University of Sussex
Browse
Harris,_Christopher_A..pdf (9.93 MB)

Multi-electrode analysis of pattern generation and its adaptation to reward

Download (9.93 MB)
thesis
posted on 2023-06-08, 14:07 authored by Christopher Harris
Much behaviour is controlled by neural circuits known as central pattern generators (CPGs). The aim of the work presented in this thesis was to uncover general mechanisms that modify the behavioural output of CPGs in ways that maximise adaptive fitness. To achieve this aim it was necessary to monitor populations of neurons associated with a CPG that responds to changes in sensory reward. I used multi-electrode arrays (MEAs) to monitor neuronal populations in semi-intact preparations of the snail Lymnaea stagnalis. Spike patterns associated with cycles of the feeding CPG were readily recorded in the buccal, cerebral and pedal ganglia. A sensory food stimulus accelerated the CPG and this acceleration was shown to depend on dopamine. Single-trial conditioning on the MEA allowed fictive feeding to be induced by a previously neutral taste stimulus. In addition to the activity of the feeding CPG the MEA also revealed a second neuronal population that had not previously been characterized. This population fires continuously in-between the cycles of the feeding CPG but becomes quiescent for a variable period following each cycle. The duration of this quiescent period often predicted the timing of the next activation of the CPG. Stimulation of a nerve associated with food reward failed to activate the CPG during the quiescent period, indicating that it reflects a ‘network refractory period’ (NRP) of the kind previously observed in locomotor CPGs. The sucrose and dopamine stimuli both significantly shortened the NRP. These results show that the MEA recording method can identify distinct populations of neurons associated with adaptive feeding behaviour, and suggest a general mechanism that allows a CPG to adapt its behavioural output to maximise reward

History

File Version

  • Published version

Pages

137.0

Department affiliated with

  • Biology and Environmental Science Theses

Qualification level

  • doctoral

Qualification name

  • phd

Language

  • eng

Institution

University of Sussex

Full text available

  • Yes

Legacy Posted Date

2013-01-22

Usage metrics

    University of Sussex (Theses)

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC