The Representation of Complex Images in Spatial Frequency Domains of Primary Visual Cortex

Abstract

The organization of cat primary visual cortex has been well mapped using simple stimuli such as sinusoidal gratings, revealing superimposed maps of orientation and spatial frequency preferences. However, it is not yet understood how complex images are represented across these maps. In this study, we ask whether a linear filter model can explain how cortical spatial frequency domains are activated by complex images. The model assumes that the response to a stimulus at any point on the cortical surface can be predicted by its individual orientation, spatial frequency, and temporal frequency tuning curves. To test this model, we imaged the pattern of activity within cat area 17 in response to stimuli composed of multiple spatial frequencies. Consistent with the predictions of the model, the stimuli activated low and high spatial frequency domains differently: at low stimulus drift speeds, both domains were strongly activated, but activity fell off in high spatial frequency domains as drift speed increased. To determine whether the filter model quantitatively predicted the activity patterns, we measured the spatiotemporal tuning properties of the functional domains in vivo and calculated expected response amplitudes from the model. The model accurately predicted cortical response patterns for two types of complex stimuli drifting at a variety of speeds. These results suggest that the distributed activity of primary visual cortex can be predicted from cortical maps like those of orientation and SF preference generated using simple, sinusoidal stimuli, and that dynamic visual acuity is degraded at or before the level of area 17.