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Arxiv|September 19, 2025
What Neuroscience Can Teach AI About Learning in Continuously Changing EnvironmentsDaniel Durstewitz, Bruno Averbeck, Georgia KoppeMolecular Psychiatry|February 17, 2019
Deep neural networks in psychiatryDaniel Durstewitz, Georgia Koppe, Andreas Meyer-LindenbergNeuropsychopharmacology : Official Publication of the American College of Neuropsychopharmacology|July 16, 2020
Deep learning for small and big data in psychiatryGeorgia Koppe, Andreas Meyer-Lindenberg, Daniel DurstewitzNature Reviews. Neuroscience|October 4, 2023
Reconstructing computational system dynamics from neural data with recurrent neural networksDaniel Durstewitz, Georgia Koppe, Max Ingo ThurmBiological Psychiatry. Cognitive Neuroscience and Neuroimaging|April 7, 2020
Psychiatric Illnesses as Disorders of Network DynamicsDaniel Durstewitz, Quentin J M Huys, Georgia KoppeFrontiers in Computational Neuroscience|September 14, 2012
An Approximation to the Adaptive Exponential Integrate-and-Fire Neuron Model Allows Fast and Predictive Fitting to Physiological DataLoreen Hertäg, Joachim Hass, Tatiana Golovko, et al.IEEE Transactions on Visualization and Computer Graphics|November 23, 2016
Topological Analysis of Inertial DynamicsAntoni Sagrista, Stefan Jordan, Andreas Just, et al.Schizophrenia Bulletin|November 30, 2018
Recurrent Neural Networks in Mobile Sampling and InterventionGeorgia Koppe, Sinan Guloksuz, Ulrich Reininghaus, et al.Journal of Neurophysiology|May 3, 2013
Method for stationarity-segmentation of spike train data with application to the Pearson cross-correlationClaudio S Quiroga-Lombard, Joachim Hass, Daniel DurstewitzNeurotoxicity Research|December 17, 2008
Comparing the prefrontal cortex of rats and primates: insights from electrophysiologyJeremy K Seamans, Christopher C Lapish, Daniel DurstewitzPageof 9