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Keywords = resting-state functional magnetic resonance imaging

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19 pages, 3739 KiB  
Article
Disturbances in Resting State Functional Connectivity in Schizophrenia: A Study of Hippocampal Subregions, the Parahippocampal Gyrus and Functional Brain Networks
by Raghad M. Makhdoum and Adnan A. S. Alahmadi
Diagnostics 2025, 15(15), 1955; https://doi.org/10.3390/diagnostics15151955 (registering DOI) - 4 Aug 2025
Abstract
Background/Objectives: Schizophrenia exhibits symptoms linked to the hippocampus and parahippocampal gyrus. This includes the entorhinal cortex (ERC) and perirhinal cortex (PRC) as anterior parts, along with the posterior segment known as the parahippocampal cortex (PHC). However, recent research has detailed atlases based on [...] Read more.
Background/Objectives: Schizophrenia exhibits symptoms linked to the hippocampus and parahippocampal gyrus. This includes the entorhinal cortex (ERC) and perirhinal cortex (PRC) as anterior parts, along with the posterior segment known as the parahippocampal cortex (PHC). However, recent research has detailed atlases based on cytoarchitectural characteristics and the hippocampus divided into four subregions: cornu ammonis (CA), dentate gyrus (DG), subiculum (SUB), and hippocampal–amygdaloid transition (HATA). This study aimed to explore the functional connectivity (FC) changes between these hippocampal subregions and the parahippocampal gyrus structures (ERC, PRC, and PHC) as well as between hippocampal subregions and various functional brain networks in schizophrenia. Methods: In total, 50 individuals with schizophrenia and 50 matched healthy subjects were examined using resting state functional magnetic resonance imaging (rs-fMRI). Results: The results showed alterations characterized by increases and decreases in the strength of the positive connectivity between the parahippocampal gyrus structures and the four hippocampal subregions when comparing patients with schizophrenia with healthy subjects. Alterations were observed among the hippocampal subregions and functional brain networks, as well as the formation of new connections and absence of connections. Conclusions: There is strong evidence that the different subregions of the hippocampus have unique functions and their connectivity with the parahippocampal cortices and brain networks are affected by schizophrenia. Full article
(This article belongs to the Section Medical Imaging and Theranostics)
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16 pages, 610 KiB  
Article
Wired Differently? Brain Temporal Complexity and Intelligence in Autism Spectrum Disorder
by Moses O. Sokunbi, Oumayma Soula, Bertha Ochieng and Roger T. Staff
Brain Sci. 2025, 15(8), 796; https://doi.org/10.3390/brainsci15080796 - 26 Jul 2025
Viewed by 894
Abstract
Background: Autism spectrum disorder (ASD) is characterised by atypical behavioural and cognitive diversity, yet the neural underpinnings linking brain activity and individual presentations remain poorly understood. In this study, we investigated the relationship between resting-state functional magnetic resonance imaging (fMRI) signal complexity and [...] Read more.
Background: Autism spectrum disorder (ASD) is characterised by atypical behavioural and cognitive diversity, yet the neural underpinnings linking brain activity and individual presentations remain poorly understood. In this study, we investigated the relationship between resting-state functional magnetic resonance imaging (fMRI) signal complexity and intelligence (full-scale intelligence quotient (FIQ); verbal intelligence quotient (VIQ); and performance intelligence quotient (PIQ)) in male adults with ASD (n = 14) and matched neurotypical controls (n = 15). Methods: We used three complexity-based metrics: Hurst exponent (H), fuzzy approximate entropy (fApEn), and fuzzy sample entropy (fSampEn) to characterise resting-state fMRI signal dynamics, and correlated these measures with standardised intelligence scores. Results: Using a whole-brain measure, ASD participants showed significant negative correlations between PIQ and both fApEn and fSampEn, suggesting that increased neural irregularity may relate to reduced cognitive–perceptual performance in autistic individuals. No significant associations between entropy (fApEn and fSampEn) and PIQ were found in the control group. Group differences in brain–behaviour associations were confirmed through formal interaction testing using Fisher’s r-to-z transformation, which showed significantly stronger correlations in the ASD group. Complementary regression analyses with interaction terms further demonstrated that the entropy (fApEn and fSampEn) and PIQ relationship was significantly moderated by group, reinforcing evidence for autism-specific neural mechanisms underlying cognitive function. Conclusions: These findings provide insight into how cognitive functions in autism may not only reflect deficits but also an alternative neural strategy, suggesting that distinct temporal patterns may be associated with intelligence in ASD. These preliminary findings could inform clinical practice and influence health and social care policies, particularly in autism diagnosis and personalised support planning. Full article
(This article belongs to the Special Issue Understanding the Functioning of Brain Networks in Health and Disease)
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21 pages, 1842 KiB  
Article
Acute Stroke Severity Assessment: The Impact of Lesion Size and Functional Connectivity
by Karolin Weigel, Christian Gaser, Stefan Brodoehl, Franziska Wagner, Elisabeth Jochmann, Daniel Güllmar, Thomas E. Mayer and Carsten M. Klingner
Brain Sci. 2025, 15(7), 735; https://doi.org/10.3390/brainsci15070735 - 9 Jul 2025
Viewed by 475
Abstract
Background/Objectives: Early and accurate prediction of stroke severity is crucial for optimizing guided therapeutic decisions and improving outcomes. This study investigates the predictive value of lesion size and functional connectivity for neurological deficits, assessed by the National Institutes of Health Stroke Scale (NIHSS [...] Read more.
