While our understanding of the way single neurons process chromatic stimuli in the early visual pathway has advanced significantly in recent years, we do not yet know how these cells interact to form stable representations of hue. Drawing on physiological studies, we offer a dynamical model of how the primary visual cortex tunes for color, hinged on intracortical interactions and emergent network effects. After detailing the evolution of network activity through analytical and numerical approaches, we discuss the effects of the model’s cortical parameters on the selectivity of the tuning curves. In particular, we explore the role of the model’s thresholding nonlinearity in enhancing hue selectivity by expanding the region of stability, allowing for the precise encoding of chromatic stimuli in early vision. Finally, in the absence of a stimulus, the model is capable of explaining hallucinatory color perception via a Turing-like mechanism of biological pattern formation.

We present a model of color processing in which intracortical neuronal dynamics within the visual cortex serve as the substrate for hue perception. Our analytical and numerical treatments of the emergent behavior seek to characterize the population dynamics underlying chromatic processing within the visual cortex, as well the roles of the various cortical parameters in determining the selectivity of the steady-state network response. We show that the system is self-organizing, capable of encoding stable representations of hue regardless of the stimulus strength, and generating spontaneous color hallucinations in the absence of any input.

This content is only available as a PDF.

Author notes

Competing Interests: The authors have declared that no competing interests exist.

Handling Editor: Gustavo Deco

This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. For a full description of the license, please visit https://creativecommons.org/licenses/by/4.0/legalcode.