Most recent paper

bioRxiv [Preprint]. 2026 Mar 6:2026.03.04.709400. doi: 10.64898/2026.03.04.709400.

ABSTRACT

Relapse remains a major challenge in opioid addiction treatment, underscoring the need for innovative therapies. Progress in neuromodulation therapies has been limited by insufficient mechanistic understanding of stimulation engagement and disease-related changes in the brain. We used a novel, focal transcranial magnetic stimulation (TMS) system to deliver high-density theta burst stimulation (hdTBS) combined with resting-state fMRI to test whether anterior cingulate cortex (ACC) stimulation reduces relapse-like behavior and alters functional circuitry in a rodent model of opiate dependence. The coil focality and stimulation parameters approximate human TMS protocols, and the targeted region represents a functional homolog of the human ACC. We trained rats to self-administer oxycodone intravenously for 14 days. We then introduced an electric barrier for 13 days, which caused cessation of drug self-administration. We assessed relapse to oxycodone seeking immediately after training (early abstinence) and after electric-barrier exposure (late abstinence). We administered daily hdTBS or sham stimulation for 7 days before the late-abstinence test. Sham-treated rats showed a time-dependent increase in oxycodone seeking during abstinence (incubation of oxycodone craving) and reduced ACC functional connectivity. In contrast, hdTBS prevented the incubation of oxycodone craving and restored ACC connectivity with the dorsal and ventral striatum. Tracer-based axonal-projection data further showed that stimulation-induced effects aligned with regions receiving dense projections from the stimulation site, suggesting that the projection architecture is critical to the propagation of focal stimulation across distributed networks. These findings identify ACC-centered circuits as mechanistically informed targets for TMS-based interventions that aim to reduce opioid relapse during abstinence.

ONE SENTENCE SUMMARY: Prefrontal TMS stimulation reduced relapse-like behavior and restored corticostriatal circuits, highlighting translational targets for addiction treatment.

PMID:41847016 | PMC:PMC12991172 | DOI:10.64898/2026.03.04.709400

J Pain Res. 2026 Mar 12;19:592723. doi: 10.2147/JPR.S592723. eCollection 2026.

ABSTRACT

PURPOSE: This study conducted a randomized controlled trial by analyzing resting-state functional magnetic resonance imaging (rs-fMRI) data to determine the mechanisms by which Tuina alleviates pain and modulates multiple brain networks in lumbar disc herniation (LDH) patients.

PATIENTS AND METHODS: This study included 38 healthy subjects and 76 LDH patients. LDH patients were randomly assigned into the test group (TG; n = 38) and control group (CG; n = 38). TG patients received 14 days of Tuina therapy, whereas CG patients received a combination of transcutaneous electrical nerve stimulation (TENS) and lumbar traction therapy. The primary outcome measure, simplified McGill Pain Questionnaire (SF-MPQ), was used to assess pain. Pain pressure threshold (PPT), Oswestry Disability Index (ODI), Beck Depression Inventory II (BDI-II), and Beck Anxiety Inventory (BAI) were evaluated as secondary outcomes. Fractional amplitude of low-frequency fluctuation (fALFF) and functional connectivity (FC) values were evaluated from the rs-fMRI data before and after treatment.

RESULTS: The SF-MPQ score significantly decreased in both TG subjects [-13.00 (-19.00, -9.00); P <0.001] and CG subjects [-11.00 (-14.00, -7.00); P <0.001]. SF-MPQ scores were significantly different between the two groups (P <0.05). In TG subjects, Tuina inhibited spontaneous neural activity in the bilateral inferior frontal gyrus triangular part (IFGtri) and suppressed the interaction between IFGtri and other brain regions. Changes in FC between IFGtri.R and STG.pole.R positively correlated with improvements in SF-MPQ scores (r = 0.511, P = 0.005). Changes in FC between IFGtri.L and IFGtri.R negatively correlated with reduced PPT of the bilateral gluteus maximus (r = -0.518, P = 0.004).

CONCLUSION: Tuina effectively alleviates pain, lumbar dysfunction, and negative emotions in LDH patients by regulating the interactions between multiple neural networks in the brain, especially through the inferior frontal gyrus triangle area.

