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Tom Tetzlaff
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2020 – today
- 2024
- [i3]Jose Villamar, Matthias Kelbling, Heather L. More, Michael Denker, Tom Tetzlaff, Johanna Senk, Stephan Thober:
Metadata practices for simulation workflows. CoRR abs/2408.17309 (2024) - 2023
- [j21]Sebastian Siegel
, Younes Bouhadjar
System model of neuromorphic sequence learning on a memristive crossbar array. Neuromorph. Comput. Eng. 3(2): 24002 (2023) - [j20]Younes Bouhadjar
Sequence learning in a spiking neuronal network with memristive synapses. Neuromorph. Comput. Eng. 3(3): 34014 (2023) - [j19]Younes Bouhadjar
Coherent noise enables probabilistic sequence replay in spiking neuronal networks. PLoS Comput. Biol. 19(5) (2023) - [c4]Sebastian Siegel
Demonstration of neuromorphic sequence learning on a memristive array. NICE 2023: 108-114 - [d1]Charl A. P. Linssen
NESTML 6.0.0. Version 6.0.0. Zenodo, 2023 [all versions] - 2022
- [j18]Jasper Albers
A Modular Workflow for Performance Benchmarking of Neuronal Network Simulations. Frontiers Neuroinformatics 16: 837549 (2022) - [j17]Younes Bouhadjar
Sequence learning, prediction, and replay in networks of spiking neurons. PLoS Comput. Biol. 18(6) (2022) - [i2]Younes Bouhadjar, Sebastian Siegel, Tom Tetzlaff, Markus Diesmann, Rainer Waser, Dirk J. Wouters:
Sequence learning in a spiking neuronal network with memristive synapses. CoRR abs/2211.16592 (2022) - [i1]Agnes Korcsak-Gorzo, Charl A. P. Linssen, Jasper Albers, Stefan Dasbach, Renato C. Duarte, Susanne Kunkel, Abigail Morrison, Johanna Senk, Jonas Stapmanns
Phenomenological modeling of diverse and heterogeneous synaptic dynamics at natural density. CoRR abs/2212.05354 (2022) - 2020
- [j16]Claudia Bachmann, Tom Tetzlaff
Firing rate homeostasis counteracts changes in stability of recurrent neural networks caused by synapse loss in Alzheimer's disease. PLoS Comput. Biol. 16(8) (2020) - [c3]Younes Bouhadjar
The speed of sequence processing in biological neuronal networks. NICE 2020: 13:1-13:2
2010 – 2019
- 2019
- [c2]Younes Bouhadjar
Constraints on sequence processing speed in biological neuronal networks. ICONS 2019: 16:1-16:9 - 2018
- [j15]Thomas Heiberg, Birgit Kriener, Tom Tetzlaff
Firing-rate models for neurons with a broad repertoire of spiking behaviors. J. Comput. Neurosci. 45(2): 103-132 (2018) - 2017
- [j14]Jyotika Bahuguna
Homologous Basal Ganglia Network Models in Physiological and Parkinsonian Conditions. Frontiers Comput. Neurosci. 11: 79 (2017) - 2015
- [c1]Farhana Sheikh
Reconfıgurable and selectively-adaptive signal processing for multi-mode wireless communication. SiPS 2015: 1-6 - 2014
- [j13]Birgit Kriener, Håkon Enger, Tom Tetzlaff
Dynamics of self-sustained asynchronous-irregular activity in random networks of spiking neurons with strong synapses. Frontiers Comput. Neurosci. 8: 136 (2014) - [j12]Moritz Helias
The Correlation Structure of Local Neuronal Networks Intrinsically Results from Recurrent Dynamics. PLoS Comput. Biol. 10(1) (2014) - [j11]Klas H. Pettersen, Henrik Lindén
Power Laws from Linear Neuronal Cable Theory: Power Spectral Densities of the Soma Potential, Soma Membrane Current and Single-Neuron Contribution to the EEG. PLoS Comput. Biol. 10(11) (2014) - 2013
- [j10]Dmytro Grytskyy, Tom Tetzlaff
A unified view on weakly correlated recurrent networks. Frontiers Comput. Neurosci. 7: 131 (2013) - [j9]Thomas Heiberg, Birgit Kriener, Tom Tetzlaff
Firing-rate models capture essential response dynamics of LGN relay cells. J. Comput. Neurosci. 35(3): 359-375 (2013) - [j8]Szymon Leski
Frequency Dependence of Signal Power and Spatial Reach of the Local Field Potential. PLoS Comput. Biol. 9(7) (2013) - 2012
- [j7]Tom Tetzlaff
Decorrelation of Neural-Network Activity by Inhibitory Feedback. PLoS Comput. Biol. 8(8) (2012) - 2010
- [j6]Eilen Nordlie, Tom Tetzlaff
Rate Dynamics of Leaky Integrate-and-Fire Neurons with Strong Synapses. Frontiers Comput. Neurosci. 4: 149 (2010)
2000 – 2009
- 2008
- [j5]Tom Tetzlaff
Dependence of Neuronal Correlations on Filter Characteristics and Marginal Spike Train Statistics. Neural Comput. 20(9): 2133-2184 (2008) - [j4]Birgit Kriener, Tom Tetzlaff
Correlations and Population Dynamics in Cortical Networks. Neural Comput. 20(9): 2185-2226 (2008) - 2004
- [j3]Tom Tetzlaff
Consequences of realistic network size on the stability of embedded synfire chains. Neurocomputing 58-60: 117-121 (2004) - 2003
- [j2]Tom Tetzlaff
The spread of rate and correlation in stationary cortical networks. Neurocomputing 52-54: 949-954 (2003) - 2002
- [j1]Tom Tetzlaff
The ground state of cortical feed-forward networks. Neurocomputing 44-46: 673-678 (2002)
Coauthor Index
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last updated on 2024-10-07 21:23 CEST by the dblp team
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