Colour and form in the early stages of cortical processing.
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Animals↗
Biomedical subjects
Daniel C Kiper
Publications and source records attributed to Daniel C Kiper.
Color vision.
Color vision starts with the absorption of light in the retinal cone photoreceptors, which transduce electromagnetic energy into electrical voltages. These voltages are transformed into action potentials by a complicated network of cells in the retina. The information is sent to the visual cortex via the lateral geniculate nucleus (LGN) in three separate color-opponent channels that have been characterized psychophysically, physiologically, and computationally. The properties of cells in the retina and LGN account for a surprisingly large body of psychophysical literature. This suggests that several fundamental computations involved in color perception occur at early levels of processing. In the cortex, information from the three retino-geniculate channels is combined to enable perception of a large variety of different hues. Furthermore, recent evidence suggests that color analysis and coding cannot be separated from the analysis and coding of other visual attributes such as form and motion. Though there are some brain areas that are more sensitive to color than others, color vision emerges through the combined activity of neurons in many different areas.
Animals↗
The detection of colored Glass patterns.
The detection of many chromatic stimuli is mediated by mechanisms that sum their inputs linearly. As a result, these mechanisms have a broad range of selectivity in color space, as do the majority of cells in the early stages of visual processing. In extrastriate cortex, there are cells with a narrow tuning in color space. The function of these cells is not fully understood: they could be involved in color categorization, or could mediate the detection of stimuli such as Glass patterns, whose properties make them undetectable by early stages of processing. We measured the tuning properties of the mechanisms responsible for the detection of colored Glass patterns and found that they have a broad tuning in color space. Our results suggest that Glass patterns are detected by a multitude of mechanisms that sum their inputs linearly.
Color Perception↗
Suppression without inhibition in visual cortex.
Neurons in primary visual cortex (V1) are thought to receive inhibition from other V1 neurons selective for a variety of orientations. Evidence for this inhibition is commonly found in cross-orientation suppression: responses of a V1 neuron to optimally oriented bars are suppressed by superimposed mask bars of different orientation. We show, however, that suppression is unlikely to result from intracortical inhibition. First, suppression can be obtained with masks drifting too rapidly to elicit much of a response in cortex. Second, suppression is immune to hyperpolarization (through visual adaptation) of cortical neurons responding to the mask. Signals mediating suppression might originate in thalamus, rather than in cortex. Thalamic neurons exhibit some suppression; additional suppression might arise from depression at thalamocortical synapses. The mechanisms of suppression are subcortical and possibly include the very first synapse into cortex.
Action Potentials↗
Testing the Bayesian model of perceived speed.
In a recent Bayesian model by Weiss, Simoncelli, and Adelson, motion perception is biased by a prior favoring slow speeds. This model predicts qualitatively an impressive variety of phenomena, including the dependence of perceived speed on contrast. We show that the model can also generate quantitative predictions: for a drifting grating with contrast c, perceived speed is proportional to c(q)/(k(q) + c(q)), with k, q constants. We tested this expression on measurements of perceived speed as a function of contrast. Observers indicated the slower of two drifting gratings, a test and a standard. For each test contrast we found the test speed that appeared to match the standard speed. The model fits the data, but only if q is less than 2, the value it would have if the internal representation of contrast were linear. The Bayesian model can make correct quantitative predictions, but needs to be extended to incorporate a more realistic, nonlinear representation of contrast.
Bayes Theorem↗
The effect of moving textures on the responses of cells in the cat's dorsal lateral geniculate nucleus.
Neurons in the dorsal lateral geniculate nucleus (dLGN) of the anaesthetized cat were activated with test stimuli (flashing spots, counterphased gratings and moving bars) in the presence of a moving background texture. Moving texture alone produced mild excitation, as a result of stimulation of the receptive field centre. Fast moving coarse textures were more effective than fine slow moving textures. The predominant effect of texture motion, however, was to reduce the response to all test stimuli displayed in the receptive field centre. The effects were similar for X- and Y-like cells. In the case of flashed spots, the sustained response was more strongly suppressed than the transient response. The direction of motion of the texture and differences in the relative motion of bar and texture had no influence on the degree of suppression. These observations are similar to effects seen on cat retinal ganglion cells, and are probably a form of gain control. Such suppressive effects are transmitted to the cortex and are likely to be evoked by large gratings, textures and by natural stimuli, all of which activate extensive regions of the receptive field surround.
Action Potentials↗