A novel single-trial methodology for studying brain response variability based on archetypal analysis

Abstract

The objective of this paper is to present a methodology for deriving an intelligible synopsis of single-trial (ST) variability in brain responses. An algorithmic procedure, relying on temporal patterning and built over archetypal analysis, is introduced. Archetypical brain waves are first derived from the ensemble of brain responses and then used to unfold the observed variability. Using these archetypes as anchor points, homogeneous groups of ST-responses are detected and contrasted with each other. The new methodology incorporates steps for organizing the variability and presenting it by means of low-dimensional maps. Magnetoencephalographic responses from a visual stimulation paradigm are used for demonstrating and validating the approach. The results show that a small number of archetypes is sufficient for describing reliably the response variability. The groups of ST-responses, delineated around these archetypes, reflect differences in the way the ongoing activity interacts with the incoming stimulus. Estimates of signal-to-noise ratio are utilized in order to demonstrate that there is a significant information loss when response variability is left untreated. Moreover, ensemble averaging is employed for uniquely recovering the “true” response. Archetypal analysis provides a concise description of response variability which potentially can contribute in the understanding of its origin.