Heading direction

…which determine the organism's heading direction. We formulate a neural field model within the mean field approximation to provide a microscopic description of the spontaneous formation of bifurcations along their movement trajectories towards multiple targets, as observed in recent animal experiments. The direction of movement corresponds to the position of the a

…are able to track uncertainty in heading direction only if they are tuned to feature slow dynamics. Second, I will show that approximate computations that only partially track uncertainty are sufficient to perform cl

Efficient navigation requires animals to track their position, velocity and heading direction (HD). Some animals’ behavior suggests that they also track uncertainties about these navigational variables, and make strategic use of these uncertainties, in line with a Bayesian computation. Ring-attractor networks have been proposed to estimate and track these navigational variables, for instance in the HD system of the fruit fly Drosophila. However, such networks are not designed to incorporate a notion of uncertainty, and therefore seem unsuited to implement dynamic Bayesian inference. Here, we c

…when the animal faces a particular direction in the world reference frame have been recorded in mammillary bodies and entorhinal cortex. The heading direction can be read out using a weighted sum of the activation of those cells. This dynamics is well described by a “ring attractor” model: the network has

Efficient navigation requires animals to track their position, velocity and heading direction (HD). Some animals’ behavior suggests that they also track uncertainties about these navigational variables, and make strategic use of these uncertainties, in line with a Bayesian computation. Ring-attractor networks have been proposed to estimate and track these navigational variables, for instance in the HD system of the fruit fly Drosophila. However, such networks are not designed to incorporate a notion of uncertainty, and therefore seem unsuited to implement dynamic Bayesian inference. Here, we c

…but also the prevailing wind direction. Moreover, we found that the compass system can re-learn the relationship between these external sensory cues

In a cross wind, the direction a fly moves through the air may differ from its heading direction, the direction defined by its body axis. I will present a model based on experimental results that reveals how a heading direction “compass” signal is combined with optic flow to compute and represent the direction that a fly is traveling. This provides a general framework for understand how flies perform vector computations.