Thomas Wennekers

发表

Language models based on Hebbian cell assemblies

Friedemann Pulvermüller, Thomas Wennekers, Max Garagnani, 2006, Journal of Physiology-Paris.

A Spiking Self-Organizing Map Combining STDP, Oscillations, and Continuous Learning

Thomas Wennekers, Timothy Rumbell, Susan L. Denham, 2014, IEEE Transactions on Neural Networks and Learning Systems.

Dynamical properties of strongly interacting Markov chains

Thomas Wennekers, Nihat Ay, 2003, Neural Networks.

Formal concepts expressed by compositional hierarchical Hebbian cell assemblies

Thomas Wennekers, 2009, BMC Neuroscience.

Analysis of spatio-temporal patterns in associative networks of spiking neurons

Thomas Wennekers, T. Wennekers, 1999 .

Dynamic Approximation of Spatiotemporal Receptive Fields in Nonlinear Neural Field Models

Thomas Wennekers, T. Wennekers, 2002, Neural Computation.

Nonlinear analysis of spatio-temporal receptive fields: III. RF-reconstruction from mean-field approximations

Thomas Wennekers, T. Wennekers, 2002, Neurocomputing.

The role of feedback in a hierarchical model of object perception.

Thomas Wennekers, Salvador Dura-Bernal, Susan L Denham, 2011, Advances in experimental medicine and biology.

A neuronal model of the language cortex

Friedemann Pulvermüller, Thomas Wennekers, Max Garagnani, 2007, Neurocomputing.

Operational Cell Assemblies as a Paradigm for Brain-Inspired Future Computing Architectures

Thomas Wennekers, T. Wennekers, 2006 .

On the Natural Hierarchical Composition of Cliques in Cell Assemblies

Thomas Wennekers, T. Wennekers, 2009, Cognitive Computation.

Neural Field Model of Receptive Field Restructuring in Primary Visual Cortex

Florentin Wörgötter, Thomas Wennekers, Katrin Suder, 2001, Neural Computation.

Nonlinear analysis of orientation tuning: Stationary properties of simple cells in V1

Thomas Wennekers, 2001, Neurocomputing.

Editorial: Cell assemblies

Ad Aertsen, Thomas Wennekers, Friedrich T. Sommer, 2003, Theory in Biosciences.

Dynamics of parameters of neurophysiological models from phenomenological EEG modeling

Eckehard Olbrich, Thomas Wennekers, 2007, Neurocomputing.

Emotions in autonomous agents: comparative analysis of mechanisms and functions

Sue L. Denham, Thomas Wennekers, John A. Barnden, 2012, Autonomous Agents and Multi-Agent Systems.

How imprecise is neuronal synchronization?

Günther Palm, Thomas Wennekers, 1999, Neurocomputing.

A natural approach to studying schema processing pdf

Thomas Wennekers, Jack McKay Fletcher, T. Wennekers, 2017, ArXiv.

Feedback in a hierarchical model of object recognition in cortex

Thomas Wennekers, Salvador Dura, Sue Denham, 2009, BMC Neuroscience.

Synchronisation und Assoziation in neuronalen Netzen

Thomas Wennekers, 1999 .

Tuned solutions in dynamic neural fields as building blocks for extended EEG models

Thomas Wennekers, T. Wennekers, 2008, Cognitive Neurodynamics.

Nonlinear analysis of spatio-temporal receptive fields: I. Dynamic approximation method

Thomas Wennekers, 2002, Neurocomputing.

Orientation Tuning Properties of Simple Cells in Area V1 Derived from an Approximate Analysis of Nonlinear Neural Field Models

Thomas Wennekers, T. Wennekers, 2001, Neural Computation.

A temporal learning rule in recurrent systems supports high spatio-temporal stochastic interactions

Thomas Wennekers, Nihat Ay, N. Ay, 2006, Neurocomputing.

Separation of Spatio-Temporal Receptive Fields into Sums of Gaussian Components

Thomas Wennekers, T. Wennekers, 2004, Journal of Computational Neuroscience.

Phase-of-firing information coding in laminar cortical architecture

Thomas Wennekers, Gleb Basalyga, Marcelo Montemurro, 2011, BMC Neuroscience.

Neural field description of state-dependent receptive field changes in the visual cortex

Florentin Wörgötter, Thomas Wennekers, Katrin Suder, 1999, ESANN.

