Most recent paper

Biol Psychiatry Cogn Neurosci Neuroimaging. 2025 Oct 16:S2451-9022(25)00303-9. doi: 10.1016/j.bpsc.2025.10.002. Online ahead of print.

ABSTRACT

BACKGROUND: It is unknown whether brain-based predictive models derived from sleep features are useful for the clinical diagnosis of Major Depressive Disorder (MDD).

METHODS: Using resting-state fMRI data from ABCD (Curated Data Release 3.0), we trained a connectome-based predictive model (CPM) on 35,778 pairwise connections (Pearson's r) from 2349 (234 participants with at least 1 psychiatric disorder, 2112 controls) participants aged 11-12 to predict sleep duration (measured from FitBit). Linear regression models were used to compare the predicted values from these CPMs with self-reported sleep duration and diagnostic group status in an independent cohort of 78 participants (57 MDD, 21 controls) aged 14-18.

RESULTS: The ABCD-based CPM predicted self-reported sleep duration in the independent cohort of MDD participants (partial r=0.332, p=0.009). Even though self-reported sleep duration did not significantly differ between diagnostic groups (t=0.13, p=0.90), the ABCD-based CPM successfully distinguished between diagnostic groups (partial r=0.334, p<0.001), and CPM-predicted sleep durations correlated with depression symptom severity (partial r=0.294, p<0.001). These diagnostic group differences were driven primarily by patterns of hypoconnectivity between various resting-state networks (including the default mode, frontoparietal, motor, subcortical, and visual associative networks).

CONCLUSIONS: CPMs trained to predict objective sleep duration are robust and generalizable. Intrinsic functional connectivity differences between clinically depressed and psychiatrically healthy adolescents are detectible by CPMs optimized for sleep prediction, underscoring the shared neural bases between sleep health and depression. Future work will test whether sleep-based CPMs are predictive of clinical course and if they generalize to other disorders beyond depression.

PMID:41109569 | DOI:10.1016/j.bpsc.2025.10.002

Dev Cogn Neurosci. 2025 Oct 12;76:101629. doi: 10.1016/j.dcn.2025.101629. Online ahead of print.

ABSTRACT

Preterm birth is a known risk factor for neurodevelopmental disabilities, but early neurobehavioral assessments and structural imaging often fail to predict long-term outcomes. This limitation underscores the need for alternative biomarkers that reflect early brain organization. Resting-state functional connectivity offers a powerful tool to track functional brain organization by characterizing resting-state networks (RSNs), potentially offering more sensitive biomarkers. However, most fMRI studies in infant populations use group-level analyses that average subject-specific data across several weeks of development, reducing sensitivity to subtle, time-sensitive deviations from typical brain trajectories, particularly in higher-order association networks. Using a recently introduced precision mapping approach, we estimated individual resting-state networks (RSNs) in a large cohort of term and preterm neonates from the developing Human Connectome Project. RSN connectivity strength increased linearly with age at scan, with primary sensory networks maturing earlier and higher-order association networks, including the default mode network (DMN), showing more gradual but pronounced changes, evolving from an immature organization in preterm infants to a more adult-like pattern in term-born infants. Longitudinal data from a subset of preterm infants confirmed ongoing network development shortly after birth. Despite this maturation, preterm infants did not reach the connectivity levels of term-born infants by term-equivalent age. These findings demonstrate that individualized RSN mapping captures heterogeneous developmental trajectories in the neonatal brain and highlights higher-order association networks, particularly the DMN, as promising early markers for monitoring neurodevelopmental outcomes in neonates.

PMID:41109198 | DOI:10.1016/j.dcn.2025.101629

Mov Disord Clin Pract. 2025 Oct 18. doi: 10.1002/mdc3.70391. Online ahead of print.

ABSTRACT

BACKGROUND: Apathy is a common early symptom of Parkinson's disease (PD), often co-occurring with cognitive decline and associated with fronto-striatal and mesocortico-limbic dysfunctions. Discrepancies between self- and caregiver-reported apathy have been preliminarily associated with cognitive impairments affecting patients' awareness and self-report accuracy.

OBJECTIVES: This study investigates discrepancies between PD patient- and informant-reported apathy in relation to the cognitive status (unimpaired-CU vs. impaired-CI), and explores neural correlates of apathy using magnetic resonance imaging (MRI).

METHODS: Apathy was assessed in 23 PD participants using self-report (AES-S) and informant (AES-I) versions of the Italian Apathy Evaluation Scale. Discrepancy scores (ΔAES) were compared between groups and correlated with cognitive performance. Resting-state fMRI examined associations between AES indices and connectivity from the bilateral nucleus accumbens, while whole-brain structural analyses assessed associations with gray matter (GM) volume.

RESULTS: PD-CI participants showed higher ΔAES, underestimating their apathy compared to PD-CU. ΔAES values correlated with attentional and visuospatial functioning. Higher AES-I scores were associated with hyperconnectivity between right nucleus accumbens, paracingulate, and medial frontal cortices. Structural analyses revealed associations between both AES-I and ΔAES values and GM volume in the cingulate gyrus.

