https://sccn.ucsd.edu/eeglab/download/eeglab_jnm03.pdf

EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis.

THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268

I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

Principles of Neural Science

Brain-computer interfaces for communication and control.

The use of electroencephalography (EEG) as a diagnostic tool is based largely on a concept of human EEG normality defined by descriptive criteria, of which the alpha rhythm is the principal electrical activity (Berger 1929). One of the features of this activity is its tendency to be reduced in amplitude or to be blocked by either internal or external stimuli to the brain (Berger 1930). This event-related desynchronization (ERD) of the EEG may be used as a highly sensitive parameter in detecting even slight functional disturbances of the cortical activity (Pfurtscheller and Aranibar 1977), provided that analytic methods of quantify these blocking reactions are available.

EEG Mapping in Patients with Transient Ischemic Attacks: A Follow-Up Study

Improvement of EEG classification with a subject-specific feature selection.

Besides statistical methods, various Artificial Intelligence approaches can be used for sleep classification. Learning vector quantization (LVQ) and the top-down induction of decision trees (TDIDT) were applied on 8-hour sleep data from infants. It was shown that with a combination of TDIDT and LVQ the input dimension of the LVQ can be reduced without decreasing the classification accuracy. Classification accuracy was between 67 and 76%, depending on the infant.

Sleep classification with a combination of symbolic learning and learning vector quantization

The paper addresses the problem of automatic sleep classification. A special effort is made to find a method of extracting reasonable descriptions of the individual sleep stages from sample measurements of EGG, EMG, EOG, etc., and from a classification of these measurements provided by an expert. The method should satisfy three requirements: classification accuracy, interpretability of the results, and the ability to select the relevant and discard the irrelevant variables. The solution suggested in this paper consists of a combination of the subsymbolic algorithm LVQ with the symbolic decision tree generator ID3. Results demonstrating the feasibility and utility of our approach are also presented.

Gert Pfurtscheller

Papers

EEG Mapping in Patients with Transient Ischemic Attacks: A Follow-Up Study

Improvement of EEG classification with a subject-specific feature selection.

Sleep classification with a combination of symbolic learning and learning vector quantization

Towards automated sleep classification in infants using symbolic and subsymbolic approaches.

Towards brain controlled movement restoration - Part II: Application of an asynchronous brain-switch