No abstract

When an animal moves through the world, its brain receives a stream of information about the body's translational movement. These incoming movement signals, relayed from sensory organs or as copies of motor commands, are referenced relative to the body. Ultimately, such body-centric movement signals must be transformed into world-centric coordinates for navigation [1]. Here we show that this computation occurs in the fan-shaped body in the Drosophila brain. We identify two cell types in the fan-shaped body, PFNd and PFNv [2,3], that conjunctively encode translational velocity signals and heading signals in walking flies. Specifically, PFNd and PFNv neurons form a Cartesian representation of body-centric translational velocity — acquired from premotor brain regions [4,5] — that is layered onto a world-centric heading representation inherited from upstream compass neurons [6-8]. Then, we demonstrate that the next network layer, comprising hΔB neurons, is wired so as to transform the representation of translational velocity from body-centric to world-centric coordinates. We show that this transformation is predicted by a computational model derived directly from electron microscopy connectomic data [9]. The model illustrates the key role of a specific network motif, whereby the PFN neurons that synapse onto the same hΔB neuron have heading-tuning differences that offset the differences in their preferred body-centric directions of movement. By integrating a world-centric representation of travel velocity over time, it should be possible for the brain to form a working memory of the path traveled through the environment [10-12].

To navigate, we must continuously estimate the direction we are headed in, and we must use this information to guide our path toward our goal1. Direction estimation is accomplished by ring attractor networks in the head direction system2,3. However, we do not understand how the sense of direction is used to guide action. Drosophila connectome analyses4,5 recently revealed two cell types (PFL2 and PFL3) that connect the head direction system to the locomotor system. Here we show how both cell types combine an allocentric head direction signal with an internal goal signal to produce an egocentric motor drive. We recorded their activity as flies navigated in a virtual reality environment toward a goal stored in memory. Strikingly, PFL2 and PFL3 populations are both modulated by deviation from the goal direction, but with opposite signs. The amplitude of PFL2 activity is highest when the fly is oriented away from its goal; activating these cells destabilizes the current orientation and drives turning. By contrast, total PFL3 activity is highest around the goal; these cells generate directional turning to correct small deviations from the goal. Our data support a model where the goal is stored as a sinusoidal pattern whose phase represents direction, and whose amplitude represents salience. Variations in goal amplitude can explain transitions between goal-oriented navigation and exploration. Together, these results show how the sense of direction is used for feedback control of locomotion.