DISCUSSION: These findings highlight the impact of cognitive dysfunction on apathy evaluation in PD, emphasizing the importance of caregiver perspective. Neuroimaging results further validated caregiver ratings, showing an association between fronto-striatal network changes and apathy. Further research is needed to clarify the role of such discrepancy in apathy assessment in predicting disease progression.

PMID:41108660 | DOI:10.1002/mdc3.70391

Magn Reson Med. 2025 Oct 17. doi: 10.1002/mrm.70110. Online ahead of print.

ABSTRACT

PURPOSE: To demonstrate the feasibility and performance of whole-brain blood oxygen level-dependent functional MRI (fMRI) in humans at 10.5 T by combining motion-robust three-dimensional gradient-echo echo-planar imaging, parallel transmission, and high-density radiofrequency (RF) receive coils.

METHODS: Resting-state fMRI time series were collected in healthy adults at 1.58 mm and approximately 2-s spatiotemporal resolution using a custom-built 16-channel transmit/80-channel receive RF array. Individualized parallel-transmission, spatial-spectral RF pulses were designed to achieve uniform water-selective excitation across the entire brain without the need for additional fat saturation. Images were reconstructed with navigator-guided joint motion and field correction. Reconstructed images were preprocessed using fMRIPrep and postprocessed using XCP-D pipelines. Relevant resting-state fMRI metrics were evaluated including temporal SNR (tSNR), amplitude of low-frequency fluctuation, and regional homogeneity. The results were compared with those obtained using uncorrected reconstruction (i.e., using same raw data but without motion or field correction).

RESULTS: Our motion-corrected reconstruction largely improved image quality for fMRI time series, reducing motion confounds when compared with uncorrected reconstruction. The reduction in motion confounds translated into an improvement in tSNR, with tSNR averaged across all volunteers being increased by about 11%. Our motion-corrected reconstruction also improved both amplitude of low-frequency fluctuation and regional homogeneity in most cortical surfaces and subcortical regions.

CONCLUSION: It is feasible to perform quality three-dimensional whole-brain blood oxygen level-dependent fMRI in humans at 10.5 T using a new comprehensive motion-robust imaging method. This work paves the way for promising future applications at 10.5 T aimed at studying brain function and networks with high spatiotemporal resolution.

PMID:41108198 | DOI:10.1002/mrm.70110

Transl Psychiatry. 2025 Oct 17;15(1):405. doi: 10.1038/s41398-025-03678-9.

ABSTRACT

Adolescence is a critical period of neural development and a sensitive window for the emergence of psychiatric symptoms. Resting-state functional MRI (rs-fMRI) provides a unique opportunity to investigate brain-behavior associations. However, the role of sex-specific differences in these associations remains underexplored, despite their potential to reveal heterogeneous neurobiological mechanisms and guide personalized interventions. In this study, we analyzed data from the Adolescent Brain Cognitive Development (ABCD) Study, comprising 7,892 adolescents (9-10 years old, 3,896 females). Using Canonical Correlation Analysis (CCA) and a rigorous cross-validation framework, we identified associations between cortical-to-cortical (Cor-Cor) and cortical-to-subcortical (Cor-Sub) functional connectivity and eight symptom domains from the Child Behavior Checklist (CBCL). Unlike previous approaches, we directly examined sex differences within the brain-behavior mappings by applying separate CCA models in boys and girls to uncover differential connectivity-behavior relationships. Our analysis uncovered two reproducible components for both Cor-Cor and Cor-Sub mappings on the whole cohort (r1 = 0.130, p < 0.001, r2 = 0.122, p < 0.01 for Cor-Cor; r1 = 0.157, p < 0.001, r2 = 0.115, p < 0.01 for Cor-Sub). Importantly, sex-stratified analyses revealed distinct patterns of brain-behavior associations. Among females, high loadings on attention and thought problems were linked to high loadings on default mode network, whereas in males, attention and thought problems were linked to sensorimotor networks. Compared to females, males also had higher loadings on internalizing symptoms, such as anxious/depressed and withdrawn/depressed symptoms, coupled with lower loadings on putamen and hippocampus functional connectivity. These findings suggest there may be fundamentally different brain-behavior mappings across the sexes in adolescence, in addition to previously reported sex differences in functional connectivity and behavioral profiles. By revealing sex-specific neural correlates of psychiatric symptoms in early adolescence, this study paves the way for sex-informed strategies in clinical risk assessment and personalized treatment design.

PMID:41107246 | DOI:10.1038/s41398-025-03678-9

Brain Res Bull. 2025 Oct 15:111587. doi: 10.1016/j.brainresbull.2025.111587. Online ahead of print.

ABSTRACT

PURPOSE: To comprehensively examine static and dynamic functional connectivity density (FCD) in temporal lobe epilepsy (TLE) with hippocampal sclerosis (HS) and MRI-negative TLE and its potential correlation with cognition.

