This book offers an overview of key recent advances in cognitive electrophysiology which concern the study of the brain’s electrical and magnetic responses to both external and internal stimuli. These can be measured using electroencephalograms (EEGs) and magneto encephalograms (MEGs).

The chapters highlight the increasing overlap in EEG and MEG analytical techniques, describing several methods applicable to both. The text discusses recent developments, including reverse correlation methods in visual-evoked potentials and a new approach to topographic mapping in high density electrode montage—relating the latest thinking on design aspects of EEG and MEG studies, in particular 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
Preface
1     Reverse Correlation and the VESPA Method—Edmund C. Lalor, Barak A. Pearlmutter, and John J. Foxe
2     Principles of Topographic Analyses for Electrical Neuroimaging—Micah M. Murray, Marzia De Lucia, Denis Brunet, and Christoph M. Michel
3     Noninvasive Estimation of Local Field Potentials: Methods and Applications—Rolando Grave de Peralta Menendez, Micah M. Murray, Gregor Thut, Theodor Landis, and Sara L. Gonzalez Andino
4     A Practical Guide to Beamformer Source Reconstruction for EEG—Jessica J. Green and John J. McDonald
5     A Practical Guide to MEG and Beamforming—Anthony T. Herdman and Douglas Cheyne
6     Dynamic Causal Modeling for Evoked Responses—Stefan J. Kiebel, Marta I. Garrido, and Karl J. Friston
7     Synchronization Analysis in EEG and MEG—Lawrence M. Ward and Sam M. Doesburg
8     Procedures and Strategies for Optimizing the Signal-to-Noise Ratio in Event-Related Potential Data—Durk Talsma and Anne-Laura van Harmelen
9     Statistical Strategies for Translational ERP Studies—Todd C. Handy, Lindsay S. Nagamatsu, Marla J.S. Mickleborough, and Teresa Y.L. Liu-Ambrose