Advances in Processing and Pattern Analysis of Biological Signals

1. Front Matter

   Pages i-ix

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2. Processing and Pattern Analysis of Normal and Pathological EEG

   1. Front Matter

      Pages xi-xi

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   2. Some New Tools for EEG Modeling and Analysis

      • Will Gersch

      Pages 1-19

   3. Signal Processing of EEG: Evidence for Chaos or Noise. An Application to Seizure Activity in Epilepsy

      • Fernando H. Lopes da Silva, Jan-Pieter Pijn, Demetrios N. Velis

      Pages 21-31

   4. Markovian Analysis of EEG Signal Dynamics in Obsessive-Compulsive Disorder

      • Alex A. Sergejew, Ah Chung Tsoi

      Pages 33-44

   5. EEG Sleep Staging Using Vectorial Autoregressive Models

      • Arnon Cohen, Felix Flomen, Nir Drori

      Pages 45-55

   6. Processing of Epileptic EEG

      • Isak Gath, Bernard Harris, Yoram Salant, Claude Feuerstein, Olaf Henriksen, Gérard Rondouin

      Pages 57-69

   7. Simultaneous EEG Recordings from Olfactory and Limbic Brain Structures: Limbic Markers during Olfactory Perception

      • Leslie Kay, Walter J. Freeman, Larry R. Lancaster Jr.

      Pages 71-84

3. Investigation of Psychophysiological Phenomena by Processing and Pattern Analysis of Evoked Potentials

   1. Front Matter

      Pages N1-N1

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   2. Single Sweep Analysis of Evoked and Event Related Potentials

      • Sergio Cerutti, Anna M. Bianchi, Diego Liberati

      Pages 85-102

   3. Spatio-Temporal Source Estimation of Evoked Potentials by Wavelet-Type Decomposition

      • Amir B. Geva, Hillel Pratt, Yehoshua Y. Zeevi

      Pages 103-122

   4. Modeling and Estimation of Amplitude and Time Shifts in Single Evoked Potential Components

      • Daniel H. Lange, Gideon F. Inbar

      Pages 123-136

   5. Testing for Synchronization in Evoked Potentials Using Higher Order Spectra Technique

      • Miram Furst, Irit Sha’aya-Segal, Hagit Messer

      Pages 137-144

   6. Analyses of Transient and Time-Varying Evoked Potentials for Detection of Brain Injury

      • Nitish V. Thakor, Xuan Kong

      Pages 145-165

4. Processing and Pattern Analysis of Neuronal Cell Activity

   1. Front Matter

      Pages N3-N3

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   2. Detection and Quantification of Correlations in Neural Populations by Coherence Analysis

      • Constantinos N. Christakos

      Pages 167-182

   3. System Identification of Spiking Sensory Neurons Using Realistically Constrained Nonlinear Time Series Models

      • Michael G. Paulin

      Pages 183-194

   4. Temporal Encoding of Visual Features by Cortical Neurons

      • Lance M. Optican, John W. McClurkin

      Pages 195-204

   5. Coherent Dynamics in the Frontal Cortex of the Behaving Monkey

      • Ad Aertsen, Michael Erb, Iris Haalman, Eilon Vaadia

      Pages 205-224

5. Processing and Pattern Analysis of ECG in Health and Disease

   1. Front Matter

      Pages N5-N5

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In recent years there has been rapid progress in the development of signal processing in general, and more specifically in the application of signal processing and pattern analysis to biological signals. Techniques, such as parametric and nonparametric spectral estimation, higher order spectral estimation, time-frequency methods, wavelet transform, and identifi­ cation of nonlinear systems using chaos theory, have been successfully used to elucidate basic mechanisms of physiological and mental processes. Similarly, biological signals recorded during daily medical practice for clinical diagnostic procedures, such as electroen­ cephalograms (EEG), evoked potentials (EP), electromyograms (EMG) and electrocardio­ grams (ECG), have greatly benefitted from advances in signal processing. In order to update researchers, graduate students, and clinicians, on the latest developments in the field, an International Symposium on Processing and Pattern Analysis of Biological Signals was held at the Technion-Israel Institute of Technology, during March 1995. This book contains 27 papers delivered during the symposium. The book follows the five sessions of the symposium. The first section, Processing and Pattern Analysis of Normal and Pathological EEG, accounts for some of the latest developments in the area of EEG processing, namely: time varying parametric modeling; non-linear dynamic modeling of the EEG using chaos theory; Markov analysis; delay estimation using adaptive least-squares filtering; and applications to the analysis of epileptic EEG, EEG recorded from psychiatric patients, and sleep EEG.

• Radiologieinformationssystem
• behavior
• cell
• classification
• electrocardiogram (ECG)
• electroencephalography (EEG)
• evaluation
• population

• Department of Biomedical Engineering, Technion-Israel Institute of Technology, Haifa, Israel

  Isak Gath

• Department of Electrical Engineering, Technion-Israel Institute of Technology, Haifa, Israel

  Gideon F. Inbar

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