Brain connectivity最新文献_第3页

Assessment of hyperacute cerebral ischemia using laser speckle contrast imaging. 利用激光斑点对比成像评估超急性脑缺血。

IF 3.4 3区医学

Brain connectivity Pub Date : 2024-09-18 DOI: 10.1089/brain.2024.0026

Bochao Niu,Guan Sihai,Hongyan Gong,Peng Hu,Pushti Shah,Xiqin Liu,Yang Xia,Dezhong Yao,Benjamin Klugah-Brown,Bharat B Biswal

{"title":"Assessment of hyperacute cerebral ischemia using laser speckle contrast imaging.","authors":"Bochao Niu,Guan Sihai,Hongyan Gong,Peng Hu,Pushti Shah,Xiqin Liu,Yang Xia,Dezhong Yao,Benjamin Klugah-Brown,Bharat B Biswal","doi":"10.1089/brain.2024.0026","DOIUrl":"https://doi.org/10.1089/brain.2024.0026","url":null,"abstract":"Accurate diagnosis of cerebral ischemia severity is crucial for clinical decision-making. Laser speckle contrast imaging based cerebral blood flow imaging can help assess the severity of cerebral ischemia by monitoring changes in blood flow. In this study, we simulated hyperacute ischemia in rats, isolating arterial and venous flow-related signals from cortical vasculature. Pearson correlation was used to examine the correlation between damaged vessels. Granger causality analysis was utilized to investigate causality correlation in ischemic vessels. Resting state analysis revealed a negative Pearson correlation between regional arteries and veins. Following cerebral ischemia induction, a positive artery-vein correlation emerged, which vanished after blood flow reperfusion. Granger causality analysis demonstrating enhanced causality coefficients for middle artery-vein pairs during occlusion, with a stronger left-right arterial effect than that of right-left, which persisted after reperfusion. These processing approaches amplify the understanding of cerebral ischemic images, promising potential future diagnostic advancements.","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"196 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142247327","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}

引用次数: 0

Associations Between Changes in Psychological Resilience and Resting-State Functional Connectivity Throughout Pediatric Concussion Recovery. 小儿脑震荡康复过程中心理复原力变化与静息状态功能连接性之间的关系

IF 2.4 3区医学

Brain connectivity Pub Date : 2024-09-01 Epub Date: 2024-07-12 DOI: 10.1089/brain.2023.0096

Olivier Brown, Zhuo Fang, Andra Smith, Katherine Healey, Roger Zemek, Andrée-Anne Ledoux

{"title":"Associations Between Changes in Psychological Resilience and Resting-State Functional Connectivity Throughout Pediatric Concussion Recovery.","authors":"Olivier Brown, Zhuo Fang, Andra Smith, Katherine Healey, Roger Zemek, Andrée-Anne Ledoux","doi":"10.1089/brain.2023.0096","DOIUrl":"10.1089/brain.2023.0096","url":null,"abstract":"Purpose: This study investigated the association between psychological resilience and resting-state network functional connectivity of three major brain networks in pediatric concussion. Methods: This was a substudy of a randomized controlled trial, recruiting children with concussion and orthopedic injury. Participants completed the Connor-Davidson Resilience 10 Scale and underwent magnetic resonance imaging at 72 h and 4-weeks postinjury. We explored associations between resilience and connectivity with the default mode network (DMN), central executive network (CEN), and salience network (SN) at both timepoints and also any change that occurred over time. We also explored associations between resilience and connectivity within each network. Results: A total of 67 children with a concussion (median age = 12.87 [IQR: 11.79-14.36]; 46% female) and 30 with orthopedic injury (median age = 12.27 [IQR: 11.19-13.94]; 40% female) were included. Seed-to-voxel analyses detected a positive correlation between 72-h resilience and CEN connectivity in the concussion group. Group moderated associations between resilience and SN connectivity at 72 h, as well as resilience and DMN connectivity over time. Regions-of-interest analyses identified group as a moderator of longitudinal resilience and within-DMN connectivity. Conclusions: These results suggest that neural recovery from concussion could be reliant on resilience. Resilience was related to functional connectivity with three of the main networks in the brain that are often impacted by concussion. Improving resilience might be investigated as a modifiable variable in children as both a protective and restorative in the context of concussion. Clinical Trial Registration Identifier: NCT05105802. PedCARE+MRI team (see Supplementary Appendix S1).","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"357-368"},"PeriodicalIF":2.4,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141315970","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}

