Most recent paper

Int J Womens Health. 2025 Feb 11;17:369-376. doi: 10.2147/IJWH.S508593. eCollection 2025.

ABSTRACT

INTRODUCTION: Endometriosis is a chronic gynecological disorder that significantly impacts women of reproductive age. Recent evidence suggests a bidirectional link between endometriosis and brain functional networks, though the causal mechanisms remain unclear. This study aims to explore these relationships using Mendelian Randomization (MR) analysis.

METHODS: Data from 191 resting-state functional MRI (rsfMRI) phenotypes and endometriosis genetic datasets were analyzed using both forward and reverse MR approaches. Genetic Instrument Selection was performed to identify valid instrumental variables, ensuring their independence from confounders and strong association with the exposure. Sensitivity analyses were conducted to ensure the robustness of the findings.

RESULTS: Forward MR analysis identified three brain networks (Pheno20, Pheno38, Pheno44) significantly associated with endometriosis risk (P FDR < 0.05). Notably, Pheno38 activity was inversely associated with fallopian tube endometriosis, whereas Pheno20 and Pheno44 were positively linked to adenomyosis. Reverse MR analysis revealed that endometriosis of the ovary was inversely associated with functional connectivity in Pheno932, a network involved in cognitive and attention processes. Sensitivity analyses confirmed the reliability of these results.

DISCUSSION: This study highlights a complex bidirectional relationship between brain functional networks and endometriosis. Increased activity in specific networks may protect against or predispose individuals to certain subtypes of endometriosis. Conversely, endometriosis also can influence brain connectivity, potentially contributing to cognitive and emotional symptoms.

PMID:39959755 | PMC:PMC11829589 | DOI:10.2147/IJWH.S508593

Psychol Med. 2025 Feb 17;55:e49. doi: 10.1017/S0033291725000054.

ABSTRACT

BACKGROUND: The COVID-19 pandemic has had a significant impact on the health of millions of people worldwide, and many manifest new or persistent symptoms long after the initial onset of the infection. One of the leading symptoms of long-COVID is cognitive impairment, which includes memory loss, lack of concentration, and brain fog. Understanding the nature and underlying mechanisms of cognitive impairment in long-COVID is important for developing preventive and therapeutic interventions.

METHODS: Our present study investigated functional connectivity (FC) changes in patients with long-COVID and their associations with cognitive impairment. Resting-state functional MRI data from 60 long-COVID patients and 52 age- and sex-matched healthy controls were analyzed using seed-based functional connectivity analysis.

RESULTS: We found increased FC between the right caudate nucleus and both the left and right precentral gyri in long-COVID patients compared with healthy controls. In addition, elevated FC was observed between the right anterior globus pallidus and posterior cingulate cortex as well as the right temporal pole in long-COVID patients. Importantly, the magnitude of FC between the caudate and the left precentral gyrus showed a significant negative correlation with Montreal Cognitive Assessment (MoCA) scores and a negative correlation with Trail Making Test B performance in the patient group.

CONCLUSION: Patients with long-COVID present enhanced FC between the caudate and the left precentral gyrus. Furthermore, those FC alterations are related to the severity of cognitive impairment, particularly in the domain of executive functions.

PMID:39957507 | DOI:10.1017/S0033291725000054

J Sleep Res. 2025 Feb 17:e70015. doi: 10.1111/jsr.70015. Online ahead of print.

ABSTRACT

To investigate the effective connectivity between the bilateral insulae and other regions of the whole brain in children with obstructive sleep apnea (OSA), and to reveal the relationships between these abnormal connections and cognitive dysfunction in this condition. Resting-state functional magnetic resonance imaging (rs-fMRI) data and clinical variables were collected from 55 children with OSA [5.0 (5.0, 8.0) years, 32 males, 28 pre-school children] and 25 healthy controls [6.0 (5.0, 9.0) years, 11 males, 9 pre-school children], matched for age, gender, and education. Rs-fMRI data were analysed to investigative group-difference in the effective connectivity between the bilateral insulae and other regions of the brain of children with OSA with those of controls. Spearman correlation analysis was conducted between these abnormal connections and clinical variables among children with OSA. Compared with controls, children with OSA showed abnormal clinical variables (i.e., increased OAHI, AHI, OAI, HI, ODI, time of SpO2 < 90%, total AI, and respiratory-related AI, while decreased minimal SpO2, FIQ, VIQ, and PIQ). Additionally, significant alterations were observed in the effective connectivity between the bilateral insulae and other regions of brain, such as frontal, parietal, occipital, and cerebellum and so forth. Furthermore, the mean values of the effective connectivity in children with OSA were significantly correlated with several sleep-related and neurocognitive parameters. There exist abnormal causal interactions between the bilateral insulae and other regions throughout the brain in OSA children, accompanied by impaired cognitive function, suggesting that the former may be a potential neural mechanism underlying the latter.

