Network Neuroscience最新文献_第10页

Allostasis as a core feature of hierarchical gradients in the human brain. 异稳态是人脑分层梯度的核心特征

IF 3.6 3区医学

Network Neuroscience Pub Date : 2022-10-01 eCollection Date: 2022-01-01 DOI: 10.1162/netn_a_00240

Yuta Katsumi, Jordan E Theriault, Karen S Quigley, Lisa Feldman Barrett

引用次数: 0

Conservative significance testing of tripartite statistical relations in multivariate neural data. 多元神经数据中三方统计关系的保守显著性检验

IF 4.7 3区医学

Network Neuroscience Pub Date : 2022-10-01 eCollection Date: 2022-01-01 DOI: 10.1162/netn_a_00259

Aleksejs Fomins, Yaroslav Sych, Fritjof Helmchen

{"title":"Conservative significance testing of tripartite statistical relations in multivariate neural data.","authors":"Aleksejs Fomins, Yaroslav Sych, Fritjof Helmchen","doi":"10.1162/netn_a_00259","DOIUrl":"10.1162/netn_a_00259","url":null,"abstract":"An important goal in systems neuroscience is to understand the structure of neuronal interactions, frequently approached by studying functional relations between recorded neuronal signals. Commonly used pairwise measures (e.g., correlation coefficient) offer limited insight, neither addressing the specificity of estimated neuronal interactions nor potential synergistic coupling between neuronal signals. Tripartite measures, such as partial correlation, variance partitioning, and partial information decomposition, address these questions by disentangling functional relations into interpretable information atoms (unique, redundant, and synergistic). Here, we apply these tripartite measures to simulated neuronal recordings to investigate their sensitivity to noise. We find that the considered measures are mostly accurate and specific for signals with noiseless sources but experience significant bias for noisy sources.We show that permutation testing of such measures results in high false positive rates even for small noise fractions and large data sizes. We present a conservative null hypothesis for significance testing of tripartite measures, which significantly decreases false positive rate at a tolerable expense of increasing false negative rate. We hope our study raises awareness about the potential pitfalls of significance testing and of interpretation of functional relations, offering both conceptual and practical advice.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"6 1","pages":"1243-1274"},"PeriodicalIF":4.7,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11117094/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48445286","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}

引用次数: 0

Theoretical foundations of studying criticality in the brain. 研究大脑临界性的理论基础

IF 4.7 3区医学

Network Neuroscience Pub Date : 2022-10-01 eCollection Date: 2022-01-01 DOI: 10.1162/netn_a_00269

Yang Tian, Zeren Tan, Hedong Hou, Guoqi Li, Aohua Cheng, Yike Qiu, Kangyu Weng, Chun Chen, Pei Sun

{"title":"Theoretical foundations of studying criticality in the brain.","authors":"Yang Tian, Zeren Tan, Hedong Hou, Guoqi Li, Aohua Cheng, Yike Qiu, Kangyu Weng, Chun Chen, Pei Sun","doi":"10.1162/netn_a_00269","DOIUrl":"10.1162/netn_a_00269","url":null,"abstract":"Criticality is hypothesized as a physical mechanism underlying efficient transitions between cortical states and remarkable information-processing capacities in the brain. While considerable evidence generally supports this hypothesis, nonnegligible controversies persist regarding the ubiquity of criticality in neural dynamics and its role in information processing. Validity issues frequently arise during identifying potential brain criticality from empirical data. Moreover, the functional benefits implied by brain criticality are frequently misconceived or unduly generalized. These problems stem from the nontriviality and immaturity of the physical theories that analytically derive brain criticality and the statistic techniques that estimate brain criticality from empirical data. To help solve these problems, we present a systematic review and reformulate the foundations of studying brain criticality, that is, ordinary criticality (OC), quasi-criticality (qC), self-organized criticality (SOC), and self-organized quasi-criticality (SOqC), using the terminology of neuroscience. We offer accessible explanations of the physical theories and statistical techniques of brain criticality, providing step-by-step derivations to characterize neural dynamics as a physical system with avalanches. We summarize error-prone details and existing limitations in brain criticality analysis and suggest possible solutions. Moreover, we present a forward-looking perspective on how optimizing the foundations of studying brain criticality can deepen our understanding of various neuroscience questions.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"6 1","pages":"1148-1185"},"PeriodicalIF":4.7,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11117095/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45719834","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}

