Publications and Preprints from Computational Neuroscience Group

W. Senn, Dold D., Kungl A.F., Ellenberger B, Jordan J., Bengio Y., Sacramento J. and Petrovici M.A..
A Neuronal Least-action Principle For Real-time Learning In Cortical Circuits. eLIFE 2024 DOI pdf

bioRxiv

J.F. Storm, P.C. Klink, J. Aru, W. Senn, R. Goebel, A. Pigorini, P. Avanzini, W. Vanduffel, P.R. Roelfsema, M. Massimini, M. Larkum, C.M.A Pennartz.
An integrative, multiscale view on consciousness theories. Neuron 2024 DOI PubMed pdf

PsyArXiv

J. Jordan, J. Sacramento, W.A.M. Wybo, M.A. Petrovici, W. Senn.
Conductance-based dendrites perform Bayes-optimal cue integration. PLoS Comput Biol 2024 DOI PubMed pdf

arXiv

A. Granier, M.A. Petrovici, W. Senn, K.A. Wilmes.
Confidence and second-order errors in cortical circuits. PNAS Nexus 2024 DOI PubMed pdf

arXiv

M. Tsai, J. Teutsch, Willem A.M. Wybo, F. Helmchen, A. Banerjee, W. Senn.
Hierarchy of prediction errors shapes the learning of context-dependent sensory representations. bioRxiv 2024 DOI pdf

N. Deperrois, M.A. Petrovici, J. Jordan, L.S. Huber, and W. Senn.
How Adversarial REM Dreams May Facilitate Creativity, and Why We Become Aware of Them. Clinical and Translational Neuroscience 2024 DOI pdf

preprints.org

B. von Hünerbein, J. Jordan, M.O. Lohuis, P. Marchesi, U. Olcese, C.M.A. Pennartz, W. Senn, M.A. Petrovici.
Increased perceptual reliability reduces membrane potential variability in cortical neurons. bioRxiv 2024 DOI pdf

K. Max, L. Kriener, G. Pineda Garcia, T. Nowotny, I. Jaras, W. Senn and M.A. Petrovici.
Learning efficient backprojections across cortical hierarchies in real time. Nature Machine Intelligence 2024 DOI pdf

arXiv

L. Kriener, K. Völk, B. von Hünerbein, F. Benitez, W. Senn, M.A. Petrovici.
Order from chaos: Interplay of development and learning in recurrent networks of structured neurons. arXiv 2024 DOI pdf

S. Brandt, M.A. Petrovici, W. Senn, K.A. Wilmes, F. Benitez.
Prospective and retrospective coding in cortical neurons. arXiv 2024 DOI pdf

K. Amunts, (...), Mihai A. Petrovici, (...), W. Senn, (...).
The coming decade of digital brain research: A vision for neuroscience at the intersection of technology and computing. Imaging Neuroscience 2024 DOI pdf

Zenodo

F. Benitez, C. Pennartz, W. Senn.
The conductor model of consciousness, our neuromorphic twins, and the human-AI deal. AI and Ethics 2024 DOI pdf

PsyArXiv

G. Schoenfeld, S. Kollmorgen, M.C. Tsai, C. Lewis, S. Han, P. Bethge, A.M. Reuss, A. Aguzzi, W. Senn, V. Mante, F. Helmchen.
Unsigned temporal difference errors in cortical L5 dendrites during learning. bioRxiv 2024 DOI pdf

K.D. Fehér, X. Omlin, L. Tarokh, C.L. Schneider, Y. Morishima, M. A. Züst, M. Wunderlin, T. Koenig, E. Hertenstein, B. Ellenberger, S. Ruch, F. Schmidig, C. Mikutta, E. Trinca, W. Senn, B. Feige, S. Klöppel, C. Nissen.
Feasibility, efficacy, and functional relevance of automated auditory closed-loop suppression of slow-wave sleep in humans. Journal of Sleep Research 2023 DOI pdf

