Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.626416
Title: Imaging fast neural activity in the brain with electrical impedance tomography
Author: Packham, B. C.
Awarding Body: University College London (University of London)
Current Institution: University College London (University of London)
Date of Award: 2013
Availability of Full Text:
Access through EThOS:
Full text unavailable from EThOS. Please try the link below.
Access through Institution:
Abstract:
Electrical impedance tomography (EIT) is an emerging medical imaging technique that can be employed to reconstruct the internal conductivity of an object from measurements made on the boundary. One proposed application for EIT is in head imaging, including imaging of impedance changes that occur with neuronal depolarisation and the imaging of acute stroke. The work of this thesis was aimed at advancing the imaging of brain pathology and function, with particular focus on the imaging of fast neural activity. Chapter 1 is a review of other brain imaging techniques, the principles of bioimpedance and EIT, and of previous impedance recordings of fast neural activity. Chapter 2 was a comparison of reconstruction algorithms for the detection of acute stroke using EIT in a realistic head-shaped tank, which entailed assessing boundary voltage rejection methods and quantitative analysis of image quality to determine the best reconstruction algorithms for the detection of acute stroke. In chapter 3, an EIT imaging dataset of fast neural activity, previously collected in a rat model, was assessed using second-level statistical parametric mapping (SPM) and the spatio-temporal propagation of the activity assessed and compared to the neurophysiological literature, which was reviewed in chapter 1. The analysis undertaken in chapter 3 illustrated some key methodological issues, which were addressed in chapter 4: new high resolution meshes and better optimised matrix inversion were employed, a new algorithm for electrode alignment was developed, also the use of SPM was validated by applying it to control datasets and through the use of statistical non-parametric mapping. Chapters 5 and 6 detail work attempting to cross-validate the use of EIT to image fast neural activity by employing a physiological stimulus, mechanical whisker displacement, and comparing the findings to other neurophysiological techniques recorded in the same model. Chapter 5 details work to validate the model and the impedance findings in this model as compared to previously published neurophysiological results, while chapter 6 details the use of other neurophysiological techniques for cross-validation.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.626416  DOI: Not available
Share: