Network neuroscience (Cambridge, Mass.)最新文献

Path analysis: A method to estimate altered pathways in time-varying graphs of neuroimaging data. 路径分析:在神经影像数据的时变图中估计改变路径的一种方法。

IF 4.7

Network neuroscience (Cambridge, Mass.) Pub Date : 2022-07-01 DOI: 10.1162/netn_a_00247

Haleh Falakshahi, Hooman Rokham, Zening Fu, Armin Iraji, Daniel H Mathalon, Judith M Ford, Bryon A Mueller, Adrian Preda, Theo G M van Erp, Jessica A Turner, Sergey Plis, Vince D Calhoun

{"title":"Path analysis: A method to estimate altered pathways in time-varying graphs of neuroimaging data.","authors":"Haleh Falakshahi, Hooman Rokham, Zening Fu, Armin Iraji, Daniel H Mathalon, Judith M Ford, Bryon A Mueller, Adrian Preda, Theo G M van Erp, Jessica A Turner, Sergey Plis, Vince D Calhoun","doi":"10.1162/netn_a_00247","DOIUrl":"https://doi.org/10.1162/netn_a_00247","url":null,"abstract":"Graph-theoretical methods have been widely used to study human brain networks in psychiatric disorders. However, the focus has primarily been on global graphic metrics with little attention to the information contained in paths connecting brain regions. Details of disruption of these paths may be highly informative for understanding disease mechanisms. To detect the absence or addition of multistep paths in the patient group, we provide an algorithm estimating edges that contribute to these paths with reference to the control group. We next examine where pairs of nodes were connected through paths in both groups by using a covariance decomposition method. We apply our method to study resting-state fMRI data in schizophrenia versus controls. Results show several disconnectors in schizophrenia within and between functional domains, particularly within the default mode and cognitive control networks. Additionally, we identify new edges generating additional paths. Moreover, although paths exist in both groups, these paths take unique trajectories and have a significant contribution to the decomposition. The proposed path analysis provides a way to characterize individuals by evaluating changes in paths, rather than just focusing on the pairwise relationships. Our results show promise for identifying path-based metrics in neuroimaging data.","PeriodicalId":520719,"journal":{"name":"Network neuroscience (Cambridge, Mass.)","volume":" ","pages":"634-664"},"PeriodicalIF":4.7,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9531579/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33493322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Normalization effect of levodopa on hierarchical brain function in Parkinson's disease. 左旋多巴对帕金森病分层脑功能的正常化作用。

IF 4.7

Network neuroscience (Cambridge, Mass.) Pub Date : 2022-06-01 DOI: 10.1162/netn_a_00232

Tao Guo, Min Xuan, Cheng Zhou, Jingjing Wu, Ting Gao, Xueqin Bai, Xiaocao Liu, Luyan Gu, Ruiqi Liu, Zhe Song, Quanquan Gu, Peiyu Huang, Jiali Pu, Baorong Zhang, Xiaojun Xu, Xiaojun Guan, Minming Zhang

{"title":"Normalization effect of levodopa on hierarchical brain function in Parkinson's disease.","authors":"Tao Guo, Min Xuan, Cheng Zhou, Jingjing Wu, Ting Gao, Xueqin Bai, Xiaocao Liu, Luyan Gu, Ruiqi Liu, Zhe Song, Quanquan Gu, Peiyu Huang, Jiali Pu, Baorong Zhang, Xiaojun Xu, Xiaojun Guan, Minming Zhang","doi":"10.1162/netn_a_00232","DOIUrl":"https://doi.org/10.1162/netn_a_00232","url":null,"abstract":"Hierarchical brain organization, in which the rich club and diverse club situate in core position, is critical for global information integration in the human brain network. Parkinson's disease (PD), a common movement disorder, has been conceptualized as a network disorder. Levodopa is an effective treatment for PD. Whether there is a functional divergence in the hierarchical brain system under PD pathology, and how this divergence is regulated by immediate levodopa therapy, remains unknown. We constructed a functional network in 61 PD patients and 89 normal controls and applied graph theoretical analyses to examine the neural mechanism of levodopa short response from the perspective of brain hierarchical configuration. The results revealed the following: (a) PD patients exhibited disrupted function within rich-club organization, while the diverse club preserved function, indicating a differentiated brain topological organization in PD. (b) Along the rich-club derivate hierarchical system, PD patients showed impaired network properties within rich-club and feeder subnetworks, and decreased nodal degree centrality in rich-club and feeder nodes, along with increased nodal degree in peripheral nodes, suggesting distinct functional patterns in different types of nodes. And (c) levodopa could normalize the abnormal network architecture of the rich-club system. This study provides evidence for levodopa effects on the hierarchical brain system with divergent functions.","PeriodicalId":520719,"journal":{"name":"Network neuroscience (Cambridge, Mass.)","volume":" ","pages":"552-569"},"PeriodicalIF":4.7,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9208001/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40224575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Structure-function coupling as a correlate and potential biomarker of cognitive impairment in multiple sclerosis. 结构-功能耦合作为多发性硬化症认知障碍的相关和潜在生物标志物。

