Synaptic targets of photoreceptors specialized to detect color and skylight polarization in Drosophila
Abstract
Color and polarization provide complementary information about the world and are detected by specialized photoreceptors. However, the downstream neural circuits that process these distinct modalities are incompletely understood in any animal. Using electron microscopy, we have systematically reconstructed the synaptic targets of the photoreceptors specialized to detect color and skylight polarization in Drosophila, and we have used light microscopy to confirm many of our findings. We identified known and novel downstream targets that are selective for different wavelengths or polarized light, and followed their projections to other areas in the optic lobes and the central brain. Our results revealed many synapses along the photoreceptor axons between brain regions, new pathways in the optic lobes, and spatially segregated projections to central brain regions. Strikingly, photoreceptors in the polarization-sensitive dorsal rim area target fewer cell types, and lack strong connections to the lobula, a neuropil involved in color processing. Our reconstruction identifies shared wiring and modality-specific specializations for color and polarization vision, and provides a comprehensive view of the first steps of the pathways processing color and polarized light inputs.
Data availability
All data generated or analyzed during this study are included in the manuscript and supporting files. Supplementary File 1 and 3 contain all connectivity data. Supplementary File 2 provides images of all EM skeletons.All code and necessary data to perform the analysis and generate the figures of this manuscript will be available from https://github.com/reiserlab.All reconstructed neurons described in the manuscript will be made available at https://fafb.catmaid.virtualflybrain.org/.
Article and author information
Author details
Funding
Howard Hughes Medical Institute
- Kit D Longden
- Aljoscha Nern
- Arthur Zhao
- Miriam A Flynn
- Connor W Laughland
- Bruck Gezahegn
- Henrique DF Ludwig
- Alex G Thomson
- Heather Dionne
- Davi D Bock
- Gerald M Rubin
- Michael B Reiser
Freie Universität Berlin
- Emil Kind
- Gizem Sancer
- Tessa Obrusnik
- Paula G Alarcón
- Mathias F Wernet
Deutsche Forschungsgemeinschaft (WE 5761/2-1)
- Mathias F Wernet
Deutsche Forschungsgemeinschaft (WE 5761/4-1)
- Mathias F Wernet
Air Force Office of Scientific Research (FA9550-19-1-7005)
- Mathias F Wernet
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Ronald L Calabrese, Emory University, United States
Version history
- Preprint posted: May 17, 2021 (view preprint)
- Received: July 1, 2021
- Accepted: December 15, 2021
- Accepted Manuscript published: December 16, 2021 (version 1)
- Accepted Manuscript updated: January 4, 2022 (version 2)
- Version of Record published: January 25, 2022 (version 3)
Copyright
© 2021, Kind et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 2,107
- Page views
-
- 371
- Downloads
-
- 9
- Citations
Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Computational and Systems Biology
- Neuroscience
Cerebellar climbing fibers convey diverse signals, but how they are organized in the compartmental structure of the cerebellar cortex during learning remains largely unclear. We analyzed a large amount of coordinate-localized two-photon imaging data from cerebellar Crus II in mice undergoing ‘Go/No-go’ reinforcement learning. Tensor component analysis revealed that a majority of climbing fiber inputs to Purkinje cells were reduced to only four functional components, corresponding to accurate timing control of motor initiation related to a Go cue, cognitive error-based learning, reward processing, and inhibition of erroneous behaviors after a No-go cue. Changes in neural activities during learning of the first two components were correlated with corresponding changes in timing control and error learning across animals, indirectly suggesting causal relationships. Spatial distribution of these components coincided well with boundaries of Aldolase-C/zebrin II expression in Purkinje cells, whereas several components are mixed in single neurons. Synchronization within individual components was bidirectionally regulated according to specific task contexts and learning stages. These findings suggest that, in close collaborations with other brain regions including the inferior olive nucleus, the cerebellum, based on anatomical compartments, reduces dimensions of the learning space by dynamically organizing multiple functional components, a feature that may inspire new-generation AI designs.
-
- Neuroscience
Ultrasonic vocalizations (USVs) fulfill an important role in communication and navigation in many species. Because of their social and affective significance, rodent USVs are increasingly used as a behavioral measure in neurodevelopmental and neurolinguistic research. Reliably attributing USVs to their emitter during close interactions has emerged as a difficult, key challenge. If addressed, all subsequent analyses gain substantial confidence. We present a hybrid ultrasonic tracking system, Hybrid Vocalization Localizer (HyVL), that synergistically integrates a high-resolution acoustic camera with high-quality ultrasonic microphones. HyVL is the first to achieve millimeter precision (~3.4–4.8 mm, 91% assigned) in localizing USVs, ~3× better than other systems, approaching the physical limits (mouse snout ~10 mm). We analyze mouse courtship interactions and demonstrate that males and females vocalize in starkly different relative spatial positions, and that the fraction of female vocalizations has likely been overestimated previously due to imprecise localization. Further, we find that when two male mice interact with one female, one of the males takes a dominant role in the interaction both in terms of the vocalization rate and the location relative to the female. HyVL substantially improves the precision with which social communication between rodents can be studied. It is also affordable, open-source, easy to set up, can be integrated with existing setups, and reduces the required number of experiments and animals.