Optimal experimental designs for fMRI via circulant biased weighing designs

TL;DR

This paper develops a theoretical framework linking fMRI experimental design to circulant biased weighing designs, establishing optimality and proposing new design classes for better estimation of brain responses.

Contribution

It introduces a general theory connecting fMRI design selection to circulant biased weighing designs and provides methods for constructing high-quality fMRI experimental designs.

Findings

Established the statistical optimality of some known fMRI designs.

Identified new classes of optimal fMRI designs.

Provided construction methods for high-quality fMRI designs.

Abstract

Functional magnetic resonance imaging (fMRI) technology is popularly used in many fields for studying how the brain reacts to mental stimuli. The identification of optimal fMRI experimental designs is crucial for rendering precise statistical inference on brain functions, but research on this topic is very lacking. We develop a general theory to guide the selection of fMRI designs for estimating a hemodynamic response function (HRF) that models the effect over time of the mental stimulus, and for studying the comparison of two HRFs. We provide a useful connection between fMRI designs and circulant biased weighing designs, establish the statistical optimality of some well-known fMRI designs and identify several new classes of fMRI designs. Construction methods of high-quality fMRI designs are also given.