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2020 – today
- 2022
[j53]Damir Dobric
, Andreas Pech, Bogdan Ghita, Thomas Wennekers:
On the Importance of the Newborn Stage When Learning Patterns with the Spatial Pooler. SN Comput. Sci. 3(2): 179 (2022)- [i2]Mina Marmpena, Fernando Garcia, Angelica Lim, Nikolas Hemion, Thomas Wennekers:
Data-driven emotional body language generation for social robotics. CoRR abs/2205.00763 (2022) - 2021
- [c11]Damir Dobric, Andreas Pech, Bogdan Ghita, Thomas Wennekers:
Improved HTM Spatial Pooler with Homeostatic Plasticity Control. ICPRAM 2021: 98-106 - 2020
- [c10]Damir Dobric, Andreas Pech, Bogdan Ghita, Thomas Wennekers:
On the Relationship Between Input Sparsity and Noise Robustness in Hierarchical Temporal Memory Spatial Pooler. ESSE 2020: 187-193
2010 – 2019
- 2018
- [j52]Rosario Tomasello, Max Garagnani, Thomas Wennekers, Friedemann Pulvermüller:
A Neurobiologically Constrained Cortex Model of Semantic Grounding With Spiking Neurons and Brain-Like Connectivity. Frontiers Comput. Neurosci. 12: 88 (2018) - [j51]Jack McKay Fletcher, Thomas Wennekers:
From Structure to Activity: Using Centrality Measures to Predict Neuronal Activity. Int. J. Neural Syst. 28(2): 1750013:1-1750013:16 (2018) - [j50]Daniel Hernández García, Samantha V. Adams, Alexander D. Rast, Thomas Wennekers, Steve B. Furber, Angelo Cangelosi:
Visual attention and object naming in humanoid robots using a bio-inspired spiking neural network. Robotics Auton. Syst. 104: 56-71 (2018) - [j49]Alexander D. Rast, Samantha V. Adams, Simon Davidson, Sergio Davies, Michael Hopkins, Andrew Rowley, Alan Barry Stokes, Thomas Wennekers, Steve B. Furber, Angelo Cangelosi:
Behavioral Learning in a Cognitive Neuromorphic Robot: An Integrative Approach. IEEE Trans. Neural Networks Learn. Syst. 29(12): 6132-6144 (2018) - 2017
- [i1]Jack McKay Fletcher, Thomas Wennekers:
A natural approach to studying schema processing. CoRR abs/1705.04536 (2017) - 2016
- [j48]Max Garagnani, Guglielmo Lucchese, Rosario Tomasello, Thomas Wennekers, Friedemann Pulvermüller:
A Spiking Neurocomputational Model of High-Frequency Oscillatory Brain Responses to Words and Pseudowords. Frontiers Comput. Neurosci. 10: 145 (2016) - [c9]Ivana Kajic, Jan Gosmann, Terrence C. Stewart, Thomas Wennekers, Chris Eliasmith:
Towards a Cognitively Realistic Representation of Word Associations. CogSci 2016 - 2015
- [c8]Ivana Kajic, Thomas Wennekers:
Neural Network Model of Semantic Processing in the Remote Associates Test. CoCo@NIPS 2015 - 2014
- [j47]Friedemann Pulvermüller, Max Garagnani, Thomas Wennekers:
Thinking in circuits: toward neurobiological explanation in cognitive neuroscience. Biol. Cybern. 108(5): 573-593 (2014) - [c7]Samantha V. Adams, Alexander D. Rast, Cameron Patterson, Francesco Galluppi, Kevin Brohan, José Antonio Pérez-Carrasco, Thomas Wennekers, Steve B. Furber, Angelo Cangelosi:
Towards Real-World Neurorobotics: Integrated Neuromorphic Visual Attention. ICONIP (3) 2014: 563-570 - 2013
- [j46]Salvador Dura-Bernal, Guillaume Garreau, Julius Georgiou, Andreas G. Andreou, Susan L. Denham, Thomas Wennekers:
Multimodal Integration of Micro-Doppler Sonar and auditory signals for Behavior Classification with convolutional Networks. Int. J. Neural Syst. 23(5) (2013) - [j45]Gleb Basalyga, Marcelo A. Montemurro, Thomas Wennekers:
Information coding in a laminar computational model of cat primary visual cortex. J. Comput. Neurosci. 34(2): 273-283 (2013) - [j44]Samantha V. Adams, Thomas Wennekers, Sue L. Denham, Phil F. Culverhouse:
Adaptive training of cortical feature maps for a robot sensorimotor controller. Neural Networks 44: 6-21 (2013) - 2012
- [j43]Timothy H. Rumbell, John A. Barnden, Susan L. Denham, Thomas Wennekers:
Emotions in autonomous agents: comparative analysis of mechanisms and functions. Auton. Agents Multi Agent Syst. 25(1): 1-45 (2012) - [j42]James Humble, Susan L. Denham, Thomas Wennekers:
Spatio-temporal pattern recognizers using spiking neurons and spike-timing-dependent plasticity. Frontiers Comput. Neurosci. 6: 84 (2012) - 2011
