Research reportFunctional neural networks underlying response inhibition in adolescents and adults
Section snippets
Material and methods
Our aim was to quantify the coupling between brain regions involved with response inhibition. To do this, we decomposed brain responses elicited by performance on a rapid, event-related visual Go/No-Go cognitive task into a series of spatially independent components, or modes, using independent component analysis (ICA) [35]. ICA is a data-driven multivariate analysis method that identifies distinct groups of brain regions with the same temporal pattern of hemodynamic signal change. We then
Network structure and interactions
The analysis identified three independent components associated principally with successful response inhibition performance. Each component depicts a distinct, functionally integrated circuit of brain regions that have the same pattern of hemodynamic change over time. Table 1 lists these components and their association to all experimental conditions of the Go/No-Go task. Brain regions within each component are listed in Table 2, along with the x, y, and z coordinates of the peak t-score for
Discussion
This study was undertaken to identify and characterize distinct, functionally integrated neural networks engaged by successful response inhibition. To date, evidence for such networks has been inferred largely from comparative studies of anatomical connections among brain regions activated by fMRI tasks that require prepotent response inhibition. Therefore, this study represents a significant step towards understanding how brain systems mutually interact to effect cognitive and behavioral
Acknowledgements
This work was supported in part by NIMH K23 MH070036 (PI Stevens) the Holton and Yanner Trusts, NIMH 1 R01 MH070539-01 (PI Kiehl), 1 R01 MH071896-01 (PI Kiehl), NIDA RO1 020709 and NIAAA P50-AA12870 (PI Pearlson) and NIBIB R01 EB 000840 and NIBIB R01 EB005846 (PI Calhoun). The authors appreciate the input provided by Drs. Karl Friston, Thomas Ethofer, Darren Gitelman, and Christopher Summerfield on the analytic methods used in this study.
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