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Laboratory of Computational Neuroscience - LCN |
Claudia Clopath, Lars Busing, Eleni Vasilaki and Wulfram Gerstner (2009)
Connectivity reflects coding: A model of voltage-based spike-timing-dependent-plasticity with homeostasis.
Nature Neuroscience,
Published online: 24 January 2010 | doi:10.1038/nn.2479.
public preprint version
Eleni Vasilaki1, Nicolas Fremaux, Robert Urbanczik, Walter Senn, Wulfram Gerstner (2009)
Spike-Based Reinforcement Learning in Continuous State and Action Space: When Policy Gradient Methods Fail
PLoS Comput Biol 5(12): e1000586. doi:10.1371/journal.pcbi.1000586
Wulfram Gerstner and Richard Naud (2009)
How good are neuron models?
Science, vol. 326: 379-380
Gediminas Luksys, Wulfram Gerstner, and Carmen Sandi (2009)
Stress, genotype and norepinephrine in the prediction of mouse behavior using reinforcement learning
Nature Neuroscience 12:1180-1186
Published online: 16 August 2009 | doi:10.1038/nn.2374
Wulfram Gerstner and Romain Brette (2009)
Adaptive exponential integrate-and-fire model.
Scholarpedia, 4:8427
Denis Sheynikhovich, Ricardo Chavarriaga, Thomas Strosslin, Angelo Arleo and
Wulfram Gerstner (2009)
Is there a geometric module for spatial orientation? Insights from a rodent navigation
model
Psychological Review, 116:540-566.
link to journal WEB site of this article
Wulfram Gerstner (2009). Spiking Neuron Models (short review article).
IN: Encyclopedia of Neuroscience. (L.R. Squire, Editor), p. 277-280 Oxford: Academic Press.
pdf-file
Wulfram Gerstner (2008)
Spike-response model
Scholarpedia, 3(12):1343
Claudia Clopath, Lorric Ziegler, Eleni Vasilaki, Lars Busing, Wulfram Gerstner (2008)
Tag-Trigger-Consolidation: A Model of Early and Late
Long-Term-Potentiation and Depression
PLoS Computational Biology 4(12): e1000248 doi:10.1371/journal.pcbi.1000248
pdf - file
Abigail Morrison, Markus Diesmann, and Wulfram Gerstner (2008)
Phenomenological models of synaptic plasticity based on spike timing
Biological Cybernetics, 98:459-478
pdf-file
Richard Naud, Nicolas Marcille, Claudia Clopath and Wulfram Gerstner (2008)
Firing patterns in the adaptive exponential integrate-and-fire model
Biological Cybernetics 99:335-347
pdf-file
Laurent Badel, Sandrine Lefort, Thomas K. Berger, Carl C. H. Petersen,
Wulfram Gerstner and Magnus J. E. Richardson (2008c)
Extracting non-linear integrate-and-fire models from experimental data using
dynamic I-V curves
Biological Cybernetics 99:361-370
pdf-file
Laurent Badel, Wulfram Gerstner and Magnus J. E. Richardson (2008b).
Spike-triggered Averages for Passive and Resonant Neurons Receiving Filtered Excitatory and Inhibitory Synaptic Drive.
Physical Review E, 78:011914 .
pdf-file
Laurent Badel, Sandrine Lefort, Romain Brette, Carl Petersen,
Wulfram Gerstner and Magnus J.E. Richardson (2008)
Dynamic I-V Curves Are Reliable Predictors of Naturalistic
Pyramidal-Neuron Voltage Traces,
J Neurophysiol 99: 656 - 666, 2008.
pdf-file
Renaud Jolivet, Felix Schuermann, Thomas K. Berger, Richard Naud, Wulfram Gerstnera, and Arnd Roth (2008b)
The quantitative single-neuron modeling competition
Biological Cybernetics 99:417-426
R. Jolivet, R. Kobayashi, A. Rauch, R. Naud, S. Shinomoto, W. Gerstner (2008)
A benchmark test for a quantitative assessment
of simple neuron models.