IF 4.7

Network neuroscience (Cambridge, Mass.) Pub Date : 2022-06-01 DOI: 10.1162/netn_a_00226

Shanna D Kulik, Ilse M Nauta, Prejaas Tewarie, Ismail Koubiyr, Edwin van Dellen, Aurelie Ruet, Kim A Meijer, Brigit A de Jong, Cornelis J Stam, Arjan Hillebrand, Jeroen J G Geurts, Linda Douw, Menno M Schoonheim

{"title":"Structure-function coupling as a correlate and potential biomarker of cognitive impairment in multiple sclerosis.","authors":"Shanna D Kulik, Ilse M Nauta, Prejaas Tewarie, Ismail Koubiyr, Edwin van Dellen, Aurelie Ruet, Kim A Meijer, Brigit A de Jong, Cornelis J Stam, Arjan Hillebrand, Jeroen J G Geurts, Linda Douw, Menno M Schoonheim","doi":"10.1162/netn_a_00226","DOIUrl":"https://doi.org/10.1162/netn_a_00226","url":null,"abstract":"Multiple sclerosis (MS) features extensive connectivity changes, but how structural and functional connectivity relate, and whether this relation could be a useful biomarker for cognitive impairment in MS is unclear. This study included 79 MS patients and 40 healthy controls (HCs). Patients were classified as cognitively impaired (CI) or cognitively preserved (CP). Structural connectivity was determined using diffusion MRI and functional connectivity using resting-state magnetoencephalography (MEG) data (theta, alpha1, and alpha2 bands). Structure-function coupling was assessed by correlating modalities, and further explored in frequency bands that significantly correlated with whole-brain structural connectivity. Functional correlates of short- and long-range structural connections (based on tract length) were then specifically assessed. Receiving operating curve analyses were performed on coupling values to identify biomarker potential. Only the theta band showed significant correlations between whole-brain structural and functional connectivity (rho = -0.26, p = 0.023, only in MS). Long-range structure-function coupling was stronger in CI patients compared to HCs (p = 0.005). Short-range coupling showed no group differences. Structure-function coupling was not a significant classifier of cognitive impairment for any tract length (short-range area under the curve (AUC) = 0.498, p = 0.976, long-range AUC = 0.611, p = 0.095). Long-range structure-function coupling was stronger in CI MS compared to HCs, but more research is needed to further explore this measure as biomarkers in MS.","PeriodicalId":520719,"journal":{"name":"Network neuroscience (Cambridge, Mass.)","volume":" ","pages":"339-356"},"PeriodicalIF":4.7,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9208024/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40224577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Minimum spanning tree analysis of brain networks: A systematic review of network size effects, sensitivity for neuropsychiatric pathology, and disorder specificity. 脑网络的最小生成树分析:对网络大小效应、神经精神病理敏感性和疾病特异性的系统回顾。

IF 4.7

Network neuroscience (Cambridge, Mass.) Pub Date : 2022-06-01 DOI: 10.1162/netn_a_00245

N Blomsma, B de Rooy, F Gerritse, R van der Spek, P Tewarie, A Hillebrand, W M Otte, C J Stam, E van Dellen

