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Items: 1 to 50 of 63

1.

A deep learning framework for neuroscience.

Richards BA, Lillicrap TP, Beaudoin P, Bengio Y, Bogacz R, Christensen A, Clopath C, Costa RP, de Berker A, Ganguli S, Gillon CJ, Hafner D, Kepecs A, Kriegeskorte N, Latham P, Lindsay GW, Miller KD, Naud R, Pack CC, Poirazi P, Roelfsema P, Sacramento J, Saxe A, Scellier B, Schapiro AC, Senn W, Wayne G, Yamins D, Zenke F, Zylberberg J, Therien D, Kording KP.

Nat Neurosci. 2019 Nov;22(11):1761-1770. doi: 10.1038/s41593-019-0520-2. Epub 2019 Oct 28. Review.

PMID:
31659335
2.

Stochasticity from function - Why the Bayesian brain may need no noise.

Dold D, Bytschok I, Kungl AF, Baumbach A, Breitwieser O, Senn W, Schemmel J, Meier K, Petrovici MA.

Neural Netw. 2019 Nov;119:200-213. doi: 10.1016/j.neunet.2019.08.002. Epub 2019 Aug 19.

3.

Prevalence and potential risk factors of flight-related neck, shoulder and low back pain among helicopter pilots and crewmembers: a questionnaire-based study.

Posch M, Schranz A, Lener M, Senn W, Äng BO, Burtscher M, Ruedl G.

BMC Musculoskelet Disord. 2019 Jan 29;20(1):44. doi: 10.1186/s12891-019-2421-7.

4.

Statistical modelling of navigational decisions based on intensity versus directionality in Drosophila larval phototaxis.

de Andres-Bragado L, Mazza C, Senn W, Sprecher SG.

Sci Rep. 2018 Jul 26;8(1):11272. doi: 10.1038/s41598-018-29533-0.

5.

Spiking neurons with short-term synaptic plasticity form superior generative networks.

Leng L, Martel R, Breitwieser O, Bytschok I, Senn W, Schemmel J, Meier K, Petrovici MA.

Sci Rep. 2018 Jul 13;8(1):10651. doi: 10.1038/s41598-018-28999-2.

6.

Spatial But Not Oculomotor Information Biases Perceptual Memory: Evidence From Face Perception and Cognitive Modeling.

Wantz AL, Lobmaier JS, Mast FW, Senn W.

Cogn Sci. 2017 Aug;41(6):1533-1554. doi: 10.1111/cogs.12437. Epub 2016 Nov 17.

PMID:
27859647
7.

Prospective Coding by Spiking Neurons.

Brea J, Gaál AT, Urbanczik R, Senn W.

PLoS Comput Biol. 2016 Jun 24;12(6):e1005003. doi: 10.1371/journal.pcbi.1005003. eCollection 2016 Jun.

8.

Somato-dendritic Synaptic Plasticity and Error-backpropagation in Active Dendrites.

Schiess M, Urbanczik R, Senn W.

PLoS Comput Biol. 2016 Feb 3;12(2):e1004638. doi: 10.1371/journal.pcbi.1004638. eCollection 2016 Feb.

9.

Hierarchical Novelty-Familiarity Representation in the Visual System by Modular Predictive Coding.

Vladimirskiy B, Urbanczik R, Senn W.

PLoS One. 2015 Dec 15;10(12):e0144636. doi: 10.1371/journal.pone.0144636. eCollection 2015.

10.

Backward reasoning the formation rules.

Senn W, Sacramento J.

Nat Neurosci. 2015 Dec;18(12):1705-6. doi: 10.1038/nn.4172. No abstract available.

PMID:
26605880
11.

Scale-Free Navigational Planning by Neuronal Traveling Waves.

Khajeh-Alijani A, Urbanczik R, Senn W.

PLoS One. 2015 Jul 9;10(7):e0127269. doi: 10.1371/journal.pone.0127269. eCollection 2015.

12.

Human and machine learning in non-Markovian decision making.

Clarke AM, Friedrich J, Tartaglia EM, Marchesotti S, Senn W, Herzog MH.

PLoS One. 2015 Apr 21;10(4):e0123105. doi: 10.1371/journal.pone.0123105. eCollection 2015.

13.

Neurons that Remember How We Got There.

Senn W, Brea J.

Neuron. 2015 Feb 18;85(4):664-6. doi: 10.1016/j.neuron.2015.01.029.

14.

Modulation of orientation-selective neurons by motion: when additive, when multiplicative?