Gait-based person and gender recognition using micro-doppler signatures

Thomas Wennekers, Julius Georgiou, Salvador Dura-Bernal, 2011, 2011 IEEE Biomedical Circuits and Systems Conference (BioCAS).

Stochastic interaction in associative nets

Thomas Wennekers, Nihat Ay, 2005, Neurocomputing.

Neural Network Model of Semantic Processing in the Remote Associates Test

Thomas Wennekers, Ivana Kajic, 2015, CoCo@NIPS.

Multimodal Integration of Micro-Doppler Sonar and auditory signals for Behavior Classification with convolutional Networks

Andreas G. Andreou, Sue L. Denham, Thomas Wennekers, 2013, Int. J. Neural Syst..

Microcircuits - Their structure, dynamics and role for brain function

John G. Taylor, Thomas Wennekers, Bruce P. Graham, 2009, Neural Networks.

STDP pattern onset learning depends on background activity.

Steve Furber, Thomas Wennekers, Susan L Denham, 2011, Advances in experimental medicine and biology.

Controlling the Speed of Synfire Chains

Günther Palm, Thomas Wennekers, G. Palm, 1996, ICANN.

Models of distributed associative memory networks in the brain

Thomas Wennekers, Friedrich T. Sommer, F. Sommer, 2003, Theory in Biosciences.

Neural field description of state-dependent visual receptive field changes

Florentin Wörgötter, Thomas Wennekers, Katrin Suder, 2000, Neurocomputing.

for Cognitive Acoustic Scene Analysis

Andrew S. Cassidy, Andreas G. Andreou, Alexandra Bendixen, 2011 .

2009 Special Issue: Spatiotemporal dynamics in the cortical microcircuit: A modelling study of primary visual cortex layer 2/3

Thomas Wennekers, Andrew Symes, T. Wennekers, 2009 .

Spatial and temporal stochastic interaction in neuronal assemblies

Thomas Wennekers, Nihat Ay, N. Ay, 2003, Theory in Biosciences.

What must come down goes up - the effect of noise on weights in spike-timing-dependent plasticity

Angelo Cangelosi, Thomas Wennekers, Michael Klein, 2015, BMC Neuroscience.

Modelling object perception in cortex: Hierarchical Bayesian networks and belief propagation

Sue L. Denham, Thomas Wennekers, Salvador Dura-Bernal, 2011, 2011 45th Annual Conference on Information Sciences and Systems.

From Structure to Activity: Using Centrality Measures to Predict Neuronal Activity

Thomas Wennekers, Jack McKay Fletcher, T. Wennekers, 2016, Int. J. Neural Syst..

Abstract Stimulus-Specific Adaptation Models

Sue L. Denham, Thomas Wennekers, Martin Coath, 2011, Neural Computation.

A Spiking Neurocomputational Model of High-Frequency Oscillatory Brain Responses to Words and Pseudowords

Friedemann Pulvermüller, Thomas Wennekers, Max Garagnani, 2017, Front. Comput. Neurosci..

Nonlinear analysis of spatio-temporal receptive fields: IV. Generic tuning properties for rectifying rate-functions

Thomas Wennekers, 2002, Neurocomputing.

Hippocampus, microcircuits and associative memory

Thomas Wennekers, Vassilis Cutsuridis, T. Wennekers, 2009, Neural Networks.

Cell Assemblies, Associative Memory and Temporal Structure in Brain Signals

Günther Palm, Thomas Wennekers, G. Palm, 2000 .

Models of distributed associative memory networks in the brain

Thomas Wennekers, Friedrich T. Sommer, F. Sommer, 2003, Theory in biosciences.

Recruitment and Consolidation of Cell Assemblies for Words by Way of Hebbian Learning and Competition in a Multi-Layer Neural Network

Friedemann Pulvermüller, Thomas Wennekers, Max Garagnani, 2009, Cognitive Computation.

Neural field description suggests feedforward mechanism of state-dependent visual receptive field changes

Thomas Wennekers, Florentin Wörgötter, Katrin Suder, 1999 .

Application of arachnid prey localisation theory for a robot sensorimotor controller

Guido Bugmann, Phil F. Culverhouse, Sue L. Denham, 2011, Neurocomputing.

Synfire graphs: from spike patterns to automata of spiking neurons

Thomas Wennekers, T. Wennekers, 2013 .

Scaling the HTM Spatial Pooler

Bogdan Ghita, Thomas Wennekers, Andreas Pech, 2020 .

Is voltage-dependent synaptic transmission in NMDA receptors a robust mechanism for working memory?

