The doctoral dissertations of the former Helsinki University of Technology (TKK) and Aalto University Schools of Technology (CHEM, ELEC, ENG, SCI) published in electronic format are available in the electronic publications archive of Aalto University - Aaltodoc.
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Advances in Modeling and Characterization of Human Neuromagnetic Oscillations

Pavan Ramkumar

Doctoral dissertation for the degree of Doctor of Science in Technology to be presented with due permission of the School of Science for public examination and debate in Auditorium U142 at the Aalto University School of Science (Espoo, Finland) on the 7th of May 2012 at 12 noon.

Overview in PDF format (ISBN 978-952-60-4616-7)   [1618 KB]
Dissertation is also available in print (ISBN 978-952-60-4615-0)

Abstract

Intracranial electrophysiological measurements as well as electromagnetic recordings from the scalp have shown that oscillatory activity in the human brain plays an important role in sensory and cognitive processing. Communication between distant brain regions seems to be mediated by oscillatory coherence and synchrony. Our brain is both reactive and reflexive: it reacts to changes in the external environment, but it is also influenced by its past and present internal state. On the one hand, task-related or induced modulations of oscillatory activity provide an important marker for cortical excitability and information processing of the reactive brain. On the other hand, spontaneous oscillatory dynamics subserves information processing of the reflexive brain.

In this thesis, methods were developed to model and characterize task-related oscillatory changes, as well as spontaneous oscillatory activity measured using magnetoencephalography (MEG). In Publication I, we developed a predictive model to capture the suppression-rebound reactivity of the ∼20 Hz mu rhythm originating in the sensorimotor cortex and applied this model to locate the cortical generators of the rhythm from independent measurements. In Publications II and III, we developed temporal and spatial variants of a data-driven method to characterize spatial, temporal, and spectral aspects of spontaneous MEG oscillations. Analysis of complex-valued Fourier coefficients identified well-known rhythms, such as the parieto-occipital ∼10-Hz and the rolandic ∼20-Hz rhythms consistently across subjects. In Publication IV, we applied independent component analysis to time-frequency representations of cortical current estimates computed from simulated as well as resting-state and naturalistic stimulation data. Group-level analysis of Fourier envelopes also identified the ∼20-Hz bilateral sensorimotor network, a subset of the default-mode network at ∼8 and ∼15 Hz, and lateralized temporal-lobe sources at ∼8 Hz.

The methods developed here represent important advances in the modeling and characterization of the brain's oscillatory activity measured using non-invasive electrophysiological methods in healthy humans.

This thesis consists of an overview and of the following 4 publications:

  1. Ramkumar P, Parkkonen L, Hari R. Oscillatory response function: Towards a parametric model of rhythmic brain activity. Human Brain Mapping, 31, 820-834, 2010.
  2. Hyvärinen A, Ramkumar P, Parkkonen L, Hari R. Independent component analysis of short-time Fourier transforms for spontaneous EEG/MEG analysis. NeuroImage, 49, 257-271, 2010.
  3. Ramkumar P, Parkkonen L, Hari R, Hyvärinen A. Characterization of neuromagnetic brain rhythms over time scales of minutes using spatial independent component analysis. Human Brain Mapping, In Press, 2011.
  4. Ramkumar P, Parkkonen L, Hyvärinen A. Group-level spatial independent component analysis of Fourier envelopes of resting-state MEG data. Under Revision, 2011.

Keywords: magnetoencephalography, oscillations, oscillatory response, mu rhythm, resting-state, naturalistic stimulation, independent component analysis, time-frequency representation

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© 2012 Aalto University

Last update 2012-10-31