- [j41]Samantha V. Adams, Thomas Wennekers, Guido Bugmann, Sue L. Denham, Phil F. Culverhouse:
Application of arachnid prey localisation theory for a robot sensorimotor controller. Neurocomputing 74(17): 3335-3342 (2011) - [j40]Robert Mill, Martin Coath, Thomas Wennekers, Susan L. Denham:
Abstract Stimulus-Specific Adaptation Models. Neural Comput. 23(2): 435-476 (2011) - [j39]Robert Mill, Martin Coath, Thomas Wennekers, Susan L. Denham:
A Neurocomputational Model of Stimulus-Specific Adaptation to Oddball and Markov Sequences. PLoS Comput. Biol. 7(8) (2011) - [c6]Salvador Dura-Bernal, Thomas Wennekers, Susan L. Denham:
Modelling object perception in cortex: Hierarchical Bayesian networks and belief propagation. CISS 2011: 1-6 - [c5]Julius Georgiou, Philippe O. Pouliquen, Andrew Cassidy, Guillaume Garreau, Charalambos M. Andreou, Guillermo Stuarts, Cyrille d'Urbal, Andreas G. Andreou, Susan L. Denham, Thomas Wennekers, Robert Mill, István Winkler, Tamás Bohm, Orsolya Szalárdy, Georg M. Klump, Simon J. Jones, Alexandra Bendixen:
A multimodal-corpus data collection system for cognitive acoustic scene analysis. CISS 2011: 1-6 - [c4]Salvador Dura-Bernal, Guillaume Garreau, Charalambos M. Andreou, Andreas G. Andreou, Julius Georgiou, Thomas Wennekers, Susan L. Denham:
Human Action Categorization Using Ultrasound Micro-Doppler Signatures. HBU 2011: 18-28
2000 – 2009
- 2009
- [j38]Thomas Wennekers:
On the Natural Hierarchical Composition of Cliques in Cell Assemblies. Cogn. Comput. 1(2): 128-138 (2009) - [j37]Max Garagnani, Thomas Wennekers, Friedemann Pulvermüller:
Recruitment and Consolidation of Cell Assemblies for Words by Way of Hebbian Learning and Competition in a Multi-Layer Neural Network. Cogn. Comput. 1(2): 160-176 (2009) - [j36]Vassilis Cutsuridis, Thomas Wennekers, Bruce P. Graham, Imre Vida, John G. Taylor:
Microcircuits - Their structure, dynamics and role for brain function. Neural Networks 22(8): 1037-1038 (2009) - [j35]Andrew Symes, Thomas Wennekers:
Spatiotemporal dynamics in the cortical microcircuit: A modelling study of primary visual cortex layer 2/3. Neural Networks 22(8): 1079-1092 (2009) - [j34]Vassilis Cutsuridis, Thomas Wennekers:
Hippocampus, microcircuits and associative memory. Neural Networks 22(8): 1120-1128 (2009) - 2007
- [j33]Péter András, Thomas Wennekers:
Cortical activity pattern computation. Biosyst. 87(2-3): 179-185 (2007) - [j32]Thomas Wennekers, Nihat Ay, Péter András:
High-resolution multiple-unit EEG in cat auditory cortex reveals large spatio-temporal stochastic interactions. Biosyst. 89(1-3): 190-197 (2007) - [j31]Eckehard Olbrich, Thomas Wennekers:
Dynamics of parameters of neurophysiological models from phenomenological EEG modeling. Neurocomputing 70(10-12): 1848-1852 (2007) - [j30]Max Garagnani, Thomas Wennekers, Friedemann Pulvermüller:
A neuronal model of the language cortex. Neurocomputing 70(10-12): 1914-1919 (2007) - [j29]Thomas Wennekers:
A cell assembly model for complex behaviour. Neurocomputing 70(10-12): 1988-1992 (2007) - 2006
- [j28]Thomas Wennekers, Nihat Ay:
A temporal learning rule in recurrent systems supports high spatio-temporal stochastic interactions. Neurocomputing 69(10-12): 1199-1202 (2006) - 2005
- [j27]Thomas Wennekers, Nihat Ay:
Stochastic interaction in associative nets. Neurocomputing 65-66: 387-392 (2005) - [j26]Friedrich T. Sommer, Thomas Wennekers:
Synfire chains with conductance-based neurons: internal timing and coordination with timed input. Neurocomputing 65-66: 449-454 (2005) - [j25]Thomas Wennekers, Nihat Ay:
Finite State Automata Resulting from Temporal Information Maximization and a Temporal Learning Rule. Neural Comput. 17(10): 2258-2290 (2005) - 2004
- [j24]Thomas Wennekers, Katrin Suder:
Fitting of spatio-temporal receptive fields by sums of Gaussian components. Neurocomputing 58-60: 929-934 (2004) - [j23]Thomas Wennekers:
Separation of Spatio-Temporal Receptive Fields into Sums of Gaussian Components. J. Comput. Neurosci. 16(1): 27-38 (2004) - 2003
