Brain connectivity最新文献

{"title":"Neurobiological Dysfunctional Substrates for the Self-Medication Hypothesis in Adult Individuals with Attention-Deficit Hyperactivity Disorder and Cocaine Use Disorder: A Fluorine-18-Fluorodeoxyglucose Positron Emission Tomography Study.","authors":"Giulia Carli,&nbsp;Marco Cavicchioli,&nbsp;Anna Lisa Martini,&nbsp;Matteo Bruscoli,&nbsp;Antonella Mafredi,&nbsp;Luca Presotto,&nbsp;Christian Mazzeo,&nbsp;Stelvio Sestini,&nbsp;Daniela Perani","doi":"10.1089/brain.2022.0076","DOIUrl":"10.1089/brain.2022.0076","url":null,"abstract":"<p><p><b><i>Objectives:</i></b> Attention-deficit hyperactivity disorder (ADHD) in adulthood shows high co-occurrence rates with cocaine use disorder (CoUD). The self-medication hypothesis (SMH) provides a theoretical explanation for this comorbidity. This study investigates the neurobiological mechanisms that could support SMH in adult patients with attention-deficit hyperactivity disorder with cocaine use disorder (ADHD-CoUD). <b><i>Materials and Methods:</i></b> We included 19 ADHD<i>-</i>CoUD patients (84.2% male; age: 32.11 years [7.18]) and 16 CoUD patients (68.7% male; age: 36.63 years [8.12]). All subjects underwent a fluorine-18-fluorodeoxyglucose positron emission tomography (¹⁸F-FDG PET) brain scan. We tested brain metabolism differences between ADHD-CoUD and CoUD patients using voxel-based and regions of interest (ROIs)-based analyses. The correlation between dependence/abstinence duration and regional brain metabolism was also assessed in the two groups. Lastly, we investigated the integrity of brain metabolic connectivity of mesocorticolimbic and nigrostriatal dopaminergic systems, and large-scale brain networks involved in ADHD and addictions. <b><i>Results:</i></b> The voxel-wise and ROIs-based approaches showed that ADHD-CoUD patients had a lower metabolism in the thalamus and increased metabolism in the amygdala and parahippocampus, bilaterally, than CoUD subjects and healthy controls (HCs). Metabolism in the thalamus negatively correlated with years of dependence in ADHD-CoUD patients. Moreover, connectivity analyses revealed that ADHD-CoUD patients had a more preserved metabolic connectivity than CoUD patients in the dopaminergic networks and large-scale networks involved in self-regulation mechanisms of attention and behaviors (i.e., anterior default mode network [ADMN], executive network [ECN], and anterior salience network [aSAN]). <b><i>Conclusions:</i></b> We demonstrated distinct neuropathological substrates underlying substance-use behaviors in ADHD-CoUD and CoUD patients. Furthermore, we provided neurobiological evidence in support of SMH, demonstrating that ADHD-CoUD patients might experience short-term advantages of cocaine assumption (i.e., compensation of dopaminergic deficiency and related cognitive-behavioral deficits).</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"13 7","pages":"370-382"},"PeriodicalIF":3.4,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10601718","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":"Effect of Extremely Preterm Birth on Adolescent Brain Network Organization.","authors":"M Fiona Molloy,&nbsp;Emily J Yu,&nbsp;Whitney I Mattson,&nbsp;Kristen R Hoskinson,&nbsp;H Gerry Taylor,&nbsp;David E Osher,&nbsp;Eric E Nelson,&nbsp;Zeynep M Saygin","doi":"10.1089/brain.2022.0077","DOIUrl":"10.1089/brain.2022.0077","url":null,"abstract":"<p><p><b><i>Introduction:</i></b> Extremely preterm (EPT) birth, defined as birth at a gestational age (GA) <28 weeks, can have a lasting impact on cognition throughout the life span. Previous investigations reveal differences in brain structure and connectivity between infants born preterm and full-term (FT), but how does preterm birth impact the adolescent connectome? <b><i>Methods:</i></b> In this study, we investigate how EPT birth can alter broadscale network organization later in life by comparing resting-state functional magnetic resonance imaging connectome-based parcellations of the entire cortex in adolescents born EPT (<i>N</i> = 22) to age-matched adolescents born FT (GA ≥37 weeks, <i>N</i> = 28). We compare these parcellations to adult parcellations from previous studies and explore the relationship between an individual's network organization and behavior. <b><i>Results:</i></b> Primary (occipital and sensorimotor) and frontoparietal networks were observed in both groups. However, there existed notable differences in the limbic and insular networks. Surprisingly, the connectivity profile of the limbic network of EPT adolescents was more adultlike than the same network in FT adolescents. Finally, we found a relationship between adolescents' overall cognition score and their limbic network maturity. <b><i>Discussion:</i></b> Overall, preterm birth may contribute to the atypical development of broadscale network organization in adolescence and may partially explain the observed cognitive deficits.