Factorial Coding of Color in Primary Visual Cortex

We introduce the notion of Morton-style factorial coding and illustrate how it may help understand information integration and perceptual coding in the brain. We show that by focusing on average responses one may miss the existence of factorial coding mechanisms that become only apparent when analyzing spike count histograms. We show evidence suggesting that the classical/non-classical receptive field organization in the cortex effectively enforces the development of Morton-style factorial codes. This may provide some cues to help understand perceptual coding in the brain and to develop new unsupervised learning algorithms. While methods like ICA (Bell & Sejnowski, 1997) develop independent codes, in Morton-style coding the goal is to make two or more external aspects of the world become independent when conditioning on internal representations. In this paper we introduce the notion of Morton-style factorial coding and illustrate how it may help analyze information integration and perceptual organization in the brain. In the neurosciences factorial codes are often studied in the context of mean tuning curves. A tuning curve is called separable if it can be expressed as the product of terms selectively influenced by different stimulus dimensions. Separable tuning curves are taken as evidence of factorial coding mechanisms. In this paper we show that by focusing on average responses one may miss the existence of factorial coding mechanisms that become only apparent when analyzing spike count histograms. Morton (1969) analyzed a wide variety of psychophysical experiments on word perception and showed that they could be explained using a model in which stimulus and context have separable effects on perception. More precisely, in Mortons’ model the joint effect of stimulus and context on a perceptual representation can be obtained by multiplying terms selectively controlled by stimulus and by context, i.e.,