Stimulus optimisation in primary visual cortex

Abstract A computational method is introduced for finding effective stimuli for sensory neurons. In single unit recording experiments, it maximises simultaneously recorded responses by changing stimuli along an estimated gradient with respect to stimuli. The estimate is the correlation between noise added to an evolving base stimulus and the response. Pixel optimisation for monkey V1 rapidly produces stimuli consistent with conventionally determined tuning even for complex cells. For the same complex cell, repeated runs of the optimisation gave solutions with different phase. Unlike reverse correlation, this method is applicable to non-linear, context-sensitive cells, possibly also in higher sensory areas.