Dear collegues,
I would like to announce my new book:
Exploration of Cortical Function
Imaging and Modeling Cortical Population Coding Strategies
Martin Stetter
Exploration of Cortical Function summarizes recent efforts aiming at
the revelation of cortical population coding and signal processing
strategies. Topics include optical detection techniques of population
activity in the submillimeter range, advanced methods for the
statistical analysis of these data, and biologically inspired neuronal
models for population activities in the framework of optimal coding,
statistical learning theory and meanfield recurrent networks.
The book covers one complete branch of population-based brain research
ranging from methods for data acquisition over data analysis up to
neuronal models for the quantification of functional principles. The
volume covers an area which is of great current interest to
researchers working on cerebral cortex. The combination of models and
image analysis techniques to examine the activity of large cohorts of
neurons is especially intriguing and prone to considerable debate.
Readership is aimed at students and researchers from many disciplines
including neuroscience, biology, physics and computer science
interested in how an interdisciplinary framework from biology,
statistics and computational neuroscience can be used to gather a
quantitative understanding of cortical function. Experimentalists may
gain insight into statistical and neuronal modeling techniques,
whereas theoreticians will find an introductory treatment of
neuroanatomy, neurophysiology and measurement techniques.
Kluwer Academic Publishers
269 pp., 132 illus.
ISBN 1-4020-0435-4 (hardcover)
ISBN 1-4020-0436-2 (paperback)
--================================================================== Dr. Martin Stetter loc : Mch-P 63-418 Siemens AG, CT IC 4 phone : +49-89-636-55734 Corporate Technology fax : +49-89-636-49767 D-81730 Muenchen, Germany mailto: martin.stetter@mchp.siemens.de ==================================================================
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