Title | ||
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State-dependent differences between functional and effective connectivity of the human cortical motor system. |
Abstract | ||
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Neural processing is based on interactions between functionally specialized areas that can be described in terms of functional or effective connectivity. Functional connectivity is often assessed by task-free, resting-state functional magnetic resonance imaging (fMRI), whereas effective connectivity is usually estimated from task-based fMRI time-series. To investigate whether different connectivity approaches assess similar network topologies in the same subjects, we scanned 36 right-handed volunteers with resting-state fMRI followed by active-state fMRI involving a hand movement task. Time-series information was extracted from identical locations defined from individual activation maxima derived from the motor task. Dynamic causal modeling (DCM) was applied to the motor task time-series to estimate endogenous and context-dependent effective connectivity. In addition, functional connectivity was computed for both the rest and the motor task condition by means of inter-regional time-series correlations. At the group-level, we found strong interactions between the motor areas of interest in all three connectivity analyses. However, although the sample size warranted 90% power to detect correlations of medium effect size, resting-state functional connectivity was only weakly correlated with both task-based functional and task-based effective connectivity estimates for corresponding region-pairs. By contrast, task-based functional connectivity showed strong positive correlations with DCM effective connectivity parameters. In conclusion, resting-state and task-based connectivity reflect different components of functional integration that particularly depend on the functional state in which the subject is being scanned. Therefore, resting-state fMRI and DCM should be used as complementary measures when assessing functional brain networks. |
Year | DOI | Venue |
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2013 | 10.1016/j.neuroimage.2012.11.027 | NeuroImage |
Keywords | Field | DocType |
Dynamic causal modeling,fMRI,Intrinsic connectivity,Resting-state | Neuroscience,Resting state fMRI,Cognitive psychology,Motor cortex,Artificial intelligence,Motor system,Functional integration,Causal model,Functional magnetic resonance imaging,Nerve net,Connectome,Machine learning,Mathematics | Journal |
Volume | ISSN | Citations |
67 | 1053-8119 | 1 |
PageRank | References | Authors |
0.37 | 19 | 3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Anne K. Rehme | 1 | 43 | 4.40 |
Simon B. Eickhoff | 2 | 1297 | 79.68 |
Christian Grefkes | 3 | 171 | 16.40 |