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"13 7","pages":"394-409"},"PeriodicalIF":3.4,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10585050","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:A Journal of Clinical Neurology, Neuroscience, & Neuroimaging</i> Advancing the Field of Neurology.","authors":"Paul Edison","doi":"10.1089/brain.2023.29053.editorial","DOIUrl":"10.1089/brain.2023.29053.editorial","url":null,"abstract":"","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"13 7","pages":"367-369"},"PeriodicalIF":3.4,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10589618","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":"Brain Connectivity: <i>A Journal of Clinical Neurology, Neuroscience, & Neuroimaging Advancing the Field of Neurology</i> Advances in Alzheimer's Disease.","authors":"Paul Edison","doi":"10.1089/brain.2023.29052.editorial","DOIUrl":"https://doi.org/10.1089/brain.2023.29052.editorial","url":null,"abstract":"","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"13 6","pages":"316-318"},"PeriodicalIF":3.4,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9986278","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 Functional Network Connectivity Among Cognitive Control Networks in the Progression of Alzheimer's Disease.","authors":"Mohammad S E Sendi, Elaheh Zendehrouh, Zening Fu, Jingyu Liu, Yuhui Du, Elizabeth Mormino, David H Salat, Vince D Calhoun, Robyn L Miller","doi":"10.1089/brain.2020.0847","DOIUrl":"10.1089/brain.2020.0847","url":null,"abstract":"<p><p><b><i>Background:</i></b> Alzheimer's disease (AD) is the most common age-related dementia that promotes a decline in memory, thinking, and social skills. The initial stages of dementia can be associated with mild symptoms, and symptom progression to a more severe state is heterogeneous across patients. Recent work has demonstrated the potential for functional network mapping to assist in the prediction of symptomatic progression. However, this work has primarily used static functional connectivity (sFC) from resting-state functional magnetic resonance imaging. Recently, dynamic functional connectivity (dFC) has been recognized as a powerful advance in functional connectivity methodology to differentiate brain network dynamics between healthy and diseased populations. <b><i>Methods:</i></b> Group independent component analysis was applied to extract 17 components within the cognitive control network (CCN) from 1385 individuals across varying stages of AD symptomology. We estimated dFC among 17 components within the CCN, followed by clustering the dFCs into 3 recurring brain states, and then estimated a hidden Markov model and the occupancy rate for each subject. Then, we investigated the link between CCN dFC features and AD progression. Also, we investigated the link between sFC and AD progression and compared its results with dFC results. <b><i>Results:</i></b> Progression of AD symptoms was associated with increases in connectivity within the middle frontal gyrus. Also, the very mild AD (vmAD) showed less connectivity within the inferior parietal lobule (in both sFC and dFC) and between this region and the rest of CCN (in dFC analysis). Also, we found that within-middle frontal gyrus connectivity increases with AD progression in both sFC and dFC results. Finally, comparing with vmAD, we found that the normal brain spends significantly more time in a state with lower within-middle frontal gyrus connectivity and higher connectivity between the hippocampus and the rest of CCN, highlighting the importance of assessing the dynamics of brain connectivity in this disease. <b><i>Conclusion:</i></b> Our results suggest that AD progress not only alters the CCN connectivity strength but also changes the temporal properties in this brain network. This suggests the temporal and spatial pattern of CCN as a biomarker that differentiates different stages of AD.