Journal of Neuroscience Methods 169: 417-424
pdf-file
F. Hermens, G. Luksys, U. Ernst
W. Gerstner, M. H. Herzog (2008)
Modeling Spatial and Temporal Aspects of Visual Backward Masking
Psych. Rev. 115: 83-100
pdf-file
T. Toyoizumi, J.-P. Pfister, K. Aihara, and W. Gerstner (2007)
Optimality Model of Unsupervised Spike-Timing Dependent Plasticity: Synaptic Memory and Weight Distribution
Neural Computation, 19: 639-671
pdf-file AND
link to
Neural Computation article
C. Clopath, R. Jolivet, A. Rauch, H.-R. Lüscher and W. Gerstner (2007)
Predicting neuronal activity with simple models of the threshold type: Adaptive Exponential Integrate-and-Fire model with two compartments
Neurocomputing 70:1668-1673,
from
www.sciencedirect.com
and pdf file
Jean-Pascal Pfister and W. Gerstner (2006)
Triplets of Spikes in a Model of Spike Timing-Dependent Plasticity
J. Neurosci., 26: 9673 - 9682
pdf file
and high-resolution figures
J.-P. Pfister, T. Toyoizumi, D. Barber, and W. Gerstner (2006)
Optimal Spike-Timing Dependent Plasticity for Precise Action Potential Firing
in supervised learning
Neural Computation 18:1309-1339
J.-P. Pfister and W. Gerstner (2006)
Beyond Pair-Based STDP: a Phenomenological Rule for Spike Triplet and Frequency Effects.
Available from: NIPS*2005 Online papers http://books.nips.cc/nips18.html.
IN: Advances in Neural Information Processing Systems 18},
Y. Weiss and B. Schölkopf and J. Platt,
MIT Press, Cambridge, pp 1083--1090
M.J.E. Richardson and W. Gerstner (2006)
Statistics of subthreshold neuronal voltage fluctuations due to conductance-based synaptic shot noise
Chaos 16:026106
R. Jolivet, A. Rauch, H.-R. Lüscher and W. Gerstner (2006)
Integrate-and-Fire models with adaptation are good enough
Available from: NIPS*2005 Online papers http://books.nips.cc/nips18.html.
IN: Advances in Neural Information Processing Systems 18},
Y. Weiss and B. Schölkopf and J. Platt,
MIT Press, Cambridge,
pp. 595--602
R. Jolivet, A. Rauch, H.-R. Lüscher and W. Gerstner (2006)
Predicting spike timing of neocortical pyramidal neurons by simple threshold models
Journal of Computational Neuroscience 21:35-49
pdf file (preprint version) and
official SpringerLink online version
Y. Aviel and W. Gerstner (2006)
From spiking neurons to rate models:
a cascade model
as an approximation to spiking neuron models with refractoriness
Phys. Rev. E 73, 051908
link to PRE
and pdf file
Laurent Badel, Wulfram Gerstner and Magnus J.E. Richardson (2006)
Dependence of the spike-triggered average voltage on membrane response properties,
Neurocomputing, Volume 69:1062-1065
Link to ScienceDirect
and pdf file
Romain Brette and Wulfram Gerstner (2005)
Adaptive Exponential Integrate-and-Fire Model as an Effective Description of Neuronal Activity
J Neurophysiol, 94: 3637 - 3642
T. Toyoizumi, J.-P. Pfister, K. Aihara, and W. Gerstner (2005)
Generalized Bienenstock-Cooper-Munro rule for spiking neurons that maximizes information transmission
Proc. Natl. Acad. Sci. USA, 102:5239-5244
pdf-file (main text) and
supporting information
M.J.E. Richardson and W. Gerstner (2005)
Synaptic shot noise and conductance fluctuations affect the membrane voltage with equal significance
Neural Computation, 17:923-947
pdf file (preprint version)
full text (printed version, MIT-press)
T. Toyoizumi, J.-P. Pfister, K. Aihara, and W. Gerstner (2005)
Spike-timing Dependent Plasticity and Mutual Information Maximization for a Spiking Neuron Model
Advances in Neural Information Processing Systems 17 ,
edited by L.K. Saul and Y. Weiss and L. Bottou (MIT-Press), pp.
