Seminar Series

Stimulus search and optimisation for visual neurons

Conventional experimental methods involve finding effective stimuli to describe the selectivity of sensory neurons. This process is not easy even in low-level sensory areas, and becomes highly difficult and subjective in higher visual areas, such as V4 and IT. Earlier stochastic methods, such as reverse correlation, aim to give a more objective and automatic way of characterising neurons at the lowest levels, but are also limited by the context-sensitivity due to non-linearities. I will describe two novel approaches that can be applied to testing higher-level neurons: 1) stimulus winnowing using large sets of natural images, 2) stimulus optimisation using gradient ascent. I will describe these and illustrate their application to neurons in visual areas STSa and V1 complex cells, respectively.