PMID:39957378 | DOI:10.1111/jsr.70015

Brain Res Bull. 2025 Feb 14:111259. doi: 10.1016/j.brainresbull.2025.111259. Online ahead of print.

ABSTRACT

Sensory impairment after stroke has become an important health problem that affects the health and quality of life of patients. Acupuncture is a widely accepted method for stroke rehabilitation. The development of fMRI provides a good platform for the study of neural activity patterns induced by acupuncture, and many studies have found that acupuncture can induce special activation of the brain in stroke patients. We introduced the inter-subject functional connectivity(ISFC) method into the study of acupuncture treatment for sensory impairment after stroke to explore the group effects of acupuncture treatment and the specific mode of action of acupuncture for sensory impairment. In this study, 24 stroke patients with limb numbness and 23 healthy controls were included, and three functional magnetic resonance scans were designed, including resting state, acupuncture task state, and acupuncture-retention state(LI11 and ST36 were used during the task fMRI). The main observation was the connection changes in 50 regions of interest, including the sensory-motor network, central executive network, thalamus, cingulate gyrus, and other brain regions. The findings showed that acupuncture could cause certain patterns of neural activity in the patients. These patterns included a significant rise in ISFC within the sensory-motor network and between the sensory-motor network and the thalamus and the central executive network. When different types of acupuncture were compared, it was found that the first effect of acupuncture was mostly large-scale activation of the sensory-motor network and the thalamus. The second effect, on the other hand, was low-intensity activation in a limited range. In general, this study explored the group mechanism of acupuncture for sensory function rehabilitation after stroke and provided some help for understanding neural activity patterns from a cross-subject dimension.

PMID:39956399 | DOI:10.1016/j.brainresbull.2025.111259

Brain Lang. 2025 Feb 15;264:105551. doi: 10.1016/j.bandl.2025.105551. Online ahead of print.

ABSTRACT

Associative theories of creativity posit that high-creativity individuals possess flexible semantic memory structures that allow broad access to varied information. However, the semantic memory structure characteristics and neural substrates of creative writing are unclear. Here, we explored the semantic network features and the predictive whole-brain functional connectivity associated with creative writing and generated mediation models. Participants completed two creative story continuation tasks. We found that keywords from written texts with superior creative writing performance encompassed more semantic categories and were highly interconnected and transferred efficiently. Connectome predictive modeling (CPM) was conducted with resting-state functional magnetic resonance imaging (fMRI) data to identify whole-brain functional connectivity patterns related to creative writing, dominated by default mode network (DMN). Semantic network features were found to mediate the relationship between brain functional connectivity and creative writing performance. These results highlight how semantic memory structure and the DMN-driven brain functional connectivity patterns support creative writing performance. Our findings extend prior research on the role of semantic memory structure and the DMN in creativity, expand upon previous research on semantic creativity, and provide insight into the cognitive and neural foundations of creative writing.

PMID:39955819 | DOI:10.1016/j.bandl.2025.105551

Mol Psychiatry. 2025 Feb 15. doi: 10.1038/s41380-025-02924-2. Online ahead of print.

