Models of motion detection

history Visual motion detection is one of the most active areas in systems neuroscience today 1,2 , and the cellular mechanisms of directional selectivity may soon be understood in unprecedented biophysical detail. Alongside undeniable technical advances such as whole-cell patch-clamp recording and the retinal slice preparation, a major determinant of this recent progress is the conceptual foundation laid almost half a century ago. Curiously, the story began with two young soldiers during World War II. A biology student, Bernhard Hassenstein, then 21, met a 19-year-old aspiring physicist , Werner Reichardt. In the craziness of wartime, they promised each other that, if they survived, they would do something great together: start the first institute of physics and biology. In 1958 they founded the Research Group of Cybernetics at the Max-Planck-Institute of Biology in Tübin-gen, Germany. In a congenial collaboration , which still sounds like the goal of every summer school in computational neuroscience, they did a series of elegant experiments, using the opto-motor response of the beetle Cholorphanus as a behavioral measure. This response is the animal's tendency to follow the movement of the visual surround to compensate for its mistaken perception of self-motion in the opposite direction. The beetle was glued to a rod so it could not move its body, head or eyes relative to the surround, but could express its behavior at decision points by rotating a 'Y-maze globe' under its feet (Fig. 1). Their results 3 led to the development of a model for motion detection that became known as the 'correlation-type motion detector', the 'Hassenstein-Reichardt model' or briefly—omitting half the original team—the 'Reichardt detector' (Fig. 2). The core computation in this model is a delay-and-compare mechanism: delaying the brightness signal as measured by one photoreceptor by a low-proposal that a shunting inhibition is the cellular implementation of the veto operation 9 , and from there directly to the current 'pre or post' debate over directionally selective ganglion cells 1. Thus, the Hassenstein-Reichardt model set the standard for how researchers thought about visual motion detection and how they designed experiments. In a more general sense, it introduced mathematical techniques and quantitative modeling to biology, clearly demonstrating that our intuition does not reach very far; instead we soon reach the point where the 'pen starts getting smarter than the person holding it'. Far beyond the question of whether the particular Hassenstein-Reichardt model is correct or not, this has …