An Introduction to Model-Based Cognitive Neuroscience

Birte U. Forstmann · Eric-Jan Wagenmakers

апр 2015. · Springer

О овој е-књизи

Two recent innovations, the emergence of formal cognitive models and the addition of cognitive neuroscience data to the traditional behavioral data, have resulted in the birth of a new, interdisciplinary field of study: model-based cognitive neuroscience. Despite the increasing scientific interest in model-based cognitive neuroscience, few active researchers and even fewer students have a good knowledge of the two constituent disciplines. The main goal of this edited collection is to promote the integration of cognitive modeling and cognitive neuroscience. Experts in the field will provide tutorial-style chapters that explain particular techniques and highlight their usefulness through concrete examples and numerous case studies. The book will also include a thorough list of references pointing the reader towards additional literature and online resources.

О аутору

Birte Forstmann is a Professor for Cognitive Neurosciences at the University of Amsterdam as well as honorary professor at the University of Leiden. She earned her PhD in 2006 at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, Germany. After completing her postdoc in 2008 at the University of Amsterdam, she became tenured Research Fellow at the Cognitive Science Center Amsterdam with the focus of model-based cognitive neurosciences. Since then she has contributed to a range of topics in cognitive neuroscience, experimental psychology, mathematical psychology, and lately also in quantitative neuroanatomy.

Eric-Jan (EJ) Wagenmakers is a professor at the Psychological Methods Unit of the University of Amsterdam. His current work concerns Bayesian inference, philosophy of science, mathematical models of cognition, and model-based cognitive neuroscience. His studies in cognitive neuroscience are guided by the conviction that mathematical process models can provide useful structure and constraint for the analysis and interpretation of brain data.