{"title":"Minimum spanning tree analysis of brain networks: A systematic review of network size effects, sensitivity for neuropsychiatric pathology, and disorder specificity.","authors":"N Blomsma, B de Rooy, F Gerritse, R van der Spek, P Tewarie, A Hillebrand, W M Otte, C J Stam, E van Dellen","doi":"10.1162/netn_a_00245","DOIUrl":"https://doi.org/10.1162/netn_a_00245","url":null,"abstract":"Brain network characteristics' potential to serve as a neurological and psychiatric pathology biomarker has been hampered by the so-called thresholding problem. The minimum spanning tree (MST) is increasingly applied to overcome this problem. It is yet unknown whether this approach leads to more consistent findings across studies and converging outcomes of either disease-specific biomarkers or transdiagnostic effects. We performed a systematic review on MST analysis in neurophysiological and neuroimaging studies (N = 43) to study consistency of MST metrics between different network sizes and assessed disease specificity and transdiagnostic sensitivity of MST metrics for neurological and psychiatric conditions. Analysis of data from control groups (12 studies) showed that MST leaf fraction but not diameter decreased with increasing network size. Studies showed a broad range in metric values, suggesting that specific processing pipelines affect MST topology. Contradicting findings remain in the inconclusive literature of MST brain network studies, but some trends were seen: (1) a more linelike organization characterizes neurodegenerative disorders across pathologies, and is associated with symptom severity and disease progression; (2) neurophysiological studies in epilepsy show frequency band specific MST alterations that normalize after successful treatment; and (3) less efficient MST topology in alpha band is found across disorders associated with attention impairments.","PeriodicalId":520719,"journal":{"name":"Network neuroscience (Cambridge, Mass.)","volume":" ","pages":"301-319"},"PeriodicalIF":4.7,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9207994/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40209499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

A multilayer network model of neuron-astrocyte populations in vitro reveals mGluR₅ inhibition is protective following traumatic injury. 体外神经元-星形胶质细胞群体的多层网络模型显示，mGluR5抑制在创伤性损伤后具有保护作用。

IF 4.7

Network neuroscience (Cambridge, Mass.) Pub Date : 2022-06-01 DOI: 10.1162/netn_a_00227

Margaret E Schroeder, Danielle S Bassett, David F Meaney

{"title":"A multilayer network model of neuron-astrocyte populations in vitro reveals mGluR5 inhibition is protective following traumatic injury.","authors":"Margaret E Schroeder, Danielle S Bassett, David F Meaney","doi":"10.1162/netn_a_00227","DOIUrl":"https://doi.org/10.1162/netn_a_00227","url":null,"abstract":"Astrocytes communicate bidirectionally with neurons, enhancing synaptic plasticity and promoting the synchronization of neuronal microcircuits. Despite recent advances in understanding neuron-astrocyte signaling, little is known about astrocytic modulation of neuronal activity at the population level, particularly in disease or following injury. We used high-speed calcium imaging of mixed cortical cultures in vitro to determine how population activity changes after disruption of glutamatergic signaling and mechanical injury. We constructed a multilayer network model of neuron-astrocyte connectivity, which captured distinct topology and response behavior from single-cell-type networks. mGluR5 inhibition decreased neuronal activity, but did not on its own disrupt functional connectivity or network topology. In contrast, injury increased the strength, clustering, and efficiency of neuronal but not astrocytic networks, an effect that was not observed in networks pretreated with mGluR5 inhibition. Comparison of spatial and functional connectivity revealed that functional connectivity is largely independent of spatial proximity at the microscale, but mechanical injury increased the spatial-functional correlation. Finally, we found that astrocyte segments of the same cell often belong to separate functional communities based on neuronal connectivity, suggesting that astrocyte segments function as independent entities. Our findings demonstrate the utility of multilayer network models for characterizing the multiscale connectivity of two distinct but functionally dependent cell populations.","PeriodicalId":520719,"journal":{"name":"Network neuroscience (Cambridge, Mass.)","volume":" ","pages":"499-527"},"PeriodicalIF":4.7,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9208011/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40209500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Structure supports function: Informing directed and dynamic functional connectivity with anatomical priors. 结构支持功能:告知定向和动态功能连接与解剖学先验。

IF 4.7

Network neuroscience (Cambridge, Mass.) Pub Date : 2022-06-01 DOI: 10.1162/netn_a_00218

David Pascucci, Maria Rubega, Joan Rué-Queralt, Sebastien Tourbier, Patric Hagmann, Gijs Plomp

