Brain connectivity最新文献

{"title":"Increased Segregation in Functional Connectivity Networks When Watching Unpleasant Arousing Videos: A Generalized Psychophysiological Interaction Analysis.","authors":"Yuqian Ni, Xia Zheng, Richard Betzel, Thomas W James","doi":"10.1089/brain.2023.0048","DOIUrl":"10.1089/brain.2023.0048","url":null,"abstract":"<p><p><b><i>Background:</i></b> Properties of functional connectivity (FC), such as network integration and segregation, are shown to be associated with various human behaviors. For example, Godwin et al. and Sun et al. found increased integration with attention allocation, whereas Cohen and D'Esposito and Shine et al. observed increased segregation with simple motor tasks. The current study investigated how viewing video clips with different valence and arousal influenced integration-segregation properties in task-based FC networks. <b><i>Methods:</i></b> We analyzed an open dataset collected by Kim et al. We performed a generalized psychophysiological interaction (gPPI) analysis paired with network analysis and community detection to investigate changes in brain network dynamics when people watched four types of videos that differed by affective valence (unpleasant or pleasant) and arousal (arousing or calm). <b><i>Results:</i></b> Results showed that unpleasant arousing videos produced greater FC deviation from the baseline (task-induced FC deviation [tiFCd]) and perturbed the brain into a more segregated state than other kinds of video. Increased segregation was only observed in association systems, not sensorimotor systems. <b><i>Discussion:</i></b> Unpleasant arousing content perturbed the brain to a functionally distinct state from the other three types of affective videos. We suggest that the change in brain state was related to people disengaging from the unpleasant arousing content or, alternatively, staying alert while exposed to unpleasant arousing stimuli. The study also added to our understanding of how combining task-based gPPI analysis with community detection methods and network segregation measures can advance our knowledge of the links between behavior and brain state changes. Impact statement Network integration and segregation is an important property of the human brain. We address the question of how affective stimuli influence brain dynamics from a functional connectivity (FC) network integration-segregation perspective. By conducting a whole-brain generalized psychophysiological interaction (gPPI) analysis paired with community detection methods, we found that highly aversive video content induced significant FC changes and perturbed the brain to a more segregated state.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"92-106"},"PeriodicalIF":3.4,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139541375","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":"A Method to Estimate Longitudinal Change Patterns in Functional Network Connectivity of the Developing Brain Relevant to Psychiatric Problems, Cognition, and Age.","authors":"Rekha Saha, Debbrata K Saha, Md Abdur Rahaman, Zening Fu, Jingyu Liu, Vince D Calhoun","doi":"10.1089/brain.2023.0040","DOIUrl":"10.1089/brain.2023.0040","url":null,"abstract":"&lt;p&gt;&lt;p&gt;&lt;b&gt;&lt;i&gt;Aim:&lt;/i&gt;&lt;/b&gt; To develop an approach to evaluate multiple overlapping brain functional change patterns (FCPs) in functional network connectivity (FNC) and apply to study developmental changes in brain function. &lt;b&gt;&lt;i&gt;Introduction:&lt;/i&gt;&lt;/b&gt; FNC, the network analog of functional connectivity (FC), is commonly used to capture the intrinsic functional relationships among brain networks. Ongoing research on longitudinal changes of intrinsic FC across whole-brain functional networks has proven useful for characterizing age-related changes, but to date, there has been little focus on capturing multivariate patterns of FNC change with brain development. &lt;b&gt;&lt;i&gt;Methods:&lt;/i&gt;&lt;/b&gt; In this article, we introduce a novel approach to evaluate multiple overlapping FCPs by utilizing FNC matrices. We computed FNC matrices from the large-scale Adolescent Brain Cognitive Development data using fully automated spatially constrained independent component analysis (ICA). We next evaluated changes in these patterns for a 2-year period using a second-level ICA on the FNC change maps. &lt;b&gt;&lt;i&gt;Results:&lt;/i&gt;&lt;/b&gt; Our proposed approach reveals several highly structured (modular) FCPs and significant results including strong brain FC between visual and sensorimotor domains that increase with age. We also find several FCPs that are associated with longitudinal changes of psychiatric problems, cognition, and age in the developing brain. Interestingly, FCP cross-covariation, reflecting coupling between maximally independent FCPs, also shows significant differences between upper and lower quartile loadings for longitudinal changes in age, psychiatric problems, and cognition scores, as well as baseline age in the developing brain. FCP patterns and results were also found to be highly reliable based on analysis of data