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.