{"title":"Structure supports function: Informing directed and dynamic functional connectivity with anatomical priors.","authors":"David Pascucci, Maria Rubega, Joan Rué-Queralt, Sebastien Tourbier, Patric Hagmann, Gijs Plomp","doi":"10.1162/netn_a_00218","DOIUrl":"https://doi.org/10.1162/netn_a_00218","url":null,"abstract":"The dynamic repertoire of functional brain networks is constrained by the underlying topology of structural connections. Despite this intrinsic relationship between structural connectivity (SC) and functional connectivity (FC), integrative and multimodal approaches to combine the two remain limited. Here, we propose a new adaptive filter for estimating dynamic and directed FC using structural connectivity information as priors. We tested the filter in rat epicranial recordings and human event-related EEG data, using SC priors from a meta-analysis of tracer studies and diffusion tensor imaging metrics, respectively. We show that, particularly under conditions of low signal-to-noise ratio, SC priors can help to refine estimates of directed FC, promoting sparse functional networks that combine information from structure and function. In addition, the proposed filter provides intrinsic protection against SC-related false negatives, as well as robustness against false positives, representing a valuable new tool for multimodal imaging in the context of dynamic and directed FC analysis.","PeriodicalId":520719,"journal":{"name":"Network neuroscience (Cambridge, Mass.)","volume":" ","pages":"401-419"},"PeriodicalIF":4.7,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9205420/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40223584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Multimodal connectome biomarkers of cognitive and affective dysfunction in the common epilepsies. 常见癫痫患者认知和情感功能障碍的多模态连接组生物标志物。

IF 4.7

Network neuroscience (Cambridge, Mass.) Pub Date : 2022-06-01 DOI: 10.1162/netn_a_00237

Raul Rodriguez-Cruces, Jessica Royer, Sara Larivière, Dani S Bassett, Lorenzo Caciagli, Boris C Bernhardt

{"title":"Multimodal connectome biomarkers of cognitive and affective dysfunction in the common epilepsies.","authors":"Raul Rodriguez-Cruces, Jessica Royer, Sara Larivière, Dani S Bassett, Lorenzo Caciagli, Boris C Bernhardt","doi":"10.1162/netn_a_00237","DOIUrl":"https://doi.org/10.1162/netn_a_00237","url":null,"abstract":"Epilepsy is one of the most common chronic neurological conditions, traditionally defined as a disorder of recurrent seizures. Cognitive and affective dysfunction are increasingly recognized as core disease dimensions and can affect patient well-being, sometimes more than the seizures themselves. Connectome-based approaches hold immense promise for revealing mechanisms that contribute to dysfunction and to identify biomarkers. Our review discusses emerging multimodal neuroimaging and connectomics studies that highlight network substrates of cognitive/affective dysfunction in the common epilepsies. We first discuss work in drug-resistant epilepsy syndromes, that is, temporal lobe epilepsy, related to mesiotemporal sclerosis (TLE), and extratemporal epilepsy (ETE), related to malformations of cortical development. While these are traditionally conceptualized as 'focal' epilepsies, many patients present with broad structural and functional anomalies. Moreover, the extent of distributed changes contributes to difficulties in multiple cognitive domains as well as affective-behavioral challenges. We also review work in idiopathic generalized epilepsy (IGE), a subset of generalized epilepsy syndromes that involve subcortico-cortical circuits. Overall, neuroimaging and network neuroscience studies point to both shared and syndrome-specific connectome signatures of dysfunction across TLE, ETE, and IGE. Lastly, we point to current gaps in the literature and formulate recommendations for future research.","PeriodicalId":520719,"journal":{"name":"Network neuroscience (Cambridge, Mass.)","volume":" ","pages":"320-338"},"PeriodicalIF":4.7,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9208009/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40223586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

An application of neighbourhoods in digraphs to the classification of binary dynamics. 有向图中的邻域在二元动力学分类中的应用。

IF 4.7

Network neuroscience (Cambridge, Mass.) Pub Date : 2022-06-01 DOI: 10.1162/netn_a_00228

Pedro Conceição, Dejan Govc, Jānis Lazovskis, Ran Levi, Henri Riihimäki, Jason P Smith

{"title":"An application of neighbourhoods in digraphs to the classification of binary dynamics.","authors":"Pedro Conceição, Dejan Govc, Jānis Lazovskis, Ran Levi, Henri Riihimäki, Jason P Smith","doi":"10.1162/netn_a_00228","DOIUrl":"https://doi.org/10.1162/netn_a_00228","url":null,"abstract":"A binary state on a graph means an assignment of binary values to its vertices. A time-dependent sequence of binary states is referred to as binary dynamics. We describe a method for the classification of binary dynamics of digraphs, using particular choices of closed neighbourhoods. Our motivation and application comes from neuroscience, where a directed graph is an abstraction of neurons and their connections, and where the simplification of large amounts of data is key to any computation. We present a topological/graph theoretic method for extracting information out of binary dynamics on a graph, based on a selection of a relatively small number of vertices and their neighbourhoods. We consider existing and introduce new real-valued functions on closed neighbourhoods, comparing them by their ability to accurately classify different binary dynamics. We describe a classification algorithm that uses two parameters and sets up a machine learning pipeline. We demonstrate the effectiveness of the method on simulated activity on a digital reconstruction of cortical tissue of a rat, and on a nonbiological random graph with similar density.","PeriodicalId":520719,"journal":{"name":"Network neuroscience (Cambridge, Mass.)","volume":" ","pages":"528-551"},"PeriodicalIF":4.7,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9208003/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40224572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