METHODS: Fifty-three healthy controls (HC), 38 TLE-HS patients, and 51 MRI-negative TLE patients underwent MRI scans of resting-state BOLD functional imaging and 3D T1WI sequence. Static functional connectivity density (FCD) and corresponding temporal dynamic FCD (dFCD) were calculated utilizing a sliding window approach and statistically compared among groups. Further seed-based functional connectivity FC analysis and ROC curve analysis were executed. Relationships between cognitive scores and FCD or dFCD values were analyzed by Spearman correlation.

RESULTS: The TLE-HS and MRI-negative TLE both demonstrated reduced static FCD values in the temporal neocortex ipsilateral to the epileptogenic focus. However, the TLE-HS revealed larger aberrant cluster sizes of reduced FC in the ipsilateral frontal and temporal lobes. For dFCD, its elevation in the ipsilateral temporal neocortex was detected only in MRI-negative TLE. The dFCD was significantly correlated with cognitive scores and revealed a moderate discrimination ability.

CONCLUSIONS: The combination of static FCD and dFCD could provide novel and complementary evidence to help deepen our understanding of the whole brain function's impairment and compensatory mechanism in TLE. The patterns of change in FCD abnormalities were similar between TLE-HS and MRI-negative TLE, which were more pronounced and widely involved in the TLE-HS group. Furthermore, dFCD may reveal more nuanced variations in MRI-negative TLE and help in discrimination.

PMID:41106485 | DOI:10.1016/j.brainresbull.2025.111587

J Affect Disord. 2025 Oct 15:120499. doi: 10.1016/j.jad.2025.120499. Online ahead of print.

ABSTRACT

Long-term fibromyalgia syndrome (FMS) patients experience chronic pain, emotional disturbances, and poor treatment responses, yet the neural mechanisms underlying disease chronicity remain unclear. This study aimed to investigate the white matter-gray matter functional connectivity (WM-GM FC) in long-term FMS patients to explore changes in brain network communication associated with chronicity and their relationship with clinical symptoms. A total of 52 FMS patients (30 long-term, 22 short-term) and 49 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (fMRI). WM-GM FC was analyzed by calculating Pearson correlation coefficients between 48 predefined white matter tracts and 82 Gy matter regions. Clinical evaluations included the Hamilton Depression Rating Scale (HAMD), Hamilton Anxiety Rating Scale (HAMA), Visual Analogue Scale (VAS), and pain duration. The results revealed that long-term FMS patients had 64 significantly reduced WM-GM FCs compared to HCs, 44 of which involved the left uncinate fasciculus (UF) and multiple gray matter regions. No significant differences in WM-GM FC were observed between short-term FMS patients and HCs. In long-term FMS patients, FC between the left UF and several gray matter regions showed negative correlations with HAMD, HAMA, VAS, and pain duration. These findings suggest that widespread reductions in WM-GM FC in long-term FMS, particularly involving the left UF, may play a crucial role in pain modulation and emotional regulation. The study provides new insights into the neural mechanisms underlying FMS chronicity and supports the potential of WM-GM FC as a biomarker for identifying pathophysiological processes and therapeutic targets in FMS. PERSPECTIVE: Fibromyalgia syndrome (FMS) patients with prolonged symptoms often face treatment resistance and worsening emotional-pain comorbidities, yet the neural basis of chronicity remains unclear. This study explored white matter-gray matter functional connectivity (WM-GM FC) in 30 long-term FMS patients, 22 short-term patients, and 49 healthy controls. Long-term patients exhibited 64 reduced WM-GM FCs, predominantly between the left uncinate fasciculus (UF)-a tract linking emotion and pain networks-and limbic/cortical regions. These disruptions correlated with higher depression, anxiety, pain severity, and duration, while short-term patients showed no significant FC differences. The findings identify left UF dysfunction as a potential neural marker of FMS chronicity, offering insights into how prolonged pain reshapes brain connectivity. Clinically, WM-GM FC could guide early interventions to prevent progression or serve as a therapeutic target, addressing the unmet need for biomarkers in managing this debilitating disorder. This advances understanding of FMS pathophysiology and highlights pathways to mitigate its long-term societal and individual burden.

PMID:41106634 | DOI:10.1016/j.jad.2025.120499

Brain Res Bull. 2025 Oct 15:111588. doi: 10.1016/j.brainresbull.2025.111588. Online ahead of print.

ABSTRACT

BACKGROUND: Internet gaming disorder (IGD) is a behavioral addiction, as revealed by previous neuroimaging studies on gray matter volume alterations and functional connectivity abnormalities that patients with internet gaming disorder have. Combining different dimensions of resting-state functional indicators may help us to understand more about the neuropathological mechanisms of online gaming disorder.

METHODS: We conducted a systematic search in PubMed, Web of Science, and Scopus from January 2000 through December 2024 to identify eligible voxel-based morphometry(VBM) studies. Using an anisotropic seed-based D-Mapping (AES-SDM) meta-analysis approach, we compared structural brain abnormalities between IGDs and healthy controls(HCs). Subsequently, resting-state functional connectivity(rs-FC) analyses were performed on 56 IGDs and 43 HCs using meta-derived regions as seeds. In addition, we performed correlation analyses to assess the relationship between functional connectivity abnormalities and clinical features.