ABSTRACT

Deficits in mediodorsal thalamus-dorsolateral prefrontal cortex (MDT-DLPFC) resting-state functional magnetic resonance imaging (rs-fMRI) connectivity and prefrontal sleep spindles have been reported in chronic and early course schizophrenia. However, the presence of these alterations in clinical high-risk for psychosis (CHR), alongside their relationships with underlying neurotransmission and cognitive function, remains to be established. Thirty-one CHR and thirty-two HC underwent: 1) 7 T rs-fMRI; 2) 7 T magnetic resonance spectroscopy imaging (MRSI); and 3) sleep electroencephalography (EEG). Rs-fMRI connectivity was analyzed by seeding the whole thalamus (WT) and seven thalamic subsections. Spindle duration was computed across all EEG channels. GABA/creatine (Cr) and glutamate/Cr were calculated in DLPFC and MDT. Relative to HC, CHR showed WT-DLPFC hypoconnectivity (p-FDR = 0.001), especially involving MDT-DLPFC (p-FDR < 0.001) and reduced prefrontal spindle duration (t-stat = -2.64, p = 0.010), while no differences were found for MRSI neuro-metabolites. We then performed clustering analysis using rs-fMRI connectivity and spindle duration to identify CHR and HC subgroups and predict their working memory (WM) performance. A cluster with intact rs-fMRI and spindle duration included mostly HC (83.33% purity), while a cluster with both measures altered involved almost entirely CHR (91.66% purity) and showed worse WM performances. We also examined MRSI metabolites' contribution to spindles and rs-fMRI connectivity with a within-group multivariable regression analysis. In HC, but not in CHR, MDT glutamate/Cr negatively predicted spindle duration and positively predicted MDT-DLPFC connectivity. Combined, these findings indicate that a multimodal neuroimaging approach can identify distinct thalamocortical dysfunctions in CHR individuals, thus informing future research aimed at developing personalized interventions in these individuals.

PMID:39955469 | DOI:10.1038/s41380-025-02924-2

J Neurol Sci. 2025 Jan 21;470:123399. doi: 10.1016/j.jns.2025.123399. Online ahead of print.

ABSTRACT

BACKGROUND: Post-stroke fatigue (PSF) is one of the most prevalent symptoms that affects quality of life and daily function after stroke. Despite a growing body of research, its pathophysiology is poorly understood. Non-invasive brain stimulation (NIBS), such as the transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS), can serve as a non-pharmacological intervention for PSF. In this review, we aim to (1) evaluate PSF neuroimaging studies to deduce potential neural mechanisms, (2) describe NIBS as a tool to probe brain structures to further understand pathophysiology of fatigue, and (3) assess NIBS as a treatment intervention for PSF.

METHODS: A systematic search was conducted for the databases PubMed, Embase, Scopus, CINAHL and Cochrane. Studies were included based on the following inclusion and exclusion criteria: >18 years with PSF, use of neuroimaging and/or NIBS for investigation or as an intervention for PSF, English language, study types including cohort, case control, or randomized controlled trials. Data extracted included participant characteristics, concept, context, study methods, and key findings relevant to the review questions.

RESULTS: A total of 30 studies met criteria. Neuroimaging papers that investigated brain structure (MRI) found conflicting associations between lesion location and PSF. Functional methods (fMRI, TMS) revealed altered resting state functional connectivity (rsFC), cortical excitability, and a disruption in interhemispheric inhibitory balance as potential mechanisms of PSF. There were no studies using TMS as an intervention for PSF. Of the six articles that used tDCS, only two reported statistically significant reductions in the severity of PSF.

CONCLUSION: Structural characteristics of stroke lesions had conflicting findings, while functional neuroimaging studies suggested that altered rsFC, cortical excitability and interhemispheric inhibitory balance contribute to the development of PSF. There were inconsistent results on the effectiveness of tDCS as an intervention for PSF, due to varying methodologies and lack of precise targeting of underlying neural mechanisms. Further investigations are needed to determine if NIBS could be a potential treatment to alleviate the effects of PSF.

PMID:39954574 | DOI:10.1016/j.jns.2025.123399

Sleep Med. 2025 Feb 6;128:174-182. doi: 10.1016/j.sleep.2025.02.009. Online ahead of print.

ABSTRACT

OBJECTIVES: Obstructive sleep apnea (OSA) is associated with potential disruptions in brain function and structure. The aim was to investigate alterations in dynamic functional connectivity (dFC) in OSA patients utilizing resting-state functional magnetic resonance imaging (rs-fMRI) and multiplication of temporal derivatives (MTD) to better understand the neurological implications of OSA.