collected in a separate scan session. &lt;b&gt;&lt;i&gt;Conclusion:&lt;/i&gt;&lt;/b&gt; In sum, our results show evidence of consistent multivariate patterns of functional change in emerging adolescents and the proposed approach provides a useful and general tool to evaluate covarying patterns of whole-brain functional changes in longitudinal data. Impact statement In this article, we introduce a novel approach utilizing functional network connectivity (FNC) matrices to estimate multiple overlapping brain functional change patterns (FCPs). The findings demonstrate several well-structured FCPs that exhibit significant changes for a 2-year period, particularly in the functional connectivity between the visual and sensorimotor domains. In addition, we discover several FCPs that are associated with psychopathology, cognition, and age. Finally, our proposed approach for studying age-related FCPs represents a pioneering method that provides a valuable tool for assessing interconnected patterns of whole-brain functional changes in longitudinal data and may be useful to study change over time with applicability to many other areas, including the study of longitudinal changes within diagnostic g","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"130-140"},"PeriodicalIF":2.4,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10954605/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139671294","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":"Coupling Between Human Brain Cortical Thickness and Glucose Metabolism from Regional to Connective Level: A Positron Emission Tomography/Magnetic Resonance Imaging Study.","authors":"Qi Huang, Yihong Yang, Na Qi, Yihui Guan, Jun Zhao, Fengchun Hua, Shuhua Ren, Fang Xie","doi":"10.1089/brain.2023.0070","DOIUrl":"10.1089/brain.2023.0070","url":null,"abstract":"<p><p><b><i>Background:</i></b> Balance between brain structure and function is implicated in aging and many brain disorders. This study aimed to investigate the coupling between brain structure and function using ¹⁸F-fludeoxyglucose positron emission tomography (PET)/magnetic resonance imaging (MRI). <b><i>Methods:</i></b> One hundred thirty-eight subjects who underwent brain ¹⁸F-FDG PET/MRI were recruited. The structural and functional coupling at the regional level was explored by calculating within-subject Spearman's correlation between glucose metabolism (GluM) and cortical thickness (CTh) across the cortex for each subject, which was then correlated with age to explore its physiological effects. Then, subjects were divided into groups of middle-aged and young adults and older adults (OAs); structural connectivity (SC) based on CTh and functional connectivity (FC) based on GluM were constructed for the two groups, respectively, followed by exploring the connective-level structural and functional coupling on SC and FC matrices. The global and local efficiency values of the brain SC and FC were also evaluated. <b><i>Results:</i></b> Of the subjects, 97.83% exhibited a significant negative correlation between regional CTh and GluM (<i>r</i> = -0.24 to -0.71, <i>p</i> < 0.05, FDR correction), and this CTh-GluM correlation was negatively correlated with age (<i>R</i> = -0.35, <i>p</i> < 0.001). For connectivity matrices, many regions showed positive correlation between SC and FC, especially in the OA group. Besides, FC exhibited denser connections than SC, resulting in both higher global and local efficiency, but lower global efficiency when the network size was corrected. <b><i>Conclusions:</i></b> This study found couplings between CTh and GluM at both regional and connective levels, which reflected the aging progress, and might provide new insight into brain disorders. Impact statement The intricate interplay between brain structures and functions plays a pivotal role in unraveling the complexities inherent in the aging process and the pathogenesis of neurological disorders. This study revealed that 97.83% subjects showed negative correlation between the brain's regional cortical thickness and glucose metabolism, while at the connective level, many regions showed positive correlations between structural and functional connectivity. The observed coupling at the regional and connective levels reflected physiological progress, such as aging, and provides insights into the brain mechanisms and potential implications for the diagnosis and treatment of brain disorders.