RESULTS: The meta-analysis showed reduced gray matter volume(GMV) in the prefrontal cortex and cingulate gyrus, alongside increased GMV in the caudate nucleus in IGD compared to HCs. Rs-FC analysis showed enhanced connectivity between the middle cingulate cortex and prefrontal, cingulate and Supplementary motor area in IGD, with functional connectivity values correlating with duration of illness; However, after correction, this correlation was not significant.

CONCLUSION: Our study suggest dysregulation of cognitive control, reward, and motor networks in IGD and emphasize the importance of prefrontal cortex and cingulate alterations in adolescent addiction mechanisms, providing insights for targeted interventions.

PMID:41106487 | DOI:10.1016/j.brainresbull.2025.111588

Neurology. 2025 Nov 11;105(9):e214298. doi: 10.1212/WNL.0000000000214298. Epub 2025 Oct 17.

ABSTRACT

BACKGROUND AND OBJECTIVES: Traumatic brain injury (TBI) is associated with widespread disruptions in functional connectivity (FC), yet how these alterations vary by injury severity remains unclear. Traditional classification systems fail to capture network-level dysfunction, limiting prognostic accuracy and targeted rehabilitation strategies. The aim of this study was to systematically evaluate fMRI-detected FC alterations after mild, moderate-severe, and severe TBI using coordinate-based meta-analysis and network-level mapping.

METHODS: A systematic search of MEDLINE/PubMed, Embase, and Web of Science was conducted to identify studies examining FC changes in TBI using fMRI. This review was not funded or prospectively registered. Studies were stratified by TBI severity and time since injury. Significant peak Montreal Neurological Institute coordinates were extracted, matched to the Yeo-17 brain network atlas, and analyzed using Seed-based d Mapping with Permutation of Subject Images (SDM-PSI). Study quality and evidence level were assessed using an adapted NIH Quality Assessment Tool and the Oxford Centre for Evidence-Based Medicine criteria. Eligible studies included adult participants with TBI assessed using resting-state or task-based fMRI; studies lacking severity classification or involving pediatric populations were excluded.

RESULTS: Seventy-six studies were included, totaling 5,064 participants (2,993 patients with TBI, 1,914 controls; mean age 35.5 vs 35.0 years; 37.6% female overall). Mild TBI (mTBI) was the most common severity (n = 59 studies; 77.6%). Twenty-two studies contributed data for meta-analysis: 15 with resting-state fMRI and 7 with task-based fMRI. Aggregated peak coordinates most frequently mapped to subcomponents of the default mode (22.9%), ventral attention (18.8%), and somatomotor (10.1%) networks in mTBI and to the frontoparietal (36%), ventral attention (20%), and dorsal attention (14.7%) networks in moderate-severe/severe TBI. SDM-PSI identified uncorrected clusters in default mode and frontoparietal regions in mTBI and moderate-severe/severe TBI, respectively, but no clusters survived family-wise error rate correction (standardized mean difference Z score range -1.986 to 3.911, p < 0.05 uncorrected). Heterogeneity was low across analyses (I2 < 21%).

DISCUSSION: FC changes after TBI potentially involve large-scale brain networks such as the default mode, attention, and executive control networks in a severity-dependent and phase-dependent manner. Although meta-analysis revealed consistent patterns, corrected statistical significance was not achieved, highlighting the need for larger, harmonized data sets and standardized analysis pipelines in future research.

PMID:41105904 | DOI:10.1212/WNL.0000000000214298

J Alzheimers Dis. 2025 Oct 17:13872877251386844. doi: 10.1177/13872877251386844. Online ahead of print.

ABSTRACT

BackgroundResting-state functional magnetic resonance imaging (fMRI) studies in dementia with Lewy bodies (DLB) and Alzheimer's disease (AD) have described connectivity alterations in large-scale brain networks. However, little is known about functional changes across disease stages, particularly in DLB.ObjectiveTo investigate functional connectivity of key brain networks in DLB patients at different stages, compare them to AD patients and healthy controls (HC), and examine associations with core clinical symptoms.MethodsNinety DLB patients (63 with mild cognitive impairment [MCI-DLB] and 27 with dementia [d-DLB]), 25 AD patients (11 MCI-AD and 14 d-AD) and 34 HC underwent clinical, neuropsychological and resting-state fMRI assessments. Region of interest (ROI)-to-ROI analyses were performed using the CONN toolbox (pFDR < 0.05).ResultsThe overall DLB group showed reduced functional connectivity within the salience network (SN) compared to HC, but not to the overall AD group. At the subgroup level, d-DLB patients showed reduced SN and frontoparietal network (FPN) connectivity compared to both HC and the overall AD group, whereas MCI-DLB did not significantly differ from either group. In the overall DLB group, SN connectivity correlated with fluctuation severity and FPN connectivity correlated with both REM sleep behavior disorder and cognitive decline. In the overall AD group, decreased default mode network (DMN) connectivity was associated with lower Mini-Mental State Examination scores.ConclusionsSN and FPN connectivity impairments relate to disease progression and core clinical features in DLB, whereas DMN connectivity is linked to cognitive decline in AD. These distinct patterns highlight divergent paths of network dysfunction in the two diseases.Clinical Trial: This study is part of the AlphaLewyMA cohort, registered on ClinicalTrials.gov (identifier: NCT01876459; registered on June 12, 2013).

