| Diffusion of CH4 and H2 in ZIF-8 L Hertäg, H Bux, J Caro, C Chmelik, T Remsungnen, M Knauth, ... Journal of Membrane Science 377 (1-2), 36-41, 2011 | 176 | 2011 |
| Amplifying the redistribution of somato-dendritic inhibition by the interplay of three interneuron types L Hertäg, H Sprekeler PLoS computational biology 15 (5), e1006999, 2019 | 52 | 2019 |
| Learning prediction error neurons in a canonical interneuron circuit L Hertäg, H Sprekeler eLife 9, e57541, 2020 | 50 | 2020 |
| An approximation to the adaptive exponential integrate-and-fire neuron model allows fast and predictive fitting to physiological data L Hertäg, J Hass, T Golovko, D Durstewitz Frontiers in computational neuroscience 6, 62, 2012 | 50 | 2012 |
| Analytical approximations of the firing rate of an adaptive exponential integrate-and-fire neuron in the presence of synaptic noise L Hertäg, D Durstewitz, N Brunel Frontiers in computational neuroscience 8, 116, 2014 | 45 | 2014 |
| Prediction-error neurons in circuits with multiple neuron types: Formation, refinement, and functional implications L Hertäg, C Clopath Proceedings of the National Academy of Sciences 119 (13), e2115699119, 2022 | 33 | 2022 |
| A Detailed Data-Driven Network Model of Prefrontal Cortex Reproduces Key Features of In Vivo Activity J Hass, L Hertäg, D Durstewitz PLoS computational biology 12 (5), e1004930, 2016 | 27 | 2016 |
| Stevens’ Handbook of Experimental Psychology and Cognitive Neuroscience R van Bork, CD van Borkulo, LJ Waldorp, AOJ Cramer, D Borsboom John Wiley & Sons, 2018 | 3 | 2018 |
| An analytical approximation to the AdEx neuron model allows fast fitting to physiological data L Hertäg, J Haß, T Golovko, D Durstewitz BMC Neuroscience 12, 1-2, 2011 | 2 | 2011 |
| Self-supervised predictive learning accounts for layer-specific cortical observations KK Nejad, P Anastasiades, L Hertäg, RP Costa bioRxiv, 2024 | 1 | 2024 |
| A computational model of prefrontal cortex based on physiologically derived cellular parameter distributions J Hass, L Hertäg, SC Quiroga Lombard, T Golovko, D Durstewitz BMC Neuroscience 14, 1-2, 2013 | 1 | 2013 |
| An analytical approximation to the AdEx neuron allows fast fitting to physiological data L Hertäg, J Hass, T Golovko, D Durstewitz Front. Comput. Neurosci. Conference Abstract: BC11: Computational …, 2011 | 1 | 2011 |
| Transcriptomic correlates of state modulation in GABAergic interneurons: A cross-species analysis J Keijser, L Hertäg, H Sprekeler Journal of Neuroscience, 2024 | | 2024 |
| A theory of temporal self-supervised learning in neocortical layers P Anastasiades, L Hertäg, RP Costa | | 2024 |
| Layer-specific control of inhibition by NDNF interneurons LB Naumann, L Hertäg, J Müller, JJ Letzkus, H Sprekeler bioRxiv, 2024.04. 29.591728, 2024 | | 2024 |
| Knowing what you don’t know: Estimating the uncertainty of feedforward and feedback inputs with prediction-error circuits L Hertäg, KA Wilmes, C Clopath bioRxiv, 2023 | | 2023 |
| Neural Networks and Neurocomputational Modeling H Toutounji, L Hertäg, D Durstewitz Stevens' Handbook of Experimental Psychology and Cognitive Neuroscience 5, 1-40, 2018 | | 2018 |
| Highly Data-driven Mathematical Description of Single Neuron and Recurrent Network Activity: Towards' high-throughput'Computational Neuroscience L Hertäg | | 2014 |
| Diffusion of CH₄ and H₂ in ZIF-8 L Hertäg, H Bux, J Caro, C Chmelik, T Remsungnen, M Knauth, ... | | 2011 |
| A theory of temporal self-supervised learning in neocortical layers KK Nejad, P Anastasiades, L Hertäg, RP Costa | | |
Daniel DurstewitzProfessor for Theoretical Neuroscience, CIMH/ Heidelberg UniversityBestätigte E-Mail-Adresse bei zi-mannheim.de