Background/Objectives: Early and accurate prediction of stroke severity is crucial for optimizing guided therapeutic decisions and improving outcomes. This study investigates the predictive value of lesion size and functional connectivity for neurological deficits, assessed by the National Institutes of Health Stroke Scale (NIHSS score), in patients with acute or subacute subcortical ischemic stroke. Methods: Forty-four patients (mean age: 68.11 years, 23 male, and admission NIHSS score 4.30 points) underwent high-resolution anatomical and resting-state functional Magnetic Resonance Imaging (rs-fMRI) within seven days of stroke onset. Lesion size was volumetrically quantified, while functional connectivity within the motor, default mode, and frontoparietal networks was analyzed using seed-based correlation methods. Multiple linear regression and cross-validation were applied to develop predictive models for stroke severity. Results: Our results showed that lesion size explained 48% of the variance in NIHSS scores (R2 = 0.48, cross-validated R2 = 0.49). Functional connectivity metrics alone were less predictive but enhanced model performance when combined with lesion size (achieving an R2 = 0.71, cross-validated R2 = 0.73). Additionally, left hemisphere connectivity features were particularly informative, as models based on left-hemispheric connectivity outperformed those using right-hemispheric or bilateral predictors. This suggests that the inclusion of contralateral hemisphere data did not enhance, and in some configurations, slightly reduced, model performance—potentially due to lateralized functional organization and lesion distribution in our cohort. Conclusions: The findings highlight lesion size as a reliable early marker of stroke severity and underscore the complementary value of functional connectivity analysis. Integrating rs-fMRI into clinical stroke imaging protocols offers a potential approach for refining prognostic models. Future research efforts should prioritize establishing this approach in larger cohorts and analyzing additional biomarkers to improve predictive models, advancing personalized therapeutic strategies for stroke management. Full article
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16 pages, 3375 KiB  
Data Descriptor
ICA-Based Resting-State Networks Obtained on Large Autism fMRI Dataset ABIDE
by Sjir J. C. Schielen, Jesper Pilmeyer, Albert P. Aldenkamp, Danny Ruijters and Svitlana Zinger
Data 2025, 10(7), 109; https://doi.org/10.3390/data10070109 - 3 Jul 2025
Viewed by 545
Abstract
Functional magnetic resonance imaging (fMRI) has become instrumental in researching the functioning of the brain. One application of fMRI is investigating the brains of people with autism spectrum disorder (ASD). The Autism Brain Imaging Data Exchange (ABIDE) facilitates this research through its extensive [...] Read more.
