One feature of visual systems that is very important is detection of image motion. Such motion may occur across the visual field, or have a component toward or away from the observer, called "motion in depth." To understand how the visual system handles motion it is important to learn how nerve cells in the complex network of the visual cortex respond physiologically to moving stimuli, including selectivity to particular directions or velocities of motion. This project combines a mathematical modelling approach with physiological recording of single cortical neurons. The intent is to obtain detailed functional information about connectivity in the visual pathway that cannot be obtained through other methods such as anatomical labelling or tissue culture. Visual stimuli will be mainly those of a moving bar array which will be modulated in space and time, using the principles of "white noise" to produce a randomized stimulus sequence. One part of the study will test how velocity sensitivity may be modeled in cortical cells, and how it may suggest connectivity and cellular mechanisms for that selectivity. The other part will test selectivity for movement sensitivity in three dimensions, analyzing monocular and binocular responses to the stimulus components. This powerful approach should give results that will have an impact not only on visual neuroscience, but also on computer vision, artificial intelligence, and neural networks.