- [j22]Thomas Wennekers, Nihat Ay:
Temporal Infomax on Markov chains with input leads to finite state automata. Neurocomputing 52-54: 431-436 (2003) - [j21]Nihat Ay, Thomas Wennekers:
Temporal infomax leads to almost deterministic dynamical systems. Neurocomputing 52-54: 461-466 (2003) - [j20]Nihat Ay, Thomas Wennekers:
Dynamical properties of strongly interacting Markov chains. Neural Networks 16(10): 1483-1497 (2003) - [j19]Thomas Wennekers, Friedrich T. Sommer, Ad Aertsen:
Editorial: Cell assemblies. Theory Biosci. 122(1): 1-4 (2003) - [j18]Thomas Wennekers, Nihat Ay:
Spatial and temporal stochastic interaction in neuronal assemblies. Theory Biosci. 122(1): 5-18 (2003) - [j17]Friedrich T. Sommer, Thomas Wennekers:
Models of distributed associative memory networks in the brain. Theory Biosci. 122(1): 55-69 (2003) - 2002
- [j16]Andreas Knoblauch, Thomas Wennekers, Friedrich T. Sommer:
Is voltage-dependent synaptic transmission in NMDA receptors a robust mechanism for working memory? Neurocomputing 44-46: 19-24 (2002) - [j15]Thomas Wennekers:
Nonlinear analysis of spatio-temporal receptive fields: I. Dynamic approximation method. Neurocomputing 44-46: 201-206 (2002) - [j14]Thomas Wennekers:
Nonlinear analysis of spatio-temporal receptive fields: II. Dynamic properties of V1 simple cells. Neurocomputing 44-46: 207-212 (2002) - [j13]Thomas Wennekers:
Nonlinear analysis of spatio-temporal receptive fields: III. RF-reconstruction from mean-field approximations. Neurocomputing 44-46: 213-218 (2002) - [j12]Thomas Wennekers:
Nonlinear analysis of spatio-temporal receptive fields: IV. Generic tuning properties for rectifying rate-functions. Neurocomputing 44-46: 219-223 (2002) - [j11]Thomas Wennekers:
Dynamic Approximation of Spatiotemporal Receptive Fields in Nonlinear Neural Field Models. Neural Comput. 14(8): 1801-1825 (2002) - [c3]Thomas Wennekers:
Nonlinear Analysis of Simple Cell Tuning in Visual Cortex. ICANN 2002: 63-68 - 2001
- [j10]Thomas Wennekers:
Nonlinear analysis of orientation tuning: Stationary properties of simple cells in V1. Neurocomputing 38-40: 439-444 (2001) - [j9]Thomas Wennekers, Frank Pasemann:
Generalized types of synchronization in networks of spiking neurons. Neurocomputing 38-40: 1037-1042 (2001) - [j8]Friedrich T. Sommer, Thomas Wennekers:
Associative memory in a pair of cortical cell groups with reciprocal projections. Neurocomputing 38-40: 1575-1580 (2001) - [j7]Katrin Suder, Florentin Wörgötter, Thomas Wennekers:
Neural Field Model of Receptive Field Restructuring in Primary Visual Cortex. Neural Comput. 13(1): 139-159 (2001) - [j6]Thomas Wennekers:
Orientation Tuning Properties of Simple Cells in Area V1 Derived from an Approximate Analysis of Nonlinear Neural Field Models. Neural Comput. 13(8): 1721-1747 (2001) - [j5]Friedrich T. Sommer, Thomas Wennekers:
Associative memory in networks of spiking neurons. Neural Networks 14(6-7): 825-834 (2001) - 2000
- [j4]Katrin Suder, Florentin Wörgötter, Thomas Wennekers:
Neural field description of state-dependent visual receptive field changes. Neurocomputing 32-33: 545-551 (2000) - [j3]Thomas Wennekers:
Dynamics of spatio-temporal patterns in associative networks of spiking neurons. Neurocomputing 32-33: 597-602 (2000)
1990 – 1999
- 1999
- [b1]Thomas Wennekers:
Synchronisation und Assoziation in neuronalen Netzen. University of Ulm, Germany, Shaker 1999, ISBN 978-3-8265-4908-3, pp. 1-218 - [j2]Thomas Wennekers, Friedrich T. Sommer:
Gamma-oscillations support optimal retrieval in associative memories of two-compartment neurons. Neurocomputing 26-27: 573-578 (1999) - [j1]Thomas Wennekers, Günther Palm:
How imprecise is neuronal synchronization? Neurocomputing 26-27: 579-585 (1999) - [c2]Katrin Suder, Florentin Wörgötter, Thomas Wennekers:
Neural field description of state-dependent receptive field changes in the visual cortex. ESANN 1999: 171-176 - 1996
- [c1]Thomas Wennekers, Günther Palm:
Controlling the Speed of Synfire Chains. ICANN 1996: 451-456
Coauthor Index
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