Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.775296
Title: Information processing in the insect mushroom body
Author: Peng, Fei
ISNI:       0000 0004 7962 4720
Awarding Body: Queen Mary, University of London
Current Institution: Queen Mary, University of London
Date of Award: 2016
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Abstract:
Insects, like bees and ants, are models for studying how animals with relatively small nervous systems might accomplish relatively complex cognitive feats. They have demonstrated the ability of learning a variety of advanced tasks, including non-elemental forms of learning and navigation through complex environments. Within the miniature brain of the insect, the mushroom body neuropil has been of great interest, and is viewed as a centre of olfactory learning and memory in a variety of insects. Here I take a theoretical approach, and explored the role of the insect mushroom body in underpinning seemingly complex cognitive capacities. Using a simple model of the bee olfactory circuitry that incorporates empirically-determined properties, I show that the circuitry mediating 'simple' associative learning can also fully explain the various 'non-elemental' forms of learning, and can effectively multi-task by replicating a range of different learning feats. I also show that projection neuron to Kenyon cell synapses plasticity and the different classes of Kenyon cells are important in controlling the generalisation discrimination trade-off. Memory storage and capacity is explored using a spiking neural model of the mushroom body circuit, and this model can account for the ability of desert ants to rapidly memorise visual routes through complex natural environments. Taken as a whole, my findings suggest that the impressive cognitive capacities of the insect might be an emergent property of the insect mushroom body circuitry, and calls into question the notion that certain forms of learning that have previously been regarded as 'higher order' or 'non-linear' are inherently more complex than 'simple' associative learning, or that they require more complex neural substrates.
Supervisor: Not available Sponsor: China Scholarship Council ; Queen Mary University of London
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.775296  DOI: Not available
Keywords: Insect mushroom body ; complex cognitive capacities
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