PT  - JOURNAL ARTICLE
AU  - Michael W. Cole
AU  - Takuya Ito
AU  - Danielle S. Bassett
AU  - Douglas H. Schultz
TI  - Activity flow over resting-state networks shapes cognitive task activations
AID  - 10.1101/055194
DP  - 2016 Jan 01
TA  - bioRxiv
PG  - 055194
4099  - http://biorxiv.org/content/early/2016/05/24/055194.short
4100  - http://biorxiv.org/content/early/2016/05/24/055194.full
AB  - Resting-state functional connectivity (FC) has helped reveal the intrinsic network organization of the human brain, yet its relevance to cognitive task activations has been unclear. Uncertainty remains despite evidence that resting-state FC patterns are highly similar to cognitive task activation patterns. Identifying the distributed processes that shape localized cognitive task activations may help reveal why resting-stateFC is so strongly related to cognitive task activations. We found that estimating task-evoked activity flow (the spread of activation amplitudes) over resting-state FC networks allows prediction of cognitive task activations in a large-scale neural network model. Applying this insight to empirical functional MRI data, we found that cognitive task activations can be predicted in held-out brain regions (and held-out individuals via estimated activity flow over resting-state FC networks. This suggests that task-evoked activity flow over intrinsic networks is a large-scale mechanism explaining the relevance of resting-state FC to cognitive task activations.