Spatial Integration of Color by V1 Neurons

Our lab is interested in understanding how V1 neurons combine light information across their spatial receptive fields (RFs). Decades of work using  achromatic bars and Gabors have generated quantitative linear models whereby a V1 neuron performs a weighted sum of light signals across its spatial receptive field to generate a response. This model works works well for V1 neurons that are maximally sensitive to achromatic edges; however, it is unknown if V1 neurons which are primarily sensitive to color perform a similar computation of light signals (Refer Fig 2 for different predictions).

To test this, we record from V1 neurons in awake behaving monkeys. We use white noise stimuli to characterize the spatiochromatic RF using spike triggered averaging (Fig 1 A & B). Next, we present stimuli that activate non-overlapping regions of the RF individually or simultaneously. Using an adaptive closed-loop stimulus generator, we identify stimuli that drive the same neuronal response but differ in how strongly they activate two regions of the RF. We define the collection of stimuli that elicit the same target firing rate as an isoresponse contour in the space of stimulus contrast (Fig 2). The shape of the isoresponse contour reveals how stimulation of the two RF regions drive the target response.

Fig 3. shows two example neurons which are most sensitive to colored light. The neuron in Fig 3A responds maximally to a blue-yellow edge. The isoresponse contour is a line suggesting this particular V1 neuron combines color signals linearly across space. The neuron in Fig 3B responds maximally to a red-cyan edge. This neuron combines color signals non-linearly across space, as is revealed by the isoresponse contour.