Functional magnetic resonance imaging (fMRI) has become instrumental in researching the functioning of the brain. One application of fMRI is investigating the brains of people with autism spectrum disorder (ASD). The Autism Brain Imaging Data Exchange (ABIDE) facilitates this research through its extensive data-sharing initiative. While ABIDE offers raw data and data preprocessed with various atlases, independent component analysis (ICA) for dimensionality reduction remains underutilized. ICA is a data-driven way to reduce dimensionality without prior assumptions on delineations. Additionally, ICA separates the noise from the signal, and the signal components correspond well to functional brain networks called resting-state networks (RSNs). Currently, no large, readily available dataset preprocessed with ICA exists. Here, we address this gap by presenting ABIDE’s data preprocessed to extract ICA-based resting-state networks, which are publicly available. These RSNs unveil neural activation clusters without atlas constraints, offering a perspective on ASD analyses that complements the predominantly atlas-based literature. This contribution provides a resource for further research into ASD, benchmarking between methodologies, and the development of new analytical approaches. Full article
(This article belongs to the Special Issue Benchmarking Datasets in Bioinformatics, 2nd Edition)
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16 pages, 1881 KiB  
Study Protocol
Derivation of Novel Imaging Biomarkers of Neonatal Brain Injury Using Bedside Diffuse Optical Tomography: Protocol for a Prospective Feasibility Study
by Sabrina Mastroianni, Anagha Vinod, Naiqi G. Xiao, Heather Johnson, Lehana Thabane, Qiyin Fang and Ipsita Goswami
NeuroSci 2025, 6(3), 60; https://doi.org/10.3390/neurosci6030060 - 30 Jun 2025
Viewed by 399
Abstract
Prognostication of neurodevelopmental outcomes for neonates with hypoxic–ischemic encephalopathy (HIE) is primarily reliant on structural assessment using conventional brain magnetic resonance imaging in the clinical setting. Diffuse optical tomography (DOT) can provide complementary information on brain function at the bedside, further enhancing prognostic [...] Read more.
Prognostication of neurodevelopmental outcomes for neonates with hypoxic–ischemic encephalopathy (HIE) is primarily reliant on structural assessment using conventional brain magnetic resonance imaging in the clinical setting. Diffuse optical tomography (DOT) can provide complementary information on brain function at the bedside, further enhancing prognostic accuracy. The predictive accuracy and generalizability of DOT-based neuroimaging markers are unknown. This study aims to test the feasibility of prospectively recruiting and retaining neonates for 12 months in a larger study that investigates the prognostic utility of DOT-based biomarkers of HIE. The study will recruit 25 neonates with HIE over one year and follow them beyond NICU discharge at 6 and 12 months of age. Study subjects will undergo resting-state DOT measurement within 7 days of life for a 30–45-min period without sedation. A customized neonatal cap with 10 sources and eight detectors per side will be used to quantify cortical functional connectivity and to generate brain networks using MATLAB-based software (version 24.2). The Ages and Stages Questionnaires—3rd edition will be used for standardized developmental assessments at follow-up. This feasibility study will help refine the design and sample-size calculation for an adequately powered larger study that determines the clinical utility of DOT-based neuroimaging in perinatal brain injury. Full article
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15 pages, 937 KiB  
Article
Insular Cortex Modulation by Repetitive Transcranial Magnetic Stimulation with Concurrent Functional Magnetic Resonance Imaging: Preliminary Findings
by Daphné Citherlet, Olivier Boucher, Manon Robert, Catherine Provost, Arielle Alcindor, Ke Peng, Louis De Beaumont and Dang Khoa Nguyen
Brain Sci. 2025, 15(7), 680; https://doi.org/10.3390/brainsci15070680 - 25 Jun 2025
Viewed by 991
Abstract
Background/Objectives: The insula is a deep, functionally heterogeneous region involved in various pathological conditions. Repetitive transcranial magnetic stimulation (rTMS) has emerged as a promising therapeutic avenue for neuromodulation, yet very few studies have directly investigated its effects on insular activity. Moreover, empirical evidence [...] Read more.
