reduced occupancy of more segregated configurations. More physically active individuals also demonstrated greater divergence between integrative and low-engagement states, whereas greater sedentary time corresponded to increased similarity among segregated configurations. Working memory performance showed parallel associations with more integrative and better-differentiated dynamic patterns. Conclusions: These findings suggest that dynamic functional network reconfiguration may represent a neurobiological mechanism linking lifestyle behaviors and cognitive health in young adulthood. Furthermore, they highlight the translational promise of engagement-driven, low-burden programs for college-aged young adults, showing that even modest variability in habitual physical activity corresponds to greater engagement and differentiation of integrative connectivity states linked to executive and broader cognitive functions.

PMID:41892670 | DOI:10.3390/brainsci16030327

Brain Sci. 2026 Mar 14;16(3):312. doi: 10.3390/brainsci16030312.

ABSTRACT

BACKGROUND: Previous research has found that mindfulness-based techniques are beneficial for reducing stress in heavy-drinking individuals. However, the underlying neurobiology of these stress-reducing effects are unclear. Moreover, much of the research examining neurobiological correlates of mindfulness has used static functional connectivity, suggesting that brain activity goes unchanged for the entire length of an MRI scan.

METHODS: In the current study, we used a state-based dynamic functional connectivity model to examine brain states during either a 10 min mindfulness session or resting control that followed an individually tailored stress imagery task. Using a hidden semi-Markov model (HSMM), six brain states and the associated dynamics of state traversal were estimated for a population of moderate-to-heavy drinkers (N = 32). We modeled the 36 Schaefer atlas regions spanning the salience and default mode networks, and the HSMM characterized each state by its distinct multivariate pattern of activity and covariance structure. Group differences in dwell times, transition behavior, and overall state dynamics were evaluated using permutation tests and mixed-effects models.

RESULTS: Participants that experienced the mindfulness session had more transitions and longer time spent in states in which the salience network was more active. Participants assigned to the control group had more transitions and increased time spent in states in which nodes of the default mode network were more active. Moreover, for control participants, increased occupancy time to SN-dominant states was associated with lower perceived stress.

CONCLUSIONS: Using HSMM provided a unique insight into network connectivity during mindful states; we believe it offers a novel approach to testing and optimizing mindful-based therapies.

PMID:41892655 | DOI:10.3390/brainsci16030312

J Pain Res. 2026 Feb 4;19:573011. doi: 10.2147/JPR.S573011. eCollection 2026.

ABSTRACT

OBJECTIVE: This study integrates resting-state functional magnetic resonance imaging (rs-fMRI) studies to systematically identify core regions of altered regional brain activity and abnormal functional connectivity within cerebral networks in patients with primary trigeminal neuralgia (PTN).

METHODS: We systematically searched PubMed, Web of Science, and EMBASE for rs-fMRI studies (between January 2010 and June 2025) comparing PTN patients with healthy controls (HCs). Through a standardized data extraction protocol, coordinates of divergent brain functional metrics and network connectivity parameters were collected. Ultimately, we included 16 studies, of which 14 were related to functional specific indices (375 patients) and 5 to functional connectivity (204 patients). Separate modality-specific Activation Likelihood Estimation (ALE) meta-analyses were conducted for studies employing Amplitude of Low-Frequency Fluctuation (ALFF/fALFF), Regional Homogeneity (ReHo), and Degree Centrality (DC), to reflect their unique neurophysiological meanings.

RESULTS: ALE analysis revealed index-specific alteration patterns with limited spatial overlap. The ALFF/fALFF analysis identified consistent hypoactivity in the left medial prefrontal cortex. In contrast, ReHo and DC analyses converged to show hyperactivity in the posterior cerebellar lobe and temporal pole. Notably, Seed-based functional connectivity analyses yielded no convergent findings, and limbic system activation was highly heterogeneous.

CONCLUSION: Our meta-analysis demonstrates that PTN involves complex, multidimensional brain remodeling, not a dysfunction of a single "pain center." The distinct spatial patterns identified by different rs-fMRI metrics underscore their complementary value in uncovering PTN pathophysiology. These findings advance the understanding of PTN's central mechanisms, support the development of targeted interventions, and highlight the need to differentiate neurophysiological metrics and clinical subtypes in future research.

PMID:41890577 | PMC:PMC13016099 | DOI:10.2147/JPR.S573011

Front Psychiatry. 2026 Mar 11;17:1745388. doi: 10.3389/fpsyt.2026.1745388. eCollection 2026.

ABSTRACT

BACKGROUND: Intermittent theta burst stimulation (iTBS) to the dorsolateral prefrontal cortex (DLPFC) for major depression has been FDA-approved in the United States since 2018. Accelerated iTBS (aiTBS) protocols of multiple treatments per day have shown promising response and remission rates for major depression, especially when combined with connectivity-guided targeting. Brain networks associated with emotion regulation demonstrate significant changes in connectivity after effective iTBS. However, these findings have been confined to treatment of the left DLPFC, despite literature suggesting equivalent outcomes with right side stimulation. To date there has not been a direct comparison of clinical outcomes and connectivity changes between left and right DLPFC aiTBS for depression.

