To effectively control their bodies, animals rely on feedback from proprioceptive mechanosensory neurons. In the Drosophila leg, different proprioceptor subtypes monitor joint position, movement direction, and vibration. Here, we investigate how these diverse sensory signals are integrated by central proprioceptive circuits. We find that signals for leg joint position and directional movement converge in second-order neurons, revealing pathways for local feedback control of leg posture. Distinct populations of second-order neurons integrate tibia vibration signals across pairs of legs, suggesting a role in detecting external substrate vibration. In each pathway, the flow of sensory information is dynamically gated and sculpted by inhibition. Overall, our results reveal parallel pathways for processing of internal and external mechanosensory signals, which we propose mediate feedback control of leg movement and vibration sensing, respectively. The existence of a functional connectivity map also provides a resource for interpreting connectomic reconstruction of neural circuits for leg proprioception.

See manuscript (https://faculty.washington.edu/tuthill/docs/functionalconnectivity.pdf) for details.

Data description:

This dataset includes calcium signals (quantified as DFF) of the downstream cell types labelled by LexA driver lines in the ventral nerve cord while optogenetically stimulating different sensory neurons subclasses in the Drosophila Femoral Chordotonal Organ (FeCO), which are club, claw, hook-f (short for hook-flexion) and hook-e (short for hook-extension). Lineage identity for each LexA lines can be found in Figure S2 in the paper. For each combination of sensory and central neurons, the following time series data are provided as *.mat files, which can be opened in Matlab:

dff:  DF/F time series recorded from each fly. Imaging data was sampled at 8.9 frames per second (fps)

dff_avg: mean DF/F from experimental flies (same as dff)

image_vec: Imaging time. (same as dff)

stim_ts: optogenetic stimulation intensity. The stimulus time series was sampled at 100 samples per second.

stim_vec: stimulation time (100 Hz)

From Chen et al., 2021. https://doi.org/10.1016/j.cub.2021.09.035

For additional requests, contact tuthill@uw.edu.