PMID:41846592 | PMC:PMC12990911 | DOI:10.2147/JPR.S592723

BMC Med. 2026 Mar 17. doi: 10.1186/s12916-026-04760-9. Online ahead of print.

ABSTRACT

BACKGROUND: Pain in knee osteoarthritis (KOA) involves maladaptive neuroplastic adaptations within the pain matrix. Tai Chi and transcranial direct current stimulation (tDCS) each alleviate KOA pain, potentially by modulating the dorsolateral prefrontal cortex (DLPFC). Whether combining them yields superior analgesic and neuromodulatory effects remains to be established.

METHODS: In this four-arm, parallel-group randomized controlled trial, 152 participants with KOA were allocated to a 12-week intervention: (1) Tai Chi combined with tDCS, (2) Tai Chi, (3) tDCS, or (4) a Health Education Control group. The primary outcome was pain intensity assessed using the Pain subscale of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Secondary outcomes included the WOMAC Stiffness and Physical Function subscales, Visual Analogue Scale (VAS), Knee Injury and Osteoarthritis Outcome Score (KOOS), Timed Up and Go Test (TUGT), and the 36-Item Short Form Health Survey (SF-36). Resting-state functional connectivity (rsFC) between the right DLPFC and key regions of the pain matrix was analyzed using functional magnetic resonance imaging (fMRI). Assessments were conducted at baseline and post-intervention.

RESULTS: The Tai Chi combined with tDCS group demonstrated a significantly greater reduction in WOMAC Pain subscores compared to the Health Education Control group (P < 0.001), the tDCS group (P = 0.003), and the Tai Chi group (P = 0.048). However, the combined intervention did not show statistically superior improvement over Tai Chi group in secondary outcomes. Neuroimaging results indicated that all active interventions decreased rsFC between the right DLPFC and several pain-matrix regions, including the left posterior cingulate cortex, bilateral thalamus, left precuneus, and left superior frontal gyrus. Furthermore, the extent of pain reduction was positively correlated with decreased connectivity between the right DLPFC and both the left posterior cingulate cortex and the left precuneus.

CONCLUSIONS: This exploratory trial suggests that combining Tai Chi with tDCS provides superior pain relief compared to either monotherapy in individuals with KOA. Post hoc exploratory neuroimaging analyses further indicate that this analgesic effect may be associated with changes in rsFC between the right DLPFC and regions of the pain matrix.

TRIAL REGISTRATION: This study was registered with the Chinese Clinical Trial Registry (ChiCTR2100047287).

PMID:41845339 | DOI:10.1186/s12916-026-04760-9

Transl Psychiatry. 2026 Mar 17. doi: 10.1038/s41398-026-03957-z. Online ahead of print.

ABSTRACT

Identifying reliable biomarkers of treatment response is central to advancing personalized psychiatry. While whole-brain functional connectivity models have shown promise in predicting clinical outcomes, especially for broad-spectrum interventions like cognitive-behavioral therapy, targeted treatments may benefit from more specific neuromarkers. In social anxiety disorder (SAD), Gaze-Contingent Music Reward Therapy (GC-MRT) is a novel attention bias modification (ABM) intervention designed to reduce preferential attentional allocation to socially threatening stimuli. Given the dorsal attention network's (DAN) key role in top-down attentional control, we tested whether resting-state intra-network DAN connectivity could serve as a neural predictor of response to GC-MRT. Participants with SAD were randomized to either receive GC-MRT (n = 22) or to a waitlist control condition (n = 24). Resting-state fMRI data were collected before and after the intervention. Intra-DAN connectivity at baseline and post-treatment were associated with post-treatment symptom severity in the GC-MRT group. Post-treatment intra-DAN connectivity significantly differed in the GC-MRT group relative to controls. These findings suggest that intra-network connectivity within the DAN may have the potential to function both as a predictive biomarker and as a neural marker of successful intervention. Our findings highlight the role of the DAN in attention-based clinical interventions and show that network-specific connectivity metrics may offer a more precise understanding of how targeted neuromodulation affects symptom change in SAD.

PMID:41844594 | DOI:10.1038/s41398-026-03957-z

Eur J Psychotraumatol. 2026 Dec;17(1):2636453. doi: 10.1080/20008066.2026.2636453. Epub 2026 Mar 17.