N. Deperrois, M.A. Petrovici, W. Senn, J. Jordan.
Learning beyond sensations: how dreams organize neuronal representations. Neuroscience & Biobehavioral Reviews 2023 DOI pdf

arXiv

W.A.M. Wybo, M.C Tsai, V.A.K. Tran, B. Illing, J. Jordan, A. Morrison, W. Senn.
NMDA-driven dendritic modulation enables multitask representation learning in hierarchical sensory processing pathways. PNAS 2023 DOI PubMed pdf

Contextual modulation of neurons in sensory processing pathways

bioRxiv

K.A. Wilmes, M.A. Petrovici, S. Sachidhanandam and W. Senn.
Uncertainty-modulated prediction errors in cortical microcircuits. bioRxiv 2023 DOI pdf

A. Korcsak-Gorzo, M.G. Müller, A. Baumbach, L. Leng, O.J. Breitwieser, S.J. van Albada, W. Senn, K. Meier, R. Legenstein, M. A. Petrovici.
Cortical oscillations support sampling-based computations in spiking neural networks. PLoS Comput Biol 2022 DOI PubMed pdf

arXiv

N. Deperrois, M.A. Petrovici, W. Senn, and J. Jordan.
Learning cortical representations through perturbed and adversarial dreaming. eLIFE 2022 DOI pdf

arXiv

E. Kreutzer, W. Senn, M.A. Petrovici.
Natural-gradient learning for spiking neurons. eLIFE 2022 DOI pdf

arXiv

W.A.M. Wybo, J. Jordan, B. Ellenberger, U. Marti Mengual, T. Nevian, W. Senn.
Data-driven reduction of dendritic morphologies with preserved dendro-somatic responses. eLIFE 10:e60936, 2021 DOI PubMed pdf

J. Jordan, M. Schmidt, W. Senn, M.A. Petrovici.
Evolving interpretable plasticity for spiking networks. eLIFE 2021 DOI PubMed pdf

arXiv

H.D. Mettler, M. Schmidt, W. Senn, M.A. Petrovici, J. Jordan.
Evolving Neuronal Plasticity Rules using Cartesian Genetic Programming. arXiv 2021 DOI pdf

J. Göltz, L. Kriener, A. Baumbach, S. Billaudelle, O. Breitwieser, B. Cramer, D. Dold, A.F. Kungl, W. Senn, J. Schemmel, K. Meier, M.A. Petrovici.
Fast and energy-efficient neuromorphic deep learning with first-spike times. Nature Machine Intelligence 823–835, 2021 DOI pdf

arXiv

P. Haider, B. Ellenberger, L. Kriener, J. Jordan, W. Senn, M.A. Petrovici.
Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons. Advances in Neural Information Processing Systems (NeurIPS) 2021 pdf

Peer-reviewed conference article - Advances in Neural Information Processing Systems 34 (NeurIPS 2021)

arXiv

C. Zhao, Y.F. Widmer, S. Diegelmann, M.A. Petrovici, S.G. Sprecher, W. Senn.
Predictive olfactory learning in Drosophila. Sci Rep 2021 DOI PubMed pdf

bioRxiv

H.D. Mettler, V. Sabado, W. Senn, M.A. Petrovici and J. Jordan .
Uncovering Neuronal Learning Principles through Artificial Evolution. ERCIM April, 2021

Article

U. Marti Mengual, W.A.M. Wybo, L.J.E. Spierenburg, M. Santello, W. Senn and T. Nevian.
Efficient low-pass dendro-somatic coupling in the apical dendrite of layer 5 pyramidal neurons in the anterior cingulate cortex. J. Neurosci. 40(46):8799–8815, 2020 DOI

B.A. Gasser, J. Kurz, W. Senn, G. Escher, M.G. Mohaupt.
Stress-induced alterations of social behavior are reversible by antagonism of steroid hormones in C57/BL6 mice. Naunyn-Schmiedeberg's Arch Pharmacol 2020 DOI pdf

