Exponential random graph modeling for complex brain networks. - Wikidata - wikimedia - TriplyDB

Exponential random graph modeling for complex brain networks.

Exponential random graph modeling for complex brain networks.

http://www.wikidata.org/entity/Q33925376

about

A two-part mixed-effects modeling framework for analyzing whole-brain network data.Gibbs distribution for statistical analysis of graphical data with a sample application to fcMRI brain images.Statistical inference for valued-edge networks: the generalized exponential random graph model.Stochastic geometric network models for groups of functional and structural connectomes.The brain as a complex system: using network science as a tool for understanding the brain.Analyzing complex functional brain networks: Fusing statistics and network science to understand the brain(*†)Brain Imaging Analysis Sets2Networks: network inference from repeated observations of sets.A neuronal network model for simulating the effects of repetitive transcranial magnetic stimulation on local field potential power spectra.Clarifying the use of aggregated exposures in multilevel models: self-included vs. self-excluded measures Resolving structural variability in network models and the brain Changes in cognitive state alter human functional brain networks.An exponential random graph modeling approach to creating group-based representative whole-brain connectivity networks Cognitive network neuroscience The brain science interface.A permutation testing framework to compare groups of brain networks.Analyzing heterogeneity in the effects of physical activity in children on social network structure and peer selection dynamics.Disentangling Brain Graphs: A Note on the Conflation of Network and Connectivity Analyses.Emerging Frontiers of Neuroengineering: A Network Science of Brain Connectivity.A statistical model for brain networks inferred from large-scale electrophysiological signals.A Network Neuroscience of Human Learning: Potential to Inform Quantitative Theories of Brain and Behavior.A parsimonious statistical method to detect groupwise differentially expressed functional connectivity networks.From phenotype to genotype in complex brain networks.Generative models for network neuroscience: prospects and promise.Diversity of meso-scale architecture in human and non-human connectomes.Network Analysis in Disorders of Consciousness: Four Problems and One Proposed Solution (Exponential Random Graph Models).

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Exponential random graph modeling for complex brain networks.

http://www.wikidata.org/entity/Q33925376

description

2011 nî lūn-bûn

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2011 թուականի Մայիսին հրատարակուած գիտական յօդուած

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2011 թվականի մայիսին հրատարակված գիտական հոդված

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2011年の論文

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2011年論文

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2011年論文

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2011年論文

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2011年論文

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2011年論文

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2011年论文

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name

Exponential random graph modeling for complex brain networks.

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Exponential random graph modeling for complex brain networks.

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Exponential random graph modeling for complex brain networks.

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Exponential random graph modeling for complex brain networks.

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JOURNAL.PONE.0020039

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Exponential random graph modeling for complex brain networks.

@en

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Paul J Laurienti

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Satoru Hayasaka

http://www.w3.org/2001/XMLSchema#string

Sean L Simpson

http://www.w3.org/2001/XMLSchema#string

P2860

Mapping anatomical connectivity patterns of human cerebral cortex using in vivo diffusion tensor imaging tractography

Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain

Collective dynamics of 'small-world' networks

Complex brain networks: graph theoretical analysis of structural and functional systems

Complex network measures of brain connectivity: uses and interpretations

Aging and the interaction of sensory cortical function and structure.

statnet: Software Tools for the Representation, Visualization, Analysis and Simulation of Network Data.

Comparison of characteristics between region-and voxel-based network analyses in resting-state fMRI data.

A new measure of centrality for brain networks

Age- and gender-related differences in the cortical anatomical network.

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e20039

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scholarly article

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10.1371/JOURNAL.PONE.0020039

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51197559

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21647450

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1007.3230

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3102079

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