ABSTRACT

Background: Frontline healthcare workers (HCWs) experience unique patterns of repeated, chronic, and unpredictable traumatic event exposure, coupled with physiologic stress in the setting of shift-work circadian rhythm disruption, contributing to high rates of post-traumatic stress syndromes (PTSS) and substantial workforce and economic burden. The neurobiology underlying HCW-specific risk remains incompletely understood.Objective: To synthesise epidemiological, neuroimaging, physiological, and interventional evidence into a mechanistic model of HCW PTSS and to identify priorities for biomarker-guided prevention and care.Method: Literature for this narrative review was identified through a comprehensive search of peer-reviewed articles in PubMed, PsycINFO, and Google Scholar up to May 2025. Studies were included if they addressed (1) the epidemiology of PTSD in healthcare settings, (2) risk and protective factors specific to occupational trauma exposure, (3) neural, physiological, or molecular mechanisms associated with stress-related disorders in trauma-exposed personnel, or (4) interventions targeting PTSD/PTSS in HCWs and first responder populations.Results: Across studies, PTSS prevalence among HCWs is variable (≈15-74%). Repeated, chronic, and unpredictable occupational trauma, exacerbated by circadian disruption, appears to destabilise frontal-limbic circuits and systemic stress pathways, culminating in allostatic overload. Converging data suggest that multimodal biomarkers, including resting-state and task-evoked fMRI metrics, MR spectroscopy, heart rate variability, sleep architecture, cortisol and inflammatory indices can identify prodromal dysregulation and define risk stratification.Conclusions: Longitudinal, multimodal cohort designs are critically needed to track trajectories and evaluate neuroscientifically-informed treatment modalities for PTSS in this population. Framing HCW PTSS as an occupational neurobiological injury highlights the need to identify and prevent functional decline. A biomarker-guided strategy that links brain-circuit measures with autonomic, sleep, and molecular indices may offer a path to earlier identification, precision interventions, and improved outcomes for a critically at-need population that is essential to our workforce.

PMID:41841360 | DOI:10.1080/20008066.2026.2636453

BMC Complement Med Ther. 2026 Mar 16. doi: 10.1186/s12906-026-05343-0. Online ahead of print.

NO ABSTRACT

PMID:41840560 | DOI:10.1186/s12906-026-05343-0

Mol Neurobiol. 2026 Mar 16;63(1):504. doi: 10.1007/s12035-026-05771-6.

ABSTRACT

Alzheimer's disease (AD) is a dementia disease that causes loss of cognitive functions. Also, it is a noncurable disease. However, early diagnosis and proper medication reduce AD's progression time. Yet, the prevailing AD diagnosis models did not concentrate on the claustrum in the brain, reducing the efficiency of the AD diagnosis. Thus, this framework proposes an effective AD identification model with claustrum segmentation based on Collapsing Linear Unit-Convolutional Neural Network (CoLU-CNN). Primarily, the resting state-functional Magnetic Resonance Imaging (rs-fMRI) is preprocessed. Then, Gray Matter (GM), White Matter (WM), Cerebrospinal Fluid (CSF), and the hippocampus are segmented. By using Rogers and Tanimoto-based K-means (RoT-Kmeans), the putamen edge is detected from the segmented GM to segment the claustrum. Likewise, the time-series extraction is performed from rs-fMRI, and network connectivity is generated by using Seed-Based Functional Connectivity (SBFC). Then, the network connectivity and segmented claustrum are mapped. Next, the features are extracted from the segmented and mapped images, and optimal features are selected by using Kent Map-based Wild Geese Optimization (KM-WGO). Lastly, the AD is classified by using CoLU-CNN. The experimental investigation stated that the proposed methodology attained 99% AD classification accuracy.

PMID:41840320 | DOI:10.1007/s12035-026-05771-6

Med Sci Sports Exerc. 2026 Mar 12. doi: 10.1249/MSS.0000000000003961. Online ahead of print.

ABSTRACT

BACKGROUND: Brain lateralization, the hemispheric specialization of functional networks, is essential for motor and cognitive functions. However, how intensive athletic training shapes hemispheric organization remains poorly understood. This study investigated the formation of functional lateralization in elite athletes through long-term intensive training and its potential alteration due to external factors, specifically sport-related concussions.

