Wulfram Gerstner -- Publications

Laboratory of Computational Neuroscience - LCN


Wulfram Gerstner - Publications



PREPRINTS and PUBLICATIONS in 2017

T. Schwalger, M. Deger and W. Gerstner (2017)
Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size.
PLoS Comput Biol 13(4): e1005507 doi.org/10.1371/journal.pcbi.1005507

F. Zenke, W. Gerstner, and S. Ganguli (2017)
The temporal paradox of Hebbian learning and homeostatic plasticity
Current Opinion in Neurobiology 2017, 43 :166-176 http://doi.org/10.1016/j.conb.2017.03.015
and link to preprint on BioRXiv.

S.P. Muscinelli, W. Gerstner, and J. Brea
Exponentially Long Orbits in Hopfield Neural Networks
Neural Computation 29, 458 - 484 (2017)
doi:10.1162/NECO_a_00919

F. Zenke and W. Gerstner (2017)
Hebbian plasticity requires compensatory processes on multiple timescales
Phil. Trans. R. Soc. B 372: 20160259. --- http://dx.doi.org/10.1098/rstb.2016.0259

M. Faraji, K. Preuschoff and W. Gerstner (2017)
Balancing New Against Old Information: The Role of Surprise
arXiv:1606.05642

A. Gilra and W. Gerstner (2017)
Predicting non-linear dynamics: a stable local learning scheme for recurrent spiking neural networks
arXiv:1702.06463

M. Deger, A. Seeholzer and W. Gerstner (2017)
Multi-contact synapses for stable networks: a spike-timing dependent model of dendritic spine plasticity and turnover.
arXiv:1609.05730 [q-bio.NC]
NEST Code on github see https://github.com/mdeger/nest-simulator/blob/stdp_structpl_synapse/models/stdp_structpl_connection_hom.h


PUBLICATIONS in 2016

T. Schwalger, M. Deger and W. Gerstner (2016)
Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size
arXiv:1611.00294

C.S.N. Brito and W. Gerstner (2016)
Nonlinear Hebbian Learning as a Unifying Principle in Receptive Field Formation
PLoS Comput Biol 12: e1005070. doi:10.1371/journal.pcbi.1005070

J. Brea and W. Gerstner (2016)
Does computational neuroscience need new synaptic learning paradigms?
Current Opinion in Behavioral Sciences 11:61-66 doi: 10.1016/j.cobeha.2016.05.012

S. Mensi, O. Hagens, W. Gerstner, and C. Pozzorini (2016)
Enhanced Sensitivity to Rapid Input Fluctuations by Nonlinear Threshold Dynamics in Neocortical Pyramidal Neurons
PLoS Comput Biol 12: e1004761. doi:10.1371/journal.pcbi.1004761

D.B. Kastner, T. Schwalger, L. Ziegler, and W. Gerstner
A model of synaptic reconsolidation
Frontiers in Neuroscience 10:206 doi: 10.3389/fnins.2016.00206

N. Fremaux and W. Gerstner (2016)
Neuromodulated Spike-Timing-Dependent Plasticity, and Theory of Three-Factor Learning Rules
Front. Neural Circuits 9:85 doi: 10.3389/fncir.2015.00085


PUBLICATIONS in 2015

F. Zenke and E.J. Agnes and W. Gerstner (2015)
Diverse synaptic plasticity mechanisms orchestrated to form and retrieve memories in spiking neural networks
Nature Comm. 6: 6922

C. Pozzorini, S. Mensi, O. Hagens, R. Naud, C. Koch, and W. Gerstner (2015)
Automated High-Throughput Characterization of Single Neurons by Means of Simplified Spiking Models
PLOS Comput. Biol. 11:e1004275

L. Ziegler, F. Zenke, D.B. Kastner, and W. Gerstner (2015)
Synpatic Consolidation: From Synapses to behavioral modeling
J. Neuroscience 35:1319-1334
link to Journal WEB page and link to Feature article in J. Neuroscience, Jan. 2015

D. Corneil and W. Gerstner (2015)
Attractor Network Dynamics Enable Preplay and Rapid Path Planning in Maze like Environments
in: Neural Information Processing Systems 28 (NIPS 2015), ed. by C. Cortes and N. D. Lawrence and D. D. Lee and M. Sugiyama and R. Garnett, pp. 1675-1683


PUBLICATIONS in 2014

G. Hennequin, T.P. Vogels and W. Gerstner (2014)
Optimal Control of Transient Dynamics in Balanced Networks Supports Generation of Complex Movements
NEURON 82: 1394-1406 PREPRINT version
see also comment by A. Renart NEURON, same issue

D. J. Rezende and W. Gerstner (2014)
Stochastic variational learning in recurrent spiking networks
Frontiers In Computational Neuroscience 8:38 doi.org/10.3389/fncom.2014.00038
download pdf

R. Naud, B. Bathellier and W. Gerstner (2014)
Spike-timing prediction in cortical neurons with active dendrites
Front. Comput. Neurosci. 8:90 doi: 10.3389/fncom.2014.00090