Background/Objectives: The insula is a deep, functionally heterogeneous region involved in various pathological conditions. Repetitive transcranial magnetic stimulation (rTMS) has emerged as a promising therapeutic avenue for neuromodulation, yet very few studies have directly investigated its effects on insular activity. Moreover, empirical evidence of target engagement of this region remains scarce. This study aimed to stimulate the insula with rTMS and assess blood oxygen level-dependent (BOLD) signal modulation using concurrent functional magnetic resonance imaging (fMRI). Methods: Ten participants were recruited, six of whom underwent a single session of 5 Hz high-frequency rTMS over the right insular cortex inside the MRI scanner. Stimulation was delivered using a compatible MRI-B91 TMS coil. Stimulation consisted of 10 trains of 10 s each, with a 50 s interval between trains. Frameless stereotactic neuronavigation ensured precise targeting. Paired t-tests were used to compare the mean BOLD signal obtained between stimulation trains with resting-state fMRI acquired before the rTMS stimulation session. A significant cluster threshold of q < 0.01 (False Discovery Rate; FDR) with a minimum cluster size of 10 voxels was applied. Results: Concurrent rTMS-fMRI revealed the significant modulation of BOLD activity within insular subregions. Increased activity was observed in the anterior, middle, and middle-inferior insula, while decreased activity was identified in the ventral anterior and posterior insula. Additionally, two participants reported transient dysgeusia following stimulation, which provides further evidence of insular modulation. Conclusions: These findings provide preliminary evidence that rTMS can modulate distinct subregions of the insular cortex. The combination of region-specific BOLD responses and stimulation-induced dysgeusia supports the feasibility of using rTMS to modulate insular activity. Full article
(This article belongs to the Section Neurotechnology and Neuroimaging)
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20 pages, 3404 KiB  
Article
Dynamic Synergy Network Analysis Reveals Stage-Specific Regional Dysfunction in Alzheimer’s Disease
by Xiaoyan Zhang, Chao Han, Jingbo Xia, Lingli Deng and Jiyang Dong
Brain Sci. 2025, 15(6), 636; https://doi.org/10.3390/brainsci15060636 - 12 Jun 2025
Viewed by 476
Abstract
Background: Alzheimer’s disease (AD) is a prevalent neurodegenerative disorder characterized by progressive neurodegeneration and connectivity deterioration. While resting-state functional magnetic resonance imaging (fMRI) provides critical insights into brain network abnormalities, traditional mutual information-based methods exhibit inherent limitations in characterizing the dynamic synergistic mechanisms [...] Read more.
Background: Alzheimer’s disease (AD) is a prevalent neurodegenerative disorder characterized by progressive neurodegeneration and connectivity deterioration. While resting-state functional magnetic resonance imaging (fMRI) provides critical insights into brain network abnormalities, traditional mutual information-based methods exhibit inherent limitations in characterizing the dynamic synergistic mechanisms between cerebral regions. Method: This study pioneered the application of an Integrated Information Decomposition (ΦID) framework in AD brain network analysis, constructing single-sample network models based on ΦID-derived synergy metrics to systematically compare their differences with mutual information-based methods in pathological sensitivity, computational robustness, and network representation capability, while detecting brain regions with declining dynamic synergy during AD progression through intergroup t-tests. Result: The key finding are as follows: (1) synergy metrics exhibited lower intra-group coefficient of variation than mutual information metrics, indicating higher computational stability; (2) single-sample reconstruction significantly enhanced the statistical power in intergroup difference detection; (3) synergy metrics captured brain network features that are undetectable by traditional mutual information methods, with more pronounced differences between networks; (4) key node analysis demonstrated spatiotemporal degradation patterns progressing from initial dysfunction in orbitofrontal–striatal–temporoparietal pathways accompanied by multi-regional impairments during prodromal stages, through moderate-phase decline located in the right middle frontal and postcentral gyri, to advanced-stage degeneration of the right supramarginal gyrus and left inferior parietal lobule. ΦID-driven dynamic synergy network analysis provides novel information integration theory-based biomarkers for AD progression diagnosis and potentially lays the foundation for pathological understanding and subsequent targeted therapy development. Full article
(This article belongs to the Special Issue Using Neuroimaging to Explore Neurodegenerative Diseases)
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19 pages, 333 KiB  
Systematic Review
The Connectivity of the Resting Brain in Primary Open-Angle Glaucoma: A Systematic Review
by Nikola Velkov, Sevdalina Kandilarova and Drozdstoy Stoyanov
Biomedicines 2025, 13(6), 1402; https://doi.org/10.3390/biomedicines13061402 - 7 Jun 2025
Viewed by 573
Abstract
Background/Objectives: Worldwide, glaucomas are the leading cause of irreversible blindness in adults. On the ocular level, they are fairly well understood; however, the functional and structural changes that occur in the brain have become a subject of great interest lately, mostly owing [...] Read more.