METHODS: Resting-state fMRI data were collected from 13 world class gymnasts (WCGs) and 14 non-athletic controls. Longitudinal data were collected from 18 soccer players and 8 golfers before and after one season, with concussions monitored in the soccer players. Hemispheric integration and segregation laterality indices (LIint and LIseg) were calculated to quantify hemispheric differences in information processing for each brain region, and the standard laterality index (LI) was employed to measure hemispheric asymmetry. Associations between laterality indices and neurotransmitter receptor/transporter densities were examined. Post-season changes in these indices were assessed to evaluate concussion effects on brain lateralization.

RESULTS: The WCGs showed significantly increased LIint in several left-hemispheric regions, including the precentral gyrus, cingulate gyrus, thalamus, superior parietal lobule, and lateral occipital cortex compared with the HCs, though no results were found in LIseg. Furthermore, the LI analysis revealed that the WCGs demonstrated higher hemispheric asymmetry in the left precentral gyrus, cingulate gyrus, and thalamus. These laterality indices also showed positive correlations with certain neurotransmitters. Similar patterns of enhanced lateralization and neurotransmitter associations were observed in soccer players and golfers. However, no significant changes in laterality indices were observed as a result of concussions sustained during the season.

CONCLUSIONS: Long-term intensive training enhances functional integration in the left hemisphere, leading to stable brain lateralization patterns resilient to sport-related concussions.

PMID:41839190 | DOI:10.1249/MSS.0000000000003961

Brain Res Bull. 2026 Mar 13:111826. doi: 10.1016/j.brainresbull.2026.111826. Online ahead of print.

ABSTRACT

OBJECTIVE: Noise-induced hearing loss impacts brain health and cognition, with dynamic functional connectivity analysis offering a promising but underexplored method for studying whole-brain activity. Therefore, this study aimed to utilise dynamic functional connectivity analysis to investigate abnormal temporal variability in whole-brain functional connectivity in patients with noise-induced hearing loss.

METHODS: In this observational study, 58 patients with noise-induced hearing loss and 42 healthy male controls, matched for age and education, underwent resting-state functional magnetic resonance imaging. The sliding window approach was employed to evaluate dynamic functional connectivity between region pairs, and k-means clustering was used to identify dynamic functional connectivity states. A two-sample t-test was used to compare differences in dynamic functional connectivity variability and state metrics between patients with noise-induced hearing loss and healthy male controls (P < 0.05). Abnormal brain dynamic functional connectivity features were identified using false discovery rate correction and least absolute shrinkage and selection operator classifier. These features were used to construct support vector machine classifiers.

RESULTS: Compared with healthy male controls, patients with noise-induced hearing loss demonstrated decreased dynamic functional connectivity between the right supplementary motor area and bilateral cuneus and increased dynamic functional connectivity between the supplementary motor area and left inferior parietal gyrus. The support vector machine classifier based on abnormal dynamic functional connectivity features selected by false discovery rate correction successfully distinguished between patients with noise-induced hearing loss and healthy male controls with an accuracy of 82.5%. The accuracy of the support vector machine classifier based on least absolute shrinkage and selection operator-selected abnormal dynamic functional connectivity features reached 96.8%.

CONCLUSION: This study revealed abnormal dynamic functional connectivity patterns in patients with noise-induced hearing loss, offering insights into the complex neuropathological mechanisms underlying long-term brain network changes associated with this disease.

PMID:41833699 | DOI:10.1016/j.brainresbull.2026.111826

Brain Res Bull. 2026 Mar 13:111825. doi: 10.1016/j.brainresbull.2026.111825. Online ahead of print.

ABSTRACT

BACKGROUND: Although resting-state functional magnetic resonance imaging (rs-fMRI)-derived functional gradients have been widely used to describe cortical hierarchical organization, their application has rarely targeted acute sleep deprivation (ASD)-related cognitive vulnerability. In particular, whether ASD induces systematic reorganization of gradient architecture and whether this reorganization contributes to spatial working memory (SWM) impairment have not yet been systematically examined.

METHODS: Fifty healthy young adult males were recruited. A 1-back task was administered to assess SWM performance before and after ASD. T1-weighted and rs-fMRI data were acquired. Functional gradient-based metrics, including standard deviation of gradient values, range of gradient values, network gradient values, and inter-network relative distances, were computed to characterize cortical hierarchical organization and were subsequently correlated with SWM behavioral performance.

