An information analysis of the interaction between sensory signals and ongoing cortical activity using a novel mechanistic cortical model, behavioural and MEG studies.

Dempster, Michael Andrew (2013) An information analysis of the interaction between sensory signals and ongoing cortical activity using a novel mechanistic cortical model, behavioural and MEG studies. PhD thesis, University of Glasgow.

Full text available as:
[img]
Preview
PDF
Download (19MB) | Preview

Abstract

In this work I present a novel mechanistic cortical model derived from the most current cortical anatomical data. The model is built at the cellular level representing the mean laminar distribution and connectivity of the neo-cortex. From this model I derive an extracellular field potential signal and simulate ongoing cortical activity using top down, local and bottom up sensory input. An information theoretic analysis is applied to the simulation data in the context of a bottom up input. This identifies a relationship between cortico-cortical oscillatory activity across a number of frequencies and the information contained in spiking neurons that have long range afferent connections. From these model predictions three auditory perception experimental paradigms are developed, implemented and analysed. I show that the behavioural data is explained by the model predictions and offer a mechanistic explanation of the effect derived from model behaviour. I perform an information analysis on magnetoencephalography data acquired from a simple 50 % auditory perception task and demonstrate prestimulus ongoing activity frequency power and phase features facilitate perception. In addition there is evidence of attention related interaction between the auditory and visual early cortices.

Item Type: Thesis (PhD)
Qualification Level: Doctoral
Keywords: MEG, computer Model, neural model, leaky integrate and fire, mechanistic model, brain rhythms, auditory steady state, perception
Subjects: B Philosophy. Psychology. Religion > BF Psychology
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QP Physiology
Colleges/Schools: College of Science and Engineering > School of Psychology
Funder's Name: UNSPECIFIED
Supervisor's Name: Gross, Prof. Joachim
Date of Award: 2013
Depositing User: Michael Andrews Dempster
Unique ID: glathesis:2013-4223
Copyright: Copyright of this thesis is held by the author.
Date Deposited: 02 May 2013 13:44
Last Modified: 02 May 2013 13:48
URI: http://theses.gla.ac.uk/id/eprint/4223

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year