Synaptic targets of photoreceptors specialized to detect color and skylight polarization in Drosophila
- Freie Universität Berlin, Germany
- Howard Hughes Medical Institute, United States
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
A two-part list of links to download the article, or parts of the article, in various formats.
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)
Synaptic targets of photoreceptors specialized to detect color and skylight polarization in Drosophila
eLife 10:e71858.
https://doi.org/10.7554/eLife.71858
Further reading
-
- Cell Biology
- Neuroscience
The amyloid beta (Aβ) plaques found in Alzheimer’s disease (AD) patients’ brains contain collagens and are embedded extracellularly. Several collagens have been proposed to influence Aβ aggregate formation, yet their role in clearance is unknown. To investigate the potential role of collagens in forming and clearance of extracellular aggregates in vivo, we created a transgenic Caenorhabditis elegans strain that expresses and secretes human Aβ1-42. This secreted Aβ forms aggregates in two distinct places within the extracellular matrix. In a screen for extracellular human Aβ aggregation regulators, we identified different collagens to ameliorate or potentiate Aβ aggregation. We show that a disintegrin and metalloprotease a disintegrin and metalloprotease 2 (ADM-2), an ortholog of ADAM9, reduces the load of extracellular Aβ aggregates. ADM-2 is required and sufficient to remove the extracellular Aβ aggregates. Thus, we provide in vivo evidence of collagens essential for aggregate formation and metalloprotease participating in extracellular Aβ aggregate removal.
-
- Computational and Systems Biology
- Neuroscience
The cerebellar granule cell layer has inspired numerous theoretical models of neural representations that support learned behaviors, beginning with the work of Marr and Albus. In these models, granule cells form a sparse, combinatorial encoding of diverse sensorimotor inputs. Such sparse representations are optimal for learning to discriminate random stimuli. However, recent observations of dense, low-dimensional activity across granule cells have called into question the role of sparse coding in these neurons. Here, we generalize theories of cerebellar learning to determine the optimal granule cell representation for tasks beyond random stimulus discrimination, including continuous input-output transformations as required for smooth motor control. We show that for such tasks, the optimal granule cell representation is substantially denser than predicted by classical theories. Our results provide a general theory of learning in cerebellum-like systems and suggest that optimal cerebellar representations are task-dependent.