Background/Objectives: Worldwide, glaucomas are the leading cause of irreversible blindness in adults. On the ocular level, they are fairly well understood; however, the functional and structural changes that occur in the brain have become a subject of great interest lately, mostly owing to improved accessibility and effectiveness of functional magnetic resonance imaging (fMRI). This, coupled with the non-invasive nature of the methodology, has contributed to an ever-growing body of research published on the topic. In this systematic review, we gather, systematize, and compare the results and methodologies reported in the literature, as pertaining to resting-state fMRI brain changes in primary open-angle glaucoma (POAG). Methods: A systematic search in PubMed, Scopus, and Web of Science was carried out, resulting in a total of 290 records identified, with 67 assessed for eligibility and 24 selected for inclusion. Results: The main findings include worse functional parameters in the early visual centers in POAG across all methodologies, reduced functional connectivity between V1 and other parts of the visual cortex, functional aberrations in higher levels of the visual system, predominantly in the ventral stream and in extravisual networks, among others. Moreover, the majority of these changes are shown to be correlated with ophthalmological measurements. Conclusions: Although studies on this matter tend to suffer from a limited sample size and a lack of methodological standardization, we nevertheless manage to present common results and conclusions regarding the effects of POAG on brain function. Full article
(This article belongs to the Special Issue Glaucoma: New Diagnostic and Therapeutic Approaches, 2nd Edition)
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16 pages, 4737 KiB  
Article
Co-Community Network Analysis Reveals Alterations in Brain Networks in Alzheimer’s Disease
by Xiaodong Wang, Zhaokai Zhang, Lingli Deng and Jiyang Dong
Brain Sci. 2025, 15(5), 517; https://doi.org/10.3390/brainsci15050517 - 18 May 2025
Viewed by 616
Abstract
Background: Alzheimer’s disease (AD) is a common neurodegenerative disease. Functional magnetic resonance imaging (fMRI) can be used to measure the temporal correlation of blood-oxygen-level-dependent (BOLD) signals in the brain to assess the brain’s intrinsic connectivity and capture dynamic changes in the brain. [...] Read more.
Background: Alzheimer’s disease (AD) is a common neurodegenerative disease. Functional magnetic resonance imaging (fMRI) can be used to measure the temporal correlation of blood-oxygen-level-dependent (BOLD) signals in the brain to assess the brain’s intrinsic connectivity and capture dynamic changes in the brain. In this study, our research goal is to investigate how the brain network structure, as measured by resting-state fMRI, differs across distinct physiological states. Method: With the research goal of addressing the limitations of BOLD signal-based brain networks constructed using Pearson correlation coefficients, individual brain networks and community detection are used to study the brain networks based on co-community probability matrices (CCPMs). We used CCPMs and enrichment analysis to compare differences in brain network topological characteristics among three typical brain states. Result: The experimental results indicate that AD patients with increasing disease severity levels will experience the isolation of brain networks and alterations in the topological characteristics of brain networks, such as the Somatomotor Network (SMN), dorsal attention network (DAN), and Default Mode Network (DMN). Conclusion: This work suggests that using different data-driven methods based on CCPMs to study alterations in the topological characteristics of brain networks would provide better information complementarity, which can provide a novel analytical perspective for AD progression and a new direction for the extraction of neuro-biomarkers in the early diagnosis of AD. Full article
(This article belongs to the Special Issue Understanding the Functioning of Brain Networks in Health and Disease)
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32 pages, 1646 KiB  
Systematic Review
Resting-State Functional MRI in Dyslexia: A Systematic Review
by Bruce Martins, Isabel A. B. Verrone, Mariana M. I. Sakamoto, Mariana Y. Baba, Melissa E. Yvata, Katerina Lukasova and Mariana P. Nucci
Biomedicines 2025, 13(5), 1210; https://doi.org/10.3390/biomedicines13051210 - 16 May 2025
Viewed by 1090
Abstract
Background/Objectives: The present review addresses and systematically analyses the most frequently reported neuropsychological and functional connectivity (FC) alterations in individuals with dyslexia compared to controls. By synthesizing extant evidence, this work aims to clarify dyslexic connectivity profiles and provide a foundation for future [...] Read more.