Lüdge T, Urbanczik R, Senn W.

Front Comput Neurosci. 2014 Jun 20;8:67. doi: 10.3389/fncom.2014.00067. eCollection 2014.

15.

A normative theory of forgetting: lessons from the fruit fly.

Brea J, Urbanczik R, Senn W.

PLoS Comput Biol. 2014 Jun 5;10(6):e1003640. doi: 10.1371/journal.pcbi.1003640. eCollection 2014 Jun.

16.

Code-specific learning rules improve action selection by populations of spiking neurons.

Friedrich J, Urbanczik R, Senn W.

Int J Neural Syst. 2014 Aug;24(5):1450002. doi: 10.1142/S0129065714500026. Epub 2013 Dec 5.

PMID:
24875790
17.

Nerve injury-induced neuropathic pain causes disinhibition of the anterior cingulate cortex.

Blom SM, Pfister JP, Santello M, Senn W, Nevian T.

J Neurosci. 2014 Apr 23;34(17):5754-64. doi: 10.1523/JNEUROSCI.3667-13.2014.

18.

Learning by the dendritic prediction of somatic spiking.

Urbanczik R, Senn W.

Neuron. 2014 Feb 5;81(3):521-8. doi: 10.1016/j.neuron.2013.11.030.

19.

Matching recall and storage in sequence learning with spiking neural networks.

Brea J, Senn W, Pfister JP.

J Neurosci. 2013 Jun 5;33(23):9565-75. doi: 10.1523/JNEUROSCI.4098-12.2013.

20.

Spike-based decision learning of Nash equilibria in two-player games.

Friedrich J, Senn W.

PLoS Comput Biol. 2012;8(9):e1002691. doi: 10.1371/journal.pcbi.1002691. Epub 2012 Sep 27.

21.

Gradient estimation in dendritic reinforcement learning.

Schiess M, Urbanczik R, Senn W.

J Math Neurosci. 2012 Feb 15;2(1):2. doi: 10.1186/2190-8567-2-2.

22.

Spatio-temporal credit assignment in neuronal population learning.

Friedrich J, Urbanczik R, Senn W.

PLoS Comput Biol. 2011 Jun;7(6):e1002092. doi: 10.1371/journal.pcbi.1002092. Epub 2011 Jun 30.

23.

Learning spike-based population codes by reward and population feedback.

Friedrich J, Urbanczik R, Senn W.

Neural Comput. 2010 Jul;22(7):1698-717. doi: 10.1162/neco.2010.05-09-1010.

24.

Spike-time-dependent plasticity and heterosynaptic competition organize networks to produce long scale-free sequences of neural activity.

Fiete IR, Senn W, Wang CZ, Hahnloser RH.

Neuron. 2010 Feb 25;65(4):563-76. doi: 10.1016/j.neuron.2010.02.003.

25.

Adaptive gain modulation in V1 explains contextual modifications during bisection learning.

Schäfer R, Vasilaki E, Senn W.

PLoS Comput Biol. 2009 Dec;5(12):e1000617. doi: 10.1371/journal.pcbi.1000617. Epub 2009 Dec 18.

26.

Spike-based reinforcement learning in continuous state and action space: when policy gradient methods fail.

Vasilaki E, Frémaux N, Urbanczik R, Senn W, Gerstner W.

PLoS Comput Biol. 2009 Dec;5(12):e1000586. doi: 10.1371/journal.pcbi.1000586. Epub 2009 Dec 4. Erratum in: PLoS Comput Biol. 2009 Dec;5(12). doi: 10.1371/annotation/307ea250-3792-4ceb-b905-162d86c96baf.

27.

A gradient learning rule for the tempotron.

Urbanczik R, Senn W.

Neural Comput. 2009 Feb;21(2):340-52. doi: 10.1162/neco.2008.09-07-605.

PMID:
19431262
28.

Stimulus sampling as an exploration mechanism for fast reinforcement learning.

Vladimirskiy BB, Vasilaki E, Urbanczik R, Senn W.

Biol Cybern. 2009 Apr;100(4):319-30. doi: 10.1007/s00422-009-0305-x. Epub 2009 Apr 10.

PMID:
19360435
29.

Reinforcement learning in populations of spiking neurons.

Urbanczik R, Senn W.

Nat Neurosci. 2009 Mar;12(3):250-2. doi: 10.1038/nn.2264. Epub 2009 Feb 15.

PMID:
19219040
30.

Learning flexible sensori-motor mappings in a complex network.