引用次数: 0

Constraining functional coactivation with a cluster-based structural connectivity network. 基于簇的结构连接网络约束功能协同激活

IF 4.7 3区医学

Network Neuroscience Pub Date : 2022-10-01 eCollection Date: 2022-01-01 DOI: 10.1162/netn_a_00242

Inhan Kang, Matthew Galdo, Brandon M Turner

{"title":"Constraining functional coactivation with a cluster-based structural connectivity network.","authors":"Inhan Kang, Matthew Galdo, Brandon M Turner","doi":"10.1162/netn_a_00242","DOIUrl":"10.1162/netn_a_00242","url":null,"abstract":"In this article, we propose a two-step pipeline to explore task-dependent functional coactivations of brain clusters with constraints from the structural connectivity network. In the first step, the pipeline employs a nonparametric Bayesian clustering method that can estimate the optimal number of clusters, cluster assignments of brain regions of interest (ROIs), and the strength of within- and between-cluster connections without any prior knowledge. In the second step, a factor analysis model is applied to functional data with factors defined as the obtained structural clusters and the factor structure informed by the structural network. The coactivations of ROIs and their clusters can be studied by correlations between factors, which can largely differ by ongoing cognitive task. We provide a simulation study to validate that the pipeline can recover the underlying structural and functional network. We also apply the proposed pipeline to empirical data to explore the structural network of ROIs obtained by the Gordon parcellation and study their functional coactivations across eight cognitive tasks and a resting-state condition.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"6 1","pages":"1032-1065"},"PeriodicalIF":4.7,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11117093/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48241204","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}

引用次数: 0

From calcium imaging to graph topology. 从钙成像到图拓扑

IF 4.7 3区医学

Network Neuroscience Pub Date : 2022-10-01 eCollection Date: 2022-01-01 DOI: 10.1162/netn_a_00262

Ann S Blevins, Dani S Bassett, Ethan K Scott, Gilles C Vanwalleghem

{"title":"From calcium imaging to graph topology.","authors":"Ann S Blevins, Dani S Bassett, Ethan K Scott, Gilles C Vanwalleghem","doi":"10.1162/netn_a_00262","DOIUrl":"10.1162/netn_a_00262","url":null,"abstract":"Systems neuroscience is facing an ever-growing mountain of data. Recent advances in protein engineering and microscopy have together led to a paradigm shift in neuroscience; using fluorescence, we can now image the activity of every neuron through the whole brain of behaving animals. Even in larger organisms, the number of neurons that we can record simultaneously is increasing exponentially with time. This increase in the dimensionality of the data is being met with an explosion of computational and mathematical methods, each using disparate terminology, distinct approaches, and diverse mathematical concepts. Here we collect, organize, and explain multiple data analysis techniques that have been, or could be, applied to whole-brain imaging, using larval zebrafish as an example model. We begin with methods such as linear regression that are designed to detect relations between two variables. Next, we progress through network science and applied topological methods, which focus on the patterns of relations among many variables. Finally, we highlight the potential of generative models that could provide testable hypotheses on wiring rules and network progression through time, or disease progression. While we use examples of imaging from larval zebrafish, these approaches are suitable for any population-scale neural network modeling, and indeed, to applications beyond systems neuroscience. Computational approaches from network science and applied topology are not limited to larval zebrafish, or even to systems neuroscience, and we therefore conclude with a discussion of how such methods can be applied to diverse problems across the biological sciences.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"6 1","pages":"1125-1147"},"PeriodicalIF":4.7,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11117109/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45200232","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}

引用次数: 0

A perturbative approach to study information communication in brain networks. 一种研究脑网络信息交流的扰动方法

IF 4.7 3区医学

Network Neuroscience Pub Date : 2022-10-01 eCollection Date: 2022-01-01 DOI: 10.1162/netn_a_00260

