Introduction

Intrinsic connectivity networks (ICNs) in schizophrenia (SZ) exhibit aberrant resting state connectivity based on regional temporal correlations relative to healthy subjects [Fornito et al., 2012]. We examined ICNs displaying abnormal connectivity in schizophrenia in an rsfMRI study and related them to similar networks extracted from the BrainMap database. BrainMap meta-analyses have identified several reliable and meaningful circuits of coactivations, i.e., areas commonly reported together in various neuroimaging analyses [Laird et al., 2013]. These circuits have been linked to coactivation networks in resting state datasets, leading to the hypothesis that they represent intrinsic networks underlying cognitive processes [Laird et al., 2011]. Here, we provide a new method of linking resting state connectivity differences to predicted cognitive deficits using metadata archived in the BrainMap database.