Publications and Preprints from Computational Neuroscience Group

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


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


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


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


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


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


J. Jordan, J. Sacramento, W.A.M. Wybo, M.A. Petrovici, W. Senn.
Learning Bayes-optimal dendritic opinion pooling. arXiv 2021 pdf

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


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


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

J. Jordan, M. Schmidt, W. Senn, M.A. Petrovici.
Evolving to learn: discovering interpretable plasticity rules for spiking networks. arXiv 2020 pdf

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


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 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


J. Sacramento, R.P. Costa, Y. Bengio, W. Senn.
Dendritic cortical microcircuits approximate the backpropagation algorithm. arXiv NIPS 2018, 2018 pdf

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


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 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 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


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

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

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

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

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.In J. Shawe-Taylor, R. Zemel, P. Bartlett, F. Pereira, and K. Weinberger, editors. Advances in Neural Information Processing Systems 24 pp. 1422-1430, 2011

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


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

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 pdf

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

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


E. Vasilaki, S. Fusi, X.J. Wang, W. Senn.
Learning flexible sensori-motor mappings in a complex network. Biol. Cybern. 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


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 Biol. Cybern. 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

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. Biol. Cybern. 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. Biol. Cybern. 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 Comput. 19:2881-2912, 2007

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

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

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

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

W. Senn, S. Fusi.
Convergence of stochastic learning in perceptrons with binary synapses. PhysRev E71:061907-1 - 061, 2005

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

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

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

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 Comput. 16: 2101-2124, 2004

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

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

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

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

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

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

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

Supplement (ps.gz)

W. Senn.
Beyond spike timing: the role of nonlinear synapses. Biol. Cybern. 87:344-355, 2002

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

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

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

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

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

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 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 Comput. 10:1251-1275, 1998

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

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

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

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

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

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

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