PMID:41105629 | DOI:10.1177/13872877251386844

Hum Brain Mapp. 2025 Oct 15;46(15):e70377. doi: 10.1002/hbm.70377.

ABSTRACT

Large-scale functional brain networks have most commonly been evaluated using static methods that assess patterns of activation or functional connectivity over an extended period. However, this approach does not capture time-varying features of functional networks, such as variability in functional connectivity or transient network states that form and dissolve over time. Addressing this gap, dynamic methods for analyzing functional magnetic resonance imaging (fMRI) data estimate time-varying properties of brain functioning. In the context of resting-state neuroimaging, dynamic methods can reveal spontaneously occurring network configurations and temporal properties of such networks. Patterns of network functioning over time during the resting state may be indicative of individual differences in cognitive-affective processes such as rumination, or the tendency to engage in a pattern of repetitive negative thinking. We first introduce the current landscape of dynamic methods and then review an emerging body of literature applying these methods to the study of rumination and depression to illustrate how dynamic methods may be used to study clinical and cognitive phenomena. An emerging body of research suggests that rumination is related to altered functional flexibility of brain networks that overlap with the canonical default mode network. An important future direction for dynamic fMRI analyses is to explore associations with more specific features of cognition.

PMID:41104784 | DOI:10.1002/hbm.70377

Indian J Psychol Med. 2025 Oct 14:02537176251381216. doi: 10.1177/02537176251381216. Online ahead of print.

ABSTRACT

BACKGROUND: As more accurate neuromodulation systems combining high-resolution electroencephalogram (EEG) and anatomical biomarkers develop, it is prudent to evaluate how refined and effective precision neuromodulation is compared to conventional techniques. Considering the growing incidence and the lack of studies outlining an optimal treatment approach, which often leads to a poorer prognosis, young-onset mania presents an ideal challenge for such a comparison.

NOVELTY: This study aims to be the first to directly compare precision and conventional neuromodulation in child and adolescent populations. It also seeks to study and compare, for the first time, changes in neuroimaging parameters caused by precision and conventional techniques. By correlating perturbation-induced changes in cortical inhibition paradigms and functional connectivity of cerebral circuits, we aim to introduce a more objective measure of therapeutic efficacy and response, as opposed to relying solely on subjective clinical scales. Furthermore, we aim to study, for the first time, task-based differential activation of brain areas in young-onset mania.

METHODS: Participants would be randomly allocated to the intervention group 1 (G1) or the active control treatment group 2 (G2). Baseline assessments of both groups will include evaluations using clinical scales (Clinical Global Impression [CGI], Brief Psychiatric Rating Scale-Child [BPRS], Young Mania Rating Scale [YMRS], Barratt's Impulsivity Scale [BIS], and Affectivity Reactivity Index [ARI]), task-based and resting-state functional magnetic resonance imaging (rs-fMRI), and transcranial magnetic stimulation (TMS)-based cortical inhibition paradigms (cortical silent period [CSP], short interval intracortical inhibition [SICI], and long interval intracortical inhibition [LICI]). G1 would receive precision-based high-definition transcranial direct current stimulation (HD-tDCS) over the right ventromedial prefrontal cortex (VMPFC) daily for 10 days with 2 sessions spaced 4 h apart. G2 would receive conventional HD-tDCS over the right VMPFC daily for 10 days with sessions spaced 4 h apart. Participants would undergo reassessment at 2 weeks following the completion of 20 sessions, using scales, task-based and rs-fMRI, and cortical inhibition paradigms, as well as at 6 weeks.

RESULTS: Data would be analyzed using the Statistical Package for the Social Sciences (SPSS) for outcome variables as defined for the study. The primary outcome variable would be the improvement in the severity of young-onset mania, as measured by YMRS and CGI scale scores, using precision over conventional HD-tDCS. The secondary outcome would be an improvement in functional connectivity, as measured by neuroimaging, and enhancement of cortical inhibition, as measured by cortical inhibition paradigms, in young-onset mania after receiving adjunctive precision over conventional HD-tDCS.

CONCLUSIONS: This study protocol aims to explore the effect of novel precision-based HD-tDCS in young-onset mania compared to conventional HD-tDCS, thereby allowing for the examination of precision neuromodulation in young-onset mania.

PMID:41104323 | PMC:PMC12521149 | DOI:10.1177/02537176251381216

Front Psychiatry. 2025 Oct 1;16:1675719. doi: 10.3389/fpsyt.2025.1675719. eCollection 2025.

ABSTRACT

BACKGROUND: Substantial interindividual variability exists in the response of adolescents with major depressive disorder (MDD) to selective serotonin reuptake inhibitors (SSRIs), and reliable early predictors of treatment response are lacking.

METHODS: Resting-state functional magnetic resonance imaging (fMRI) data and clinical scale scores were collected from 69 adolescents with first-episode, drug-naïve MDD. Based on treatment response assessed after 8 weeks of SSRIs therapy, participants were categorized into a responder group (n=37) and a non-responder group (n=32). Graph-theoretical analysis was then performed on the pre-treatment resting-state functional networks of both groups.

