Quantifying information flow in fMRI using the Kullbakc-Leibler divergence

Abstract

Extracting the directional interaction between activated brain areas from functional magnetic resonance imaging (fMRI) time series measurements of their activity is a significant step in understanding the process of brain functions. In this paper, the directional interaction between fMRI time series characterizing the activity of two neuronal sites is quantified using a measure derived from the Kullback-Leibler divergence. A parametric approach based on the autoregressive (AR) and autoregressive exogenous (ARX) modelling is proposed for estimating this measure. The links between the proposed measure and other existing information measures for quantifying the directional interaction between neuronal sites is discussed. The significance and effectiveness of the proposed measure is illustrated on both simulated and real fMRI data sets.