RESULTS: Compared with the rested wakefulness condition, ASD significantly impaired SWM performance. Functional gradient analysis revealed significant alterations in both global (standard deviation and range) and local (gradient values of specific subnetworks) features of the top three principal gradients. Notably, the standard deviation of Gradient 2 was significantly negatively correlated with omission rate. In addition, relative distances between multiple networks within Gradient 2 and 3 were also closely associated with SWM performance.

CONCLUSION: From the perspective of functional gradients, the present study highlights the global and local gradient reorganization following ASD, as well as the importance of maintaining a balance between functional segregation and integration across subnetworks in sustaining SWM performance.

PMID:41833697 | DOI:10.1016/j.brainresbull.2026.111825

Commun Biol. 2026 Mar 14. doi: 10.1038/s42003-026-09839-w. Online ahead of print.

ABSTRACT

At dawn, we experience a shift from slumber to sentience following neurophysiological transitions, termed as sleep inertia (SI). Although resting-state fMRI studies have discovered brain reorganizations during SI, the neural basis underlying impaired alertness in SI remains unclear. We conduct simultaneous EEG-fMRI recordings on 26 adults with repeated measures of pre-sleep, nocturnal sleep and consecutive post-sleep awakenings. Using the psychomotor vigilance task (PVT) to probe tonic alertness, we discover that cingulo-opercular network (CON) activation, inclusive of thalamus, troughs upon awakening, and increments along with the post-sleep awake duration. The dynamic recovery of thalamus activity during SI depends on prior sleep architecture and the awake duration, mediating the PVT performances on awakening. Although CON connectivity remains stable, the connectivity changes between thalamus and frontoparietal network (FPN) are associated with changes of thalamic activation and PVT performances during SI. Collectively, thalamic activity and its coupling with the FPN support the restoration of tonic alertness during SI, providing a concise framework for the neural mechanisms underlying cognitive recovery upon awakening.

PMID:41832350 | DOI:10.1038/s42003-026-09839-w

Biol Psychiatry. 2026 Mar 12:S0006-3223(26)00099-5. doi: 10.1016/j.biopsych.2026.03.002. Online ahead of print.

ABSTRACT

BACKGROUND: Adolescence is a vulnerable period for the onset of anxiety and depression, yet their neurodevelopmental origins remain unclear.

METHODS: In this 7-year prospective longitudinal study, we recorded resting-state electroencephalogram (EEG) data at ages 7, 9, and 11, followed by fMRI scanning and symptom assessments at age 13. Using connectome-based predictive modeling, we examined whether childhood EEG patterns could predict adolescent symptoms, with rigorous control analyses and external validation in the Healthy Brain Network dataset (HBN, n = 384). We further characterized the developmental trajectories of these predictive networks. To mechanistically ground these electrophysiological markers, we conducted mediation analyses to test whether the amygdala-seeded circuits mediate the link between childhood EEG dynamics and adolescent symptom severity.

RESULTS: We identified dissociable EEG indicators emerging at age 9 that predicted adolescent anxiety (alpha, 8-12 Hz) and depression (beta1, 12-18 Hz). Importantly, the dynamic maturation of these EEG networks highlighted distinct neurodevelopmental susceptibilities, in which longitudinal EEG shifts between ages 9 and 11 predicted symptom severity in adolescence. The divergent developmental trajectories of EEG-based networks were characterized by opposing hemispheric lateralization: leftward for anxiety and rightward for depression. Mechanistically, these predictive associations were mediated by lateralized amygdala-ventrolateral prefrontal cortex (vlPFC) circuits, with the right and left vlPFC pathways selectively mediating anxiety risk and depression risk, respectively. These models generalized robustly to the independent HBN cohort.

CONCLUSIONS: Our findings highlight early neurobiological indicators of distinct developmental trajectories and susceptibilities for anxiety and depression, providing a foundation for early risk stratification and targeted precision prevention.

PMID:41831747 | DOI:10.1016/j.biopsych.2026.03.002

Clin Nutr ESPEN. 2026 Mar 12:103117. doi: 10.1016/j.clnesp.2026.103117. Online ahead of print.

