Information transfer rate in fMRI experiments measured using mutual information theory

Abstract

Information theory provides a mathematical framework for analysis of fMRI experiments. By modeling the fMRI experiment as a communication system, various results from information theory can be applied to measure information transfer rate in fMRI experiments. The information transfer rate has important implications for design and analysis of brain–computer interface (BCI) experiments. A key factor in the effective implementation of BCI techniques is to achieve maximum information transfer rate. In this report, mutual information rate (MIR) was used to evaluate the efficiency of alternative experimental designs. The channel capacity, a fundamental physical limit on the rate at which information can be extracted from an fMRI experiment, was estimated and compared with the theoretical limit specified by the Hartley–Shannon Theorem. We present an information theory framework for the analysis of fMRI time-series assuming a known hemodynamic response function. Using MIR to evaluate fMRI experimental designs, we show that block lengths of 3–5 s have maximum information transfer rates. For designs with shorter block lengths, the MIR is limited by the channel capacity. For experimental designs with longer block lengths, the MIR is limited by the low source information transmission rate.