1409-1416
pdf-file
D. Sheynikhovich, R. Chavarriaga, T. Strösslin and W. Gerstner (2005)
Spatial Representation and Navigation in a Bio-inspired Robot
In:
Biomimetic Neural Learning for Intelligent Robots: Intelligent Systems, Cognitive Robotics, and Neuroscience,
edited by Stefan Wermter, Günther Palm, Mark Elshaw , pp. 245-264.
pdf-file
T. Strösslin, D. Sheynikhovich, R. Chavarriaga, and W. Gerstner (2005)
Robust self-localisation and navigation based on hippocampal place cells
NEURAL NETWORKS 18 (9): 1125-1140
pdf-file
T. Strösslin, R. Chavarriaga, D. Sheynikhovich, and W. Gerstner (2005)
Modeling Path Integrator Recalibration Using Hippocampal Place cells
In:
ICANN 2005,
edited by W. Duch et al., Lecture Notes in Computer Science Vol. 3696
, pp. 51-56.
pdf-file
Ricardo Chavarriaga, Thomas Strösslin, Denis Sheynikhovich and
Wulfram Gerstner (2005)
A computational model of parallel navigation systems
in rodents
Neuroinformatics, 3:223-241
pdf-file
Ricardo Chavarriaga, Thomas Strösslin, Denis
Sheynikhovich and Wulfram Gerstner (2005)
Competition between cue response and place response:
A model of rat navigation behaviour
Connection Science, 17: 167-183.
pdf-file
J. Mayor and W. Gerstner (2005)
Noise-enhanced computation in a model of a cortical column
NEUROREPORT 16 (11): 1237-1240
pdf-file (preprint version)
J. Mayor and W. Gerstner (2005)
Signal buffering in random networks of spiking neurons: microscopic vs. macroscopic phenomena
Phys. Rev. E 72, 051906 (2005)
pdf-file
M.J.E. Richardson, O. Melamed, G. Silberberg, W. Gerstner
and H. Markram (2005)
Short-term synaptic plasticity orchestrates the response of
pyramical cells and interneurons to population bursts
J. Computational Neuroscience 18:323-331
pdf file
O. Melamed and G. Silberberg and H. Markram and
W. Gerstner and M.J.E. Richardson (2004)
Subthreshold cross-correlations between cortical neurons:
A reference model with static synapses.
Neurocomputing 65-66 (special issue of the CNS'04 conference):685-690
pdf file
R. Jolivet and T. J. Lewis and W. Gerstner (2004)
Generalized Integrate-and-Fire Models of Neuronal Activity Approximate Spike Trains of a Detailed Model to a High Degree of Accuracy.
J. Neurophysiology 92: 959-976
pdf file (preprint version)
J. del R. Millan and F. Renkens and J. Mourino and W. Gerstner (2004b)
Brain actuated interaction
Artificial Intelligence, 159:241-259
[ pdf file]
J. del R. Millan and F. Renkens and J. Mourino and W. Gerstner (2004)
Non-invasive Brain actuated control of a mobile robot by Human EEG
IEEE Transactions Biomedical Engineering, 51:1026-1033
[ pdf file]
O. Melamed and W. Gerstner and W. Maass and M. Tsodyks and H. Markram (2004)
Coding and Learning of behavioral sequences
Trends in Neurosciences, 27:11-14
A. Arleo and F. Smeraldi and W. Gerstner (2004)
Cognitive navigation based on non-uniform Gabor space sampling, unsupervised
growing networks, and reinforcement learning.
IEEE Transactions on Neural Networks, 15:639-652.
J. Mayor and W. Gerstner (2004)
Transient information flow in a network of excitatory and inhibitory model neurons: role of noise and signal autocorrelation
J. Physiology (Paris) Vol. 98: 417-428
pdf file
R. Jolivet and W. Gerstner (2004)
Predicting spike times of a detailed conductance-based neuron model driven by stochastic spike arrival.
available from
Q-Bio archive: q-bio.NC/0407010
J. Physiology (Paris) Vol. 98: 442-451
[ pdf file ],
[
link to J. Physiology (Paris) ]
A. Tonnelier and W. Gerstner (2003)
Piecewise linear differential equations and integrate-and-fire neurons : insights from two-dimensional membrane models,
Phys. Rev. E 67, 021908,
[ pdf file]
J. Mayor and W. Gerstner (2003)
Online processing of multiple inputs in a sparsely-connected recurrent neural network
Proc. Joint International Conference ICANN/ICONIP 2003,
Kaynak et al. (Eds.),
Springer, LNCS 2714, pp. 839-845,
[ pdf file]
R. Jolivet, T.J. Lewis and W. Gerstner (2003)
The Spike Response Model: a Framework to Predict Neuronal Spike
Trains.
