Determining functional connectivity using fMRI data with diffusion-based anatomical weighting.
about
A multimodal approach for determining brain networks by jointly modeling functional and structural connectivity3D interactive tractography-informed resting-state fMRI connectivity.A review of neuroimaging studies of young relatives of individuals with schizophrenia: a developmental perspective from schizotaxia to schizophrenia.Understanding structural-functional relationships in the human brain: a large-scale network perspective.Bayesian Models for fMRI Data Analysis.Bayesian vector autoregressive model for multi-subject effective connectivity inference using multi-modal neuroimaging data.Analyzing complex functional brain networks: Fusing statistics and network science to understand the brain(*†)Brain Imaging AnalysisFusing DTI and fMRI data: a survey of methods and applications.Cortical network models of impulse firing in the resting and active states predict cortical energetics.Integrated Analysis and Visualization of Group Differences in Structural and Functional Brain Connectivity: Applications in Typical Ageing and Schizophrenia.Bayesian Estimation of Conditional Independence Graphs Improves Functional Connectivity Estimates.Cortical Network Models of Firing Rates in the Resting and Active States Predict BOLD Responses.Resting-State Retinotopic Organization in the Absence of Retinal Input and Visual Experience.A Bayesian Double Fusion Model for Resting-State Brain Connectivity Using Joint Functional and Structural Data.Structural and functional, empirical and modeled connectivity in the cerebral cortex of the rat.Semiparametric Bayes conditional graphical models for imaging genetics applications.Track-weighted dynamic functional connectivity (TW-dFC): a new method to study time-resolved functional connectivity.High-dimensional tests for functional networks of brain anatomic regions.Integrated multimodal network approach to PET and MRI based on multidimensional persistent homology.A Hierarchical Bayesian Model for the Identification of PET Markers Associated to the Prediction of Surgical Outcome after Anterior Temporal Lobe Resection.Bayesian Multiresolution Variable Selection for Ultra-High Dimensional Neuroimaging Data.Function-specific and Enhanced Brain Structural Connectivity Mapping via Joint Modeling of Diffusion and Functional MRI.
P2860
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P2860
Determining functional connectivity using fMRI data with diffusion-based anatomical weighting.
description
2012 nî lūn-bûn
@nan
2012 թուականի Մայիսին հրատարակուած գիտական յօդուած
@hyw
2012 թվականի մայիսին հրատարակված գիտական հոդված
@hy
2012年の論文
@ja
2012年論文
@yue
2012年論文
@zh-hant
2012年論文
@zh-hk
2012年論文
@zh-mo
2012年論文
@zh-tw
2012年论文
@wuu
name
Determining functional connect ...... on-based anatomical weighting.
@ast
Determining functional connect ...... on-based anatomical weighting.
@en
Determining functional connect ...... on-based anatomical weighting.
@nl
type
label
Determining functional connect ...... on-based anatomical weighting.
@ast
Determining functional connect ...... on-based anatomical weighting.
@en
Determining functional connect ...... on-based anatomical weighting.
@nl
prefLabel
Determining functional connect ...... on-based anatomical weighting.
@ast
Determining functional connect ...... on-based anatomical weighting.
@en
Determining functional connect ...... on-based anatomical weighting.
@nl
P2093
P2860
P1433
P1476
Determining functional connect ...... on-based anatomical weighting.
@en
P2093
F DuBois Bowman
Gordana Derado
Lijun Zhang
P2860
P304
P356
10.1016/J.NEUROIMAGE.2012.05.032
P407
P577
2012-05-24T00:00:00Z