Dynamic Causal Modeling applied to fMRI data shows high reliability.
about
Circuit to construct mapping: a mathematical tool for assisting the diagnosis and treatment in major depressive disorderConvergent evidence for hierarchical prediction networks from human electrocorticography and magnetoencephalography.Characterization of task-free and task-performance brain states via functional connectome patterns.Functional Magnetic Resonance Imaging Methods.Abnormal effective connectivity and psychopathological symptoms in the psychosis high-risk stateWorking memory load modulation of parieto-frontal connections: evidence from dynamic causal modeling.Disrupted effective connectivity between the amygdala and orbitofrontal cortex in social anxiety disorder during emotion discrimination revealed by dynamic causal modeling for FMRIAbnormal left-sided orbitomedial prefrontal cortical-amygdala connectivity during happy and fear face processing: a potential neural mechanism of female MDDNeural networks underlying contributions from semantics in reading aloud.Advancing understanding of affect labeling with dynamic causal modeling.Cerebral network disorders after stroke: evidence from imaging-based connectivity analyses of active and resting brain states in humans.Estimating the directed information to infer causal relationships in ensemble neural spike train recordingsDominance of the Unaffected Hemisphere Motor Network and Its Role in the Behavior of Chronic Stroke Survivors.Characterizing and differentiating task-based and resting state fMRI signals via two-stage sparse representations.Connectivity Analysis is Essential to Understand Neurological Disorders.Dynamic causal modelling of effective connectivity from fMRI: are results reproducible and sensitive to Parkinson's disease and its treatment?Bypassing primary sensory cortices--a direct thalamocortical pathway for transmitting salient sensory information.Network connectivity and individual responses to brain stimulation in the human motor system.Test-retest reliability of effective connectivity in the face perception network.Dynamic causal modelling on infant fNIRS data: A validation study on a simultaneously recorded fNIRS-fMRI dataset.
P2860
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P2860
Dynamic Causal Modeling applied to fMRI data shows high reliability.
description
2009 nî lūn-bûn
@nan
2009 թուականի Յուլիսին հրատարակուած գիտական յօդուած
@hyw
2009 թվականի հուլիսին հրատարակված գիտական հոդված
@hy
2009年の論文
@ja
2009年論文
@yue
2009年論文
@zh-hant
2009年論文
@zh-hk
2009年論文
@zh-mo
2009年論文
@zh-tw
2009年论文
@wuu
name
Dynamic Causal Modeling applied to fMRI data shows high reliability.
@ast
Dynamic Causal Modeling applied to fMRI data shows high reliability.
@en
type
label
Dynamic Causal Modeling applied to fMRI data shows high reliability.
@ast
Dynamic Causal Modeling applied to fMRI data shows high reliability.
@en
prefLabel
Dynamic Causal Modeling applied to fMRI data shows high reliability.
@ast
Dynamic Causal Modeling applied to fMRI data shows high reliability.
@en
P2093
P2860
P1433
P1476
Dynamic Causal Modeling applied to fMRI data shows high reliability
@en
P2093
Brianna Schuyler
John M Ollinger
Terrence R Oakes
P2860
P304
P356
10.1016/J.NEUROIMAGE.2009.07.015
P407
P577
2009-07-18T00:00:00Z