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.

Analysis of the Structure of Time–Frequency Information in Electromagnetic Brain Signals

Ville Mäkinen

Dissertation for the degree of Doctor of Science in Technology to be presented with due permission of the Department of Engineering Physics and Mathematics for public examination and debate in Auditorium F1 at Helsinki University of Technology (Espoo, Finland) on the 28th of April, 2006, at 12 noon.

Overview in PDF format (ISBN 951-22-8025-6)   [2544 KB]
Dissertation is also available in print (ISBN 951-22-8024-8)


This thesis encompasses methodological developments and experimental work aimed at revealing information contained in time, frequency, and time–frequency representations of electromagnetic, specifically magnetoencephalographic, brain signals.

The work can be divided into six endeavors. First, it was shown that sound slopes increasing in intensity from undetectable to audible elicit event-related responses (ERRs) that predict behavioral sound detection. This provides an opportunity to use non-invasive brain measures in hearing assessment. Second, the actively debated generation mechanism of ERRs was examined using novel analysis techniques, which showed that auditory stimulation did not result in phase reorganization of ongoing neural oscillations, and that processes additive to the oscillations accounted for the generation of ERRs. Third, the prerequisites for the use of continuous wavelet transform in the interrogation of event-related brain processes were established. Subsequently, it was found that auditory stimulation resulted in an intermittent dampening of ongoing oscillations. Fourth, information on the time–frequency structure of ERRs was used to reveal that, depending on measurement condition, amplitude differences in averaged ERRs were due to changes in temporal alignment or in amplitudes of the single-trial ERRs. Fifth, a method that exploits mutual information of spectral estimates obtained with several window lengths was introduced. It allows the removal of frequency-dependent noise slopes and the accentuation of spectral peaks. Finally, a two-dimensional statistical data representation was developed, wherein all frequency components of a signal are made directly comparable according to spectral distribution of their envelope modulations by using the fractal property of the wavelet transform. This representation reveals noise buried processes and describes their envelope behavior.

These examinations provide for two general conjectures. The stability of structures, or the level of stationarity, in a signal determines the appropriate analysis method and can be used as a measure to reveal processes that may not be observable with other available analysis approaches. The results also indicate that transient neural activity, reflected in ERRs, is a viable means of representing information in the human brain.

This thesis consists of an overview and of the following 6 publications:

  1. Mäkinen V, May P, Tiitinen H, 2004. Transient brain responses predict the temporal dynamics of sound detection in humans. NeuroImage 21, 701-706. © 2004 Elsevier Science. By permission.
  2. Mäkinen V, Tiitinen H, May P, 2005. Auditory event-related responses are generated independently of ongoing brain activity. NeuroImage 24, 961-968. © 2005 Elsevier Science. By permission.
  3. Mäkinen VT, Tiitinen H, May PJC, 2004. Auditory evoked responses are additive to brain oscillations. Neurology and Clinical Neurophysiology. © 2004 by authors.
  4. Mäkinen VT, May PJC, Tiitinen H, 2004. Human auditory event-related processes in the time–frequency plane. NeuroReport 15, 1767-1771.
  5. Tiitinen H, Mäkinen VT, Kičić D, May PJC, 2005. Averaged and single-trial brain responses in the assessment of human sound detection. NeuroReport 16, 545-548.
  6. Mäkinen VT, May PJC, Tiitinen H, 2005. The use of stationarity and nonstationarity in the detection and analysis of neural oscillations. NeuroImage 28, 389-400. © 2005 Elsevier Science. By permission.

Keywords: auditory system, EEG, envelope analysis, ERF, ERP, MEG, spectrum, time–frequency transforms, wavelets

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© 2006 Helsinki University of Technology

Last update 2011-05-26