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"122-129"},"PeriodicalIF":3.4,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139671295","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":"Changes in Resting-State Networks in Children with Growth Hormone Deficiency.","authors":"Ju-Rong Ding, Chenyu Feng, Hui Zhang, Yuan Li, Zhiling Tang, Qiang Chen, Xin Ding, Mei Wang, Zhongxiang Ding","doi":"10.1089/brain.2023.0059","DOIUrl":"10.1089/brain.2023.0059","url":null,"abstract":"<p><p><b><i>Purpose:</i></b> Growth hormone deficiency (GHD) refers to the partial or complete lack of growth hormone. Short stature and slow growth are characteristic of patients with GHD. Previous neuroimaging studies have suggested that GHD may cause cognitive and behavioral impairments in patients. Resting-state networks (RSNs) are regions of the brain that exhibit synchronous activity and are closely related to our cognition and behavior. Therefore, the purpose of the current study was to explore cognitive and behavioral abnormalities in children with GHD by investigating changes in RSNs. <b><i>Methods:</i></b> Resting-state functional magnetic resonance imaging (rs-fMRI) data of 26 children with GHD and 15 healthy controls (HCs) were obtained. Independent component analysis was used to identify seven RSNs from rs-fMRI data. Group differences in RSNs were estimated using two-sample <i>t</i>-tests. Correlation analysis was employed to investigate the associations among the areas of difference and clinical measures. <b><i>Results:</i></b> Compared with HCs, children with GHD had significant differences in the salience network (SN), default mode network (DMN), language network (LN), and sensorimotor network (SMN). Moreover, within the SN, the functional connectivity (FC) value of the right posterior supramarginal gyrus was negatively correlated with the adrenocorticotropic hormone and the FC value of the left anterior inferior parietal gyrus was positively correlated with insulin-like growth factor 1. <b><i>Conclusions:</i></b> These results suggest that alterations in RSNs may account for abnormal cognition and behavior in children with GHD, such as decreased motor function, language withdrawal, anxiety, and social anxiety. These findings provide neuroimaging support for uncovering the pathophysiological mechanisms of GHD in children. Impact statement Children with growth hormone deficiency (GHD) generally experience cognitive and behavioral abnormalities. However, there are few neuroimaging studies on children with GHD. Moreover, prior research has not investigated the aberrant brain function in patients with GHD from the perspective of brain functional networks. Therefore, this study employed the independent component analysis method to investigate alterations within seven commonly observed resting-state networks due to GHD. The results showed that children with GHD had significant differences in the salience network, default mode network, language network, and sensorimotor network. This provides neuroimaging support for revealing the pathophysiological mechanisms of GHD in children.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"84-91"},"PeriodicalIF":3.4,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139541217","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":"<i>Brain Connectivity:</i> <i>A Journal of Clinical Neurology, Neuroscience, & Neuroimaging</i>.","authors":"Paul Edison","doi":"10.1089/brain.2024.29060.editorial","DOIUrl":"10.1089/brain.2024.29060.editorial","url":null,"abstract":"","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"14 2","pages":"81-83"},"PeriodicalIF":3.4,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140157491","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":"Acknowledgment of Reviewers 2023.","authors":"","doi":"10.1089/brain.2023.29058.ack","DOIUrl":"https://doi.org/10.1089/brain.2023.29058.ack","url":null,"abstract":"","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"14 1","pages":"80"},"PeriodicalIF":3.4,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139929976","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":"Attention Please! Unravelling the Link Between Brain Network Connectivity and Cognitive Attention Following Acquired Brain Injury: A Systematic Review of Structural and Functional Measures.","authors":"Athena Stein, Jacob R Thorstensen, Jonathan M Ho, Daniel P Ashley, Kartik K Iyer, Karen M Barlow","doi":"10.1089/brain.2023.0067","DOIUrl":"10.1089/brain.2023.0067","url":null,"abstract":"<p><p>Traumatic brain injury (TBI) and stroke are the most common causes of acquired brain injury (ABI), annually affecting 69 million and 15 million people, respectively. Following ABI, the relationship between brain network disruption and common cognitive issues including attention dysfunction is heterogenous. Using PRISMA guidelines, we systematically reviewed 43 studies published by February 2023 that reported correlations between attention and connectivity. Across all ages and stages of recovery, following TBI, greater attention was associated with greater structural efficiency within/between executive control network (ECN), salience network (SN), and default mode network (DMN) and greater functional connectivity (fc) within/between ECN and DMN, indicating DMN interference. Following stroke, greater attention was associated with greater structural connectivity (sc) within ECN; or greater fc within the dorsal attention network (DAN). In childhood ABI populations, decreases in structural network segregation were associated with greater attention. Longitudinal recovery from TBI was associated with normalization of DMN activity, and in stroke, normalization of DMN and DAN activity. Results improve clinical understanding of attention-related connectivity changes after ABI. Recommendations for future research include increased use of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) to measure connectivity at the point of care, standardized attention and connectivity outcome measures and analysis pipelines, detailed reporting of patient symptomatology, and casual analysis of attention-related connectivity using brain stimulation.