Background/Objectives: The present review addresses and systematically analyses the most frequently reported neuropsychological and functional connectivity (FC) alterations in individuals with dyslexia compared to controls. By synthesizing extant evidence, this work aims to clarify dyslexic connectivity profiles and provide a foundation for future research and clinical translation. Methods: This systematic review analyzed publications from the last 10 years in two scientific databases, focusing on individuals with dyslexia, without previous injuries, who underwent resting-state functional magnetic resonance imaging (rs-fMRI) assessments, comparing them with typical readers. Results: This review revealed that most dyslexia studies on brain FC using rs-fMRI focused on children (92%), underscoring a gap in research on adults and limiting our understanding of brain maturation processes and neuroplasticity across the lifespan. FC alterations primarily involved ipsilateral connections (60%), with reduced connectivity mainly in the left hemisphere (40%), particularly in posterior regions, aligning with the neurobiological hypothesis of phonological and visual–phonological dysfunctions in dyslexia. Conversely, increased connectivity in the right hemisphere (20%) may indicate the engagement of an alternative network and highlight the complexity of neural adaptations in dyslexia. Conclusions: The findings highlight a significant gap in the study of adult dyslexia and suggest that FC alterations predominantly affect the left hemisphere, with possible compensatory mechanisms in the right hemisphere. Reading fluency improvements in dyslexia may be linked to connectivity changes across multiple brain networks rather than the classical reading circuitry alone. Increased and decreased connectivity in various regions related to executive function, language, and salience processing indicate that broader cognitive mechanisms play a key role in reading performance. Full article
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18 pages, 1065 KiB  
Review
Multimodal Neuroimaging of Obesity: From Structural-Functional Mechanisms to Precision Interventions
by Wenhua Liu, Na Li, Dongsheng Tang, Lang Qin and Zhiqiang Zhu
Brain Sci. 2025, 15(5), 446; https://doi.org/10.3390/brainsci15050446 - 25 Apr 2025
Cited by 1 | Viewed by 1087
Abstract
Purpose: Obesity’s metabolic consequences are well documented; however, its neurobiological underpinnings remain elusive. This systematic review addresses a critical gap by synthesizing evidence on obesity-induced neuroplasticity across structural, functional, and molecular domains through advanced neuroimaging. Methods: According to PRISMA guidelines, we systematically searched [...] Read more.
Purpose: Obesity’s metabolic consequences are well documented; however, its neurobiological underpinnings remain elusive. This systematic review addresses a critical gap by synthesizing evidence on obesity-induced neuroplasticity across structural, functional, and molecular domains through advanced neuroimaging. Methods: According to PRISMA guidelines, we systematically searched (2015–2024) across PubMed/Web of Science, employing MeSH terms: (“Obesity” [Majr]) AND (“Neuroimaging” [Mesh] OR “Magnetic Resonance Imaging” [Mesh]). A total of 104 studies met the inclusion criteria. The inclusion criteria required the following: (1) multimodal imaging protocols (structural MRI/diffusion tensor imaging/resting-state functional magnetic resonance imaging (fMRI)/positron emission tomography (PET)); (2) pre-/post-intervention longitudinal design. Risk of bias was assessed via the Newcastle-Ottawa Scale. Key Findings: 1. Structural alterations: 7.2% mean gray matter reduction in prefrontal cortex (Cohen’s d = 0.81). White matter integrity decline (FA reduction β = −0.33, p < 0.001) across 12 major tracts. 2. Functional connectivity: Resting-state hyperactivity in mesolimbic pathways (fALFF + 23%, p-FDR < 0.05). Impaired fronto–striatal connectivity (r = −0.58 with BMI, 95% CI [−0.67, −0.49]). 3. Interventional reversibility: Bariatric surgery restored prefrontal activation (Δ = +18% vs. controls, p = 0.002). Neurostimulation (transcranial direct current stimulation (tDCS) enhanced cognitive control (post-treatment β = 0.42, p = 0.009). Conclusion: 1. Obesity induces multidomain neural reorganization beyond traditional reward circuits. 2. Neuroimaging biomarkers (e.g., striatal PET-dopamine binding potential) predict intervention outcomes (AUC = 0.79). 3. Precision neuromodulation requires tripartite integration of structural guidance, functional monitoring, and molecular profiling. Findings highlight neuroimaging’s pivotal role in developing stage-specific therapeutic strategies. Full article
(This article belongs to the Special Issue Application of MRI in Brain Diseases)
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18 pages, 6464 KiB  
Article
Resting-State fMRI and Post-Ischemic Stroke Functional Recovery: Unraveling Causality and Predicting Therapeutic Targets
by Mu-Zhi Li, Yin-Li Shi, Xiao-Jun He, Si-Cun Wang, Jun Liu, Zhong Wang, Hai-Xia Dang and Ya-Nan Yu
Int. J. Mol. Sci. 2025, 26(8), 3608; https://doi.org/10.3390/ijms26083608 - 11 Apr 2025
Viewed by 790
Abstract
Research on functional recovery after ischemic stroke has primarily focused on non-invasive brain stimulation and motor rehabilitation therapies, while direct pharmacological interventions are relatively underexplored. This study utilized a bidirectional Mendelian randomization approach to investigate the causal relationship between 191 resting-state functional magnetic [...] Read more.
