Brain connectivity最新文献

{"title":"Differences Between Resting-State fMRI BOLD Variability and Default Mode Network Connectivity in Healthy Older and Younger Adults.","authors":"Vanessa Scarapicchia, Heather Kwan, Alexis Czippel, Jodie R Gawryluk","doi":"10.1089/brain.2023.0078","DOIUrl":"10.1089/brain.2023.0078","url":null,"abstract":"<p><p><b><i>Background:</i></b> Resting-state fMRI analyses have been used to examine functional connectivity in the aging brain. Recently, fluctuations in the fMRI BOLD signal have been used as a potential marker of integrity in neural systems. Despite its increasing popularity, the results of BOLD variability analyses and traditional seed-based functional connectivity analyses have rarely been compared. The current study examined fMRI BOLD signal variability and default mode network seed-based analyses in healthy older and younger adults to better understand the unique contributions of these methodological approaches. <b><i>Methods:</i></b> Thirty-four healthy participants were separated into a younger adult group (age 25-35, <i>n</i> = 17) and an older adult group (age 65+, <i>n</i> = 17). For each participant, a map of the standard deviation of the BOLD signal (SDBOLD) was derived. Group comparisons examined differences in resting-state SDBOLD in younger versus older adults. Seed-based analyses were used to examine differences between younger and older adults in the default mode network. <b><i>Results:</i></b> Between-group comparisons revealed significantly greater BOLD variability in widespread brain regions in older relative to younger adults. There were no significant differences between younger and older adults in the default mode network connectivity. <b><i>Conclusion:</i></b> The current findings align with an increasing number of studies reporting greater BOLD variability in older relative to younger adults. The current results also suggest that the traditional resting state examination methods may not detect nuanced age-related differences. Further large-scale studies in an adult lifespan sample are needed to better understand the functional relevance of the BOLD variability in normative aging.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"391-398"},"PeriodicalIF":2.4,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141544497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Acute Exercise Improves Large-Scale Brain Network Segregation in Healthy Older Adults.","authors":"Yash Kommula, Daniel D Callow, Jeremy J Purcell, J Carson Smith","doi":"10.1089/brain.2024.0003","DOIUrl":"10.1089/brain.2024.0003","url":null,"abstract":"<p><p><b><i>Introduction</i></b>: Age-related cognitive decline and mental health problems are accompanied by changes in resting-state functional connectivity (rsFC) indices, such as reduced brain network segregation. Meanwhile, exercise can improve cognition, mood, and neural network function in older adults. Studies on effects of exercise on rsFC outcomes in older adults have chiefly focused on changes after exercise training and suggest improved network segregation through enhanced within-network connectivity. However, effects of acute exercise on rsFC measures of neural network integrity in older adults, which presumably underlie changes observed after exercise training, have received less attention. In this study, we hypothesized that acute exercise in older adults would improve functional segregation of major cognition and affect-related brain networks. <b><i>Methods:</i></b> To test this, we analyzed rsFC data from 37 healthy and physically active older adults after they completed 30 min of moderate-to-vigorous intensity cycling and after they completed a seated rest control condition. Conditions were performed in a counterbalanced order across separate days in a within-subject crossover design. We considered large-scale brain networks associated with cognition and affect, including the frontoparietal network (FPN), salience network (SAL), default mode network (DMN), and affect-reward network (ARN). <b><i>Results:</i></b> We observed that after acute exercise, there was greater segregation between SAL and DMN, as well as greater segregation between SAL and ARN. <b><i>Conclusion:</i></b> These findings indicate that acute exercise in active older adults alters rsFC measures in key cognition and affect-related networks in a manner that opposes age-related dedifferentiation of neural networks that may be detrimental to cognition and mental health.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"369-381"},"PeriodicalIF":2.4,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141417731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Resting-State Network Analysis Reveals Altered Functional Brain Connectivity in Essential Tremor.","authors":"Sheng-Min Huang, Cheung-Ter Ong, Yu-Ching Huang, Nan-Hao Chen, Ting-Kai Leung, Chun-Ying Shen, Li-Wei Kuo","doi":"10.1089/brain.2024.0004","DOIUrl":"10.1089/brain.2024.0004","url":null,"abstract":"<p><p><b><i>Introduction:</i></b> Essential tremor (ET) comprises motor and non-motor-related features, whereas the current neuro-pathogenetic basis is still insufficient to explain the etiologies of ET. Although cerebellum-associated circuits have been discovered, the large-scale cerebral network connectivity in ET remains unclear. This study aimed to characterize the ET in terms of functional connectivity as well as network. We hypothesized that the resting-state network (RSN) within cerebrum could be altered in patients with ET. <b><i>Methods:</i></b> Resting-state functional magnetic resonance imaging (fMRI) was used to evaluate the inter- and intra-network connectivity as well as the functional activity in ET and normal control. Correlation analysis was performed to explore the relationship between RSN metrics and tremor features. <b><i>Results:</i></b> Comparison of inter-network connectivity indicated a decreased connectivity between default mode network and ventral attention network in the ET group (<i>p</i> < 0.05). Differences in functional activity (assessed by amplitude of low-frequency fluctuation, ALFF) were found in several brain regions participating in various RSNs (<i>p</i> < 0.05). The ET group generally has higher degree centrality over normal control. Correlation analysis has revealed that tremor features are associated with inter-network connectivity (|r| = 0.135-0.506), ALFF (|r| = 0.313-0.766), and degree centrality (|r| = 0.523-0.710). <b><i>Conclusion:</i></b> Alterations in the cerebral network of ET were detected by using resting-state fMRI, demonstrating a potentially useful approach to explore the cerebral alterations in ET.