RESULTS: Significant group differences emerged in several global attribute metrics and multiple brain region node attribute metrics (including the left middle frontal gyrus, hippocampus, parahippocampal gyrus, amygdala, pallidum, as well as the right anterior cingulate cortex and inferior parietal lobule). Partial correlation analyses revealed ​negative correlations between nodal efficiency in the left middle frontal gyrus, hippocampus, and parahippocampal gyrus, as well as degree centrality in the right anterior cingulate gyrus, and the reduction rate in Hamilton Depression Rating Scale-17 score. Furthermore, logistic regression analysis identified lower nodal efficiency in the right inferior parietal lobule and higher clustering coefficient in the left pallidum as significant predictors of SSRIs treatment response.

CONCLUSIONS: Pre-treatment functional network topological metrics differentiating responders and non-responders demonstrate potential as predictors for SSRIs treatment response in adolescents with MDD.

PMID:41103731 | PMC:PMC12521158 | DOI:10.3389/fpsyt.2025.1675719

Front Neurosci. 2025 Oct 1;19:1544748. doi: 10.3389/fnins.2025.1544748. eCollection 2025.

ABSTRACT

INTRODUCTION: This report deals with advanced processing of blood oxygenation-dependent (BOLD) functional magnetic resonance imaging (fMRI) signals. It does not address functional characteristics of the human cortex, such as functional connectivity. fMRI is based on measurement of BOLD variations of transverse relaxation time T2 * or T2 . T2 * or T2 can be calculated when multiple echoes of the MRI signal are recorded and may be more resistant to artifacts or better characterize tissue properties than the echoes themselves.

OBJECTIVES: To develop a robust-to-noise algorithm for dynamic T2 * mapping from a three gradient-echo (GRE) signal, allowing exploration of the potential of quantitative T2 * mapping.

METHODS: fMRI resting-state and block-design visual task three-echo data were acquired from nine healthy volunteers. A significant problem in multi-echo T2 * fitting is the noise in the echoes. The majority of BOLD-denoising methods first pinpoint some source of noise and subsequently remove the respective noise time series. We instead first postulated that the blood oxygenation changes smoothly and consequently developed a state-of-the-art denoising algorithm that minimizes total variation (TV), enforcing smoothness in the processed BOLD echoes while preserving local temporal signal means. To ensure that calculated T2 * time courses are also smooth, they were estimated from TV-denoised echoes. We used a denoising approach initially proposed by Professor Stanley Osher for two-dimensional (2D) images that has been very successful, most prominently in space research, where it enabled the reconstruction of the first-ever image of a black hole. To our knowledge, Osher's approach has so far not been used elsewhere for the denoising of one-dimensional fMRI time series.

RESULTS: Signal-to-noise and contrast-to-noise distributions of the denoised echoes, as well as of the T2 * time series, were superior to those obtained by the current fMRI denoising methods (3dDespike, tedana, NORDIC). The denoised echoes and the T2 * time courses match the shape of the theoretical hemodynamic function much better than previous results.

CONCLUSION: The TV-minimizing fMRI time series denoising algorithm yields denoised echoes of unprecedented quality, enabling estimation of smooth, dynamic T2 * maps, i.e., a transition from qualitative-only fMRI echoes to fMRI signals endowed with time units.

PMID:41103727 | PMC:PMC12521463 | DOI:10.3389/fnins.2025.1544748

Trials. 2025 Oct 16;26(1):421. doi: 10.1186/s13063-025-09171-4.

ABSTRACT

BACKGROUND: Reducing opioid use is challenging due to limited evidence-based weaning methods and a lack of interventions to mitigate withdrawal symptoms. An emerging intervention using transcutaneous auricular neurostimulation (tAN) is being developed to reduce opioid withdrawal symptoms, but its mechanisms of action are not yet well understood. This is a clinical trial performed to investigate the mechanisms of tAN in managing pain and opioid withdrawal during opioid taper in adults with chronic pain.

METHODS: This is a single-site, randomized, double-blind, and sham-controlled superiority framework trial during an inpatient opioid taper for participants on long-term opioid therapy for chronic pain. Participants are recruited for an inpatient stay at a large, academic medical center in the United States. Included participants are adults between 18 and 75 years of age who have the presence of pain more than half of the days in the past 6 months, are prescribed opioid medication, have a willingness to taper the opioid dose by at least 10%, and have a urine drug screen positive for the prescribed opioid but negative for illicit drugs and nonprescribed opioids. Participants are excluded with a condition affecting their safety of participation (e.g., epileptic seizures, current suicidal ideation, current abuse of illicit drugs or alcohol, pregnancy), a condition that precludes fMRI assessment (implanted medical device, claustrophobia), or a status affecting pain medication intake (e.g., surgery in the past month, opioid prescription dose > 200 morphine milligram equivalents per day, history of neurological diseases or traumatic brain injury, active treatment for cancer). Participants are randomized to receive either active tAN (n = 20) or sham tAN (n = 20). Both groups undergo a mild-to-moderate opioid taper on day 1 and are maintained at the reduced level for 4 days under inpatient medical supervision. The primary outcome measure, brain functional magnetic resonance imaging (fMRI), is used to measure BOLD signals and resting functional connectivity (z-value) of pain networks. Secondary outcome measures are self- and clinician-observed opioid withdrawal scales, behavioral assessment questionnaires, and quantitative sensory testing (QST) data. The first subject enrollment was completed from July 25 to 28, 2023. The total enrollment count was set to 40 with two arms of equal ratios. Randomization stratification by gender at birth was performed. The study physician, intervention-providing staff member, and outcome-assessing study coordinator each perform recruitment, and each is blinded to treatment group assignment. Safety and harm measures of opioid withdrawal will be assessed with the Clinical and Subject-reported Opiate Withdrawal Scores. Vital signs will be assessed three times per day, and adverse events will be recorded and reported as necessary.

