Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published March 22, 2023 | Supplemental Material + Submitted
Report Open

Restructuring of olfactory representations in the fly brain around odor relationships in natural sources

Abstract

A core challenge of olfactory neuroscience is to understand how neural representations of odor are generated and progressively transformed across different layers of the olfactory circuit into formats that support perception and behavior. The encoding of odor by odorant receptors in the input layer of the olfactory system reflects, at least in part, the chemical relationships between odor compounds. Neural representations of odor in higher order associative olfactory areas, generated by random feedforward networks, are expected to largely preserve these input odor relationships. We evaluated these ideas by examining how odors are represented at different stages of processing in the olfactory circuit of the vinegar fly D. melanogaster. We found that representations of odor in the mushroom body (MB), a third-order associative olfactory area in the fly brain, are indeed structured and invariant across flies. However, the structure of MB representational space diverged significantly from what is expected in a randomly connected network. In addition, odor relationships encoded in the MB were better correlated with a metric of the similarity of their distribution across natural sources compared to their similarity with respect to chemical features, and the converse was true for odor relationships encoded in primary olfactory receptor neurons (ORNs). Comparison of odor coding at primary, secondary, and tertiary layers of the circuit revealed that odors were significantly regrouped with respect to their representational similarity across successive stages of olfactory processing, with the largest changes occurring in the MB. The non-linear reorganization of odor relationships in the MB indicates that unappreciated structure exists in the fly olfactory circuit, and this structure may facilitate the generalization of odors with respect to their co-occurence in natural sources.

Additional Information

The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license. We thank D. Anderson for sharing the UAS-OpGCam6f and nls-OpGCaMP6s fly lines. We thank A. Kennedy for modeling code and assistance with adapting the olfactory network model in this study. We thank V. Hauser for contributions to compiling natural odor source datasets. We thank P. Kandimalla for advising on connectomic analyses. We thank members of the Hong lab for careful readings of the manuscript. This work was supported by NIH grant R01MH117825 to E.J.H., and by the NSF/CIHR/DFG/FRQ/UKRI-MRC Next Generation Networks for Neuroscience Program (Award #2014217) to T.O.S. and E.J.H. AUTHOR CONTRIBUTIONS. J.Y.Y., T. F.O., T.O.S., and E.J.H. conceived the project, analyzed data, and wrote the manuscript. J.Y.Y. and K.V.D. performed imaging experiments in PN axons and KC somata. T.F.O. performed imaging experiments in ORN axons and PN dendrites and supervised curation of the natural odor source database. J.Y.Y., T.F.O., M.S.B., and W.M.H. analyzed data and generated figures. E.J.H. and T.O.S. supervised the project and acquired funding. The authors have declared no competing interest.

Attached Files

Submitted - 2023.02.15.528627v2.full.pdf

Supplemental Material - media-1.csv

Supplemental Material - media-2.csv

Supplemental Material - media-3.csv

Supplemental Material - media-4.csv

Files

media-3.csv
Files (8.3 MB)
Name Size Download all
md5:773161538688adb7ef3c210497792706
4.6 kB Preview Download
md5:fc7dd90dd27f6bf22a1e2845ef08b374
14.6 kB Preview Download
md5:42aafb8a19815544029310670064297e
36.0 kB Preview Download
md5:c2f3500177b446b2585744097ddd28d3
8.2 MB Preview Download
md5:ff25bddf49f209f536b730cd574174e2
2.2 kB Preview Download

Additional details

Created:
August 20, 2023
Modified:
December 22, 2023