Computational Neuroscience - A First Course provides an essential introduction to computational neuroscience and equips readers with a fundamental understanding of modeling the nervous system at the membrane, cellular, and network level. The book, which grew out of a lecture series held regularly for more than ten years to graduate students in neuroscience with backgrounds in biology, psychology and medicine, takes its readers on a journey through three fundamental domains of computational neuroscience: membrane biophysics, systems theory and artificial neural networks. The required mathematical concepts are kept as intuitive and simple as possible throughout the book, making it fully accessible to readers who are less familiar with mathematics. Overall, Computational Neuroscience - A First Course represents an essential reference guide for all neuroscientists who use computational methods in their daily work, as well as for any theoretical scientist approaching the field of computational neuroscience.

Autorentext

Hanspeter Mallot received his PhD from the Faculty of Biology, University of Mainz, Germany, in 1986. In the following years, he held postdoctoral and research positions at the Massachusetts Institute of Technology, the Ruhr-University Bochum, the Max-Planck-Institute for Biological Cybernetics in Tübingen and the Institute for Advanced Study, Berlin. In 2000, he was appointed Professor of Cognitive Neuroscience at the Eberhard-Karls-University, Tübingen. Research focusses on spatial cognition in rats, humans and robots, using behavioral experiments in virtual reality, eye-movement recordings, and simulated agents in hard- and software.

Hanspeter Mallot is currently Professor of Cognitive Neuroscience. He is a member of the editorial board of the journal "Spatial Cognition and Computation". In the past, he served as a president of the European Neural Network Society (ENNS), as president of the German Society for Cognitive Science (GK) and as a member of the Neuroscience review pannel of the Deutsche Forschungsgemeinschaft.

Inhalt

Excitable Membranes and Neural Conduction.- Receptive Fields and the Specificity of Neuronal Firing.- Coding and Representation.- Fourier Analysis for Neuroscientists.- Artificial Neural Networks.