DISCUSSION: Understanding the mechanisms of action of tAN will lead to the development of more effective future non-pharmacologic treatments in mitigating withdrawal while gradually tapering participants off prescription opioid management.

TRIAL REGISTRATION: Clinicaltrials.gov, NCT05555485. Registered on 15 September 2022.

PMID:41102821 | DOI:10.1186/s13063-025-09171-4

J Affect Disord. 2025 Oct 14:120455. doi: 10.1016/j.jad.2025.120455. Online ahead of print.

ABSTRACT

BACKGROUND: Chronic insomnia disorder (CID) is one of the most common but heterogeneous sleep disturbances with varied clinical manifestations. A more in-depth understanding of the brain functional deviations associated with symptom subtypes will help elucidate the mechanisms involved in CID. The present study examined the topological properties of the brain networks associated with the CID subtype, focusing particularly on prolonged sleep onset latency (SOL), to ascertain whether these properties mediate the diverse clinical subtypes of CID.

METHODS: Ninety-two participants were included in the study, comprising 42 CID patients with prolonged SOL (PSOL group), 24 CID patients with non-prolonged SOL (NPSOL group), and 26 sex- and age-matched good sleepers (GS group). Graph theoretical analysis was used to assess the brain network's global and nodal topological property deviations among these groups. Spearman's correlation analyses were performed to explore the relationship between topological properties and clinical measures.

RESULTS: Although the PSOL and NPSOL groups showed similar alterations in network topological properties compared with good sleepers, the PSOL group exhibited specific deviations from the NPSOL group, including reduced nodal efficiency (Ne) of the left ventral prefrontal cortex (vPFC) and increased global shortest path length (Lp). Notably, the decreased Ne in the vPFC and increased Lp both correlated with higher Sleep Latency Score (SLS) (r = -0.397, p < 0.001; r = 0.336, p = 0.001).

CONCLUSION: Clinical subtypes of CID have shared and unique alterations in brain network topological properties. Prolonged SOL is particularly associated with disruptions in global information integration and impaired nodal transmission efficiency of vPFC. These findings shed new light on the neural mechanisms underlying CID heterogeneity.

PMID:41101492 | DOI:10.1016/j.jad.2025.120455

Body Image. 2025 Oct 15;55:101984. doi: 10.1016/j.bodyim.2025.101984. Online ahead of print.

ABSTRACT

OBJECTIVE: Muscularity-oriented disordered eating, characterized by disordered eating symptoms driven by the pursuit of a muscular physique, is an emerging public health concern. Although childhood maltreatment has been linked to thinness-oriented disordered eating, underpinned by the pursuit of a thin ideal, little is known about the longitudinal associations between specific subtypes and muscularity-oriented disordered eating or the neural mechanisms mediating these associations.

METHOD: This study used two-wave data from an ongoing research project tracking college freshmen at a university in Chongqing, China. At Time 1, 212 participants (Age: M (SD) = 18.87 (0.97) years; 38% men) completed behavioral assessments and resting-state fMRI scans, and 144 returned for follow-up at Time 2. We examined these relationships through connectome-based predictive modeling (CPM) and mediation analysis.

RESULTS: Only childhood physical abuse showed a significant indirect effect on T2 muscularity-oriented disordered eating via T1 muscularity-oriented disordered eating. CPM identified the most significant predictive connections in the dorsolateral prefrontal cortex, inferior frontal gyrus, and cerebellum, with positive muscularity-oriented disordered eating networks primarily linking the salience/limbic network to the cerebellum and the fronto-parietal network to the default mode network. In the brain-behavior model, childhood physical abuse's effect on muscularity-oriented disordered eating was partly mediated by these CPM-derived networks.

CONCLUSIONS: Childhood physical abuse emerged as a predictor of muscularity-oriented disordered eating from both behavioral and neural perspectives. These findings underscore the clinical importance of early identification of childhood physical abuse and support the development of integrated psychological and neurobiological interventions to prevent the development of muscularity-oriented disordered eating.

PMID:41101090 | DOI:10.1016/j.bodyim.2025.101984

PLoS One. 2025 Oct 16;20(10):e0334028. doi: 10.1371/journal.pone.0334028. eCollection 2025.

