Phase Synchronisation in Superimposed Electrophysiological Data
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Helsinki University of Technology |
Diplomityö
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Date
2007
Department
Major/Subject
Informaatiotekniikka
Mcode
T-61
Degree programme
Language
en
Pages
(6) + 71
Series
Abstract
There is experimental and theoretical evidence that functional units on various scales of the nervous system express properties of self-sustained oscillators. For example, this quality is present in several models for a neuron's membrane potential dynamics. Perturbation theory then leads to a formulation of the oscillator's dynamic interactions solely based on phase evolutions. In such models mutual synchronisation can occur. Verification that this effect takes place in the nervous system and is relevant for information integration requires calculating quantities such as a matrix of bivariate phase-locking statistics from multi-unit electrophysiological measurements. For this, data with high temporal resolution is favourable, rendering invasive recordings of local field potentials or non-invasive techniques like EEG or MEG suitable. This thesis provides interpretation for the spectral analysis of the synchronisation matrix with respect to phase reduced oscillator dynamics underlying the data. The relation of eigenvectors and order parameters as well as eigenvalues and population size are highlighted and the clustering into phase locked subpopulations is described. A modification reducing the difficulties in establishing the entrainment relation among oscillators is discussed. Furthermore, the problem is addressed that in many experimental situations the sensor has no direct access to the oscillator but instead measures a superposition of several units. In such cases spurious synchronisation not related to actual neuronal interaction will appear. It is shown how source extraction methods and other approaches can partly circumvent this problem.Description
Supervisor
Oja, ErkkiThesis advisor
Vigário, RicardoKeywords
nonlinear oscillators, Hilbert's transform, phase synchronisation, source separation, phase reduction, Meanfield theory, Order-parameter, inverse problem, LFP, EEG/MEG