Results
Before reporting our main findings, we provide a brief summary of our methods to ensure that our later exposition is clear and accessible. Specifically, we investigated functional mechanisms that facilitate network reorganization associated with value learning by assessing ISC (Fig. 1A) and ISFC (Fig. 1B) estimated from functional MRI (fMRI) data acquired in 20 healthy subjects (9 females; ages 19-53 years; mean age = 26.7 years) over four consecutive days. Each scanning session contained both data collected while the subject rested and data collected while the subject engaged in a value-learning task. From each session, we extracted the BOLD time series of 112 cortical and subcortical regions defined by the Harvard-Oxford atlas \cite{smith2004advances, woolrich2009bayesian}. We next measured ISC by estimating the correlation between regional BOLD signal time series for each pair of \(S\) subjects. This procedure resulted in an \(S\times S\) correlation matrix for each brain region. Next, we constructed a functional connectivity matrix for each subject and each scan, where each ijth element in the \(N\times N\) matrix indicated the wavelet coherence between the time series of region i and the time series of region j. We then measured ISFC for a given subject and region \(i\) by computing the Pearson correlation between row \(i\) in that subject’s functional connectivity matrix and the average of row \(i\) in all of the other subjects’ functional connectivity matrices. We performed this calculation for every region, resulting in an ISFC array of length \(N\) for each subject. For additional methodological details, see Materials and Methods and Supplementary Information.