More than the sum of its parts: Merging network psychometrics and network neuroscience with application in autism. 超过其部分的总和:将网络心理测量学和网络神经科学与自闭症的应用相结合。

IF 4.7

Network neuroscience (Cambridge, Mass.) Pub Date : 2022-06-01 DOI: 10.1162/netn_a_00222

Joe Bathelt, Hilde M Geurts, Denny Borsboom

{"title":"More than the sum of its parts: Merging network psychometrics and network neuroscience with application in autism.","authors":"Joe Bathelt, Hilde M Geurts, Denny Borsboom","doi":"10.1162/netn_a_00222","DOIUrl":"https://doi.org/10.1162/netn_a_00222","url":null,"abstract":"Network approaches that investigate the interaction between symptoms and behaviours have opened new ways of understanding psychological phenomena in health and disorder in recent years. In parallel, network approaches that characterise the interaction between brain regions have become the dominant approach in neuroimaging research. In this paper, we introduce a methodology for combining network psychometrics and network neuroscience. This approach utilises the information from the psychometric network to obtain neural correlates that are associated with each node in the psychometric network (network-based regression). Moreover, we combine the behavioural variables and their neural correlates in a joint network to characterise their interactions. We illustrate the approach by highlighting the interaction between the triad of autistic traits and their resting-state functional connectivity associations. To this end, we utilise data from 172 male autistic participants (10-21 years) from the autism brain data exchange (ABIDE, ABIDE-II) that completed resting-state fMRI and were assessed using the autism diagnostic interview (ADI-R). Our results indicate that the network-based regression approach can uncover both unique and shared neural correlates of behavioural measures. For instance, our example analysis indicates that the overlap between communication and social difficulties is not reflected in the overlap between their functional brain correlates.","PeriodicalId":520719,"journal":{"name":"Network neuroscience (Cambridge, Mass.)","volume":" ","pages":"445-466"},"PeriodicalIF":4.7,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9207995/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40209497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A mixed-modeling framework for whole-brain dynamic network analysis. 全脑动态网络分析的混合建模框架。

IF 4.7

Network neuroscience (Cambridge, Mass.) Pub Date : 2022-06-01 DOI: 10.1162/netn_a_00238

Mohsen Bahrami, Paul J Laurienti, Heather M Shappell, Dale Dagenbach, Sean L Simpson

{"title":"A mixed-modeling framework for whole-brain dynamic network analysis.","authors":"Mohsen Bahrami, Paul J Laurienti, Heather M Shappell, Dale Dagenbach, Sean L Simpson","doi":"10.1162/netn_a_00238","DOIUrl":"https://doi.org/10.1162/netn_a_00238","url":null,"abstract":"The emerging area of dynamic brain network analysis has gained considerable attention in recent years. However, development of multivariate statistical frameworks that allow for examining the associations between phenotypic traits and dynamic patterns of system-level properties of the brain, and drawing statistical inference about such associations, has largely lagged behind. To address this need we developed a mixed-modeling framework that allows for assessing the relationship between any desired phenotype and dynamic patterns of whole-brain connectivity and topology. This novel framework also allows for simulating dynamic brain networks with respect to desired covariates. Unlike current tools, which largely use data-driven methods, our model-based method enables aligning neuroscientific hypotheses with the analytic approach. We demonstrate the utility of this model in identifying the relationship between fluid intelligence and dynamic brain networks by using resting-state fMRI (rfMRI) data from 200 participants in the Human Connectome Project (HCP) study. We also demonstrate the utility of this model to simulate dynamic brain networks at both group and individual levels. To our knowledge, this approach provides the first model-based statistical method for examining dynamic patterns of system-level properties of the brain and their relationships to phenotypic traits as well as simulating dynamic brain networks.","PeriodicalId":520719,"journal":{"name":"Network neuroscience (Cambridge, Mass.)","volume":" ","pages":"591-613"},"PeriodicalIF":4.7,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9208000/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40224571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1