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"4-38"},"PeriodicalIF":2.4,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138450817","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 Feeling of Time Passing Is Associated with Recurrent Sustained Activity and Theta Rhythms Across the Cortex.","authors":"Emma M Millon, Ali E Haddad, Han Yan M Chang, Laleh Najafizadeh, Tracey J Shors","doi":"10.1089/brain.2023.0010","DOIUrl":"10.1089/brain.2023.0010","url":null,"abstract":"<p><p><b><i>Introduction:</i></b> We are constantly estimating how much time has passed, and yet know little about the brain mechanisms through which this process occurs. In this pilot study, we evaluated so-called subjective time estimation with the temporal bisection task, while recording brain activity from electroencephalography (EEG). <b><i>Methods:</i></b> Nine adult participants were trained to distinguish between two durations of visual stimuli as either \"short\" (400 msec) or \"long\" (1600 msec). They were then presented with stimulus durations in between the long and short stimuli. EEG data from 128 electrodes were examined with a novel analytical method that identifies segments of sustained cortical activity during the task. <b><i>Results:</i></b> Participants tended to categorize intermediate durations as \"long\" more frequently than \"short\" and were thus experiencing time as moving faster while overestimating the amount of time passing. Their mean bisection point (during which frequency of selecting short vs. long is equal) was closer to the geometric mean of task stimuli (800 msec) rather than the arithmetic mean (1000 msec). In contrast, sustained brain activity occurred closer to the arithmetic mean. The recurrence rate of this activity was highly related to the bisection point, especially when analyzed within naturally occurring theta oscillations (4-8 Hz) (<i>r</i> = -0.90). <b><i>Discussion:</i></b> Sustained activity across the cortex within the theta range may reflect temporal durations, whereas its repeated appearance relates to the subjective feeling of time passing.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"39-47"},"PeriodicalIF":3.4,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138450818","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":"Dysregulated Salience Network Control over Default-Mode and Central-Executive Networks in Schizophrenia Revealed Using Stochastic Dynamical Causal Modeling.","authors":"Deepa S Thakuri, Puskar Bhattarai, Dean F Wong, Ganesh B Chand","doi":"10.1089/brain.2023.0054","DOIUrl":"10.1089/brain.2023.0054","url":null,"abstract":"<p><p><b><i>Introduction:</i></b> Neuroimaging studies suggest that the human brain consists of intrinsically organized, large-scale neural networks. Among these networks, the interplay among the default-mode network (DMN), salience network (SN), and central-executive network (CEN) has been widely used to understand the functional interaction patterns in health and disease. This triple network model suggests that the SN causally controls over the DMN and CEN in healthy individuals. This interaction is often referred to as SN's dynamic regulating mechanism. However, such interactions are not well understood in individuals with schizophrenia. <b><i>Methods:</i></b> In this study, we leveraged resting-state functional magnetic resonance imaging data from schizophrenia (<i>n</i> = 67) and healthy controls (<i>n</i> = 81) and evaluated the directional functional interactions among DMN, SN, and CEN using stochastic dynamical causal modeling methodology. <b><i>Results:</i></b> In healthy controls, our analyses replicated previous findings that SN regulates DMN and CEN activities (Mann-Whitney <i>U</i> test; <i>p</i> < 10^-8). In schizophrenia, however, our analyses revealed a disrupted SN-based controlling mechanism over the DMN and CEN (Mann-Whitney <i>U</i> test; <i>p</i> < 10^-16). <b><i>Conclusions:</i></b> These results indicate that the disrupted controlling mechanism of SN over the other two neural networks may be a candidate neuroimaging phenotype in schizophrenia.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"70-79"},"PeriodicalIF":2.4,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10890948/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139073347","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":"<i>Brain Connectivity:</i> <i>A Journal of Clinical Neurology, Neuroscience, & Neuroimaging</i>.","authors":"Paul Edison","doi":"10.1089/brain.2024.29059.editorial","DOIUrl":"10.1089/brain.2024.29059.editorial","url":null,"abstract":"","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"14 1","pages":"1-3"},"PeriodicalIF":3.4,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139929975","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}