Advanced Data Analysis in Neuroscience
Designed for use as a textbook in statistics for students from the neuro- and biosciences Integrates statistical analysis with a dynamical systems perspective and computational modeling Reviews almost all areas of applied statistics, including advanced topics for computational neuroscientistsProvides interactive examples and MATLAB-based example codes
| Autor: | Durstewitz, Daniel |
|---|---|
| ISBN: | 9783319867502 |
| Sprache: | Englisch |
| Seitenzahl: | 292 |
| Produktart: | Kartoniert / Broschiert |
| Verlag: | Springer International Publishing |
| Veröffentlicht: | 11.08.2018 |
| Untertitel: | Integrating Statistical and Computational Models |
| Schlagworte: | bootstrap methods machine learning multivariate maps and recurrent neural networks multivariate statistics neural time series nonlinear dynamical systems nonparametric time series modeling reconstructing state spaces from experimental data statistical methods in neuroscience statistical parameter estimation |
Daniel Durstewitz is Professor for Theoretical Neuroscience and Head of the Department of Theoretical Neuroscience at the Central Institute of Mental Health, Mannheim, and the University of Heidelberg. He is also the coordinator and a director of the Bernstein Center for Computational Neuroscience Heidelberg-Mannheim. He has authored numerous articles in the fields of theoretical and computational neuroscience, applying and advancing various statistical and modeling techniques. Together with Jeremy Seamans, he has also developed an influential computational theory of dopamine function in the prefrontal cortex.