I did my second M. Sc. project under the supervision of Bruce Cumming and Andrew Parker in the Physiology Laboratory at Oxford, and this turned out to be the beginning of a long and fruitful collaboration which saw me moving to the States for 4 years. My project related to an interesting observation Andrew and Bruce had just made in their influentual Nature paper of 1997. This tied in nicely with my project with Richard, because it also involved anti-correlated stimuli. Bruce and Andrew had measured the response of disparity-sensitive neurons in V1 to anti-correlated random-dot stereograms. The highly successful energy model of these neurons, proposed 7 years earlier by Ohzawa, DeAngelis and Freeman in Science, predicted that their disparity tuning curves should invert when they were probed with anti-correlated stimuli. Sure enough, in a triumph for theoretical neuroscience, the curves did invert. However, their amplitude also decreased, and this was not predicted by the model. Because anti-correlated stimuli do not cause a perception of depth, it was possible that this reduction in amplitude represented feedback (or the absence of expected feedback) from higher brain areas. However, it was also possible that a suitable feedforward model might also give a reduced amplitude for anti-correlated stimuli. Andrew and Bruce asked me to see if I could find such a model.
It turned out to be quite simple to modify the stereo energy model to produce this. All you have to do is apply half-wave rectification before inputs from the two eyes are combined, as opposed to after binocular combination as in the energy model. So, the reduction in amplitude does not necessarily depend on feedback from extrastriate areas.
In theory, I would have used this modified version of the energy model in all my subsequent modelling, on the grounds that it more accurately captures the behaviour of real neurons. However, the energy model is very easy to analyse mathematically, whereas the additional non-linearity makes my model almost impossible to say anything about analytically (at least, I haven't been able to!). So, in most of my subsequent population models, I have used the energy model to describe V1 cells. I feel quite fond of this paper, because it was my first encounter with the wonderful stereo energy model of Ohzawa et al. 1990. Much of my subsequent work has been trying to understand the behaviour of this deceptively simple model.
It turned out to be quite simple to modify the stereo energy model to produce this. All you have to do is apply half-wave rectification before inputs from the two eyes are combined, as opposed to after binocular combination as in the energy model. So, the reduction in amplitude does not necessarily depend on feedback from extrastriate areas.
In theory, I would have used this modified version of the energy model in all my subsequent modelling, on the grounds that it more accurately captures the behaviour of real neurons. However, the energy model is very easy to analyse mathematically, whereas the additional non-linearity makes my model almost impossible to say anything about analytically (at least, I haven't been able to!). So, in most of my subsequent population models, I have used the energy model to describe V1 cells. I feel quite fond of this paper, because it was my first encounter with the wonderful stereo energy model of Ohzawa et al. 1990. Much of my subsequent work has been trying to understand the behaviour of this deceptively simple model.