Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.532217
Title: Information quantification for spike trains and field potentials
Author: Mehboob, Zareen
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2011
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Abstract:
Neural signals are recorded from various regions of the brain and are analysed to understand the working mechanism of neurons and how they interpret external environment. The aim is to understand how this nature's supercomputer works. This helps in exploring human systems and intelligence, treat mental conditions and develop smart machines. Neural data recordings are collected from individual neurons and from populations of neurons. The single neuronal activity recordings are spike train and the activity generated from multiple neurons are field potentials. The data obtained are in enormous amount and of millisecond precision, as a consequence their processing is not a trivial task and efficient techniques are required for decoding these datasets. This work proposes several methods for the analysis of spike train and field potentials. A self-organising map based clustering is applied to synchronous spike train and generates topographically ordered and information-preserving clusters that help interpret how stimuli features are encoded by the neurons. An information-coupled empirical mode decomposition framework is developed for field potentials. It extracts informative oscillatory functions and information coding frequency bands in the recordings. This has several applications. The informative modes reveal underlying neuronal activities w.r.t stimuli, which otherwise have to be extracted by bandpass filters, followed by Fourier or wavelets analysis. It can also be used to analyse neuronal population activity under a medical condition or to understand neuronal interactions by information-connectivity analysis among electrodes. The proposed framework is developed into the form of a toolbox which can be used for educational and research purposes.
Supervisor: Yin, Hujun Sponsor: Higher Education Commission of Pakistan
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.532217  DOI: Not available
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