ABSTRACT

Neuropathic pain (NP) is caused by damage to the peripheral or central nervous system and is associated with adverse complex sensory and affective symptoms. There are few current treatment options for NP, and opioid analgesics have severe side effects which can lead to opioid abuse. Therefore, the development of innovative, effective, and safe alternatives is urgently needed. This study will assess the effects of ginger root extract's anti-inflammatory and anti-oxidant properties on individuals with sciatica via the microbiome-gut-brain axis. Eighty participants (18-85 years) with chronic sciatica, classified as lean (n=40, BMI <25 kg/m2) or obese (n=40, BMI ≥30 kg/m2), will be stratified by age, sex, and BMI to receive 2,000 mg/day of ginger extract or placebo for eight weeks. Primary outcomes are pain-associated outcomes and brain neuroplasticity by assessing functional (resting state-fMRI) and structural (Diffusion Tensor Imaging) connectivity. Secondary outcomes include gut function (gut microbiota composition using 16S rRNA sequencing analysis, intestinal permeability assessing concentrations of plasma lipopolysaccharide binding protein and fecal zonulin, and fecal metabolites using LC-MS/MS analysis) and neuroinflammation: nCounter® Neuroinflammation Panel analysis. We will evaluate outcomes at baseline and end of study. We will employ intention-to-treat principle and per-protocol for data analysis. Hierarchical linear modeling is utilized to estimate ginger supplementation's effects while properly accounting for data dependency and identified covariates. This study was approved by the Bioethics Committee of the Texas Tech University Health Sciences Center, Lubbock, TX. Participants will sign an informed consent form before enrolling in the study. Our team will actively disseminate the results from this trial through academic conference presentations and peer-reviewed journals. We are now actively recruiting subjects for this study. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT06817018.

PMID:41831719 | DOI:10.1016/j.clnesp.2026.103117

J Neurol Neurosurg Psychiatry. 2026 Mar 13:jnnp-2025-336798. doi: 10.1136/jnnp-2025-336798. Online ahead of print.

ABSTRACT

BACKGROUND: Despite the impact of depression in multiple sclerosis (MS), the neurobiological mechanisms underlying its pathogenesis are still poorly understood. Disrupted functional connectivity (FC) within the reward circuit has been observed in major depressive disorder (MDD), highlighting its essential role in the neurobiology of depression. Here, we hypothesised that an analogous dysconnectivity may underpin depression in MS.

METHODS: The present study aimed to investigate FC of key nodes of the reward circuit (nucleus accumbens, NAcc and ventral tegmental area, VTA) in MS patients with depression (MS-D; n=30, 22 females), characterising differences with MS patients without depression (MS-nD; n=30, 17 females) and MDD patients without MS (n=30, 23 females). Furthermore, dynamic causal modelling (DCM) was applied to resting-state functional magnetic resonance imaging (fMRI) data to characterise effective connectivity (EC), which refers to the causal influences of brain regions involved in the circuit.

RESULTS: MS-D group showed reduced FC compared with both MS-nD and MDD, suggesting that the association of depression with MS may reflect dysfunction of the reward circuit. The DCM analysis showed inhibitory self-connections, a negative modulation of VTA in MS-D>MS-nD, a negative modulation between VTA, NAcc and the right amygdala as an effect of having depression and no EC differences for MS-D>MDD.

CONCLUSIONS: The present connectivity study revealed promising results for understanding the pathophysiology of depression in MS. A combined FC-EC investigation of the reward circuit may represent a potential non-invasive in vivo MRI biomarker for understanding the onset of core depressive symptoms, supporting the development of effective and personalised therapies.

PMID:41825870 | DOI:10.1136/jnnp-2025-336798

J Affect Disord. 2026 Mar 11:121610. doi: 10.1016/j.jad.2026.121610. Online ahead of print.

ABSTRACT

OBJECTIVE: The habenula is implicated in mood regulation and sleep-wake processes and has been increasingly studied in major depressive disorder (MDD). This exploratory imaging-genetics study examined the potential associations between candidate gene polymorphisms, habenula-centered brain connectivity, and clinical symptom severity in patients with MDD.

METHODS: Ten candidate genes related to mood and circadian regulation were genotyped in patients with MDD and in healthy controls. All participants underwent 3 T structural and resting-state functional MRI. Seed-based structural and functional connectivity analyses were conducted focusing on the habenula. Imaging-genetics associations were examined with corrections for multiple comparisons.

