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Author: | Schleimer, Jan-Hendrik |
Title: | Phase Synchronisation in Superimposed Electrophysiological Data |
Publication type: | Master's thesis |
Publication year: | 2007 |
Pages: | (6) + 71 Language: eng |
Department/School: | Tietotekniikan osasto |
Main subject: | Informaatiotekniikka (T-61) |
Supervisor: | Oja, Erkki |
Instructor: | Vigário, Ricardo |
OEVS: | Electronic archive copy is available via Aalto Thesis Database.
Instructions Reading digital theses in the closed network of the Aalto University Harald Herlin Learning CentreIn the closed network of Learning Centre you can read digital and digitized theses not available in the open network. The Learning Centre contact details and opening hours: https://learningcentre.aalto.fi/en/harald-herlin-learning-centre/ You can read theses on the Learning Centre customer computers, which are available on all floors.
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Location: | P1 Ark Aalto 7001 | Archive |
Keywords: | nonlinear oscillators Hilbert's transform phase synchronisation source separation phase reduction Meanfield theory Order-parameter inverse problem LFP EEG/MEG |
Abstract (eng): | 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. |
ED: | 2007-09-19 |
INSSI record number: 34588
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