S. Billaudelle, Y. Stradmann, K. Schreiber, B. Cramer, A. Baumbach, D. Dold, J. Göltz, A.F. Kungl, T.C. Wunderlich, A. Hartel, E. Müller, O. Breitwieser, C. Mauch, M. Kleider, A. Grübl, Da. Stöckel, C. Pehle, A. Heimbrecht, P. Spilger, G. Kiene, V. Karasenko, W. Senn, M.A. Petrovici, J. Schemmel, K. Meier.
Versatile emulation of spiking neural networks on an accelerated neuromorphic substrate. IEEE Xplore 2020 DOI pdf

arXiv

B.A. Richards, T.P. Lillicrap, P. Beaudoin, Y. Bengio, R. Bogacz, A. Christensen, C. Clopath, R.P. Costa, A. de Berker, S. Ganguli, C.J. Gillon, D. Hafner, A. Kepecs, N. Kriegeskorte, P. Latham, G.W. Lindsay, K.D. Miller, R. Naud, C.C. Pack, P. Poirazi, P. Roelfsema, J. Sacramento, A. Saxe, B. Scellier, A.C. Schapiro, W. Senn, G. Wayne, D. Yamins, F. Zenke, J. Zylberberg, D. Therien and K.P. Kording.
A deep learning framework for neuroscience. Nat. Neurosci. 22: 1761-1770, 2019 DOI pdf

T. Mesnard, G. Vignoud, J. Sacramento, W. Senn, Y. Bengio.
Ghost Units Yield Biologically Plausible Backprop in Deep Neural Networks. arXiv 2019 DOI pdf

D. Dold, A.F. Kungl, J. Sacramento, M.A. Petrovici, K. Schindler, J. Binas, Y. Bengio, W. Senn.
Lagrangian neurodynamics for real-time error-backpropagation across cortical areas. 2019 pdf

D. Dold, I. Bytschok, A.F. Kungl, A. Baumbach, O. Breitwieser, W. Senn, J. Schemmel, K. Meier, M.A. Petrovici.
Stochasticity from function - Why the Bayesian brain may need no noise. Neural Networks 2019 DOI pdf

arXiv

J. Sacramento, R.P. Costa, Y. Bengio, W. Senn.
Dendritic cortical microcircuits approximate the backpropagation algorithm. Advances in Neural Information Processing Systems (NeurIPS) 2018 pdf

Peer-reviewed conference article - Advances in Neural Information Processing Systems 31 (NeurIPS 2018)

arXiv

Luziwei Leng, R. Martel, O. Breitwieser, I. Bytschok, W. Senn, J. Schemmel, K. Meier & M.A. Petrovici .
Spiking neurons with short-term synaptic plasticity form superior generative networks. Nature Scientific Reports 8: 10651, 2018 DOI pdf

arXiv

L. de Andres-Bragado, C. Mazza, W. Senn and S.G. Sprecher.
Statistical modelling of navigational decisions based on intensity versus directionality in Drosophila larval phototaxis. Nature Scientific Reports online, 2018 DOI pdf

J. Sacramento, R. Ponte Costa, Y. Bengio, W. Senn.
Dendritic error backpropagation in deep cortical microcircuits. arXiv 2017 DOI pdf

A.L. Wantz, J.S. Lobmaier, F.W. Mast, W. Senn.
Spatial But Not Oculomotor Information Biases Perceptual Memory: Evidence From Face Perception and Cognitive Modeling. Cognitive Science 41:1533–1554, 2017 DOI

Y. Bengio, B. Scellier, O. Bilaniuk, J. Sacramento, W. Senn.
Feedforward Initialization for Fast Inference of Deep Generative Networks is biologically plausible. arXiv 2016 DOI pdf

J. Brea, A. Gaál, R. Urbanczik †, W. Senn.
Prospective Coding by Spiking Neurons. PLoS Comput Biol 12(6): e100500, 2016 DOI pdf

M. Schiess, R. Urbanczik, W. Senn.
Somato-dendritic Synaptic Plasticity and Error-backpropagation in Active Dendrites. PLoS Comput Biol 12(2): e1004638, 2016 DOI pdf

