Exploration of Cortical Function summarizes recent research
efforts aiming at the revelation of cortical population coding and
signal processing strategies. Topics include optical detection
techniques of population activity in the sub-millimeter range,
advanced methods for the statistical analysis of these data, and
biologically inspired neuronal modeling techniques for population
activities in the frameworks of optimal coding, statistical
learning theory, and mean-field recurrent networks.
Exploration of Cortical Function is unique in that it covers one
complete branch of population-based brain research ranging from
techniques for data acquisition over data analysis up to modeling
techniques 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 error and debate.
The intended readership is students and researchers from many
disciplines, including neuroscience, biology, physics, and computer
science, interested in how an interdisciplinary framework from
biology advanced 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.
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