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"13 6","pages":"334-343"},"PeriodicalIF":2.4,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10442683/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10043596","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":"Rosalind Franklin Society Proudly Announces the 2022 Award Recipient for <i>Brain Connectivity</i>.","authors":"Tara Chand","doi":"10.1089/brain.2023.29051.rfs2022","DOIUrl":"https://doi.org/10.1089/brain.2023.29051.rfs2022","url":null,"abstract":"","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"13 6","pages":"315"},"PeriodicalIF":3.4,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9961577","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":"Mass Spectrometry Imaging in Alzheimer's Disease.","authors":"Masaya Ikegawa, Nobuto Kakuda, Tomohiro Miyasaka, Yumiko Toyama, Takashi Nirasawa, Karolina Minta, Jörg Hanrieder","doi":"10.1089/brain.2022.0057","DOIUrl":"10.1089/brain.2022.0057","url":null,"abstract":"<p><p><b><i>Introduction:</i></b> Amyloid-beta (Aβ) pathology is the precipitating histopathological characteristic of Alzheimer's disease (AD). Although the formation of amyloid plaques in human brains is suggested to be a key factor in initiating AD pathogenesis, it is still not fully understood the upstream events that lead to Aβ plaque formation and its metabolism inside the brains. <b><i>Methods:</i></b> Matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) has been successfully introduced to study AD pathology in brain tissue both in AD mouse models and human samples. By using MALDI-MSI, a highly selective deposition of Aβ peptides in AD brains with a variety of cerebral amyloid angiopathy (CAA) involvement was observed. <b><i>Results:</i></b> MALDI-MSI visualized depositions of shorter peptides in AD brains; Aβ1-36 to Aβ1-39 were quite similarly distributed with Aβ1-40 as a vascular pattern, and deposition of Aβ1-42 and Aβ1-43 was visualized with a distinct senile plaque pattern distributed in parenchyma. Moreover, how MALDI-MSI covered <i>in situ</i> lipidomics of plaque pathology has been reviewed, which is of interest as aberrations in neuronal lipid biochemistry have been implicated in AD pathogenesis. <b><i>Discussion:</i></b> In this study, we introduce the methodological concepts and challenges of MALDI-MSI for the studies of AD pathogenesis. Diverse Aβ isoforms including various C- and N-terminal truncations in AD and CAA brain tissues will be visualized. Despite the close relationship between vascular and plaque Aβ deposition, the current strategy will define cross talk between neurodegenerative and cerebrovascular processes at the level of Aβ metabolism.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"13 6","pages":"319-333"},"PeriodicalIF":2.4,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10494909/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10207425","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":"Concordance of Intrinsic Brain Connectivity Measures Is Disrupted in Alzheimer's Disease.","authors":"Xiangliang Chen,&nbsp;Oezguer A Onur,&nbsp;Nils Richter,&nbsp;Ronja Fassbender,&nbsp;Hannes Gramespacher,&nbsp;Qumars Befahr,&nbsp;Boris von Reutern,&nbsp;Kim Dillen,&nbsp;Heidi I L Jacobs,&nbsp;Juraj Kukolja,&nbsp;Gereon R Fink,&nbsp;Julian Dronse","doi":"10.1089/brain.2020.0918","DOIUrl":"https://doi.org/10.1089/brain.2020.0918","url":null,"abstract":"<p><p><b><i>Background:</i></b> Recently, a new resting-state functional magnetic resonance imaging (rs-fMRI) measure to evaluate the concordance between different rs-fMRI metrics has been proposed and has not been investigated in Alzheimer's disease (AD). <b><i>Methods:</i></b> 3T rs-fMRI data were obtained from healthy young controls (YC, <i>n</i> = 26), healthy senior controls (SC, <i>n</i> = 29), and AD patients (<i>n</i> = 35). The fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity (ReHo), and degree centrality (DC) were analyzed, followed by the calculation of their concordance using Kendall's W for each brain voxel across time. Group differences in the concordance were compared globally, within seven intrinsic brain networks, and on a voxel-by-voxel basis with covariates of age, sex, head motion, and gray matter volume. <b><i>Results:</i></b> The global concordance was lowest in AD among the three groups, with similar differences for the single metrics. When comparing AD to SC, reductions of concordance were detected in each of the investigated networks apart from the limbic network. For SC in comparison to YC, lower global concordance without any network-level difference was observed. Voxel-wise analyses revealed lower concordance in the right middle temporal gyrus in AD compared to SC and lower concordance in the left middle frontal gyrus in SC compared to YC. Lower fALFF were observed in the right angular gyrus in AD in comparison to SC, but ReHo and DC showed no group differences. <b><i>Conclusions:</i></b> The concordance of resting-state measures differentiates AD from healthy aging and may represent a novel imaging marker in AD.