RESULTS: Sixty-nine patients with MDD and forty-one healthy controls of Korean ethnicity were included. In MDD, structural connectivity between the left habenula and the left inferior frontal gyrus was significantly associated with rs2304672, and connectivity between the left habenula and the right ventral anterior thalamic nucleus was associated with rs7123390. Across all participants, functional connectivity between the left habenula and right parahippocampal gyrus showed consistent significant associations with multiple symptom domains, including depression and sleep disturbance.

CONCLUSION: In this modest-sized sample, preliminary imaging-genetics associations involving habenula-centered circuits were observed. These findings should be considered exploratory and hypothesis generating. Larger, adequately powered studies are required to confirm whether genetic variations meaningfully contribute to individual differences in habenular connectivity and symptom expression in patients with MDD.

PMID:41825747 | DOI:10.1016/j.jad.2026.121610

Neurotherapeutics. 2026 Mar 12;23(2):e00884. doi: 10.1016/j.neurot.2026.e00884. Online ahead of print.

ABSTRACT

Personalized transcranial magnetic stimulation (TMS) targeting holds promise for improving depression treatment, but its clinical translation is hindered by limited open-source implementation and systematic comparisons of target reproducibility and clinical relevance. We implemented two leading personalized TMS-target generating approaches, namely refined seed-based (RSA) and hierarchical clustering (HCA) algorithms, and compared them on (1) test-retest reliability of derived targets, and (2) association of target-sgACC connectivity with depressive symptoms. Using resting-state fMRI data from healthy and depressed individuals, spatial reliability was quantified via inter-run Euclidean distances, and clinical relevance was assessed through correlations between depression severity and functional connectivity of targets with sgACC. Effects of global signal regression (GSR) were also evaluated. The results showed that RSA produced targets in more superior and postrior part of DLPFC and demonstrated significantly higher test-retest reliability than HCA (smaller inter-run Euclidean distances). Further, RSA-derived target-sgACC connectivity correlated positively with depression severity, which was absent in HCA-derived targets. In addition, GSR improved spatial reliability for RSA but not HCA. Our results indicate that RSA exhibits superior test-retest reliability and symptom association compared to HCA, yet large-scale clinical trials are warranted to determine which approach yields superior therapeutic efficacy, and open-sourced implementation may accelerate clinical adoption.

PMID:41825227 | DOI:10.1016/j.neurot.2026.e00884

J Cereb Blood Flow Metab. 2026 Mar 13:271678X261431043. doi: 10.1177/0271678X261431043. Online ahead of print.

ABSTRACT

Recent advances in functional PET (fPET) enable modeling of metabolic processes with second-level temporal resolution, opening applications such as imaging molecular connectivity comparable to fMRI. However, high-temporal fPET is more noise-sensitive, making meaningful signal extraction challenging. We developed a component-based preprocessing method adapted from fMRI, which models structured noise with tissue-specific regressors and removes low-frequency uptake trends (CompCor). This approach was applied to 20 high-temporal [18F]FDG-fPET scans from a long-axial PET/CT system (1 s frames) and 16 scans from a PET/MR scanner (3 s frames). Filtering methods were compared across frequency bands, and their effects on metabolic connectivity (M-MC) assessed. Connectivity was strongly influenced by filter strategy and scanner type. CompCor produced more consistent, structured networks than standard bandpass filters. Intermediate frequency bands (0.01-0.1 Hz) gave the most reliable connectivity across PET/CT and PET/MR (r = 0.89), while high-sensitivity PET/CT also revealed structured patterns at 0.1-0.2 Hz. Compared to fMRI, fPET networks appeared more spatially cohesive but less differentiated. In sum, high-temporal [18F]FDG-fPET enables high within-scan reliability estimation of resting-state M-MC when paired with appropriate denoising, opening a new avenue in molecular imaging. Scanner characteristics and preprocessing critically affect signal quality, while our physiologically informed pipeline improves comparability across systems and studies.

PMID:41823344 | DOI:10.1177/0271678X261431043

Eur J Neurosci. 2026 Mar;63(6):e70457. doi: 10.1111/ejn.70457.