W. Senn, J. Sacramento.
Backward reasoning the formation rules. Nat. Neurosci. 18(12):1705-1706, 2015 DOI pdf

B.B. Vladimirskiy, R. Urbanczik, W. Senn.
Hierarchical Novelty-Familiarity Representation in the Visual System by Modular Predictive Coding. PLoS ONE 10(12): e0144636, 2015 DOI

A.M. Clarke, J. Friedrich, E.M. Tartaglia, S. Marchesotti, W. Senn, M.H. Herzog.
Human and Machine Learning in Non-Markovian Decision Making. PLoS ONE 10(4): e0123105, 2015 DOI

W. Senn, J. Brea.
Neurons that Remember How We Got There. Neuron 85(4):664-666, 2015 DOI

A. Khajeh-Alijani, R. Urbanczik, W. Senn.
Scale-Free Navigational Planning by Neuronal Traveling Waves. PLoS ONE 10(7): e0127269, 2015 DOI

J. Brea, W. Senn.
Vom Nutzen des Vergessens oder was uns die Fruchtfliege ­lehren kann. VSAO J. 2:32-33, 2015

J. Brea, R. Urbanczik, W. Senn.
A Normative Theory of Forgetting: Lessons from the Fruit Fly. PLoS Comput Biol 10(6): e1003640, 2014 DOI pdf

J. Friedrich, R. Urbanczik, W. Senn.
Code-specific Learning Rules Improve Action Selection by Populations of Spiking Neurons. Int. J. of Neural Systems 24: 1, 2014 DOI

500 Dollar Reward

R. Urbanczik, W. Senn.
Learning by the dendritic prediction of somatic spiking. Neuron 81(3):521–528, 2014 DOI pdf

Supplement

T. Lüdge, R. Urbanczik, W. Senn.
Modulation of orientation-selective Neurons by motion: when additive, when multiplicative?. Front. Comput.Neurosci. 8:67, 2014 DOI

SM Blom, J.P. Pfister, M. Santello, W. Senn & T. Nevian.
Nerve injury-induced neuropathic pain causes disinhibition of the anterior cingulate cortex. J. Neurosci. 34(17):5754-5764, 2014 DOI pdf

W. Senn, J.P. Pfister.
Reinforcement learning in cortical networks in Encyclopedia of Computational Neuroscience, Springer Encyclopedia of Computational Neuroscience 2014 DOI pdf

W. Senn, J.P. Pfister.
Spike-Timing-Dependent Plasticity, Learning Rules in Encyclopedia of Computational Neuroscience, Springer Encyclopedia of Computational Neuroscience 2014 DOI pdf

R. Caspar, Supervisors: W. Senn, R. Urbanczik.
Master Thesis: "Mapping the Hodkgin-Huxley Neuron to an Escape Rate Neuron". 2013

J. Brea, W. Senn, J.P. Pfister.
Matching Recall and Storage in Sequence Learning with Spiking Neural Networks. J. Neurosci. 33(23): 9565–9575, 2013 DOI pdf

M. Schiess, R. Urbanzik, W. Senn.
Gradient estimation in dendritic reinforcement learning. J. Math Neuroscience 2: 2, 2012 DOI

J. Friedrich, W. Senn.
Spike-based Decision Learning of Nash Equilibria in Two-Player Games. PLoS Comput Biol 2012 DOI

Paper with Supplementary Materials

J. Brea, W. Senn, and J.-P. Pfister.
Sequence learning with hidden units in spiking neural networks. Advances in Neural Information Processing Systems (NeurIPS) pp. 1422-1430, 2011 pdf

Peer-reviewed conference article - Advances in Neural Information Processing Systems 24 (NIPS 2011)

J. Friedrich, R. Urbanczik, W. Senn.
Spatio-Temporal Credit Assignment in Neuronal Population Learning. PLoS Comput Biol 7:1-13, 2011 DOI pdf

Supplement

J. Friedrich, R. Urbanczik, W. Senn.
Learning Spike-Based Population Codes by Reward and Population Feedback. Neural Computation 22:1698-1717, 2010 DOI

I.R. Fiete, W. Senn, C.Z.H. Wang, R.H.R. Hahnloser.
Spike-Time-Dependent Plasticity and Heterosynaptic Competition Organize Networks to Produce Long Scale-Free Sequences of Neural Activity. Neuron 65:563-576, 2010 DOI PubMed pdf

