Daniel Durstewitz
Affiliations: | Research Group Computational Neuroscience | Central Institute of mental Health, Mannheim, Baden-Württemberg, Germany |
Area:
Dopamine, biophysically realistic modelsGoogle:
"Daniel Durstewitz"Mean distance: 16.26 (cluster 17)
Cross-listing: Computational Biology Tree
Children
Sign in to add trainee| Joachim Hass | post-doc | 2010- | Central Institute for Mental Health, Mannheim |
| Eleonora Russo | post-doc | 2012- | BCCN - Heidelberg Mannheim |
| Hazem Toutounji | post-doc | 2014- | Central Institute of mental Health |
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Publications
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| Durstewitz D, Koppe G, Thurm MI. (2023) Reconstructing computational system dynamics from neural data with recurrent neural networks. Nature Reviews. Neuroscience. 24: 693-710 |
| Domanski APF, Kucewicz MT, Russo E, et al. (2023) Distinct hippocampal-prefrontal neural assemblies coordinate memory encoding, maintenance, and recall. Current Biology : Cb |
| Melbaum S, Russo E, Eriksson D, et al. (2022) Conserved structures of neural activity in sensorimotor cortex of freely moving rats allow cross-subject decoding. Nature Communications. 13: 7420 |
| Russo E, Ma T, Spanagel R, et al. (2021) Coordinated prefrontal state transition leads extinction of reward-seeking behaviors. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience |
| Koppe G, Meyer-Lindenberg A, Durstewitz D. (2020) Deep learning for small and big data in psychiatry. Neuropsychopharmacology : Official Publication of the American College of Neuropsychopharmacology |
| Oettl LL, Scheller M, Filosa C, et al. (2020) Phasic dopamine reinforces distinct striatal stimulus encoding in the olfactory tubercle driving dopaminergic reward prediction. Nature Communications. 11: 3460 |
| Durstewitz D, Huys QJM, Koppe G. (2020) Psychiatric Illnesses as Disorders of Network Dynamics. Biological Psychiatry. Cognitive Neuroscience and Neuroimaging |
| Monfared Z, Durstewitz D. (2020) Existence of n-cycles and border-collision bifurcations in piecewise-linear continuous maps with applications to recurrent neural networks Nonlinear Dynamics. 101: 1037-1052 |
| Koppe G, Toutounji H, Kirsch P, et al. (2019) Identifying nonlinear dynamical systems via generative recurrent neural networks with applications to fMRI. Plos Computational Biology. 15: e1007263 |
| Durstewitz D, Koppe G, Meyer-Lindenberg A. (2019) Deep neural networks in psychiatry. Molecular Psychiatry |