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Washington: Our brain networks at rest are in readiness for action to execute even the simplest of behaviours, researchers including one of Indian origin have
found.
Researchers from Wayne State University and Florida Atlantic University in the US used a simple experimental task, having each participant perform a simple motor control behaviour (tapping their forefinger to a visual cue) that alternated between behaviour and rest. Brain activity was acquired using functional MRI (fMRI), a technique that allows collection of dynamic signals from within the brain when the subject is doing a task as well as when they are at rest.
Using relatively complex modelling of fMRI signals, the team studied brain network interactions between two important brain regions: the dorsal anterior cingulate cortex (dACC), used for control, and the supplementary motor area (SMA), used for motor movements. “These results suggest that directional interactions from the SMA to the dACC during the rest period may in fact
potentiate task-related interactions in the opposite direction,” said Professor Vaibhav Diwadkar from Wayne State University’s School of Medicine.
He noted that the studies confirm what has been long suggested and independently demonstrated: that the brain’s networks are always in a state of potentiation for action, precisely because it is impossible to predict what they will
be required to do at any given time. It is unlikely that the brain can ever be at true rest, researchers said.
The research is one of the few attempts to systematically investigate directional interactions between brain networks in the resting state and show how this state might potentiate the opposite direction of the same network task-related processing. “Our findings are compelling because brain networks are in patterns of incessantly complex directional interactions,” said Diwadkar.
“Directionality is difficult to measure, and our complex analyses show that it is possible to estimate this from fMRI data,” he said. The study was published in the journal PLoS One.