M. Deger, T. Schwalger, R. Naud, and W. Gerstner (2014)
Fluctuations and information filtering in coupled populations of spiking neurons with adaptation
Phys. Rev. E 90, 062704

C. Tomm, M. Avermann, C. Petersen, W. Gerstner and T.P. Vogels (2014)
Connection-type-specific biases make uniform random network models consistent with cortical recordings ,
J. Neurophysiology 112:1801-1814

F. Zenke and W. Gerstner (2014)
Limits to high-speed simulations of spiking neural networks using general-purpose computers
Frontiers in neuroinformatics 8:76 doi:10.3389/fninf.2014.00076


PUBLICATIONS in 2013

F. Zenke, G. Hennequin and W. Gerstner (2013)
Synaptic Plasticity in Neural Networks Needs Homeostasis with a Fast Rate Detector
PLOS Comput. Biol. 9:e1003330, DOI: 10.1371/journal.pcbi.1003330

C. Pozzorini, R. Naud, S. Mensi, and W. Gerstner (2013)
Temporal whitening by power-law adaptation in neocortical neurons
Nature Neuroscience 16:942 - 948. PREPRINT version

N. Fremaux and H. Sprekeler and W. Gerstner (2013)
Reinforcement Learning Using a Continuous Time Actor-Critic Framework with Spiking Neurons
PLOS Comput. Biol. 9: e1003024. doi:10.1371/journal.pcbi.1003024

V. Pawlak, D.S. Greenberg, H. Sprekeler, W. Gerstner, Jason ND Kerr (2013)
Changing the responses of cortical neurons from sub- to suprathreshold using single spikes in vivo
eLIFE - DOI: http://dx.doi.org/10.7554/eLife.00012
See also comment by: Costa, Watt, Sjostrom

R. Naud and W. Gerstner (2013)
Can we predict every spike?
IN: Spike Timing: Mechanisms and Function, P.M Dilorenzo and J.D. Victor (Editors) CRC Press

H. Lutcke, F. Gerhard, F. Zenke, W. Gerstner and F. Helmchen (2013)
Inference of neuronal network spike dynamics and topology from calcium imaging data
Front. Neural Circuits 7:201 doi: 10.3389/fncir.2013.00201

J. Ruter, H. Sprekeler, W. Gerstner, and M.H. Herzog (2013)
The Silent Period of Evidence Integration in Fast Decision Making
PLOS ONE, 8: e46525


PUBLICATIONS in 2012

W. Gerstner and H. Sprekeler and G. Deco (2012)
Theory and Simulation in Neuroscience
Science 338:60-65 (2012) Preprint

G. Hennequin and T.P. Vogels and W. Gerstner (2012)
Non-normal amplification in random balanced neuronal networks
PHYSICAL REVIEW E 86:011909

R. Naud and W. Gerstner (2012)
Coding and Decoding with Adapting Neurons: A Population Approach to the Peri-Stimulus Time Histogram
PLOS Comput. 8:e100271

R. Naud and W. Gerstner (2012)
The performance (and limits) of simple neuron models: Generalizations of the leaky integrate-and-fire model
IN: Computational Systems Neurobiology, Nicolas Le Novere (Editor), Springer ISBN-10: 9400738579 ISBN-13: 978-9400738577

M. Avermann, C. Tomm, C. Mateo, W. Gerstner and C.C.H. Petersen (2012)
Microcircuits of excitatory and inhibitory neurons in layer 2/3 of mouse barrel cortex.
J. Neurophysiol 107:3116-3134

S. Mensi, R. Naud, C. Pozzorini, M. Avermann, C.C.H. Petersen and W. Gerstner (2012)
Parameter extraction and classification of three cortical neuron types reveals two distinct adaptation mechanisms,
J. Neurophysiol., 107:1756-1775, 2012.

M.H. Herzog, K.C. Aberg, N. Fremaux W. Gerstner and H. Sprekeler,
Perceptual learning, roving and the unsupervised bias,
Vision Research, Vol. 61, pp. 95-99, 2012.

J. Ruter, N. Marcille, H. Sprekeler, W. Gerstner and M.H. Herzog
Paradoxical Evidence Integration in Rapid Decision Processes,
PLOS Comput. Biol., 8: e1002382


PUBLICATIONS in 2011

T. Vogels, H. Sprekeler, F. Zenke, C. Clopath and W. Gerstner (2011)
Inhibitory Plasticity Balances Excitation and Inhibition in Sensory Pathways and Memory Networks,
Science, Vol. 334:1569-1573, 2011.