METHODS: Forty-four patients aged 50-79 with chronic major depressive disorder underwent open-label accelerated fMRI-guided aiTBS (45 sessions, 9 days) to the DLPFC (18 left, 26 right). Depression, anxiety, and anhedonia symptoms were assessed, and resting-state fMRI was obtained at baseline (Visit 1), after 15 sessions (Visit 2), and end of treatment (Visit 3). Patients who were not demonstrating at least 10% improvement in depression at Visit 2 were switched to contralateral stimulation for the remaining 30 sessions.

RESULTS: For the entire cohort (N = 44), mean depression (IDS-C30) scores decreased significantly over the course of treatment. Mean change in IDS-C30, GAD-7, TEPS, SHAPS, and BISBAS between participants with right-sided stimulation (N = 26) and those with left-sided stimulation (N = 18) were not statistically different. Functional connectivity analysis demonstrated significant decreases in connectivity from Visit 1 to Visit 3 between default mode network and limbic networks in patients receiving right DLPFC iTBS, whereas patients receiving left DLPFC iTBS demonstrated limited changes in connectivity.

CONCLUSION: Accelerated iTBS to the right DLPFC appears to have equivalent efficacy as aiTBS to the left DLPFC in terms of magnitude of reduction of depressive, anxious, and anhedonic symptoms in a late-life population. However, connectivity changes associated with treatment were asymmetric, and may reflect hemispheric lateralization of functional network responses to iTBS. Further work is needed to confirm the comparative efficacy and network dynamics of left versus right hemisphere aiTBS for depression.

PMID:41890433 | PMC:PMC13014255 | DOI:10.3389/fpsyt.2026.1745388

Front Hum Neurosci. 2026 Mar 11;20:1757604. doi: 10.3389/fnhum.2026.1757604. eCollection 2026.

ABSTRACT

BACKGROUND: Medical staff frequently experience sleep deprivation, impacting both their health and patient care quality. Understanding brain network changes under sleep deprivation can guide preventive strategies. This study aims to determine how total sleep deprivation (TSD) alters brain network topology in medical professionals.

METHODS: Using graph-theory analysis of resting-state fMRI data from 36 medical staff, we assessed global and local brain network properties following TSD and normal sleep (rested wakefulness, RW), examining topological changes and their correlation with cognitive performance.

RESULTS: Small-world properties were present in both conditions, but the TSD condition showed higher clustering coefficients (p = 0.044). Key nodal changes included increased degree centrality in the right superior medial frontal gyrus (p = 0.0006) and decreased nodal efficiency in the left fusiform gyrus (p = 0.0004). Using the right superior medial frontal gyrus as ROI, enhanced functional connectivity (zFC) was observed in multiple bilateral frontal/temporal regions (peak t > 4.5). These topological changes correlated with cognitive deficits: reduced Digit Symbol Test (DST) scores (p < 0.001), prolonged Number Connection Test-A (NCT-A) and Line Tracing Test (LTT) completion times (p < 0.05), while increased clustering coefficients (Cp) positively correlated with NCT-A/SDT performance changes (r = 0.341-0.411, p < 0.05). And older staff exhibited greater vulnerability in global network efficiency and path length (r = -0.352, r = 0.390, p < 0.05).

CONCLUSION: By identifying key brain network nodes affected by TSD, this study provides insights into neural adaptations under TSD, offering an evidence-based framework for developing both therapeutic interventions and preventive strategies to mitigate cognitive and health impacts in high-risk populations.

PMID:41890345 | PMC:PMC13013376 | DOI:10.3389/fnhum.2026.1757604

Imaging Neurosci (Camb). 2026 Mar 24;4:IMAG.a.1179. doi: 10.1162/IMAG.a.1179. eCollection 2026.

ABSTRACT

Determining the functional organization of the auditory cortex (AC) has been difficult with conventional task-based approaches due to the broad responsiveness of auditory subregions to various acoustic properties. Moreover, most studies have investigated functional organization of AC with static methods, although the brain has shown to be organized into dynamic networks. Here, we investigated dynamically varying coactivation patterns of the local networks in the auditory cortex (AC) determined from 7T fMRI data. Dynamic AC patterns successfully captured interindividual variability, as indicated by significantly higher variability between than within individuals for the AC pattern occurrence rates and spatial topographies. The coactivation patterns shared similarities between resting-state and auditory-task data, as indicated by the group-level similarity of 0.84 and individual-level similarity of 0.71 in the spatial topographies. Furthermore, the occurrence rates of AC patterns identified in the task data, using pattern templates derived from resting-state data, correlated with specific task contrast regressors. Our results suggest that the AC function can be characterized by a set of dynamically varying coactivation patterns. These patterns are consistently observed during resting state and auditory stimulation, and they become synchronized with auditory inputs. These findings enhance our understanding of the relationship between spontaneous and stimulus-driven activity in the AC and support the development of more time-efficient paradigms for studying its functional organization.

PMID:41890246 | PMC:PMC13015430 | DOI:10.1162/IMAG.a.1179

Hum Brain Mapp. 2026 Apr 1;47(5):e70509. doi: 10.1002/hbm.70509.

