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Rockefeller

A Neuronal Circuit Architecture for Angular Integration in Drosophila

Abstract

dc:description.abstract

<p>While navigating their environment, many animals keep track of their angular heading over time. However, a neuronal-circuit architecture for computing heading remains unknown in any species. In this thesis, I describe a set of neurons in the Drosophila central complex whose wiring and physiology provide a means to shift an angular heading estimate when the fly turns. I show that these clockwise- and counterclockwise-shifting neurons each exist in two subtypes, with spatiotemporal activity profiles that suggest opposing roles for each subtype at the start and end of a turn. Shifting neurons are required for the heading system to properly track the fly's heading in the dark, and their stimulation induces a shift in the heading signal in the expected direction. I also provide evidence that the angular position of visual landmarks is flexibly associated with the fly's internal heading estimate as it explores its environment. A specific circuit-level model based on known cell types is proposed to account for this flexible association. The central features of the biological circuits described here are analogous to computational models proposed for headdirection cells in rodents and may inform how neural systems, in general, perform angular calculations.</p>

Degree

thesis:*
Name thesis:degree_name
Doctor of Philosophy (PhD)
Level thesis:degree_level
Thesis
Year
2017

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Green, Jonathan
Contributors dc:contributor
  • Gaby Maimon

Subjects

dc:subject × 7

Identifiers

dc:identifier.*
OAI identifier oai:identifier
oai:digitalcommons.rockefeller.edu:student_theses_and_dissertations-1399

Chain of custody

source
Harvested from
Rockefeller
Base URL
digitalcommons.rockefeller.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Green, Jonathan. A Neuronal Circuit Architecture for Angular Integration in Drosophila. Thesis thesis, 2017. https://digitalcommons.rockefeller.edu/student_theses_and_dissertations/405