Brain Signal Analysis

Recent developments in the tools and techniques of data acquisition and analysis in cognitive electrophysiology. Cognitive electrophysiology concerns the study of the brain's electrical and magnetic responses to both external and internal events. These can be measured using electroencephalograms (EEGs) or magnetoencephalograms (MEGs). With the advent of functional magnetic resonance imaging (fMRI), another method of tracking brain signals, the tools and techniques of ERP, EEG and MEG data acquisition and analysis have been developing at a similarly rapid pace, and this book offers an overview of key recent advances in cognitive electrophysiology. The chapters highlight the increasing overlap in EEG and MEG analytic techniques, describing several methods applicable to both; they discuss recent developments, including reverse correlation methods in visual-evoked potentials and a new approach to topographic mapping in high-density electrode montage; and they relate the latest thinking on design aspects of EEG/MEG studies, discussing how to optimize the signal-to-noise ratio as well as statistical developments for maximizing power and accuracy in data analysis using repeated-measure ANOVAS. Contributors Denis Brunet, Douglas Cheyne, Marzia De Lucia, Sam M. Doesburg, John J. Foxe, Karl J. Friston, Marta I. Garrido, Sara L. Gonzalez Andino, Rolando Grave de Peralta Menendez, Jessica J. Green, Todd C. Handy, Anthony T. Herdman, Stefan J. Kiebel, Edmund C. Lalor, Theodor Landis, Teresa Y. L. Liu-Ambrose, John. J. McDonald, Christoph M. Michel, Marla J. S. Mickleborough, Micah M. Murray, Lindsay S. Nagamatsu, Barak A. Pearlmutter, Durk Talsma, Gregor Thut, Anne-Laura van Harmelen, Lawrence M. Ward