ABSTRACT

While resting-state brain dysfunctions have been extensively investigated in Alzheimer's disease (AD), the dynamic alterations of functional systems remain poorly understood. We employed co-activation pattern (CAP) analysis to characterize the functional-state alterations in 243 participants using resting-state fMRI data and applied graph theory analysis to estimate corresponding topological properties. The CAP analysis identified five distinct brain states across groups: State 1 (limbic network dominated), State 2 (dorsal attention network (DAN) and central executive network dominated), State 3 (default mode network and central executive network dominated), State 4 (somatomotor network and ventral attention network dominated), and State 5 (DAN, sensorimotor, and visual networks dominated). Compared to cognitively unimpaired individuals, State 3 demonstrated significantly reduced persistence and resilience in both mild cognitive impairment (MCI) and AD groups. Additionally, both clinical groups (MCI and AD) exhibited decreased transitions from State 2 to State 5 and reduced self-transitions within State 3. Graph theory analysis revealed that compared to cognitively unimpaired individuals, MCI and AD individuals had increased node degree centrality and node efficiency, alongside decreased node local efficiency in regions within the default mode network (DAN) and visual network, which corresponded well with CAP analysis results. Our findings provide a multiscale framework linking dynamic state instability to static network reorganization, advancing understanding of the dynamic functional alterations underlying cognitive decline in AD spectrum disorders.

PMID:41889068 | DOI:10.1002/hbm.70509

Cogn Affect Behav Neurosci. 2026 Mar 26. doi: 10.3758/s13415-026-01422-4. Online ahead of print.

ABSTRACT

Adaptive decision-making under risk requires individuals to flexibly adjust their risk-taking behavior after losses. Such post-loss risk adjustment is shaped by self-control (SC) and achievement motivation (AM), yet whether and how these two traits interact to influence this adjustment remains unknown, as well as its underlying neural correlates. To address this question, we recruited two independent samples (discovery: N1 = 425; replication: N2 = 182) to ask them undergo the resting-state fMRI scanning, finish the psychological measurements, and Balloon Analogue Risk Task (BART) used to measure post-loss risk adjustment (Kloss). The behavior results showed a significant interaction effect between SC and AM: higher SC predicted greater post-loss risk reduction (lower Kloss), but only among individuals with low AM, indicating that achievement motivation moderates how self-control shapes adaptive reactions to loss. At the neural level, converging voxel-based morphometry and rsFC results revealed an interaction effect between SC and AM in the left putamen along with functional connectivity (FC) between the left putamen and the anterior cingulate cortex (ACC). Moreover, a moderated mediation analysis demonstrated that the left putamen-ACC FC mediated the relationship between SC and Kloss exclusively in low-AM individuals. These effects replicated in the independent sample, underscoring the robustness of the behavior results and the identified function pathway. Collectively, these findings highlight a putamen-ACC circuit through which self-control and achievement motivation jointly influence adaptive post-loss risk adjustment. The results provide novel evidence that SC and AM shape risk-taking behavior through through mechanisms associated with monitoring and processing of conflict signals.

PMID:41888330 | DOI:10.3758/s13415-026-01422-4

Brain Topogr. 2026 Mar 27;39(3):38. doi: 10.1007/s10548-026-01187-6.

ABSTRACT

Mild cognitive impairment (MCI) is regarded a potential early stage of Alzheimer's disease (AD) and associated with a significantly increased risk of progression to AD. This study aims to evaluate whole-brain static functional connectivity (SFC) disruptions with the default mode network (DMN) seed points in patients with MCI by resting-state functional magnetic resonance imaging (rs-fMRI), and to explore whether these disruptions could serve as potential markers for MCI progression to AD. Retrospective rs-fMRI data with MCI (n = 36) and corresponding matched healthy controls (HCs) (n = 26) were collected for comparison. Independent component analysis (ICA) was used to extract DMN regions, and SFC was calculated for four seed points within the DMN. Two-sample t-tests were performed to compare group differences in SFC strength between the MCI and HC groups, and Pearson correlation analyses were conducted. Compared to HCs, the MCI group showed both increased and decreased SFC between four subregions and multiple brain regions, decreased SFC was more widely distributed than increased SFC. Abnormal connectivity was more prominent in the first two key nodes compared to the latter two. Affected regions primarily located in the precuneus, frontal gyri, temporal gyri, postcentral gyrus, caudate nucleus, lingual gyrus, and fusiform gyrus. The SFC value between the right angular gyrus and the right insula was significantly negatively correlated with MoCA scores (r = - 0.385, p < 0.05, FDR-corrected). It reveals a decline in the functional integration capacity within the DMN, as well as complex reorganization and abnormal connectivity patterns between the DMN and other brain networks. The altered interactions between DMN subregions and abnormal brain areas are significantly associated with episodic memory disturbance in MCI.

PMID:41888327 | DOI:10.1007/s10548-026-01187-6

Sci Rep. 2026 Mar 26;16(1):9978. doi: 10.1038/s41598-026-39424-4.

NO ABSTRACT

PMID:41888182 | DOI:10.1038/s41598-026-39424-4