Fig. 1: The Drosophila HD system.

a, HD cells (EPG neurons) form a ring attractor network in the EB. Their axons project to the PB, where they form two linearized topographic maps of HD. b, The position of the EPG activity bump is influenced by ER neurons that encode the positions of visual HD cues or the direction of the wind. ER neurons are inhibitory and the most active ER neurons push the bump to the location where their inhibitory output is minimal. ER → EPG connections are anatomically all-to-all but their weights are shaped by Hebbian plasticity at ER → EPG synapses, such that each ER neuron generally makes functional synapses onto only a subset of EPG neurons. c, Schematic ER → EPG weights. Given a single visual cue and a steady wind direction, associative LTD is predicted to produce a diagonal notch of weak connections in each weight matrix. EPG neurons are sorted by their preferred HD. ER neurons are sorted by their preferred cue position. If the two cues are aligned in the simulated environment, Hebbian plasticity should align the notches. d, We hypothesize that cue salience and stability affect bump attractor dynamics and learning. e, We image EPG neurons in head-fixed flies walking on a spherical treadmill. As the fly turns on the spherical treadmill, the virtual environment rotates around the fly in the expected direction. Here, the environment contains a bright vertical stripe that serves as an HD cue. f, The bump of EPG activity tracks the fly’s fictive HD in a virtual reality environment, with a relatively constant angular offset. Bump position rotates clockwise in the EB (imaged from the posterior side of the head) as HD rotates counterclockwise; therefore, to account for this directionality, we always plot (−HD) to make it easier to visualize the correspondence between bump position and HD.