How neurons detect the direction of motion is a prime example of neural computation: Motion vision is found in the visual systems of virtually all sighted animals, it is important for survival, and it requires interesting computations with well-defined linear and nonlinear processing steps—yet the whole process is of moderate complexity. Research on motion vision was pioneered by Werner Reichardt, who, together with Bernhard Hassenstein, proposed a correlation-type motion detector model that could account for their observations of insect optomotor behavior in a quantitative way. However, what neurons constitute the model and what biophysical mechanisms underly the various operations defined algorithmically in the model remained elusive for many decades. Only recently, the genetic methods available in the fruit fly Drosophila and the charting of a connectome of its visual system have led to rapid progress and unprecedented detail in our understanding of how neurons compute the direction of motion in this organism. The picture that emerged incorporates not only the identity, morphology, and synaptic connectivity of each neuron involved but also its neurotransmitters, its receptors, and their subcellular localization. Together with the neurons’ membrane potential responses to visual stimulation, this information provides the basis for a biophysically realistic model of the circuit that computes the direction of visual motion and reveals the neural implementation of the algorithmic model proposed by Werner Reichardt almost 70 years ago.
Organizer
Chris de Zeeuw
c.dezeeuw@erasmusmc.nl