Proc. Joint International Conference ICANN/ICONIP 2003,
Kaynak et al. (Eds.),
Springer, LNCS 2714, pp. 846-853,
[ pdf file]
J.-P. Pfister, D. Barber, and W. Gerstner (2003)
Optimal Hebbian Learning: a Probabilistic Point of View.
Proc. Joint International Conference ICANN/ICONIP 2003,
Kaynak et al. (Eds.),
Springer, LNCS 2714, pp. 92-98,
[ pdf file]
J. del R. Millan, F. Renkens, J. Mourino, and W. Gerstner,
Non-Invasive Brain-Actuated Control of a Mobile Robot. "
P roceedings of the 18th International Joint Conference on Artificial Intelligence, pp. 1121--1126
[ pdf file]",
Thomas Strösslin and Wulfram Gerstner (2003)
Reinforcement Learning in Continuous State
and Action Space
presented at: Artificial Neural Networks - ICANN 2003
pdf file
See also:
PhD thesis, EPFL, Thomas Stroesslin
BOOK: `Spiking Neuron Models -
Single Neurons, Populations, Plasticity'
Cambridge Univ. Press (2002)
W. Gerstner and W. Kistler (2002).
Mathematical formulations of Hebbian Learning.
Biological Cybernetics, 87:404-415.
[ pdf file]
W.M. Kistler and W. Gerstner (2002).
Stable Propagation of Activity Pulses in Populations of Spiking Neurons.
Neural Computation, 14:987-997
Abstract .
Here is the link to the pdf via the
Neural Computation Web page
A. Herrmann and W. Gerstner (2002).
Noise and the PSTH response to current transients:
II: Integrate-and-fire model with slow recovery and
application to motoneuron data.
Journal of Computational Neuroscience 12:83-95
Abstract .
[ pdf file]
W. Gerstner (2002).
Integrate-and-Fire Neurons and Networks.
In: The Handbook of Brain Theory and Neural Networks, Second edition, (M.A. Arbib, Ed.), Cambridge, MA:
The MIT Press, 2002 , pp. 577-581
[ pdf file]
W. Gerstner (2001).
Coding Properties of Spiking Neurons:
Reverse and Cross-Correlations.
Neural Networks 14:599-610
Abstract
[ pdf file]
A. Herrmann and W. Gerstner (2001).
Noise and the PSTH response to current transients:
I. General theory and application to the integrate-and-fire neuron.
Journal of Computational Neuroscience 11:135-151,
Abstract
[ pdf file]
R. Kempter and W. Gerstner and J.L. van Hemmen (2001).
Intrinsic stabilization of outout firing rates by
spike-based Hebbian learning
Neural Computation, 13:2709-2741
Abstract
[ pdf file]
M. Spiridon and W. Gerstner (2001).
Effect of lateral connections on the accuracy of the population
code for a network of spiking neurons.
NETWORK - Computation in Neural Systems, 12:409-421
Abstract .
[ pdf file]
A. Arleo and W. Gerstner (2001).
Hippocampal spatial model for state space representation
in robotics and reinforcement learning
.
Proceedings of the fifth European Workshop on Reinforcement Learning,
M.A. Wiering (Ed.), CKI Utrecht University
A. Arleo and W. Gerstner (2001).
Spatial orientation in navigating agents: Modeling head-direction
cells.
Neurocomputing 38-40:1059-1065
[ pdf file]
A. Arleo, F. Smeraldi, S. Hug, and W. Gerstner (2001).
Place Cells and Spatial Navigation based on Vision, Path Integration, and Reinforcement Learning.
In: Advances in Neural Information Processing Systems 13, MIT-Press, Denver, December 2000. pp. 89-95
[pdf file],
W. Gerstner (2001)
A Framework for Spiking Neuron Models:
The Spike Response Model
In: The Handbook of Biological Physics, Vol.4 (Ch. 12),
pp 469-516
Frank Moss and Stan Gielen (Eds.),
Elsevier Science, 2001
W. Gerstner (2001)
What's different with spiking neurons?