Thomas Wennekers, Andreas Knoblauch, Friedrich T. Sommer, 2002, Neurocomputing.

Iterative Retrieval In Associative Memories By Threshold Control Of Different Neural Models

Günther Palm, Thomas Wennekers, Friedrich T. Sommer, 1995 .

Emergent feature sensitivity in a model of the auditory thalamocortical system.

Thomas Wennekers, Martin Coath, Robert Mill, 2011, Advances in experimental medicine and biology.

A Neurocomputational Model of Stimulus-Specific Adaptation to Oddball and Markov Sequences

Sue L. Denham, Thomas Wennekers, Martin Coath, 2011, PLoS Comput. Biol..

Adaptive training of cortical feature maps for a robot sensorimotor controller

Phil F. Culverhouse, Sue L. Denham, Thomas Wennekers, 2013, Neural Networks.

The Parallel HTM Spatial Pooler with Actor Model

Bogdan Ghita, Thomas Wennekers, Andreas Pech, 2020 .

Behavioral Learning in a Cognitive Neuromorphic Robot: An Integrative Approach

Angelo Cangelosi, Steve Furber, Thomas Wennekers, 2018, IEEE Transactions on Neural Networks and Learning Systems.

Towards a Cognitively Realistic Representation of Word Associations

Thomas Wennekers, Terrence C. Stewart, Chris Eliasmith, 2016, CogSci.

Emergence of small-world structure in networks of spiking neurons through STDP plasticity.

Thomas Wennekers, Gleb Basalyga, P. M. Gleiser, 2011, Advances in experimental medicine and biology.

Special Issue on Computational Neuroscience

Thomas Wennekers, 2012, Journal of Neuroscience Methods.

Information coding in a laminar computational model of cat primary visual cortex

Marcelo A. Montemurro, Thomas Wennekers, Gleb Basalyga, 2012, Journal of Computational Neuroscience.

Nonlinear analysis of spatio-temporal receptive fields: II. Dynamic properties of V1 simple cells

Thomas Wennekers, 2002, Neurocomputing.

Synfire chains with conductance-based neurons: internal timing and coordination with timed input

Thomas Wennekers, Friedrich T. Sommer, F. Sommer, 2005, Neurocomputing.

A multimodal-corpus data collection system for cognitive acoustic scene analysis

Andrew S. Cassidy, Andreas G. Andreou, Sue L. Denham, 2011, 2011 45th Annual Conference on Information Sciences and Systems.

Visual attention and object naming in humanoid robots using a bio-inspired spiking neural network

Angelo Cangelosi, Steve B. Furber, Thomas Wennekers, 2018, Robotics Auton. Syst..

Information-theoretic grounding of finite automata in neural systems

Thomas Wennekers, Nihat Ay, 2002 .

Editorial: Cell Assemblies

Ad Aertsen, Thomas Wennekers, Friedrich T. Sommer, 2003 .

A Hebbian cell assembly based neural field model for the remote associate task and creative search

Thomas Wennekers, Ivana Kajic, 2015, BMC Neuroscience.

Bidirectional completion of cell assemblies in the cortex

Günther Palm, Thomas Wennekers, Friedrich T. Sommer, 1998 .

Gamma-oscillations support optimal retrieval in associative memories of two-compartment neurons

Thomas Wennekers, Friedrich T. Sommer, 1999, Neurocomputing.

Dynamics of spatio-temporal patterns in associative networks of spiking neurons

Thomas Wennekers, T. Wennekers, 2000, Neurocomputing.

A Neurobiologically Constrained Cortex Model of Semantic Grounding With Spiking Neurons and Brain-Like Connectivity

Friedemann Pulvermüller, Thomas Wennekers, Max Garagnani, 2018, Front. Comput. Neurosci..

Learning Bidirectional Connections Between Areas With Standard Spike-Timing-Dependent Plasticity

Angelo Cangelosi, Thomas Wennekers, M. Klein, 2016 .

A robust sound perception model suitable for neuromorphic implementation

Giacomo Indiveri, Thomas Wennekers, Sadique Sheik, 2014, Front. Neurosci..

Thinking in circuits: toward neurobiological explanation in cognitive neuroscience

Friedemann Pulvermüller, Thomas Wennekers, Max Garagnani, 2014, Biological Cybernetics.

Emergent Auditory Feature Tuning in a Real-Time Neuromorphic VLSI System

Giacomo Indiveri, Thomas Wennekers, Sadique Sheik, 2011, Front. Neurosci..