Research on functional recovery after ischemic stroke has primarily focused on non-invasive brain stimulation and motor rehabilitation therapies, while direct pharmacological interventions are relatively underexplored. This study utilized a bidirectional Mendelian randomization approach to investigate the causal relationship between 191 resting-state functional magnetic resonance imaging (rs-fMRI) features and post-ischemic stroke functional recovery (PISFR). Significant rs-fMRI phenotypes were identified, and Mendelian randomization was employed to determine their associated proteins. Bidirectional Mendelian randomization identified four rs-fMRI phenotypes potentially associated with functional recovery after ischemic stroke. Subsequent MR analysis, using pheno12 as the outcome and plasma protein as the exposure, highlighted Fas-Associated protein with Death Domain (FADD) as a significant protein. Further exploration within the protein–protein interaction (PPI) network identified FADD, Cysteinyl Aspartate Specific Proteinase 8 (CASP8), and Receptor-Interacting Serine/Threonine-Protein Kinase 1 (RIPK1) as potential drug targets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated that these proteins are involved in the extrinsic apoptotic pathway, providing new insights for pharmacological strategies in post-ischemic stroke recovery. This study offers genetic evidence linking rs-fMRI to functional recovery post-ischemic stroke and identifies potential drug targets that may facilitate therapeutic interventions to enhance recovery after ischemic stroke. Full article
(This article belongs to the Section Molecular Neurobiology)
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13 pages, 1047 KiB  
Article
Neuroimaging Changes in the Sensorimotor Network and Visual Network in Bipolar Disorder and Their Relationship with Genetic Characteristics
by Chunguo Zhang, Yiding Han, Haohao Yan, Yangpan Ou, Jiaquan Liang, Wei Huang, Xiaoling Li, Chaohua Tang, Jinbing Xu, Guojun Xie and Wenbin Guo
Biomedicines 2025, 13(4), 898; https://doi.org/10.3390/biomedicines13040898 - 8 Apr 2025
Cited by 1 | Viewed by 595
Abstract
Objective: Patients with bipolar disorder (BD) may exhibit common and significant changes in brain activity across different networks. Our aim was to investigate the changes in functional connectivity (FC) within different brain networks in BD, as well as their neuroimaging homogeneity, heterogeneity, [...] Read more.
Objective: Patients with bipolar disorder (BD) may exhibit common and significant changes in brain activity across different networks. Our aim was to investigate the changes in functional connectivity (FC) within different brain networks in BD, as well as their neuroimaging homogeneity, heterogeneity, and genetic variation. Methods: In this study, we analyzed the seed points and whole-brain FC of the sensorimotor network (SMN) and visual network (VN) in 83 healthy controls (HCs) and 77 BD patients, along with their genetic neuroimaging associations. Results: The results showed that, compared to HCs, BD patients exhibited abnormal FC in the SMN and VN brain regions. However, after three months of treatment, there were no significant differences in SMN and VN FC in the brain regions of the patients compared to pre-treatment levels. Enrichment analysis indicated that genes associated with changes in FC were shared among different SMN seed points, but no shared genes were found among VN seed points. Conclusions: In conclusion, changes in SMN FC may serve as a potential neuroimaging marker in BD patients. Our genetic neuroimaging association analysis may help to comprehensively understand the molecular mechanisms underlying FC changes in BD patients. Full article
(This article belongs to the Section Neurobiology and Clinical Neuroscience)
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14 pages, 7466 KiB  
Article
Impaired Cerebral Hemodynamics in Asymptomatic Carotid Artery Stenosis Assessed by Resting-State Functional MRI
by Kaio F. Secchinato, Pedro H. R. da Silva, Guilherme R. Rodrigues, Ana P. A. C. Ferreira, Octavio M. Pontes-Neto and Renata F. Leoni
J. Vasc. Dis. 2025, 4(2), 15; https://doi.org/10.3390/jvd4020015 - 7 Apr 2025
Cited by 1 | Viewed by 947
Abstract
Background/Objectives: Cerebrovascular reactivity (CVR) and time shift (TS) are vascular-related parameters that reflect cerebral perfusion and may be associated with the risk of developing stroke in patients with asymptomatic carotid artery stenosis (ACAS). We investigated CVR and TS in patients with ACAS using [...] Read more.