Varun Madan Mohan, Arpan Banerjee

{"title":"A perturbative approach to study information communication in brain networks.","authors":"Varun Madan Mohan, Arpan Banerjee","doi":"10.1162/netn_a_00260","DOIUrl":"10.1162/netn_a_00260","url":null,"abstract":"How communication among neuronal ensembles shapes functional brain dynamics is a question of fundamental importance to neuroscience. Communication in the brain can be viewed as a product of the interaction of node activities with the structural network over which these activities flow. The study of these interactions is, however, restricted by the difficulties in describing the complex dynamics of the brain. There is thus a need to develop methods to study these network-dynamical interactions and how they impact information flow, without having to ascertain dynamics a priori or resort to restrictive analytical approaches. Here, we adapt a recently established network analysis method based on perturbations, it to a neuroscientific setting to study how information flow in the brain can raise from properties of underlying structure. For proof-of-concept, we apply the approach on in silico whole-brain models. We expound on the functional implications of the distributions of metrics that capture network-dynamical interactions, termed net influence and flow. We also study the network-dynamical interactions at the level of resting-state networks. An attractive feature of this method is its simplicity, which allows a direct translation to an experimental or clinical setting, such as for identifying targets for stimulation studies or therapeutic interventions.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"6 1","pages":"1275-1295"},"PeriodicalIF":4.7,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11117119/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43106021","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}

引用次数: 0

Computational approaches to treatment response prediction in major depression using brain activity and behavioral data: A systematic review. 使用脑活动和行为数据预测重度抑郁症治疗反应的计算方法:系统回顾

IF 4.7 3区医学

Network Neuroscience Pub Date : 2022-10-01 eCollection Date: 2022-01-01 DOI: 10.1162/netn_a_00233

Povilas Karvelis, Colleen E Charlton, Shona G Allohverdi, Peter Bedford, Daniel J Hauke, Andreea O Diaconescu

{"title":"Computational approaches to treatment response prediction in major depression using brain activity and behavioral data: A systematic review.","authors":"Povilas Karvelis, Colleen E Charlton, Shona G Allohverdi, Peter Bedford, Daniel J Hauke, Andreea O Diaconescu","doi":"10.1162/netn_a_00233","DOIUrl":"10.1162/netn_a_00233","url":null,"abstract":"Major depressive disorder is a heterogeneous diagnostic category with multiple available treatments. With the goal of optimizing treatment selection, researchers are developing computational models that attempt to predict treatment response based on various pretreatment measures. In this paper, we review studies that use brain activity data to predict treatment response. Our aim is to highlight and clarify important methodological differences between various studies that relate to the incorporation of domain knowledge, specifically within two approaches delineated as data-driven and theory-driven. We argue that theory-driven generative modeling, which explicitly models information processing in the brain and thus can capture disease mechanisms, is a promising emerging approach that is only beginning to be utilized in treatment response prediction. The predictors extracted via such models could improve interpretability, which is critical for clinical decision-making. We also identify several methodological limitations across the reviewed studies and provide suggestions for addressing them. Namely, we consider problems with dichotomizing treatment outcomes, the importance of investigating more than one treatment in a given study for differential treatment response predictions, the need for a patient-centered approach for defining treatment outcomes, and finally, the use of internal and external validation methods for improving model generalizability.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"6 1","pages":"1066-1103"},"PeriodicalIF":4.7,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11117101/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47027829","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}

引用次数: 0

Functional coordinates: Modeling interactions between brain regions as points in a function space. 功能坐标：将大脑区域之间的相互作用建模为功能空间中的点

IF 4.7 3区医学

Network Neuroscience Pub Date : 2022-10-01 eCollection Date: 2022-01-01 DOI: 10.1162/netn_a_00264

Craig Poskanzer, Stefano Anzellotti

{"title":"Functional coordinates: Modeling interactions between brain regions as points in a function space.","authors":"Craig Poskanzer, Stefano Anzellotti","doi":"10.1162/netn_a_00264","DOIUrl":"10.1162/netn_a_00264","url":null,"abstract":"Here, we propose a novel technique to investigate nonlinear interactions between brain regions that captures both the strength and type of the functional relationship. Inspired by the field of functional analysis, we propose that the relationship between activity in separate brain areas can be viewed as a point in function space, identified by coordinates along an infinite set of basis functions. Using Hermite polynomials as bases, we estimate a subset of these values that serve as \"functional coordinates,\" characterizing the interaction between BOLD activity across brain areas. We provide a proof of the convergence of the estimates in the limit, and we validate the method with simulations in which the ground truth is known, additionally showing that functional coordinates detect statistical dependence even when correlations (\"functional connectivity\") approach zero. We then use functional coordinates to examine neural interactions with a chosen seed region: the fusiform face area (FFA). Using k-means clustering across each voxel's functional coordinates, we illustrate that adding nonlinear basis functions allows for the discrimination of interregional interactions that are otherwise grouped together when using only linear dependence. Finally, we show that regions in V5 and medial occipital and temporal lobes exhibit significant nonlinear interactions with the FFA.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"6 1","pages":"1296-1315"},"PeriodicalIF":4.7,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11117108/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46636915","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}

