By Todd C. Handy
Contemporary advancements within the instruments and methods of knowledge acquisition and research in cognitive electrophysiology.
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Extra resources for Brain Signal Analysis: Advances in Neuroelectric and Neuromagnetic Methods
2005). An intuitive way of understanding the main difference between these approaches is that the k-means approach operates independently for each number of clusters, whereas the hierarchical clustering approach operates in a bottom-up manner wherein the number of clusters is initially large and progressively diminishes. , GFP) or with data that have been normalized. However, it has the disadvantage of varying from one run to the other because of the iterative randomization nature of the algorithm (see Murray et al.
These topographic analysis methods allow the experimenter to obtain additional statistically based information and neurophysiologic interpretability beyond what is available from canonical waveform analyses. For each of these analyses we provide the reader with both a conceptual and mathematical description of its implementation, its outcome, and its interpretability. Topographic analysis methods are intuitive and easy-to-use approaches that can remove much of the guesswork often confronting ERP researchers and also assist in identifying the information contained within data sets.
1958. Nonlinear Problems in Random Theory. Cambridge: MIT Press. 2 Principles of Topographic Analyses for Electrical Neuroimaging Micah M. Murray, Marzia De Lucia, Denis Brunet, and Christoph M. , topographic) information available from high-density electrode montages to render statistical information concerning modulations in response strength, latency, and topography both between and within experimental conditions and/or groups of subjects. We also present new methods of analyses for single-subject and single-trial data sets.