R. Urbanczik, W. Senn.
A gradient learning rule for the tempotron. Neural Computation 21:340-352, 2009 DOI

R. Schäfer, E. Vasilaki, W. Senn.
Adaptive Gain Modulation in V1 Explains Contextual Modifications during Bisection Learning. PLoS Comput Biol 5:1-12, 2009 DOI pdf

M. Murayama, E. Pérez-Garci, T. Nevian, T. Bock, W. Senn, M.E. Larkum.
Dendritic encoding of sensory stimuli controlled by deep cortical interneurons. Nature 457:1137-1141, 2009 DOI pdf

Supplement

E. Vasilaki, S. Fusi, X.J. Wang, W. Senn.
Learning flexible sensori-motor mappings in a complex network. Biological Cybernetics 100:147–158, 2009 DOI

W. Senn.
Mathematisierung der Biologie: Mode oder Notwendigkeit? Aktualität und Vergänglichkeit der Leitwissenschaften in Reihe "Berner Kulturhistorische Vorlesungen", Peter Lang AG, Internationaler Verlag der Wissenschaften S. 97-118, 2009

R. Urbanczik, W. Senn.
Reinforcement learning in populations of spiking neurons. Nat. Neurosci. 12:250-252, 2009 DOI

Supplement

E. Vasilaki, N. Frémaux, R. Urbanczik, W. Senn, W. Gerstner.
Spike-Based Reinforcement Learning in Continuous State and Action Space: When Policy Gradient Methods Fail. PLoS Comput Biol 5:1-17, 2009 DOI

B.B. Vladimirskiy, E. Vasilaki, R. Urbanczik, W. Senn.
Stimulus sampling as an exploration mechanism for fast reinforcement learning. Springer-Verlag Biological Cybernetics 100:319-330, 2009 DOI

K. Thurley, W. Senn, Hans-R. Lüscher.
Dopamine increases the gain of the input-output response of rat prefrontal pyramidal neurons. J. Neurophysiol. 99:2985-2997, 2008 DOI PubMed

Y. Kim, B.B. Vladimirskiy, W. Senn.
Modulating the granularity of category formation by global cortical states. Front. Comput.Neurosci. 2:1-14, 2008 DOI

M. Giugliano, G. La Camera, S. Fusi, W. Senn.
The response of cortical neurons to in vivo-like input current: theory and experiment II. Time-varying and spatially distributed inputs. Biological Cybernetics 99(4-5):303-18, 2008 DOI

G. La Camera, M. Giuglianio, W. Senn, S. Fusi.
The response of cortical neurons to in vivo-like input current: theoryand experiment I. Noisy inputs with stationary statistics. Biological Cybernetics 99(4-5):279-301, 2008 DOI

J.M. Brader, W. Senn, S. Fusi.
Learning real-world stimuli in a neural network with spike-driven synaptic dynamics. Neural Computation 19:2881-2912, 2007 DOI PubMed pdf

R. Schäfer, E. Vasilaki, W. Senn.
Perceptual learning via modification of cortical top-down signals. PLoS Comput Biol 3(8):e165, 2007 DOI

Suppl. Schaefer_topdown

S. Fusi, W. Senn.
Eluding oblivion with smart stochastic selection of synaptic updates. Chaos: An Interdisciplinary Journal of Nonlinear Science 16, 026112, 1-11, 2006 DOI

T. Nyffeler, P. Wurtz, H.-R. Lüscher, C.W. Hess, W. Senn, T. Pflugshaupt, R. von Wartburg, M. Lüthi, R.M. Müri.
Extending lifetime of plastic changes in the human brain. EJN 24:2961-2966 , 2006 DOI

G. La Camera, A. Rauch, D. Thurbon, H.-R. Lüscher, W. Senn, S. Fusi.
Multiple Time Scales of Temporal Response in Pyramidal and Fast Spiking Cortical Neurons. Epub 2006 Jun 28. J. Neurophysiol. 96(6):3448-3464 , 2006 DOI PubMed

