The concept of cognitive reserve proposes that specific life experiences result in more flexible or resilient cognitive processing that allows some people to cope better than others with age- or disease-related brain changes. Imaging studies seeking to understand the neural implementation of cognitive reserve have most often used task-related fMRI studies. Using that approach, we recently described a task-invariant cognitive reserve network whose expression correlated with IQ and that moderated between cortical thickness and cognitive performance. Here we sought to identify a pattern of resting BOLD connectivity related to cognitive reserve. We identified a connectome pattern whose connectivity correlated with IQ both the derivation sample and a separate replication sample. The majority of the edges showing positive relationships with IQ implicate frontal regions. In the derivation sample, connectivity either moderated the relationship between mean cortical thickness and a set of cognitive outcomes or accounted for unique variance in cognitive performance after accounting for cortical thickness. In a replication sample we found that expression of this connectome accounted for unique variance in cognitive performance beyond cortical thickness. Our findings represent an intermediate level of replication  and are very unlikely to have arisen purely by type-I error. This connectivity pattern therefore meets our theoretical criteria for a cognitive reserve-related network. In addition to providing insight into the neural implementation of cognitive reserve, expression of this connectome could potentially be used as a direct measure of cognitive reserve, and as an outcome measure for intervention studies that seek to influence cognitive reserve.

Pre-processing and analysis steps can be found with detailed explanation in the published manuscript

Variables are explained in detail in accompanying manual  (README.docx) . The source code in matlab is annotated in the *.m files; all data are stores in  *.mat files Sample use of the source code has been provided in the accompanying manual  (README.docx)

Contents:

Manual explaining all variables and several analysis streams:    README.docx

3 Matlab data archives:                                                                NKI_data.mat, CUMC_data.mat, and CUMC_results.mat

Several  *.m files, including derivation of a functional-connectivity pattern, performing LOOCV and bootstrap estimation; brain-behavioral analysis to generate tables 3 and 4 in the manuscript; and code to generate figure 2 in the manuscript.