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"382-390"},"PeriodicalIF":2.4,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141315973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Interest and Usefulness of Resting State fMRI in Brain Connectivity Research.","authors":"Roxane Hoyer, Steven Laureys","doi":"10.1089/brain.2024.0052","DOIUrl":"10.1089/brain.2024.0052","url":null,"abstract":"","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"354-356"},"PeriodicalIF":2.4,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141791949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rosalind Franklin Society Proudly Announces the 2023 Award Recipient for <i>Brain Connectivity</i>.","authors":"Liara Rizzi","doi":"10.1089/brain.2024.59245.rfs2023","DOIUrl":"https://doi.org/10.1089/brain.2024.59245.rfs2023","url":null,"abstract":"","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"14 7","pages":"351"},"PeriodicalIF":2.4,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142131860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Atlas-Based Labeling of Resting-State fMRI.","authors":"Hrishikesh Kambli, Alberto Santamaria-Pang, Ivan Tarapov, Elham Beheshtian, Licia P Luna, Haris Sair, Craig Jones","doi":"10.1089/brain.2023.0080","DOIUrl":"10.1089/brain.2023.0080","url":null,"abstract":"<p><p><b><i>Background:</i></b> Functional magnetic resonance imaging (fMRI) has the potential to provide noninvasive functional mapping of the brain with high spatial and temporal resolution. However, fMRI independent components (ICs) must be manually inspected, selected, and interpreted, requiring time and expertise. We propose a novel approach for automated labeling of fMRI ICs by establishing their characteristic spatio-functional relationship. <b><i>Methods:</i></b> The approach identifies 9 resting-state networks and 45 ICs and generates a functional activation feature map that quantifies the spatial distribution, relative to an anatomical labeled atlas, of the z-scores of each IC across a cohort of 176 subjects. The cosine-similarity metric was used to classify unlabeled ICs based on the similarity to the spatial distribution of activation with the pregenerated feature map. The approach was tested on three fMRI datasets from the 1000 functional connectome projects, consisting of 280 subjects, that were not included in feature map generation. <b><i>Results:</i></b> The results demonstrate the effectiveness of the approach in classifying ICs based on their spatial features with an accuracy of better than 95%. <b><i>Conclusions:</i></b> The approach significantly reduces expert time and computation time required for labeling ICs, while improving reliability and accuracy. The spatio-functional relationship also provides an explainable relationship between the functional activation and the anatomically defined regions.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"319-326"},"PeriodicalIF":2.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141178938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Disrupted Dynamic Network Attribution Associated with Gait Disorder in Cerebral Small Vessel Disease.","authors":"Xia Zhou, Chaojuan Huang, Zhiwei Li, Mingxu Li, Wenwen Yin, Mengmeng Ren, Yating Tang, Jiabin Yin, Wenhui Zheng, Chao Zhang, Xueying Li, Ke Wan, Xiaoqun Zhu, Zhongwu Sun","doi":"10.1089/brain.2023.0092","DOIUrl":"10.1089/brain.2023.0092","url":null,"abstract":"<p><p><b><i>Background and Aims:</i></b> Previous research has focused on static functional connectivity in gait disorders caused by cerebral small vessel disease (CSVD), neglecting dynamic functional connections and network attribution. This study aims to investigate alterations in dynamic functional network connectivity (dFNC) and topological organization variance in CSVD-related gait disorders. <b><i>Methods:</i></b> A total of 85 patients with CSVD, including 41 patients with CSVD and gait disorders (CSVD-GD), 44 patients with CSVD and non-gait disorders (CSVD-NGD), and 32 healthy controls (HC), were enrolled in this study. Five networks composed of 10 independent components were selected using independent component analysis. Sliding time window and <i>k</i>-means clustering methods were used for dFNC analysis. The relationship between alterations in the dFNC properties and gait metrics was further assessed. <b><i>Results:</i></b> Three reproducible dFNC states were determined (State 1: sparsely connected, State 2: intermediate pattern, and State 3: strongly connected). CSVD-GD showed significantly higher fractional windows (FW) and mean dwell time (MDT) in State 1 compared with CSVD-NGD. Higher local efficiency variance was observed in the CSVD-GD group compared with HC, but no differences were found in the global efficiency comparison. Both the FW and MDT in State 1 were negatively correlated with gait speed and step length, and the relationship between MDT of State 1 and gait speed was mediated by overall cognition, information processing speed, and executive function. <b><i>Conclusions:</i></b> Our study uncovered abnormal dFNC indicators and variations in topological organization in CSVD-GD, offering potential early prediction indicators and freshening insights into the underlying pathogenesis of gait disturbances in CSVD.