METHODS: This cross-sectional study eventually recruited 111 patients, aged 25-65 years. We categorized participants based on the apnea-hypopnea index (AHI) assessed via polysomnography (PSG), 43 patients were groupAHI <15 and 68 patients were group AHI ≥15. Rs-fMRI and neuropsychological assessments were conducted to assess the brain function and visual-spatial memory, respectively. We evaluated the intergroup differences in dFC as well as its correlation with clinical parameters.

RESULTS: The dFC analysis identified five distinct connectivity states, comprising four hyperconnected states (State 1, 2, 3, and 5) and one hypoconnected state (State 4). Group AHI≥ 15 showed altered fraction time (FT) and mean dwell time (MDT) in States 1, 3, and 4. The partial correlation showed that the FT/MDT of State 1 negatively correlated with hypoxia parameters, while the FT/MDT of State 3 positively correlated with total sleep time in Group AHI≥ 15. Group AHI≥ 15 exhibited a negative association between FT of state 3 and Visuospatial/Executive score in MoCA (r = -0.297, p = 0.033).

CONCLUSIONS: Untreated male moderate to severe OSA patients exhibited altered in dFC, which significantly correlated with hypoxia parameters and cognitive performance, high lighting that dFC changes may be an indicator of the neurological consequence of OSA, especially moderate to severe OSA.

PMID:39954375 | DOI:10.1016/j.sleep.2025.02.009

Brain Behav Immun. 2025 Feb 12:S0889-1591(25)00026-1. doi: 10.1016/j.bbi.2025.01.013. Online ahead of print.

ABSTRACT

Currently, our understanding of the metabolic and immune pathways involved in obsessive-compulsive disorder (OCD), as well as the precise mechanisms by which metabolism and immunity impact brain activity and function, is limited. This study aimed to examine the alterations in serum metabolites, inflammatory markers, brain activity, and brain functional connectivity (FC) among individuals with OCD and investigate the relationship between these factors. The study included 55 individuals with moderate-to-severe OCD (either drug-naïve or not taking medication for at least eight weeks) and 54 healthy controls (HCs). The High-Performance Liquid Chromatography-Tandem Mass Spectrometry (HPLC-MS/MS) technique was used to detect serum metabolites, whereas the enzyme-linked immunosorbent assay (ELISA) was utilized to identify inflammatory markers. The FC of the brain was investigated using rs-fMRI. The findings demonstrated that individuals with OCD exhibited significant alterations in 11 metabolites compared to HCs. In particular, 10 of these metabolites exhibited an increase, while one metabolite displayed a decrease. Additionally, individuals with OCD experienced a marked elevation in the levels of five inflammatory factors (TNF-α, IL-1β, IL-2, IL-6, and IL-12). Rs-fMRI analysis revealed that individuals with OCD exhibited atypical FC in various brain regions, such as the postcentral gyrus, angular gyrus, and middle temporal gyrus. These specific brain areas are closely associated with sensory-motor processing, cognitive control, and emotion regulation. Further stepwise multiple regression analysis revealed that serum metabolite levels, particularly phosphatidylcholine, and inflammatory markers such as IL-1β could predict alterations in brain FC among individuals diagnosed with OCD. In summary, this study uncovered that individuals with OCD exhibit alterations in serum metabolites, inflammatory markers, brain activity, and FC. The findings suggest that these metabolites and inflammatory markers might play a role in the development and progression of OCD by affecting brain activity and the FC of neural networks.

PMID:39952302 | DOI:10.1016/j.bbi.2025.01.013

Sci Rep. 2025 Feb 14;15(1):5524. doi: 10.1038/s41598-025-86762-w.

