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Structured sampling of olfactory input by the fly mushroom body

Zheng, Zhihao, Li, Feng, Fisher, Corey, Ali, Iqbal J., Sharifi, Nadiya, Calle-Schuler, Steven, Hsu, Joseph, Masoodpanah, Najla, Kmecova, Lucia, Kazimiers, Tom, Perlman, Eric, Nichols, Matthew, Li, Peter H., Jain, Viren, Bock, Davi D.·2020
DOI 10.1101/2020.04.17.047167

Preprint — published as 10.1016/j.cub.2022.06.031 · Paper page

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Abstract

Associative memory formation and recall in the adult fruit fly Drosophila melanogaster is subserved by the mushroom body (MB). Upon arrival in the MB, sensory information undergoes a profound transformation. Olfactory projection neurons (PNs), the main MB input, exhibit broadly tuned, sustained, and stereotyped responses to odorants; in contrast, their postsynaptic targets in the MB, the Kenyon cells (KCs), are nonstereotyped, narrowly tuned, and only briefly responsive to odorants. Theory and experiment have suggested that this transformation is implemented by random connectivity between KCs and PNs. However, this hypothesis has been challenging to test, given the difficulty of mapping synaptic connections between large numbers of neurons to achieve a unified view of neuronal network structure. Here we used a recent whole-brain electron microscopy (EM) volume of the adult fruit fly to map large numbers of PN- to-KC connections at synaptic resolution. Comparison of the observed connectome to precisely defined null models revealed unexpected network structure, in which a subset of food-responsive PN types converge on individual downstream KCs more frequently than expected. The connectivity bias is consistent with the neurogeometry: axons of the overconvergent PNs tend to arborize near one another in the MB main calyx, making local KC dendrites more likely to receive input from those types. Computational modeling of the observed PN-to-KC network showed that input from the overconvergent PN types is better discriminated than input from other types. These results suggest an ‘associative fovea’ for olfaction, in that the MB is wired to better discriminate more frequently occurring and ethologically relevant combinations of food-related odors.

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Image 1
CC-BY-NC-ND · From the PDF
Figure 1 Structured olfactory input to the mushroom body.
Figure 1 Structured olfactory input to the mushroom body.CC-BY-NC-ND · From the PDF
Image 3
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Image 4
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Image 5
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Image 6
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Figure 2 Biased sampling of community PNs by KCs.
Figure 2 Biased sampling of community PNs by KCs.CC-BY-NC-ND · From the PDF
Figure 3 Over-convergence of community PNs to KCs.
Figure 3 Over-convergence of community PNs to KCs.CC-BY-NC-ND · From the PDF
Figure 4 Arbor overlap between subsets of community PNs and KCs.
Figure 4 Arbor overlap between subsets of community PNs and KCs.CC-BY-NC-ND · From the PDF
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Subsampling of data from current study, with Caron et al. sample size (random bouton null model)
Subsampling of data from current study, with Caron et al. sample size (random bouton null model)CC-BY-NC-ND · From the PDF
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Authors
Zheng, Z., Li, F., Fisher, C., Ali, I. J., Sharifi, N., Calle-Schuler, S., Hsu, J., Masoodpanah, N., Kmecova, L., Kazimiers, T., Perlman, E., Nichols, M., Li, P. H., Jain, V., & Bock, D. D.
ORCID
Publisher
openRxiv
Published
2020-04-18
DOI
10.1101/2020.04.17.047167
Cited by
22
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0
Type
Preprint
Licence
www.biorxiv.org/about/FAQ#license (vor)

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