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EPSRC Reference: GR/R52206/01
Title: Germination-growth processes,Boolean model statistics and neuronal networks
Principal Investigator: Molchanov, Professor I
Other Investigators:
Researcher Co-Investigators:
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Department: Statistics
Organisation: University of Glasgow
Scheme: Standard Research (Pre-FEC)
Starts: 01 February 2002 Ends: 31 July 2002 Value (£): 10,383
EPSRC Research Topic Classifications:
Statistics & Appl. Probability
EPSRC Industrial Sector Classifications:
No relevance to Underpinning Sectors
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Summary on Grant Application Form
The research consists of three parts. First, consider that seeds are randomly scattered according to a non-Poisson process and will be stimulated after a random time. A seed, once stimulated, immediately tries to germinate and at the same time to prohibit other seeds from germination by generating a spherical inhibited region the radius of which grows at a constant speed. A stimulated seed fails to germinate if its location has been inhibited before stimulation. Limit theorems for the total number of germinations will be studied. Second, suppose that realisations of a Boolean model are observed. If a full realisation in a sampling window is observable, the intensity can be estimated. In this research, estimation methods based on an incompletely observed realisation will be developed. Finally, heavy traffic systems will be used to model neuronal behaviours such as spike trains, their interaction and propagation along dendrites that may lead to activation of a neuron. These seemingly unrelated problems were motivated by a study (Chiu, Quine and Stewart, Biometrics, 56, pp. 755-760) of modelling autoinhibited releases of neurotransmitters at a synapse by a Poisson germination-growth process; the estimation of its intensity was based on incomplete observations of the corresponding Boolean model realisations.
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Organisation Website: http://www.gla.ac.uk