Background/Objectives: Cerebrovascular reactivity (CVR) and time shift (TS) are vascular-related parameters that reflect cerebral perfusion and may be associated with the risk of developing stroke in patients with asymptomatic carotid artery stenosis (ACAS). We investigated CVR and TS in patients with ACAS using resting-state magnetic resonance imaging based on blood-oxygen-level-dependent contrast (BOLD-MRI). Methods: We included twenty patients with severe unilateral ACAS and twenty age-matched controls. Individual CVR maps were obtained through a voxel-wise regression of the MRI signal, using the global signal filtered in a specific frequency range (0.02–0.04 Hz) as the regressor. A recursive cross-correlation method provided individual TS maps through the BOLD low-frequency fluctuation. CVR and TS values were obtained for the territories irrigated by the main cerebral arteries (anterior, middle, and posterior) separated into proximal, intermediary, and distal regions. Results: Compared to controls, ACAS patients presented reduced CVR and increased TS in the distal parts of the brain vascular territories. Individual CVR and TS values varied more within the patient group than controls. Such individual variability may help identify patients eligible for intervention better than the stenosis grade. Conclusions: CVR and TS may indicate subtle hemodynamic changes and assist in identifying regions at higher risk of neuronal damage or ischemic stroke on an individual basis, aiding in the stratification of patients with ACAS based on their risk of progressing to stroke. Full article
(This article belongs to the Section Neurovascular Diseases)
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12 pages, 4367 KiB  
Article
Exploring the Potential of Voxel-Mirrored Homotopic Connectivity (VMHC) and Regional Homogeneity (ReHo) in Understanding Cognitive Changes After Heart Transplantation
by Qian Qin, Jia Liu, Wenliang Fan, Xinli Zhang, Jue Lu, Xiaotong Guo, Ziqiao Lei and Jing Wang
Biomedicines 2025, 13(4), 873; https://doi.org/10.3390/biomedicines13040873 - 3 Apr 2025
Viewed by 635
Abstract
Objective: This study aimed to investigate the application value of voxel-mirrored homotopic connectivity (VMHC) and regional homogeneity (ReHo) in evaluating cognitive impairment after heart transplantation. Methods: A total of 68 heart transplant patients and 56 healthy controls were included. ReHo and [...] Read more.
Objective: This study aimed to investigate the application value of voxel-mirrored homotopic connectivity (VMHC) and regional homogeneity (ReHo) in evaluating cognitive impairment after heart transplantation. Methods: A total of 68 heart transplant patients and 56 healthy controls were included. ReHo and VMHC were calculated using DPARSF software. A two-sample t-test was applied to compare the differences in ReHo and VMHC between the two groups, and a Pearson correlation analysis was performed by extracting the VMHC and ReHo values of different brain regions and correlating them with cognitive scale scores of the patient groups. Results: Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores were lower in the heart transplant group than in the control group (MMSE: t = 4.028, p < 0.001; MoCA: t = 4.914, p < 0.001). Compared with the control group, the ReHo values of Frontal_Sup_R (t = −4.422, p < 0.001), Thalamus_L (t = −3.911, p < 0.001), and Calcarine_L (t = −3.640, p < 0.001) were lower in the heart transplantation group, while the ReHo of Temporal_Sup_L was higher (t = 4.609, p < 0.001). VMHC was elevated for bilateral Cerebellum_Crus1 (t = 3.803, p < 0.001) and decreased for bilateral calcarine (t = −3.424, p < 0.001). The ReHo of Frontal_Sup_R was positively correlated with MMSE (r = 0.345, p = 0.004) and MoCA (r = 0.376, p = 0.002). The ReHo of Temporal_Sup_L was also positively correlated with MMSE (r = 0.397, p < 0.001) and MoCA (r = 0.542, p < 0.001). The VMHC of bilateral calcarine showed a positive correlation with MMSE (r = 0.513, p < 0.001) and MoCA (r = 0.398, p < 0.001). Other differential brain regions showed no significant correlation with the MMSE and MoCA scale scores. Conclusions: Cognitive decline was observed in heart transplant patients. Heart transplant patients exhibited altered ReHo and VMHC in several brain regions compared with healthy controls. These changes may underlie impaired cognitive function in heart transplant patients. These findings may contribute to understanding the neural mechanisms of cognitive changes in heart transplant patients and could inform future research on potential intervention strategies. Full article
(This article belongs to the Special Issue Advanced Research on Heart Failure and Heart Transplantation)
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