Plausible Neural Networks for Biological Modelling,
Henk Mastebroek and Hans Vos (Eds.), Kluwer Academic Publishers
pp. 23- 48
A. Arleo and W. Gerstner (2000)
Spatial Cognition and Neuro-Mimetic Navigation:
A Model of Hippocampal Place Cell Activity
Biological Cybernetics, 83:287-299.
[pdf file],
Here is the
online version of the special issue
A. Arleo and W. Gerstner (2000)
Modeling Rodent Head-direction Cells and Place Cells for Spatial Learning in Bio-mimetic Robotics,
Sixth Int. Conf. on the Simulation of Adaptive Behavior, from Animals to Animats --SAB2000, Paris.
W. Gerstner (2000)
Population Dynamics of Spiking Neurons:
Fast Transients, Asynchronous States, and Locking.
Neural Computation 12:43-89.
[ pdf file]
Hans E. Plesser and W. Gerstner (2000)
Noise in integrate-and-fire neurons:
from stochastic input to escape rates
Neural Computation 12:367-384.
[ pdf file]
A. Herrmann, W.Gerstner. (2000)
Effect of noise on neuron transient response.
Neurocomputing 32-33: 147-154
H.E. Plesser, W.Gerstner. (2000)
Escape rate models for noisy integrate-and-fire neurons
Neurocomputing 32-33: 219-224
R. Kempter, W. Gerstner, and J. L. van Hemmen (1999)
Hebbian Learning and Spiking Neurons
Physical Review E, 59:4498-4514
Abstract
[ pdf file]
M. Spiridon and W. Gerstner W (1999)
Noise spectrum and signal transmission through
a population of spiking neurons
Network: Computation in Neural Systems, 10:257-272
[ pdf file]
Mar DJ, Chow CC, Gerstner W, Adams RW, and Collins JJ (1999)
Noise-shaping in a population of coupled model neurons
Proceedings of the National Academy of Sciences, 96: 10450-10455
g
Angelo Arleo, Wulfram Gerstner (1999)
Neuro-Mimetic Navigation Systems: A Computational Model of the Hippocampus,
In: Intelligence Artificielle Située,
edited by A. Grogoul and J.-A. Meyer, Hermes(Paris), 1999, pp. 193-211
A. Arleo and W. Gerstner (1999)
A vision-driven model of
hippocampal place cells and
temporally asymmetric LTP-induction for action learning,
In: ICANN'99 Artificial Neural Networks,}
conference publication 470, IEE (UK),
pp. 132-137
W. Gerstner (1999)
Rapid signal transmission by populations of spiking neurons.
In: ICANN'99 Artificial Neural Networks,}
conference publication 470, IEE (UK),
pp. 7-12
A. Herrmann and W. Gerstner (1999)
Understanding the PSTH response to synaptic input
In: ICANN'99 Artificial Neural Networks,}
conference publication 470, IEE (UK),
pp. 1012-1017
R. Kempter, W. Gerstner, and J. L. van Hemmen (1999)
Spike-Based Compared to
Rate-Based Hebbian Learning
NIPS conference, Denver, December 1998.
Advances in Neural Information Processing Systems 11,
MIT-Press, edited by M.S. Kearns and S.A. Solla and D. A. Cohn, pp. 125-131
R. Kempter, W. Gerstner, H. Wagner, and J. L. van Hemmen (1999)
The quality of Coincidence detection and ITD-tuning:
a theoretical framework.
Psychophysics, Physiology and Models
of Hearing. T. Dau, V. Hohmann, and B. Kollmeier (Eds.),
World Scientific, Singapore, pp. 185-194.
R. Kempter, W. Gerstner, J.L. van Hemmen, and H. Wagner (1998)
Extracting oscillations: neuronal coincidence detection
with noisy periodic spike input.
