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Experience with computational modeling approaches, brain connectivity techniques, and multivariate statistics will confer an advantage.
We also apply functional connectivity techniques to understand large-scale networks in the brain — and how those networks contribute to behavior.
Newer connectivity techniques allow the study of effective connectivity.
Two of these techniques, structural equation modeling and dynamic causal modeling, are model-based effective connectivity techniques.
HTML and PHP were used to render a dynamic web interface and the appropriate database connectivity techniques were utilized for quick and easy information retrieval.
In contrast, GC and other casual connectivity techniques are specifically designed to examine the significance of the relative changes in activity of sources.
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This promising wireless-connectivity technique increases successfully both the traffic capacity and the frequency diversity.
One feature that distinguishes diffusion MRI tractography from other brain connectivity mapping techniques is the ability to map only the pathways that connect 2 different regions.
However, brain imaging and cerebral connectivity analytical techniques have provided invaluable insights into such mechanisms and identified two main patterns of brain reorganization depending on stroke severity.
The application of connectivity analysis techniques based on fMRI data may improve our understanding of the interactions between brain regions haemodynamically involved during GSW discharges.
More recently David and colleagues [39] applied effective connectivity analysis techniques including DCM to fMRI data from (GAERS) rats to demonstrate concordance between the drivers revealed by DCM and the trigger identified using intracranial recordings.
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