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dc.contributor.authorCroteau-Chonka, Elise
dc.date.accessioned2022-04-05T16:12:46Z
dc.date.available2022-04-05T16:12:46Z
dc.date.submitted2021-08-01
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/335787
dc.description.abstractAn animal’s survival depends on timely decisions informed by sensory information. Studies in humans and large model organisms have elucidated auxiliary roles of large brain regions in the evolution of such perceptual decisions. What remains challenging is acquiring a detailed understanding of the underlying neural mechanisms at a synaptic level and across entire brain circuits. The Drosophila melanogaster larva is an apt model system for probing the mechanisms of decision-making given its rich behavioural repertoire, small nervous system, genetic tractability, and available neuronal wiring diagrams. Taking inspiration from the application of two-alternative forced choice (TAFC) tasks to study perceptual decision-making in other model systems, I employed a closed-loop system to optogenetically activate larval nociceptive neurons based on the direction of precisely detected lateral head sweeps (i.e. casts). I sought to uncover the behavioural computations driving the stereotyped larval navigation sequence comprising repeated head casts followed by crawling in a new direction. I found that in control conditions where stimulus intensity is identical between left and right casts, the percentage of larvae that stop exploration and crawl in the direction favourable for survival (i.e. toward the first stimulated direction) significantly increases with number of casts. However, in experimental conditions where the aversive stimulus differs between sides, the percentage that accept the correct side (i.e. lower intensity) increases more significantly with cast number. When controlling for integrated intensity across casts, I observe a higher fraction of larvae accepting the lower intensity stimulus in experimental conditions compared to controls. These results suggest a mechanism of side-to-side comparison and possible sensory evidence accumulation that facilitates improved decision-making. In this thesis, I introduce the construction and implementation of two computational models for comparison to the larval behaviour trajectories. Both models reflect features of the experiment paradigm, though they differ in their assumptions about how the larva uses information from its environment to guide the acceptance or rejection of a given cast. The resulting predictions I generated about larval behaviour capture some, but not all, qualitative signatures within both the experimental and control datasets. I explore avenues for future model investigation and collection of additional behavioural data in order to draw more definitive mechanistic conclusions. While powerful, the closed-loop system I employed tracks only a single larva at a time. Transitioning my sensory discrimination task to a high-throughput system would be advantageous not only to expand the investigation of other stimulus levels but also to screen stimuli of different valences or from other sensory modalities. In this thesis, I detail my contributions to the development, validation, testing, and experimental application of a new tracking system that is capable of behaviour detection and closed-loop optogenetic and thermogenetic stimulation of 16 larvae simultaneously. This facilitated the first observations of operant conditioning in the Drosophila larva in which the animal successfully adapted its casting behaviour following repeated coupling with reward presentation. Although operant learning occurs over a longer time scale than perhaps what is required for perceptual decision-making, the two tasks are related in creating an association between the animal’s body posture and available sensory information. Together, my work on the sensory discrimination task, behavioural modeling, tool development, and analysis of the operant learning results lays a foundation for future investigation of decision-making behaviour in Drosophila larvae, with implications for further understanding the circuit mechanisms underlying larval taxis, learning, and memory.
dc.description.sponsorshipC T Taylor Cambridge International Scholarship
dc.rightsAll Rights Reserved
dc.rights.urihttps://www.rioxx.net/licenses/all-rights-reserved/
dc.subjectDrosophila melanogaster
dc.subjectlarva
dc.subjectneuroscience
dc.subjectbehaviour
dc.subjectnavigation
dc.subjectdecision-making
dc.subjectdecision making
dc.subjecttwo-alternative forced choice
dc.subjectBayesian inference
dc.subjectmodels
dc.subjecthigh-throughput
dc.subjecttracker
dc.titleBehavioural principles underlying navigational decision-making in Drosophila melanogaster larvae
dc.typeThesis
dc.type.qualificationlevelDoctoral
dc.type.qualificationnameDoctor of Philosophy (PhD)
dc.publisher.institutionUniversity of Cambridge
dc.date.updated2022-04-01T17:21:38Z
dc.identifier.doi10.17863/CAM.83223
rioxxterms.licenseref.urihttps://www.rioxx.net/licenses/all-rights-reserved/
dc.contributor.orcidCroteau-Chonka, Elise [0000-0001-5116-3772]
rioxxterms.typeThesis
dc.publisher.collegeTrinity
cam.supervisorZlatic, Marta
cam.depositDate2022-04-01
pubs.licence-identifierapollo-deposit-licence-2-1
pubs.licence-display-nameApollo Repository Deposit Licence Agreement


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