Coupled Intrinsic Connectivity: A Principled Method for Exploratory Analysis of Paired Data

Abstract

We present a novel voxel-based connectivity approach for paired functional magnetic resonance imaging (fMRI) data collected under two different conditions labeled the Coupled Intrinsic Connectivity Distribution (coupled-ICD). Our proposed method jointly models both conditions to incorporate additional spatial information into the connectivity metric. When presented with paired data, conventional voxel-based methods analyze each condition separately. However, nonlinearities introduced during processing can cause this approach to underestimate differences between conditions. We show that commonly used methods can underestimate functional changes and evaluate our coupled-ICD solution using a study comparing cocaine-dependent subjects and healthy controls. Our approach detected differences between paired conditions in similar brain regions as the conventional approaches while revealing additional changes. Follow-up seed-based analysis confirmed, via cross validation, connectivity differences between conditions in regions detected by coupled-ICD that were undetected using conventional methods. This approach of jointly analyzing paired connectivity data provides a new and important tool with many clinically relevant applications.