引用次数: 0

Call for Papers for Special Issue on Brain-Computer Interfaces. 脑机接口特刊征稿启事。

IF 2.4 3区医学

Brain connectivity Pub Date : 2024-09-01 DOI: 10.1089/brain.2024.14072.cfp

Jianjun Meng, Christoph Guger

引用次数: 0

Acute Exercise Improves Large-Scale Brain Network Segregation in Healthy Older Adults. 急性运动可改善健康老年人的大规模脑网络分隔。

IF 2.4 3区医学

Brain connectivity Pub Date : 2024-09-01 Epub Date: 2024-07-11 DOI: 10.1089/brain.2024.0003

Yash Kommula, Daniel D Callow, Jeremy J Purcell, J Carson Smith

{"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":"Introduction: 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. Methods: 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). Results: We observed that after acute exercise, there was greater segregation between SAL and DMN, as well as greater segregation between SAL and ARN. Conclusion: 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.","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}

引用次数: 0

Differences Between Resting-State fMRI BOLD Variability and Default Mode Network Connectivity in Healthy Older and Younger Adults. 健康老年人和年轻人静息状态 fMRI BOLD 变异性与默认模式网络连接性之间的差异。

IF 2.4 3区医学

Brain connectivity Pub Date : 2024-09-01 Epub Date: 2024-07-30 DOI: 10.1089/brain.2023.0078

Vanessa Scarapicchia, Heather Kwan, Alexis Czippel, Jodie R Gawryluk

{"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":"Background: 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. Methods: Thirty-four healthy participants were separated into a younger adult group (age 25-35, n = 17) and an older adult group (age 65+, n = 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. Results: 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. Conclusion: 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.","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}

引用次数: 0

Resting-State Network Analysis Reveals Altered Functional Brain Connectivity in Essential Tremor. 静息态网络分析揭示本质性震颤的大脑功能连接性改变

IF 2.4 3区医学

Brain connectivity Pub Date : 2024-09-01 Epub Date: 2024-07-25 DOI: 10.1089/brain.2024.0004

Sheng-Min Huang, Cheung-Ter Ong, Yu-Ching Huang, Nan-Hao Chen, Ting-Kai Leung, Chun-Ying Shen, Li-Wei Kuo

{"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":"Introduction: 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. Methods: 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. Results: Comparison of inter-network connectivity indicated a decreased connectivity between default mode network and ventral attention network in the ET group (p < 0.05). Differences in functional activity (assessed by amplitude of low-frequency fluctuation, ALFF) were found in several brain regions participating in various RSNs (p < 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). Conclusion: 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.","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}

引用次数: 0

The Interest and Usefulness of Resting State fMRI in Brain Connectivity Research. 静息状态 fMRI 在大脑连接性研究中的兴趣和作用。

IF 2.4 3区医学

Brain connectivity Pub Date : 2024-09-01 Epub Date: 2024-08-07 DOI: 10.1089/brain.2024.0052

Roxane Hoyer, Steven Laureys

引用次数: 0

Rosalind Franklin Society Proudly Announces the 2023 Award Recipient for Brain Connectivity. 罗莎琳德-富兰克林学会自豪地宣布 2023 年大脑连接奖获得者。

IF 2.4 3区医学

Brain connectivity Pub Date : 2024-09-01 DOI: 10.1089/brain.2024.59245.rfs2023

Liara Rizzi

引用次数: 0

Atlas-Based Labeling of Resting-State fMRI. 基于图谱的静息状态 fMRI 标记。

IF 2.4 3区医学

Brain connectivity Pub Date : 2024-08-01 Epub Date: 2024-07-10 DOI: 10.1089/brain.2023.0080

Hrishikesh Kambli, Alberto Santamaria-Pang, Ivan Tarapov, Elham Beheshtian, Licia P Luna, Haris Sair, Craig Jones

{"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":"Background: 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. Methods: 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. Results: The results demonstrate the effectiveness of the approach in classifying ICs based on their spatial features with an accuracy of better than 95%. Conclusions: 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.","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}

引用次数: 0

Disrupted Dynamic Network Attribution Associated with Gait Disorder in Cerebral Small Vessel Disease. 与脑小血管疾病步态障碍相关的动态网络归因紊乱。

IF 2.4 3区医学

Brain connectivity Pub Date : 2024-08-01 Epub Date: 2024-07-12 DOI: 10.1089/brain.2023.0092

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

{"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":"Background and Aims: 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. Methods: 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 k-means clustering methods were used for dFNC analysis. The relationship between alterations in the dFNC properties and gait metrics was further assessed. Results: 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. Conclusions: 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.","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}

引用次数: 0