Detecting brain activation in FMRI data without prior knowledge of mental event timing

Abstract

Almost all methods of detecting brain activation in fMRI data depend on prior knowledge of mental event timing. For example, the investigator may be required to stipulate the short time intervals during which mental activity occurs. In addition, the hemodynamic response to mental activity is often assumed to be linearly additive, and the shape of that response is frequently estimated or modeled. Analysis methods that do not make these assumptions still require prior knowledge of characteristics of the spatial distribution of neural activity. This paper describes a new method of analyzing fMRI data that does not rely on any of these assumptions. Instead, our approach is based on the following simple premise: the time course of signal in activated voxels will not vary significantly when an entire task protocol is repeated by the same individual. The model-independence of this approach makes it suitable for "screening" fMRI data for brain activation that may have unanticipated timing. Retrospective examination of the time course of the detected signals may be used to understand the nature of the activity. We demonstrate the method by using it to detect brain activation in two subjects who performed hand sensorimotor tasks according to block and single-trial designs.