Computations of the Cerebellar Granular Layer

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dc.contributor.advisor Sneyd, J en
dc.contributor.advisor Montgomery, J en
dc.contributor.author Bratby, Peter en
dc.date.accessioned 2016-10-07T03:14:54Z en
dc.date.issued 2016 en
dc.identifier.uri http://hdl.handle.net/2292/30662 en
dc.description.abstract Due to its strikingly regular structure, the cerebellum is widely thought to implement a universal neuronal computation. The leading candidate is the `adaptive filter' which is analogous to an analysis-synthesis filter whose output weights are modified by a simple synaptic learning rule. In this formulation, the cerebellar granular layer forms part of the analysis pathway, and is commonly assumed to implement a spatio-temporal recoding where inputs are recombined into an expanded set of output signals. The nature of the recoding is unknown, although its dense connectivity suggests that circuit-level mechanisms play an important role, a view supported by simulations of recurrent neural networks. By developing computational simulations of neural network models of the cerebellar granular layer, I examine how the structure of neural networks enables them to effectively generate adaptive filter basis signals, and relate this to the known granular layer microcircuit. `Cerebellum-like' structures in sharks and electric sh are thought to be the evolutionary precursor to the cerebellum, and have been characterised as adaptive filters which cancel the predictable component of a sensory signal. The sophistication of recoding implemented by cerebellum-like structures appears to increase through evolutionary time in a way that parallels increasingly recurrent connectivity. Networks constructed using a neural network training algorithm demonstrate the potential versatility of the granular layer circuit, whereas a more realistic `winner-take-all' network reproduces some of its experimentally known properties. en
dc.publisher ResearchSpace@Auckland en
dc.relation.ispartof PhD Thesis - University of Auckland en
dc.relation.isreferencedby UoA99264960812202091 en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. en
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm en
dc.rights.uri http://creativecommons.org/licenses/by-nc-sa/3.0/nz/ en
dc.title Computations of the Cerebellar Granular Layer en
dc.type Thesis en
thesis.degree.discipline Mathematics en
thesis.degree.grantor The University of Auckland en
thesis.degree.level Doctoral en
thesis.degree.name PhD en
dc.rights.holder Copyright: The author en
dc.rights.accessrights http://purl.org/eprint/accessRights/OpenAccess en
pubs.elements-id 542460 en
pubs.record-created-at-source-date 2016-10-07 en


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http://creativecommons.org/licenses/by-nc-sa/3.0/nz/ Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by-nc-sa/3.0/nz/

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