ABSTRACT

How does the brain support 'wellbeing'? Because it is a multidimensional construct, it is likely the product of multiple co-active brain networks that vary across individuals. This is perhaps why prior neuroimaging studies have found inconsistent anatomical associations with wellbeing. Furthermore, these used 'laboratory-style' or 'resting-state' methods not amenable to finding manifold networks. To address these issues, we had participants watch a full-length romantic comedy-drama film during functional magnetic resonance imaging. We hypothesised that individual differences in wellbeing measured before scanning would be correlated with individual differences in brain networks associated with 'embodied' and 'narrative' self-related processing. Indeed, searchlight spatial inter-participant representational similarity and subsequent analyses revealed seven sets of co-activated networks associated with individual differences in wellbeing. Two were 'embodied self' related, including brain regions associated with autonomic and affective processing. Three sets were 'narrative self' related, involving speech, language, and autobiographical memory-related regions. Finally, two sets of visual-attention-related networks emerged. These results suggest that the neurobiology of wellbeing in the real world is supported by diverse but functionally definable and separable sets of networks. This has implications for psychotherapy where individualised interventions might target, e.g., neuroplasticity in language-related narrative over embodied self or visual-attentional related processes.

PMID:39952989 | DOI:10.1038/s41598-025-86762-w

J Am Stat Assoc. 2024;119(548):2508-2520. doi: 10.1080/01621459.2024.2370593. Epub 2024 Jul 29.

ABSTRACT

Independent component analysis (ICA) is widely used to estimate spatial resting-state networks and their time courses in neuroimaging studies. It is thought that independent components correspond to sparse patterns of co-activating brain locations. Previous approaches for introducing sparsity to ICA replace the non-smooth objective function with smooth approximations, resulting in components that do not achieve exact zeros. We propose a novel Sparse ICA method that enables sparse estimation of independent source components by solving a non-smooth non-convex optimization problem via the relax-and-split framework. The proposed Sparse ICA method balances statistical independence and sparsity simultaneously and is computationally fast. In simulations, we demonstrate improved estimation accuracy of both source signals and signal time courses compared to existing approaches. We apply our Sparse ICA to cortical surface resting-state fMRI in school-aged autistic children. Our analysis reveals differences in brain activity between certain regions in autistic children compared to children without autism. Sparse ICA selects coactivating locations, which we argue is more interpretable than dense components from popular approaches. Sparse ICA is fast and easy to apply to big data.

PMID:39949839 | PMC:PMC11824601 | DOI:10.1080/01621459.2024.2370593

Med Image Comput Comput Assist Interv. 2024 Oct;15003:519-529. doi: 10.1007/978-3-031-72384-1_49. Epub 2024 Oct 3.

ABSTRACT

Higher-order properties of functional magnetic resonance imaging (fMRI) induced connectivity have been shown to unravel many exclusive topological and dynamical insights beyond pairwise interactions. Nonetheless, whether these fMRI-induced higher-order properties play a role in disentangling other neuroimaging modalities' insights remains largely unexplored and poorly understood. In this work, by analyzing fMRI data from the Human Connectome Project Young Adult dataset using persistent homology, we discovered that the volume-optimal persistence homological scaffolds of fMRI-based functional connectomes exhibited conservative topological reconfigurations from the resting state to attentional task-positive state. Specifically, while reflecting the extent to which each cortical region contributed to functional cycles following different cognitive demands, these reconfigurations were constrained such that the spatial distribution of cavities in the connectome is relatively conserved. Most importantly, such level of contributions covaried with powers of aperiodic activities mostly within the theta-alpha (4-12 Hz) band measured by magnetoencephalography (MEG). This comprehensive result suggests that fMRI-induced hemodynamics and MEG theta-alpha aperiodic activities are governed by the same functional constraints specific to each cortical morpho-structure. Methodologically, our work paves the way toward an innovative computing paradigm in multimodal neuroimaging topological learning. The code for our analyses is provided in https://github.com/ngcaonghi/scaffold_noise.

PMID:39949393 | PMC:PMC11816146 | DOI:10.1007/978-3-031-72384-1_49

Ageing Res Rev. 2025 Feb 11:102688. doi: 10.1016/j.arr.2025.102688. Online ahead of print.

ABSTRACT

INTRODUCTION: Despite normal cognitive abilities, subjective memory complaints (SMC) are common in older adults and are linked to mild memory impairment. SMC may be a sign of subtle cognitive decline and underlying pathological changes, according to research; however, there is not enough data to support the use of resting-state functional connectivity to identify early changes in the brain network before cognitive symptoms manifest.