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"327-339"},"PeriodicalIF":2.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141315971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Particulate Matter Exposure and Default Mode Network Equilibrium During Early Adolescence.","authors":"Clara G Zundel, Samantha Ely, Cole Brokamp, Jeffrey R Strawn, Tanja Jovanovic, Patrick Ryan, Hilary A Marusak","doi":"10.1089/brain.2023.0072","DOIUrl":"10.1089/brain.2023.0072","url":null,"abstract":"<p><p><b><i>Background:</i></b> Air pollution exposure has been associated with adverse cognitive and mental health outcomes in children, adolescents, and adults, although youth may be particularly susceptible given ongoing brain development. However, the neurodevelopmental mechanisms underlying the associations among air pollution, cognition, and mental health remain unclear. We examined the impact of particulate matter (PM_2.5) on resting-state functional connectivity (rsFC) of the default mode network (DMN) and three key attention networks: dorsal attention, ventral attention, and cingulo-opercular. <b><i>Methods:</i></b> Longitudinal changes in rsFC within/between networks were assessed from baseline (9-10 years) to the 2-year follow-up (11-12 years) in 10,072 youth (<i>M ± SD</i> = 9.93 + 0.63 years; 49% female) from the Adolescent Brain Cognitive Development (ABCD^®) study. Annual ambient PM_2.5 concentrations from the 2016 calendar year were estimated using hybrid ensemble spatiotemporal models. RsFC was estimated using functional neuroimaging. Linear mixed models were used to test associations between PM_2.5 and change in rsFC over time while adjusting for relevant covariates (e.g., age, sex, race/ethnicity, parental education, and family income) and other air pollutants (O₃, NO₂). <b><i>Results:</i></b> A PM_2.5 × time interaction was significant for within-network rsFC of the DMN such that higher PM_2.5 concentrations were associated with a smaller increase in rsFC over time. Further, significant PM_2.5 × time interactions were observed for between-network rsFC of the DMN and all three attention networks, with varied directionality. <b><i>Conclusion:</i></b> PM_2.5 exposure was associated with alterations in the development and equilibrium of the DMN-a network implicated in self-referential processing-and anticorrelated attention networks, which may impact trajectories of cognitive and mental health symptoms across adolescence.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"307-318"},"PeriodicalIF":2.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11387001/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141178943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Probabilistic Tractography-Based Tremor Network Connectivity in Tremor Dominant Parkinson's Disease and Essential Tremor plus.","authors":"Shweta Prasad, Archith Rajan, Madhura Ingalhalikar, Rose Dawn Bharath, Jitender Saini, Pramod Kumar Pal","doi":"10.1089/brain.2023.0066","DOIUrl":"10.1089/brain.2023.0066","url":null,"abstract":"<p><p><b><i>Background:</i></b> The basal ganglia-thalamocortical (BGTC) and cerebello-thalamocortical (CTC) networks are implicated in tremor genesis; however, exact contributions across disorders have not been studied. <b><i>Objective:</i></b> Evaluate the structural connectivity of BGTC and CTC in tremor-dominant Parkinson's disease (TDPD) and essential tremor plus (ETP) with the aid of probabilistic tractography and graph theory analysis. <b><i>Methods:</i></b> Structural connectomes of the BGTC and CTC were generated by probabilistic tractography for TDPD (<i>n</i> = 25), ETP (ET with rest tremor, <i>n</i> = 25), and healthy control (HC, <i>n</i> = 22). The Brain Connectivity Toolbox was used for computing standard topological graph measures of segregation, integration, and centrality. Tremor severity was ascertained using the Fahn-Tolosa-Marin tremor rating scale (FTMRS). <b><i>Results:</i></b> There was no difference in total FTMRS scores. Compared with HC, TDPD had a lower global efficiency and characteristic path length. Abnormality in segregation, integration, and centrality of bilateral putamen, globus pallidus externa (GPe), and GP interna (GPi), with reduction of centrality of right caudate and cerebellar lobule 8, was observed. ETP showed reduction in segregation and integration of right GPe and GPi, ventrolateral posterior nucleus, and centrality of right putamen, compared with HC. Differences between TDPD and ETP were a reduction of strength of the right putamen, and lower clustering coefficient, local efficiency, and strength of the left GPi in TDPD. <b><i>Conclusions:</i></b> Contrary to expectations, TDPD and ETP may not be significantly different with regard to tremor pathogenesis, with definite overlaps. There may be fundamental similarities in network disruption across different tremor disorders with the same tremor activation patterns, along with disease-specific changes.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"340-350"},"PeriodicalIF":2.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141315972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advances in Understanding Brain Connectivity.","authors":"Jennifer L Whitwell, Steven Laureys","doi":"10.1089/brain.2024.0047","DOIUrl":"10.1089/brain.2024.0047","url":null,"abstract":"","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"305-306"},"PeriodicalIF":2.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141466142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}