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"13 6","pages":"344-355"},"PeriodicalIF":3.4,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9982586","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":"Hypermetabolic Cerebellar Connectome in Alzheimer's Disease.","authors":"Vinay Gupta, Samuel Booth, Ji Hyun Ko","doi":"10.1089/brain.2020.0937","DOIUrl":"10.1089/brain.2020.0937","url":null,"abstract":"<p><p><b><i>Introduction:</i></b> Regional hypermetabolism in Alzheimer's disease (AD), especially in the cerebellum, has been consistently observed but often neglected as an artefact produced by the commonly used proportional scaling procedure in the statistical parametric mapping. We hypothesize that the hypermetabolic regions are also important in disease pathology in AD. <b><i>Methods:</i></b> Using fluorodeoxyglucose (FDG)-positron emission tomography (PET) images from 88 AD subjects and 88 age-sex matched normal controls (NL) from the publicly available Alzheimer's Disease Neuroimaging Initiative database, we developed a general linear model-based classifier that differentiated AD patients from normal individuals (sensitivity = 87.50%, specificity = 82.95%). We constructed region-region group-wise correlation matrices and evaluated differences in network organization by using the graph theory analysis between AD and control subjects. <b><i>Results:</i></b> We confirmed that hypermetabolism found in AD is not an artefact by replicating it using white matter as the reference region. The role of the hypermetabolic regions has been further investigated by using the graph theory. The differences in betweenness centrality (BC) between AD and NL network were correlated with region weights of FDG PET-based AD classifier. In particular, the hypermetabolism in cerebellum was accompanied with higher BC. The brain regions with higher BC in AD network showed a progressive increase in FDG uptake over 2 years in prodromal AD patients (<i>n</i> = 39). <b><i>Discussion:</i></b> This study suggests that hypermetabolism found in AD may play an important role in forming the AD-related metabolic network. In particular, hypermetabolic cerebellar regions represent a good candidate for further investigation in altered network organization in AD.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"13 6","pages":"356-366"},"PeriodicalIF":2.4,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10494901/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10566181","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":"Static and Dynamic Functional Connectivity Alterations in Alzheimer's Disease and Neuropsychiatric Diseases.","authors":"Teppei Matsui,&nbsp;Ken-Ichiro Yamashita","doi":"10.1089/brain.2022.0044","DOIUrl":"https://doi.org/10.1089/brain.2022.0044","url":null,"abstract":"<p><p><b><i>Background:</i></b> To date, numerous studies have documented various alterations in resting brain activity in Alzheimer's disease (AD) and other neuropsychiatric diseases. In particular, disease-related alterations of functional connectivity (FC) in the resting state networks (RSN) have been documented. Altered FC in RSN is useful not only for interpreting the phenotype of diseases but also for diagnosing the diseases. More recently, several studies proposed the dynamics of resting-brain activity as a useful marker for detecting altered RSNs related to AD and other diseases. <b><i>Objectives:</i></b> In this article, we review recent studies exploring alterations of static and dynamic functional connectivity in AD and other neuropsychiatric diseases. We then discuss how to utilize and interpret dynamics of FC for studying resting brain activity in diseases. <b><i>Results:</i></b> In contrast to previous studies, which focused on FC calculated using an entire fMRI scan (static FC), newer studies focused on the temporal dynamics of FC within the scan (dynamic FC) to provide more sensitive measures to characterize RSNs. However, despite the increasing popularity of dynamic FC, several statistical investigations of dynamic FC cautioned that the results obtained in commonly used analyses for dynamic FC require careful interpretation. <b><i>Conclusions:</i></b> Although static and dynamic FC are likely to be a useful tool to detect altered RSN in patients affected by AD and other neuropsychiatric disorders, interpretation of altered dynamic FC in patients require special care. Impact statement We review recent studies of static and dynamic functional connectivity (dFC) in Alzheimer's disease and discuss interpretation of dFC.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"13 5","pages":"307-314"},"PeriodicalIF":3.4,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10019566","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}