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.

Subcortical Representation of Non-Fourier Image Features

“…Visual stimuli were generated by computer and displayed monocularly on a gamma-corrected 21 inch cathode ray tube monitor with a mean luminance 26 cd/m 2 using the Psychophysics Toolbox extensions (Brainard, 1997) for MATLAB (The MathWorks). The linear relationship between stimulus intensity commanded by the software and the output luminance of the monitor was confirmed in two ways: (1) with a light meter (Konica Minolta, Model LS-100) and (2) as previously described (Zhang et al, 2007), by performing a fast Fourier transform on visual stimuli photographed with a Dalsa 1M30 CCD camera. All stimuli were presented as full-field images covering 43°ϫ 57°of visual space, and the monitor was refreshed at 100 Hz.…”

“…However, this relationship was not found for guinea pig retinal ganglion Y-cells in vitro (Demb et al, 2001). The different cortical TF tuning curves may then bolster the argument for an intracortical origin of non-Fourier responses, as the higher grating TF cutoff may reflect properties inherent to area 18 neurons and the lower envelope TF cutoff is consistent with input from area 17 (Allison et al, 2001;Zhang et al, 2007). Recording from LGN Y-cells allowed us to examine the relationship between grating and envelope TF tuning curves in the subcortical neurons projecting to cortex.…”

BOLD neurovascular coupling does not change significantly with normal aging

“…First, the neural input function was not measured directly. Thus, our conclusions only apply to primary sensory cortices where the neural input function can be assumed to match the time course of the stimulus [Albrecht and Hamilton, ; Boynton, ; Carandini and Sengpiel, ; Logothetis et al, ; Zhan et al, ; Zhang et al, ]. Though aging has been shown to affect the firing properties of sensory neurons [Fu et al, ; Leventhal et al, ; Schmolesky et al, ; Wang et al, ; Zhang et al, ], its effect on aggregate neural activity in sensory cortex is relatively small.…”

“…Thus the input function is usually not known. However, physiological work has demonstrated that in the primary sensory cortex, the time course of the neuronal response closely matches the time course of the sensory stimulus (Albrecht and Hamilton, 1982;Boynton, 2011;Carandini and Sengpiel, 2004;Logothetis et al, 2001;Zhan et al, 2005;Zhang et al, 2007]. Thus, we assume that within primary visual and primary auditory cortex, n t ð Þ sensory input where n(t) represents the time course of the neural input function.…”

Whither the hypercolumn?

“…To be sure, other systematic representations of stimulus parameters have been reported, including orientation, direction and disparity in primate MT (DeAngelis & Newsome, 1999; Diogo et al 2008), direction and spatial frequency in cat area 17 and 18 (Issa et al 2000; Shmuel & Grinvald, 1996; Zhang et al 2007; but see Sirovich & Uglesich, 2004), frequency bandwidth and space/localization in auditory cortex (e.g. Read et al 2001), as well as higher order properties (e.g.…”