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Title: Multi-electrode analysis of pattern generation and its adaptation to reward
Author: Harris, Christopher
ISNI:       0000 0004 2730 8830
Awarding Body: University of Sussex
Current Institution: University of Sussex
Date of Award: 2012
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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
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: QP0351 Neurophysiology and neuropsychology