Overview of experimental analyses.

<p>The schematic summaries the modeling experiments undertaken in the present study. Symbols are introduced that describe how the HCP task data (<i>green</i>), the ARCHI task data (<i>yellow</i>), and the rest data (<i>blue</i>) were used to (<i>A</i>) evaluate the idea of network co-occurrence modeling and (<i>B</i>) test explicit hypotheses about the commonalities and differences between human brain activity in task-constrained and idling brain states [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004994#pcbi.1004994.ref003" target="_blank">3</a>, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004994#pcbi.1004994.ref006" target="_blank">6</a>]. <i>Stars</i> indicate brain networks derived as mutually overlapping spatiotemporal patterns from independent component analysis (ICA), principle component analysis (PCA), sparse PCA, and factor analysis (FA). <i>Cubes</i> indicate discrete brain regions derived as mutually disjoint voxel groups from k-means and ward clustering. <i>Empty stars</i> or <i>cubes</i> indicate learning a network decomposition or region segregation from brain activity maps without the task labels (i.e., "unsupervised statistical learning"). <i>Filled stars</i> or <i>cubes</i> indicate learning a classification algorithm of 18 typical psychological tasks based on brain activity maps summarized as networks or regions with the task labels (i.e., "supervised statistical learning"). The origin of the <i>arrows</i> indicate from what data (HCP tasks, ARCHI tasks, or rest) the networks and regions were obtained. The <i>arrows</i> point to the set of psychological tasks that was captured by a predictive model based on the previously derived networks and regions. These symbols indicate the provenance of the results shown in the other figures.