Estimating distributed coding efficiency in orthogonal models of facial processing.

Abstract

Orthogonal facial processing models attempt to mimic the local decomposition performed in the visual cortex by simple cell receptive fields. The purpose of this study was to investigate how the neurophysiological validity of orthogonal models of facial processing could be improved by implementing a "whitening" filter, based on current knowledge of similar filtering that occurs in the retina. By using a metric known as the "distributed coding efficiency index" (DCE), this study demonstrates that an orthogonal facial processing model significantly increased coding efficiency when a low-pass, zero-phase whitening filter was applied. The extent to which orthogonal decomposition of filtered data represents a realistic V1 model is discussed.