ABSTRACT

Poststroke aphasia significantly impacts the quality of life in older adults, yet the underlying neural mechanisms linking macro-scale network hierarchy and micro-scale molecular architecture remain unclear. This study investigated alterations of the principal functional connectivity gradient and their transcriptomic underpinnings in older adults with poststroke aphasia. We recruited 27 patients with aphasia and 29 age-matched healthy controls. Resting-state fMRI data were analyzed using diffusion map embedding to characterize the principal functional connectivity gradient. Patients exhibited a compressed gradient range, characterized by diminished differentiation in unimodal networks (visual and somatomotor) and disordered integration in multimodal networks, including the ventral attention network and the default mode network. These gradient alterations were significantly correlated with language deficits. Furthermore, partial least squares regression revealed that the spatial pattern of gradient changes was associated with normative gene expression profiles related to synaptic transmission, trans-synaptic signaling, and calcium ion binding. Machine learning models incorporating gradient features and lesion volume successfully predicted individual differences in language performance. These findings suggest that poststroke aphasia involves a disruption of the cortical functional hierarchy that is constrained by specific molecular architectures, providing novel insights into the neurobiological mechanisms of language recovery and potential targets for precision rehabilitation in aging populations.

PMID:41823306 | DOI:10.1111/ejn.70457

Front Psychol. 2026 Feb 25;17:1675737. doi: 10.3389/fpsyg.2026.1675737. eCollection 2026.

ABSTRACT

Functional near-infrared spectroscopy (fNIRS) has emerged as a promising technique in motor cognitive neuroscience and has become an important neuroimaging tool for the study of motor cognition. This review synthesizes evidence from fNIRS studies to elucidate the neural mechanisms that underlie exercise-induced improvements in executive function in older adults. A systematic search was conducted across six electronic databases from inception to March 20, 2025, and 27 relevant articles were included. These studies were systematically reviewed to examine the neural mechanisms by which exercise improves executive function in older adults along five dimensions: (1) resting-state brain activity; (2) task-evoked brain activity during executive function tasks; (3) acute exercise-induced immediate improvement in brain activity; (4) sustained effects on brain activity following acute exercise; and (5) long-term enhancements in brain activity after regular physical exercise. The results showed that a decrease in cerebral oxygenation accompanied brain aging, weakened hemodynamic oscillations, and abnormal resting-state functional coupling. A two-stage neural compensation model may underlie the exercise intervention aimed at improving executive function in older adults. Acute exercise can temporarily improve executive function by expanding the "resource pool" to increase neural resources and enhance prefrontal cortical hemodynamic activity and recruitment of neural resources. Chronic exercise achieves structural-functional optimization and efficient use of neural resources through the accumulation effect of repeated acute exercise stimulation, thereby continuously improving executive function. Therefore, we suggest that future studies should conduct large-scale RCTs using multimodal neuroimaging methods combining ERP, fMRI, and fNIRS. This will compensate for the shortcomings of fNIRS and provide a deeper understanding of how exercise remodels brain networks, thereby establishing a theoretical basis for precision interventions targeting brain aging.

PMID:41822427 | PMC:PMC12975482 | DOI:10.3389/fpsyg.2026.1675737

Neurobiol Lang (Camb). 2026 Jan 13;7:NOL.a.208. doi: 10.1162/NOL.a.208. eCollection 2026.

ABSTRACT

Age-related declines in cognitive function are often accompanied by changes in brain activity and network organization. This study investigated the relationship between resting state brain activity and age-related differences in speech production. We hypothesized that older adults would exhibit altered functional connectivity and activation intensity, correlating with reduced speech quality. Resting state functional MRI data were collected and a composite measure of speech complexity and fluency was calculated from younger and older adults. Results revealed significantly worse speech performance in older adults, accompanied by less segregated whole-brain networks, reduced amplitude of low-frequency fluctuations, and more heterogeneous brain states. Univariate regression analyses indicated stronger brain-behavior relationships in younger adults, while multivariate regression analyses revealed that age-related differences in resting state brain state patterns critically relate to speech production differences. Notably, the language network remained relatively stable with age, whereas whole-brain status became very important for speech performance in older adults. These findings suggest that resting state brain activity, particularly whole brain network characteristics, may serve as a stable biomarker of age-related changes in speech production.

PMID:41822136 | PMC:PMC12978676 | DOI:10.1162/NOL.a.208