The motivation for our data-driven approach is to confirm the patterns of dysfunction linked to alcohol (general disconnection) and nicotine (network dysfunction) derived from seed based analyses. Instead, we expect to observe these patterns of intrinsic connectivity using a whole brain analysis. We also expect to identify aspects of network dysfunction not previously found in the literature that can help refining future studies of substance use. Another goal is to find the main effects that discriminate between substances as well as effects that characterize their interaction. We chose to use the gICA approach because it is especially useful for capturing both specific and unique aspects of the connectivity.
