Characterizing the color tuning of a neuron is easy if its response is linearly related to signals from the three classes of cone photoreceptor. In this case, a set of only three numbers (e.g. the weight from each cone type) is sufficient to describe neuronal color tuning. We are investigating how well this model describes the responses neurons in the primary visual cortex of macaque monkeys.
Under the model, the collection of stimuli that give rise to a given neuronal response (e.g. 10 spikes/sec) lie on a plane in 3-D color space. To test this prediction, we measure the isoresponse surfaces of individual V1 neurons using an adaptive algorithm. The isoresponse surfaces of some neurons are well approximated by planes, but for other neurons this approximation is poor. We would like to understand how the shapes of isoresponse surfaces are related to preferred colors, and how these shapes influence human color perception.