ABSTRACT

The COVID-19 pandemic had profound effects on developing adolescents that, to date, remain incompletely understood. Youth with preexisting mental health problems and associated brain alterations were at increased risk for higher stress and poor mental health. This study investigated impacts of adolescent pre-pandemic mental health problems and their neural correlates on stress, negative emotions and poor mental health during the first 15 months of the COVID-19 pandemic. N = 2,641 adolescents (median age = 12.0 years) from the Adolescent Brain Cognitive Development (ABCD) cohort were studied, who had pre-pandemic data on anxiety, depression, and behavioral (attention, aggression, social withdrawal, internalizing, externalizing) problems, longitudinal survey data on mental health, stress and emotions during the first 15 months following the outbreak, structural MRI, and resting-state fMRI. Data were analyzed using mixed effects mediation and moderation models. Preexisting mental health and behavioral problems predicted higher stress, negative affect and negative emotions (β = 0.09-0.21, CI=[0.03,0.32]), and lower positive affect (β = -0.21 to -0.09, CI=[-0.31,-0.01]) during the first ~6 months of the outbreak. Pre-pandemic structural characteristics of brain regions supporting social function and emotional processing (insula, superior temporal gyrus, orbitofrontal cortex, and the cerebellum) mediated some of these relationships (β = 0.10-0.15, CI=[0.01,0.24]). The organization of pre-pandemic brain circuits moderated (attenuated) associations between preexisting mental health and pandemic stress and negative emotions (β = -0.17 to -0.06, CI=[-0.27,-0.01]). Preexisting mental health problems and their structural brain correlates were risk factors for youth stress and negative emotions during the early months of the outbreak. In addition, the organization of some brain circuits was protective and attenuated the effects of preexisting mental health issues on youth responses to the pandemic's stressors.

PMID:41100534 | DOI:10.1371/journal.pone.0334028

Eur Phys J Spec Top. 2025;234(15):4127-4137. doi: 10.1140/epjs/s11734-025-01591-2. Epub 2025 Mar 25.

ABSTRACT

This mini-review examines functional connectivity in resting-state functional magnetic resonance imaging (rs-fMRI) among opioid users. The goal is to summarize existing research data and clarify the implications of altered brain connectivity in this population. The first part of the review addresses the critical question of how opioid addiction influences the functional connectivity of key brain networks, such as the default mode network (DMN), salience network (SN), and executive control network (ECN). It examines the neurological basis of opioid addiction, the principles of rs-fMRI, different methodologies employed in this type of research, and inconsistencies and methodological challenges that complicate the interpretation of findings. The second part of the article presents findings derived from our ongoing research in the field. We tested 42 participants of whom 23 healthy controls and 19 patients with opioid use disorder. Each participant underwent an MRI scanning procedure comprised of structural, resting-state and task sequences. The neuroimaging data was processed using the CONN Toolbox running on MATLAB. Our preliminary rs-fMRI findings reveal significant disruptions in functional connectivity in individuals with opioid addiction within DMN and SN networks involved in cognitive functions such as decision-making and impulse control. The review concludes by emphasizing the importance of standardizing research practices, conducting longitudinal randomized studies, and developing a more holistic approach to understanding the effects of heroin addiction. These efforts would contribute to the development of personalized and effective intervention strategies.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1140/epjs/s11734-025-01591-2.

PMID:41098388 | PMC:PMC12518422 | DOI:10.1140/epjs/s11734-025-01591-2

Schizophr Res. 2025 Oct 14;285:323-329. doi: 10.1016/j.schres.2025.10.007. Online ahead of print.

ABSTRACT

BACKGROUND: Early-onset schizophrenia (EOS) is a rare and severe subtype of schizophrenia, characterized by auditory hallucinations (AH). However, studies on AH in EOS are significantly fewer than in adult schizophrenia, and the underlying mechanisms remain unclear.

METHODS: We studied 81 first-episode, drug-naïve EOS patients, grouped by the severity of AH, and compared them with 32 healthy controls. We analyzed the topological properties of the brain's functional network. Using nodes with distinct topological properties as regions of interest (ROI), we examined the correlation between ROI-based functional connectivity and AH scores.

RESULTS: The resting-state brain functional network of EOS patients exhibited small-world network properties (sparsity = 0.05-0.34). Significant differences in degree centrality (DC) and nodal efficiency (NE) were found in the left superior temporal gyrus (STG) (false discovery rate-corrected P [PFDR] < 0.05). Post hoc multiple comparisons revealed that in DC, there were no significant differences between the non-AH group and the mild AH group, but significant differences were observed among the other groups (PFDR < 0.05). In NE, no significant differences were found between the non-AH group and both the mild and severe AH groups, while significant differences were observed among the other groups (PFDR < 0.05). Changes in functional connectivity between the left STG and the left cingulate gyrus (CG) were significantly correlated with AH scores (r = 0.316, PFDR = 0.0303).

CONCLUSIONS: This study implicates dysfunctional circuitry between the left superior temporal gyrus and the left cingulate gyrus in the neurobiology of auditory hallucinations in EOS.

PMID:41092760 | DOI:10.1016/j.schres.2025.10.007