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Recent developments in lesion-symptom mapping (LSM) have spurred rapid growth. This volume provides comprehensive coverage of the steps and considerations involved in LSM. The chapters cover the definition and types of brain lesions, how to prepare them for analysis, standard LSM methods, network-based LSM methods, and approaches of transient lesions induced by brain stimulation. These chapters are supplemented by practical, hands-on mini tutorials on implementing the different analyses using freely-available software. In the Neuromethods series style, chapters include the kind of detail and key advice from the specialists needed to get started using LSM in your laboratory. Cutting-edge and thorough, Lesion-to-Symptom Mapping: Principles and Tools connects core conceptual issues with available tools, making it a valuable resource for experienced and new researchers.
This book provides a practical, easy-to-understand guide to carrying out multilevel regression/growth curve analysis (GCA) of time course or longitudinal data in the behavioral sciences, particularly cognitive science, cognitive neuroscience, and psychology. With a minimum of statistical theory and technical jargon, the author focuses on the concrete issue of applying GCA to behavioral science data and individual differences. Throughout the book, R code illustrates how to implement the analyses and generate the graphs. The example datasets, code, and more are available on the author¿s website.
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