Generalized types of synchronization in networks of spiking neurons

Frank Pasemann, Thomas Wennekers, 2001, Neurocomputing.

Spatial and Temporal Stochastic Interaction in Neuronal Assemblies

Thomas Wennekers, Nihat Ay, 2003 .

Finite State Automata Resulting from Temporal Information Maximization and a Temporal Learning Rule

Thomas Wennekers, Nihat Ay, T. Wennekers, 2005, Neural Computation.

Syntactic sequencing in Hebbian cell assemblies

Günther Palm, Thomas Wennekers, G. Palm, 2009, Cognitive Neurodynamics.

Temporal Infomax Leads to Almost Deterministic Dynamical Systems

Thomas Wennekers, Nihat Ay, N. Ay, 2002, Neurocomputing.

Spatio-temporal pattern recognizers using spiking neurons and spike-timing-dependent plasticity

Sue L. Denham, Thomas Wennekers, James Humble, 2012, Front. Comput. Neurosci..

A cell assembly model for complex behaviour

Thomas Wennekers, 2007, Neurocomputing.

Associative memory in a pair of cortical cell groups with reciprocal projections

Thomas Wennekers, Friedrich T. Sommer, F. Sommer, 2001, Neurocomputing.

High-resolution multiple-unit EEG in cat auditory cortex reveals large spatio-temporal stochastic interactions

Thomas Wennekers, Nihat Ay, Péter András, 2007, Biosyst..

Large-scale computational model of cat primary visual cortex

Thomas Wennekers, Gleb Basalyga, 2009, BMC Neuroscience.

Modelling studies on the computational function of fast temporal structure in cortical circuit activity

Thomas Wennekers, Friedrich T Sommer, F. Sommer, 2000, Journal of Physiology-Paris.

Nonlinear Analysis of Simple Cell Tuning in Visual Cortex

Thomas Wennekers, 2002, ICANN.

Cortical activity pattern computation

Thomas Wennekers, Péter András, T. Wennekers, 2007, Biosyst..

A Spiking Neuron Model of Word Associations for the Remote Associates Test

Thomas Wennekers, Terrence C. Stewart, Chris Eliasmith, 2017, Front. Psychol..

Fitting of spatio-temporal receptive fields by sums of Gaussian components

Thomas Wennekers, Katrin Suder, K. Suder, 2004, Neurocomputing.

Temporal Infomax on Markov Chains with Input Leads to Finite State Automata

Thomas Wennekers, Nihat Ay, N. Ay, 2002, Neurocomputing.

Semantic grounding in a neurobiologically-constrained cortex-model with realistic connectivity and spiking neurons

Thomas Wennekers, Max Garagnani, Friedemann Pulvermüller, 2017 .

Associative memory in networks of spiking neurons

Thomas Wennekers, Friedrich T. Sommer, F. Sommer, 2001, Neural Networks.

Improved HTM Spatial Pooler with Homeostatic Plasticity Control

Bogdan Ghita, Thomas Wennekers, Andreas Pech, 2021, ICPRAM.

Controlling the Speed of Synnre Chains

Thomas Wennekers, T. Wennekers, 1996 .

The sleeping brain as a complex system

Eckehard Olbrich, Peter Achermann, Thomas Wennekers, 2011, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

A neuroanatomically grounded Hebbian-learning model of attention–language interactions in the human brain

Friedemann Pulvermüller, Thomas Wennekers, Max Garagnani, 2008, The European journal of neuroscience.

Pattern formation in intracortical neuronal fields

Thomas Wennekers, Michael Bestehorn, Axel Hutt, 2003, Network.

On the relation between neural modelling and experimental neuroscience

Thomas Wennekers, T. Wennekers, G. Palm, 1997 .

A neural network model of the cortico-hippocampal interplay and the representation of contexts

Günther Palm, Thomas Wennekers, G. Palm, 1995, Behavioural Brain Research.

Visual cortex recruitment during language processing in blind individuals is explained by Hebbian learning

Friedemann Pulvermüller, Thomas Wennekers, Max Garagnani, 2019, Scientific Reports.

Brain connections of words, perceptions and actions: A neurobiological model of spatio-temporal semantic activation in the human cortex

Friedemann Pulvermüller, Thomas Wennekers, Max Garagnani, 2017, Neuropsychologia.

SYNCHRONOUS CHAOS IN HIGH-DIMENSIONAL MODULAR NEURAL NETWORKS

Frank Pasemann, Thomas Wennekers, 1996 .