MATERIALS AND METHODS: In this study, the topological structure and regional connectivity of the brain functional network in SMC individuals were analyzed using graph theoretical analysis in both weighted and binarized network models, alongside healthy controls. Resting-state functional magnetic resonance imaging data was collected from 24 SMCs and 39 cognitively normal people. Analysis of both binary and weighted graph theory was done using the Dosenbach Atlas as a basis based on area under curves (AUCs) for the graph network parameters, which comprised of six node metrics and nine global measures. We then performed group comparisons using statistical analyses based on Network-Based Statistics functional connectomes. Finally, the relationship between global graph measures and cognition was examined using neuropsychological tests such as the Mini-Mental State Examination (MMSE) and the Alzheimer Disease Assessment Scale (ADAS score).

RESULTS: The topologic properties of brain functional connectomes at both global and nodal levels were tested. The SMC patients showed increased functional connectivity in clustering coefficient global (P < 0.00001), global efficiency (P < 0.00001), and normalized characteristic path length or Lambda (P < 0.00001), while there was decreased functional connectivity in Modularity (P < 0.04542), characteristic path length (0.00001), and small-worldness or Sigma (P < 0.00001) in binary networks model. In contrast, SMC patients only exhibited decreased functional connectivity in Assortativity identified by weighted networks model. Furthermore, some brain regions located in the default mode network, sensorimotor, occipital, and cingulo-opercular network in SMC patients showed altered nodal centralities. No significant correlation was found between global metrics and MMSE scores in both groups using binary metrics. However, in cognitively normal individuals, negative correlation was observed with weighted metrics in global and local efficiency and Lambda. While In SMC patients, a significant positive correlation was found between ADAS scores and local efficiency in both binary and weighted metrics.

CONCLUSION: The findings suggest that functional impairments in SMC patients might be associated with disruptions in the global and regional topological organization of the brain's functional connectome, offering new and significant insights into the pathophysiological mechanisms underlying SMC.

PMID:39947486 | DOI:10.1016/j.arr.2025.102688

Front Neurol. 2025 Jan 29;16:1467175. doi: 10.3389/fneur.2025.1467175. eCollection 2025.

ABSTRACT

Currently, HIV-associated neurocognitive disorders (HAND) remains one of the major challenges faced by people living with HIV (PLWH). HAND involves the vulnerability of neural circuits caused by synaptic degeneration and abnormal synaptic pruning. In recent years, connectomics has been gradually applied to HAND research as a cutting-edge method for describing the structural and functional connectivity patterns of the brain, to further elucidate the specific mechanisms underlying these neural circuit vulnerabilities. Using multimodal neuroimaging techniques such as diffusion tensor imaging (DTI), structural magnetic resonance imaging (sMRI), and resting-state functional magnetic resonance imaging (rs-fMRI), researchers can detail the connectome network changes in the brains of PLWH. These technologies offer potential biomarkers for the early diagnosis, prognosis, and treatment monitoring of HAND, while also providing new avenues for personalized prediction of cognitive status. Here, we start with the pathogenesis and risk factors of HAND, providing a comprehensive review of the basic concepts of unimodal and multimodal macro connectomics and related graph theory methods, and we review the latest progress in HAND connectomics research. We emphasize the use of connectomics to identify specific disease patterns of HIV-associated neurodegeneration and discuss the potential research directions and challenges in understanding these diseases from a connectomics perspective.

PMID:39944538 | PMC:PMC11813760 | DOI:10.3389/fneur.2025.1467175

Int J Clin Health Psychol. 2025 Jan-Mar;25(1):100547. doi: 10.1016/j.ijchp.2025.100547. Epub 2025 Jan 29.

