Joint time-frequency analysis of EEG signals based on a phase-space interpretation of the recording process

Time-frequency transforms are used to identify events in clinical EEG data. Data are recorded as part of a study for correlating the performance of human subjects during a memory task with pathological events in the EEG, called spikes. The spectrogram and the scalogram are reviewed as tools for evaluating spike activity. A statistical evaluation of the continuous wavelet transform across trials is used to quantify phase-locking events. For simultaneously improving the time and frequency resolution, and for representing the EEG of several channels or trials in a single time-frequency plane, a multichannel matching pursuit algorithm is used. Fundamental properties of the algorithm are discussed as well as preliminary results, which were obtained with clinical EEG data.

[1]  G. Dietsch,et al.  Fourier-Analyse von Elektrencephalogrammen des Menschen , 1932, Pflüger's Archiv für die gesamte Physiologie des Menschen und der Tiere.

[2]  Michael J. Kahana,et al.  Direct brain recordings fuel advances in cognitive electrophysiology , 2010, Trends in Cognitive Sciences.

[3]  Caterina Giannini,et al.  Phase I trial: safety and feasibility of intracranial electroencephalography using hybrid subdural electrodes containing macro- and microelectrode arrays. , 2008, Neurosurgical focus.

[4]  C.-C. Jay Kuo,et al.  Audio Source Separation with Matching Pursuit and Content-Adaptive Dictionaries (MP-CAD) , 2007, 2007 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics.

[5]  Isa Conradsen,et al.  Automatic epileptic seizure onset detection using Matching Pursuit: A case study , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[6]  Calvin J. Schneider,et al.  Computer modeling of epilepsy , 2010 .

[7]  Gregory A Worrell,et al.  INTRACRANIAL ELECTROENCEPHALOGRAPHY WITH SUBDURAL GRID ELECTRODES: TECHNIQUES, COMPLICATIONS, AND OUTCOMES , 2008, Neurosurgery.

[8]  B. Onaral,et al.  Wavelet analysis for EEG feature extraction in deception detection , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

[9]  M. Kahana,et al.  Reset of human neocortical oscillations during a working memory task , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[10]  Daniel Studer,et al.  From EEG dependency multichannel matching pursuit to sparse topographic EEG decomposition , 2006, Journal of Neuroscience Methods.

[11]  Stéphane Mallat,et al.  Matching pursuits with time-frequency dictionaries , 1993, IEEE Trans. Signal Process..

[12]  Asbjørn Mohr Drewes,et al.  Multichannel matching pursuit validation and clustering—A simulation and empirical study , 2011, Journal of Neuroscience Methods.

[13]  Mark R. Bower,et al.  Microseizures and the spatiotemporal scales of human partial epilepsy. , 2010, Brain : a journal of neurology.

[14]  Reza Tafreshi,et al.  A novel wavelet-based index to detect epileptic seizures using scalp EEG signals , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[15]  Dimitrios I. Fotiadis,et al.  Epileptic Seizure Detection in EEGs Using Time–Frequency Analysis , 2009, IEEE Transactions on Information Technology in Biomedicine.

[16]  Pierre-Pascal Lenck-Santini,et al.  Enhanced Oscillatory Activity in the Hippocampal–Prefrontal Network Is Related to Short-Term Memory Function after Early-Life Seizures , 2011, The Journal of Neuroscience.

[17]  B. H. Jansen,et al.  Spectral Decomposition of EEG Intervals Using Walsh and Fourier Transforms , 1981, IEEE Transactions on Biomedical Engineering.

[18]  Philipp Berens,et al.  CircStat: AMATLABToolbox for Circular Statistics , 2009, Journal of Statistical Software.

[19]  G. Buzsáki.  Rhythms of the brain , 2006 .

[20]  M. Manosevitz.  High-Speed Scanning in Human Memory , .

[21]  Andreas Schulze-Bonhage,et al.  Human neocortical oscillations exhibit theta phase differences between encoding and retrieval , 2006, NeuroImage.

[22]  Shie Qian,et al.  Signal approximation via data-adaptive normalized Gaussian functions and its applications for speech processing , 1992, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[23]  K. Blinowska,et al.  Multichannel matching pursuit and EEG inverse solutions , 2005, Journal of Neuroscience Methods.

[24]  Marcin Roszkowski,et al.  Time-frequency-space localization of epileptic EEG oscillations. , 2005, Acta neurobiologiae experimentalis.