Neural Computation, 10:1987-2017
[ pdf file]
W. Gerstner (1998)
Spiking neurons
In: W. Maass and C.M. Bishop (Editors),
Pulsed Neural Networks, MIT press, pp. 3-54
W. Gerstner (1998)
Populations of spiking neurons
In: W. Maass and C.M. Bishop (Editors),
Pulsed Neural Networks, MIT press, pp. 261-295
W. Gerstner, R. Kempter, J.L. van Hemmen, and H. Wagner (1998)
Hebbian learning of pulse timing in the barn owl auditory system
In: W. Maass and C.M. Bishop (Editors),
Pulsed Neural Networks, MIT press, pp. 353-377
M. Spiridon, C.C. Chow and W. Gerstner (1998)
Frequency spectrum of coupled stochastic neurons
with refractoriness.
in: L. Niklasson, M. Boden. and T. Ziemke (Eds.),
ICANN'98, Springer-Verlag,
pp. 337-342
S. Wimbauer, W. Gerstner and J.L. van Hemmen (1998)
Analysis of a correlation-based model for the development
of orientation-selective receptive fields in the visual cortex.
Network 9:449-466
R. Kempter, W. Gerstner and J.L. van Hemmen (1998)
How the threshold of a neuron determines its capacity
for coincidence detection.
BioSystems 48:105-112
W. Gerstner (1998)
Supervised Learning for Neural Networks:
A Tutorial with JAVA exercises
Technical Report (see also our
Neural Java Applets
).
Kistler W, Gerstner W, and van Hemmen JL (1997)
Reduction of Hodgkin-Huxley equations to a
threshold model.
Neural Comput. 9:1069-1100
W. Gerstner and L.F. Abbott (1997)
Learning navigational maps through potentiation
and modulation of hippocampal place cells.
J. Comput. Neurosci. 4:79-94
- Abstract,
- text.ps.Z,
- Figs.ps.Z
W. Gerstner, A. K. Kreiter, H. Markram, and A.V.M .Herz (1997)
Neural codes: firing rates and beyond
Proc. Natl. Acad. Sci. USA 94:12740-12741
R. Ritz, W. Gerstner, R. Gaudoin, and J.L. van Hemmen (1997)
Poisson-like neuronal firing due to multiple synfire chains
in simultaneous action
In: Computational Neuroscience: Trends in Research 1997,
Plenum Press, New York, pp. 801-806
W. Gerstner, R. Kempter, J.L. van Hemmen, and H. Wagner (1997)
A developmental learning rule for coincidence tuning in the barn owl
auditory system
In: Computational Neuroscience: Trends in Research 1997,
Plenum Press, New York, pp. 665-669
Gerstner W, Kempter R, van Hemmen JL, and Wagner H (1996)
A neuronal learning rule for sub-millisecond temporal coding.
Nature, 383 :76-78
Abstract,
[ figs.pdf ]
[ reprint.pdf ]
Gerstner W (1996)
Rapid phase locking in systems of pulse-coupled oscillators
with delays
Phys. Rev. Lett. 76 :1755-1758
Fuentes U, Ritz R, Gerstner W, and van Hemmen JL (1996)
Vertical Signal Flow and Oscillations in a
3-Layer Model of the Cortex
J. Comput. Neurosci. 3:125-136
Gerstner W, van Hemmen JL, and Cowan JD (1996)
What matters in neuronal locking
Neural Computation 8:1653-1676
- Abstract,
- text.ps.Z,
- figs.ps.Z,
Kempter R, Gerstner W, van Hemmen JL, and Wagner H (1996)
Temporal coding
in the sub-millisecond range:
Model of barn owl auditory pathway
Advances in Neural Information Processing Systems 8, MIT Press,
Cambridge, pp.124 - 130
Gerstner W (1995)
Time structure of the activity in neural network models .
Phys. Rev. E, 51 :738-758
[ pdf file]
Fohlmeister C, Gerstner W, Ritz R, and van Hemmen JL (1995)
Spontaneous excitations in the visual cortex: stripes, spirals,
rings, and collective bursts.
Neural Comput. 7 :905-914
Gaudoin R, Gerstner W, and van Hemmen JL (1995)
Multiple synfire chains in simultaneous action.
Goettingen Neurobiology Report,
Proceedings of the 23rd Goettingen Neurobiology
Conference 1995, Volume 2,
p. 898 (poster)
Schiegg A, Gerstner W, Ritz R, and van Hemmen JL (1995)
Intracellular Ca^2+ stores can account for the time course of LTP
induction: A model of Ca^2+ dynamics in dendritic spines.