ABSTRACT

Despite both internet gaming disorder (IGD) and gambling disorder (GD) being officially recognized as medical conditions by the World Health Organization, controversies persist. A transdiagnostic study may help inform classification and intervention approaches. IGD and GD may share or have distinct neural and behavioral features. To investigate, resting-state functional magnetic resonance imaging (fMRI) and self-reported behavioral data were collected from 58 individuals with GD, 31 with IGD, and 83 healthy control (HC) participants. After controlling for demographics, both GD and IGD groups scored lower on measures of gambling-related positive play. Neural data revealed reduced brain connectivity in the right rectus/orbital frontal gyrus in GD and IGD groups compared to HC participants. IGD participants displayed increased dynamic brain activity in the left triangular inferior frontal gyrus compared with GD and HC participants. Relatively decreased modular flexibility was also observed in GD but not IGD participants, relative to HC participants. Multiclass classification results showed that the indicators of gambling-related positive play, as well as dynamic brain activity and connectivity patterns, were useful for classifying GD, IGD, and HC participants, outperforming the use of either neural signals or self-report indicators alone. The shared phenotypes of GD and IGD groups provide insight into common features of behavioral addictions, and the combination of self-report and neural measures may provide the most robust approach for classification of diagnostic groups.

PMID:39944189 | PMC:PMC11815891 | DOI:10.1016/j.ijchp.2025.100547

Transl Psychiatry. 2025 Feb 12;15(1):49. doi: 10.1038/s41398-025-03249-y.

ABSTRACT

Suicide is a complex behavior strongly associated with depression. Despite extensive research, an objective biomarker for evaluating suicide risk precisely and timely is still lacking. Using the precision resting-state fMRI method, we studied 61 depressive patients with suicide ideation (SI) or suicide attempt (SA), and 35 patients without SI to explore functional biomarkers of suicide risk. Among them, 21 participants also completed electroconvulsive therapy (ECT) treatment, allowing the examination of functional changes across different risk states within the same individual. Functional networks were localized in each subject using resting-state fMRI and then an individualized connectome was constructed to represent the subject's functional brain organization. We identified a set of connections that track suicide risk (r = 0.41, p = 0.001) and found that these risk-associated connections were hyper-connected in the frontoparietal network (FPN, p = 0.008, Cohen's d = 0.58) in patients with suicide risk compared to those without. Moreover, ECT treatment significantly reduced (p = 0.001, Cohen's d = 0.56) and normalized these FPN hyper-connections. These findings suggest that connections involving FPN may constitute an important biomarker for evaluating suicide risk and may provide potential targets for interventions such as non-invasive brain stimulation.

PMID:39939611 | DOI:10.1038/s41398-025-03249-y

J Imaging Inform Med. 2025 Feb 12. doi: 10.1007/s10278-025-01434-5. Online ahead of print.

ABSTRACT

Functional magnetic resonance imaging (fMRI) is extensively used in clinical and preclinical settings to study brain function; however, fMRI data is inherently noisy due to physiological processes, hardware, and external noise. Denoising is one of the main preprocessing steps in any fMRI analysis pipeline. This process is challenging in preclinical data in comparison to clinical data due to variations in brain geometry, image resolution, and low signal-to-noise ratios. In this paper, we propose a structure-preserved algorithm based on a 3D Wasserstein generative adversarial network with a 3D dense U-net-based discriminator called 3D U-WGAN. We apply a 4D data configuration to effectively denoise temporal and spatial information in analyzing preclinical fMRI data. GAN-based denoising methods often utilize a discriminator to identify significant differences between denoised and noise-free images, focusing on global or local features. To refine the fMRI denoising model, our method employs a 3D dense U-Net discriminator to learn both global and local distinctions. To tackle potential oversmoothing, we introduce an adversarial loss and enhance perceptual similarity by measuring feature space distances. Experiments illustrate that 3D U-WGAN significantly improves image quality in resting-state and task preclinical fMRI data, enhancing signal-to-noise ratio without introducing excessive structural changes in existing methods. The proposed method outperforms state-of-the-art methods when applied to simulated and real data in a fMRI analysis pipeline.

PMID:39939477 | DOI:10.1007/s10278-025-01434-5

Brain Res Bull. 2025 Feb 10:111250. doi: 10.1016/j.brainresbull.2025.111250. Online ahead of print.

ABSTRACT

OBJECTIVE: To compare the brain functional changes in tinnitus patients of varying severities, in order to elucidate the complex relationship between tinnitus symptoms and neural mechanisms, providing a basis for personalized treatment for tinnitus patients with varying severity levels.