T. Nyffeler, P. Wurtz, H.-R. Lüscher, C.W. Hess, W. Senn, T. Pflugshaupt, R. von Wartburg, M. Luthi, R.M. Muri.
Repetitive TMS over the human oculomotor cortex: Comparison of 1-Hz and theta burst stimulation. Epub 2006 Oct 17. Neurosci. Lett. 409(1):57-60 , 2006 PubMed

W. Senn, S. Fusi.
Convergence of stochastic learning in perceptrons with binary synapses. Phys. Rev. E E71:061907-1 - 061, 2005 DOI PubMed pdf

W. Senn, S. Fusi.
Learning only when necessary: better memories of correlated patterns in networks with bounded synapses. Neural Computation 17:2106-2138, 2005 DOI PubMed

J. Reutimann, V. Yakovlev, S. Fusi, W. Senn.
Climbing neuronal activity as an event-based cortical representation of time. J. Neurosci. 24(13):3295-3303 , 2004 DOI PubMed pdf

G. La Camera, W. Senn, S. Fusi.
Comparison between networks of conductance- and current-driven neurons: stationary spike rates and subthreshold depolarization. Neurocomputing 58-60:253-258 , 2004 DOI

G. La Camera, A. Rauch, H.-R. Lüscher, W. Senn, S. Fusi.
Minimal models of adapted neuronal response to in vivo-like input currents. Neural Computation 16: 2101-2124, 2004 DOI PubMed

W. Senn, S. Fusi.
Slow stochastic learning with global inhibition: a biological solution to the binary perceptron problem. Neurocomputing 58-60:321-326 , 2004 DOI

M.E. Larkum, W. Senn, H.-R. Lüscher.
Top-down dendritic input increases the gain of layer 5 pyramidal neurons. Cereb. Cortex 14:1059-1070, 2004 DOI PubMed pdf

G. La Camera, W. Senn, S. Fusi.
Equivalent networks of conductance- and current driven neurons. In: O.Kaynak (eds.): Suppl. Proceedings of ICANN/ICONIP, 2003, LCNS 2714, pp. 449-452, Springer Verlag, 2003

T. Berger, W. Senn, H.-R. Lüscher.
Hyperpolarization-activated current Ih disconnects somatic and dendritic spike initiation zones in layer V pyramidal neurons. J. Neurophysiol. 90:2428-2437, 2003 DOI PubMed pdf

A. Rauch, G. La Camera, H.-R. Lüscher, W. Senn, S. Fusi.
Neocortical pyramidal cells respond as integrate-and-fire neurons to in vivo-like input currents. J. Neurophysiol. 90:1598-1612, 2003 DOI PubMed pdf

W. Senn, N.J. Buchs.
Spike-based synaptic plasticity and the emergence of direction selective simple cells: mathematical analysis. J. Comput. Neurosci. 14:119-138, 2003 DOI PubMed

M. Carandini, D.J. Heeger, W. Senn.
A synaptic explanation of suppression in visual cortex. J. Neurosci. 22(22):10053-10065, 2002 DOI PubMed

W. Senn, M. Schneider, B. Ruf.
Activity-dependent development of axonal and dendritic delays, or, why synaptic transmission should be unreliable. Neural Computation 14:583-619, 2002 DOI PubMed

Supplement (ps.gz)

W. Senn.
Beyond spike timing: the role of nonlinear synapses. Biological Cybernetics 87:344-355, 2002 DOI PubMed

G. La Camera, A. Rauch, W. Senn, H.-R. Lüscher, S. Fusi.
Firing rate adaptation without losing sensitivity to input fluctuations. In: J.R. Dorronsoro (Ed.):. Springer-Verlag Proceedings of ICANN 2002, LNCS 2415, pp. 180-185, 2002

N.J. Buchs, W. Senn.
Spike-based synaptic plasticity and the emergence of direction selective simple cells: simulation results. J. Comput. Neurosci. 13:167:186, 2002 DOI PubMed