R. Naud, F. Gerhard, S. Mensi, and W. Gerstner (2011)
Improved similarity measures for small sets of spike trains
Neural Computation 23:3016-3069

S. Mensi, R. Naud, and W. Gerstner (2011)
From Stochastic Nonlinear Integrate-and-Fire to Generalized Linear Models
Advances in Neural Information Processing Systems 24 edited by J. Shawe-Taylor and R.S. Zemel and P. Bartlett and F. Pereira and K.Q. Weinberger (2011) NIPS 2011, 24:0794

H. Markram and J. Sjostrom and W. Gerstner (2011)
A history of spike-timing-dependent plasticity
Front. Syn. Neurosci. 3:4. doi: 10.3389/fnsyn.2011.00004

F. Gerhard, G. Pipa, B. Lima, S. Neuenschwander, and W. Gerstner (2011)
Extraction of network topology from multi-electrode recordings: Is there a small-world effect?
Front. Comput. Neurosci. 5:4. doi: 10.3389/fncom.2011.00004

W. Gerstner (2011)
Hebbian Learning and Plasticity
To appear in: From Neuron to Cognition via Computational Neuroscience, edited by Michael Arbib and Jimmy Bonaiuto, MIT Press Cambridge Chapter 9

R. Naud and W. Gerstner (2011)
Can We Predict Every Spike?
IN: Spike Timing: Mechanisms and Function, Ed. by P.M. Dilorenzo and J.D. Victor, CRC Press planned to appear in 2012, now scheduled for March 2013


PUBLICATIONS in 2010

N. Fremaux, H. Sprekeler and W. Gerstner (2010)
Functional Requirements for Reward-Modulated Spike-Timing-Dependent Plasticity,
Journal of Neuroscience, Vol. 30, Nr. 40, pp. 13326-13337

Claudia Clopath, Lars Busing, Eleni Vasilaki and Wulfram Gerstner (2010)
Connectivity reflects coding: A model of voltage-based spike-timing-dependent-plasticity with homeostasis.
Nature Neuroscience, 13:344 - 352
doi:10.1038/nn.2479. Public Preprint version
Link to NEWS and VIEWS of N. Spruston and J. Cang

Claudia Clopath and Wulfram Gerstner (2010)
Voltage and spike timing interact in STDP - a unified model
Front. Syn. Neurosci., 2:25 doi: 10.3389/fnsyn.2010.00025

Guillaume Hennequin, Wulfram Gerstner and Jean-Pascal Pfister (2010)
STDP in adaptive neurons gives close-to-optimal information transmission
Front. Comput. Neurosci. 4:143, doi: 10.3389/fncom.2010.00143

W. Gerstner (2010)
From Hebb rules to STDP: a personal account
Front. Syn. Neurosci. 2:151. doi: 10.3389/fnsyn.2010.00151

Jesper Sjostrom and Wulfram Gerstner (2010)
Spike-timing dependent plasticity .
Scholarpedia, 5(2):1362 Here the pdf file with high-resolution figures

F. Gerhard and W. Gerstner (2010)
Rescaling, thinning or complementing? On goodness-of-fit procedures for point process models and Generalized Linear Models, IN: Advances in Neural Information Processing Systems 23 (NIPS2010), edited by J. Lafferty and C. K. I. Williams and J. Shawe-Taylor and R.S. Zemel and A. Culotta 23:767



PUBLICATIONS in 2009

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



PUBLICATIONS in 2008

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



PUBLICATIONS in 2007
M.H. Herzog and M. Esfeld and W. Gerstner (2007)
Consciousness and the small network argument
Neural Networks 20:1054-1056 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



PUBLICATIONS in 2006

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


PUBLICATIONS in 2005


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


PUBLICATIONS 2004


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) ]


PUBLICATIONS 2003


L. F. Abbott and W. Gerstner (2004)
Homeostasis and Learning through Spike-Timing Dependent Plasticity
Unpublished Lecture Notes of the 2003 LesHouches summer school in Neurophysics. [ pdf file]

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


PUBLICATIONS 2002


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]


PUBLICATIONS 2001


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


PUBLICATIONS 2000


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


PUBLICATIONS 1999


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.


PUBLICATIONS 1998


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 ).


PUBLICATIONS 1997


Kistler W, Gerstner W, and van Hemmen JL (1997)
Reduction of Hodgkin-Huxley equations to a threshold model.
Neural Comput. 9:1015-1045

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


PUBLICATIONS 1996


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;
presented at the 1995 NIPS conference in Denver, here the Online proceedings paper


PUBLICATIONS 1995


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


PUBLICATIONS 1994


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


PUBLICATIONS 1993


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 (1993c)
Why spikes? Hebbian learning and retrieval of time-resolved excitation patterns .
Biol. Cybern. 69 :503-515


PUBLICATIONS 1992


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


PUBLICATIONS 1990-91


van Hemmen JL, Gerstner W, Herz AVM, Kuehn R, Sulzer B, and Vaas M (1990)
Encoding and decoding of patterns which are correlated in space and time.
In: Konnektionismus in Artificial Intelligence und Kognitionsforschung , G. Dorffner (Ed.), Springer--Verlag Berlin Heidelberg, pp. 153-162

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 .


Back to home page of Wulfram Gerstner.
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LCN - Laboratory of Computational Neuroscience
IC - Computer Science Department
EPFL - Swiss Federal Institute of Technology