METHOD: 62 patients with chronic tinnitus were divided into severe and mild tinnitus group. 31 healthy controls (HC) matched for age, gender and education level were included. Resting-state functional magnetic resonance imaging was performed for all subjects, and the values of regional homogeneity (ReHo), amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF) and functional connectivity (FC) were calculated. One-way analysis of variance (ANOVA) was used to compare the differences among the three groups. Correlational analysis was conducted between imaging metrics and clinical information.

RESULTS: Compared to the mild tinnitus, the severe tinnitus shows increased ReHo and ALFF values in the left superior temporal gyrus (STG), middle temporal gyrus (MTG), supramarginal gyrus (SMG), angular gyrus (ANG), and middle occipital gyrus (MOG), as well as increased ReHo values in the left superior frontal gyrus (SFG) and ALFF values in the right ANG. In the severe tinnitus group, the FC between the bilateral ANG and the left MTG, the right ANG and the right medial SFG, the right ANG and the right anterior cingulate gyrus (ACG), as well as between the left SFG and the left rectus gyrus, was increased compared to the mild tinnitus group. In mild tinnitus group, the ReHo of left STG is correlated with tinnitus severity by Tinnitus Handicap Inventory.

CONCLUSION: Patients with different severity of tinnitus exhibit different compensatory mechanisms in brain function, highlighting the need for stratified analysis based on severity when investigating the underlying neural mechanisms.

PMID:39938755 | DOI:10.1016/j.brainresbull.2025.111250

Physiol Behav. 2025 Feb 10:114842. doi: 10.1016/j.physbeh.2025.114842. Online ahead of print.

ABSTRACT

Accumulating evidence suggests that the menstrual cycle and its endogenous ovarian hormones, including progesterone (PROG) and estradiol (E2), affect cognitive performance in women, particularly by modulating the prefrontal regions. In this study, we investigated whether differences in PROG and E2 levels modulate attentional control by affecting the prefrontal cognitive control areas. An fMRI scan was conducted on 53 naturally cycling healthy women in their late follicular phase (FP, n = 28) or mid-luteal phase (LP, n = 25) to examine the resting and task states during the completion of a face‒gender Stroop task. PROG was found to be positively correlated with the nodal efficiency of the inferior frontal gyrus (IFG) in the resting-state executive control network. At the behavioral level, while accuracy in categorizing male faces remained similar, participants in the mid-LP were significantly more accurate in categorizing female faces than those in the late FP. At the neural level, both the univariate and multivariate results indicated that higher levels of PROG enhance the detection and resolution of female incongruent faces through the activation of the bilateral IFG. These findings expand evidence of the effects of ovarian hormones on prefrontal-based attentional control in the social context.

PMID:39938608 | DOI:10.1016/j.physbeh.2025.114842

J Psychiatr Res. 2025 Jan 30;183:61-71. doi: 10.1016/j.jpsychires.2025.01.048. Online ahead of print.

ABSTRACT

Fibromyalgia (FM) is a complex medical condition. The nested hierarchical model of self and its extension to the pain matrix could represent an integrated theoretical framework that might comprehensively captures FM clinical feautres. A multi-level meta-analysis was conducted. Resting-state functional connectivity (RS-FC) studies that compared patients with FM and healthy controls (HCs) were included. The association between RS-FC among self-related brain regions and pain intensity was also explored in the FM group. Eleven studies were eligible for meta-analytic procedures. Patients with FM, compared to HCs, were characterized by an increased RS-FC between the default mode network (DMN) and areas ascribed to interoceptive (e.g., insula) and exteroceptive (e.g., premotor, visual/auditory cortices) self layers. The clinical group also showed a reduced RS-FC among regions of the pain matrix (i.e., periaqueductal gray matter, somatosensory areas) involved in pain modulation. An increased RS-FC within DMN together with a heightened RS-FC between DMN and interoceptive self areas were positively associated to pain intensity reported by patients with FM. The nested hierarchical model of self and its extension to the pain matrix might represent comprehensive neurobiological backgrounds for clarifying core mind-body clinical features of FM.

PMID:39938202 | DOI:10.1016/j.jpsychires.2025.01.048