G. La Camera, S. Fusi, W. Senn, A. Rauch, H.-R. Lüscher.
When NMDA receptor conductances increase inter-spike interval variability. In: J.R. Dorronsoro (Ed):. Springer-Verlag Proceedings of ICANN 2002, LNCS 2415, pp. 235-240, 2002

J. Reutimann, S. Fusi, W. Senn, V. Yakovlev, E. Zohary.
A model of expectation effects in inferior temporal cortex. Neurocomputing 38-40:1533-1540, 2001 DOI

W. Senn, H. Markram, M. Tsodyks.
An algorithm for modifying neurotransmitter release probability based on pre- and post-synaptic spike timing. Neural Computation 13(1):35-68, 2001 DOI PubMed

N.J. Buchs, W. Senn.
Learning direction selectivity through spike-timing dependent modification of neurotransmitter release probability. Neurocomputing 38-40:121-127, 2001 DOI

W. Senn, R. Urbanczik.
Similar non-leaky integrate-and-fire neurons with instantaneous couplings always synchronize. SIAM J Appl. Math 61(4):1143-1155, 2001

J. Tabak, W. Senn, M.J. O’Donovan, J. Rinzel.
Modeling of spontaneous activity in developing spinal cord using activity-dependent depression in an excitatory network. J. Neurosci. 20(8):3041-3056, 2000 DOI PubMed

W. Senn, R. Urbanczik.
Similar nonleaky integrate-and-fire neurons with instantaneous couplings always synchronize. SIAM J Appl. Math 61, No 4, 1143-1155, 2000

W. Senn.
Equilibrium forms of crystals and stable norm. J. Appl. Math. and Phys. 49:919-933, 1998 DOI pdf

W. Senn, T. Wannier, J. Kleinle, H.-R. Lüscher, L. Müller, J. Streit, K. Wyler.
Pattern generation by two coupled time-discrete neural networks with synaptic depression. Neural Computation 10:1251-1275, 1998 DOI PubMed

W. Senn.
Phase-locking in the multidimensional Frenkel-Kontorova model. Math Zeitschrift 227:623–643, 1998 DOI pdf

W. Senn, I. Segev, M. Tsodyks.
Reading neuronal synchrony with depressing synapses. Neural Computation 10:815-819, 1998 DOI PubMed

T. Wannier, W. Senn.
Recruitment of reticulospinal neurones and steady locomotion in lamprey. Neural Networks 11:1005-1015, 1998 DOI PubMed

W. Senn, K. Wyler, H.P. Clamann, J. Kleinle, H.-R. Lüscher, L. Müller.
Size principle and information theory. Biological Cybernetics 76:11-22, 1997 DOI PubMed

W. Senn, K. Wyler, J. Streit, M. Larkum, H.-R. Lüscher, H. Mey, L. Müller, D. Steinhauser, K. Vogt, T. Wannier.
Dynamics of a random neural network with synaptic depression. Neural Networks 9 No. 4:575-588, 1996 DOI

J. Kleinle, K. Vogt, H.-R. Lüscher, L. Müller, W. Senn, K. Wyler, J. Streit.
Transmitter concentration profiles in the synaptic cleft: an analytical model of release and diffusion. Biophys. J. 71:2413-2426, 1996 DOI PubMed

W. Eugster, W. Senn.
A cospectral correlation model for measurement of turbulent NO_2 flux. Boundary-Layer Meteorology 74:321-340, 1995 DOI pdf

W. Senn.
Differentiability properties of the minimal average action. Calc. Var. 3:343-384, 1995 DOI pdf

Ch. Meier, W. Senn, R. Hauser, M. Zimmermann.
Strange limits of stability in host parasitoid systems. J. Math. Biol. 32:563-572, 1994 DOI pdf

W. Senn.
Strikte Konvexität für Variationsprobleme auf dem n-dimensionalen Torus. manuscripta mathematica 71:45-65, 1991 DOI pdf

W. Senn.
Über Mosers regularisiertes Variationsproblem für minimale Blätterungen des n-dimensionalen Torus. J. Appl. Math. and Phys. 42: 527-546, 1991 DOI pdf