引用次数: 0

Effects of classic psychedelic drugs on turbulent signatures in brain dynamics. 经典迷幻药对大脑动力学中湍流特征的影响

IF 4.7 3区医学

Network Neuroscience Pub Date : 2022-10-01 eCollection Date: 2022-01-01 DOI: 10.1162/netn_a_00250

Josephine Cruzat, Yonatan Sanz Perl, Anira Escrichs, Jakub Vohryzek, Christopher Timmermann, Leor Roseman, Andrea I Luppi, Agustin Ibañez, David Nutt, Robin Carhart-Harris, Enzo Tagliazucchi, Gustavo Deco, Morten L Kringelbach

{"title":"Effects of classic psychedelic drugs on turbulent signatures in brain dynamics.","authors":"Josephine Cruzat, Yonatan Sanz Perl, Anira Escrichs, Jakub Vohryzek, Christopher Timmermann, Leor Roseman, Andrea I Luppi, Agustin Ibañez, David Nutt, Robin Carhart-Harris, Enzo Tagliazucchi, Gustavo Deco, Morten L Kringelbach","doi":"10.1162/netn_a_00250","DOIUrl":"10.1162/netn_a_00250","url":null,"abstract":"Psychedelic drugs show promise as safe and effective treatments for neuropsychiatric disorders, yet their mechanisms of action are not fully understood. A fundamental hypothesis is that psychedelics work by dose-dependently changing the functional hierarchy of brain dynamics, but it is unclear whether different psychedelics act similarly. Here, we investigated the changes in the brain's functional hierarchy associated with two different psychedelics (LSD and psilocybin). Using a novel turbulence framework, we were able to determine the vorticity, that is, the local level of synchronization, that allowed us to extend the standard global time-based measure of metastability to become a local-based measure of both space and time. This framework produced detailed signatures of turbulence-based hierarchical change for each psychedelic drug, revealing consistent and discriminate effects on a higher level network, that is, the default mode network. Overall, our findings directly support a prior hypothesis that psychedelics modulate (i.e., \"compress\") the functional hierarchy and provide a quantification of these changes for two different psychedelics. Implications for therapeutic applications of psychedelics are discussed.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"6 1","pages":"1104-1124"},"PeriodicalIF":4.7,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11117113/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46397302","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}

引用次数: 0

NFV/SDN as an Enabler for Dynamic Placement Method of mmWave Embedded UAV Access Base Stations 基于NFV/SDN的毫米波嵌入式无人机接入基站动态布局方法

IF 4.7 3区医学

Network Neuroscience Pub Date : 2022-09-26 DOI: 10.3390/network2040029

G. Tran, Masanori Ozasa, Jin Nakazato

{"title":"NFV/SDN as an Enabler for Dynamic Placement Method of mmWave Embedded UAV Access Base Stations","authors":"G. Tran, Masanori Ozasa, Jin Nakazato","doi":"10.3390/network2040029","DOIUrl":"https://doi.org/10.3390/network2040029","url":null,"abstract":"In the event of a major disaster, base stations in the disaster area will cease to function, making it impossible to obtain life-saving information. Therefore, it is necessary to provide a wireless communication infrastructure as soon as possible. To cope with this situation, we focus on NFV/SDN (Network Function Virtualization/Software-Defined Networking)-enabled UAVs equipped with a wireless communication infrastructure to provide services. The access link between the UAV and the user is assumed to be equipped with a millimeter-wave interface to achieve high throughput. However, the use of millimeter-waves increases the effect of attenuation, making the deployment of UAVs problematic. In addition, if multiple UAVs are deployed in a limited frequency band, co-channel interference will occur between the UAVs, resulting in a decrease in the data rate. Therefore, in this paper, we propose a method that combines UAV placement and frequency division for a non-uniform user distribution in an environment with multiple UAVs. As a result, it is found that the offered data rate is improved by using our specific placement method, in terms of not only the average but also the outage user rate.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"105 1","pages":"479-499"},"PeriodicalIF":4.7,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80622505","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: 5