J. Neurophysiol., 74 :1046-1055
Gerstner W and van Hemmen JL (1994a)
How to describe neural activity -- spikes, rates, or assemblies?
In: Advances in Neural Information Processing Systems 6 ,
Cowan JD, Tesauro G, and Alspector J (Eds.),
Morgan Kaufmann Publishers, San Francisco, CA
pp. 463-470
Gerstner W and van Hemmen JL (1994b)
Coding and information processing in neural networks .
In: Models of Neural Networks, Vol. 2 .
Domany E, van Hemmen JL, and Schulten K (Eds.),
Springer-Verlag, New York,
pp. 1-92
Ritz R, Gerstner W, and van Hemmen JL (1994) Associative Binidng and segregation in a network of spiking neurons . In: Models of Neural Networks, Vol. 2 . Domany E, van Hemmen JL, and Schulten K (Eds.), Springer-Verlag, New York, pp. 175-219
Wimbauer S, Gerstner W, and van Hemmen JL (1994a)
Motion detection in a Linsker network .
In: ICANN'94, Proceedings of the International Conference
on Artificial Neural Networks, Sorrento, Italy, 26-19 May 1994 ,
Marinaro M and Morasso PG (Eds.)
Springer-Verlag, London Berlin Heidelberg New York,
pp. 1001-1004
Wimbauer S, Gerstner W, and van Hemmen JL (1994b)
Emergence of spatio-temporal receptive fields and
its application to motion detection .
Biol. Cybern., 72 :81-92
Ritz R, Gerstner W, Fuentes U, and van Hemmen JL (1994)
A biologically motivated and analytically soluble model
of collective oscillations in the cortex:
II. Application to binding and pattern segmentation .
Biol. Cybern. 71 :349-358
Gerstner W (1993)
Kodierung und Signaluebertragung in Neuronalen
Systemen: Assoziative Netzwerke mit stochastisch
feuernden Neuronen ;
Verlag Harri Deutsch, Thun, Frankfurt am Main,
Reihe Physik, Bd. 15
Gerstner W and van Hemmen JL (1993)
Coherence and incoherence in a globally coupled
ensemble of pulse-emitting units .
Phys. Rev. Lett. 71 :312-315
Gerstner W and van Hemmen JL (1993b)
Spikes or Rates? -- Stationary, oscillatory, and
spatio-temporal states in an associative network of spiking neurons .
In: ICANN'93, Proceedings of the International Conference
on Artificial Neural Networks, Amsterdam, 13-16 September 1993 ,
Gielen G and Kappen B (Eds.),
Springer-Verlag, London Berlin Heidelberg New York,
pp. 633-638
Gerstner W, Ritz R, and van Hemmen JL (1993a)
A biologically motivated and analytically soluble model
of collective oscillations in the cortex: I. Theory of weak locking .
Biol. Cybern. 68 :363-374
Gerstner W, Ritz R, and van Hemmen JL (1993b)
Why spikes? Hebbian learning and retrieval
of time-resolved excitation patterns .
Biol. Cybern. 69 :503-515
Gerstner W and van Hemmen JL (1992a)
Associative memory in a network of 'spiking' neurons .
Network 3 :139-164
Gerstner W and van Hemmen JL (1992b)
Universality in neural networks:
The importance of the mean firing rate.
Biol. Cybern. 67 :195-205
van Hemmen JL, Gerstner W, and Ritz R (1992)
A 'microscopic' model of collective oscillations in the cortex .
In: Neural network dynamics, Proceedings of the workshop on
complex dynamics in neural networks, June 17-21 1991 at IIASS, Vietri .
Taylor JG, Caianiello ER, Cotterill RMJ, and Clark ER (Eds.),
Springer Verlag, London Berlin Heidelberg New York,
pp. 250-257
Gerstner W (1991)
Associative memory in a network of 'biological' neurons .
In: Advances in Neural Information Processing Systems 3 ,
Lippmann RP, Moody JE, and Touretzky DS (Eds.),
Morgan Kaufmann Publishers, San Mateo, pp. 84-90
Some teaching material for a course on spiking neuron models: PartI - Single Neuron Models and PartII - Population Models and PartIII - Models of Synaptic Plasticity .