Vasilaki E, Fusi S, Wang XJ, Senn W.

Biol Cybern. 2009 Feb;100(2):147-58. doi: 10.1007/s00422-008-0288-z. Epub 2009 Jan 20.

PMID:
19153762
31.

Dendritic encoding of sensory stimuli controlled by deep cortical interneurons.

Murayama M, Pérez-Garci E, Nevian T, Bock T, Senn W, Larkum ME.

Nature. 2009 Feb 26;457(7233):1137-41. doi: 10.1038/nature07663. Epub 2009 Jan 18.

PMID:
19151696
32.

The response of cortical neurons to in vivo-like input current: theory and experiment: II. Time-varying and spatially distributed inputs.

Giugliano M, La Camera G, Fusi S, Senn W.

Biol Cybern. 2008 Nov;99(4-5):303-18. doi: 10.1007/s00422-008-0270-9. Epub 2008 Nov 15. Review.

PMID:
19011920
33.

The response of cortical neurons to in vivo-like input current: theory and experiment : I. Noisy inputs with stationary statistics.

La Camera G, Giugliano M, Senn W, Fusi S.

Biol Cybern. 2008 Nov;99(4-5):279-301. doi: 10.1007/s00422-008-0272-7. Epub 2008 Nov 5. Review.

PMID:
18985378
34.

Special issue on quantitative neuron modeling.

Jolivet R, Roth A, Schürmann F, Gerstner W, Senn W.

Biol Cybern. 2008 Nov;99(4-5):237-9. doi: 10.1007/s00422-008-0274-5. No abstract available.

35.

Modulating the granularity of category formation by global cortical States.

Kim Y, Vladimirskiy BB, Senn W.

Front Comput Neurosci. 2008 Jun 3;2:1. doi: 10.3389/neuro.10.001.2008. eCollection 2008.

36.

Special issue on object localization.

Leibold C, Senn W.

Biol Cybern. 2008 Jun;98(6):447. doi: 10.1007/s00422-008-0231-3. No abstract available.

PMID:
18491158
37.

Dopamine increases the gain of the input-output response of rat prefrontal pyramidal neurons.

Thurley K, Senn W, Lüscher HR.

J Neurophysiol. 2008 Jun;99(6):2985-97. doi: 10.1152/jn.01098.2007. Epub 2008 Apr 9.

38.

Learning real-world stimuli in a neural network with spike-driven synaptic dynamics.

Brader JM, Senn W, Fusi S.

Neural Comput. 2007 Nov;19(11):2881-912.

39.

Perceptual learning via modification of cortical top-down signals.

Schäfer R, Vasilaki E, Senn W.

PLoS Comput Biol. 2007 Aug;3(8):e165.

40.

Extending lifetime of plastic changes in the human brain.

Nyffeler T, Wurtz P, Lüscher HR, Hess CW, Senn W, Pflugshaupt T, von Wartburg R, Lüthi M, Müri RM.

Eur J Neurosci. 2006 Nov;24(10):2961-6.

PMID:
17156218
41.

Repetitive TMS over the human oculomotor cortex: comparison of 1-Hz and theta burst stimulation.

Nyffeler T, Wurtz P, Lüscher HR, Hess CW, Senn W, Pflugshaupt T, von Wartburg R, Lüthi M, Müri RM.

Neurosci Lett. 2006 Nov 27;409(1):57-60. Epub 2006 Oct 17.

PMID:
17049743
42.

Eluding oblivion with smart stochastic selection of synaptic updates.

Fusi S, Senn W.

Chaos. 2006 Jun;16(2):026112.

PMID:
16822044
43.

Multiple time scales of temporal response in pyramidal and fast spiking cortical neurons.

La Camera G, Rauch A, Thurbon D, Lüscher HR, Senn W, Fusi S.

J Neurophysiol. 2006 Dec;96(6):3448-64. Epub 2006 Jun 28.

44.
45.

Convergence of stochastic learning in perceptrons with binary synapses.

Senn W, Fusi S.

Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Jun;71(6 Pt 1):061907. Epub 2005 Jun 16.

PMID:
16089765
46.

Minimal models of adapted neuronal response to in vivo-like input currents.

La Camera G, Rauch A, Lüscher HR, Senn W, Fusi S.

Neural Comput. 2004 Oct;16(10):2101-24.

PMID:
15333209
47.

Top-down dendritic input increases the gain of layer 5 pyramidal neurons.

Larkum ME, Senn W, Lüscher HR.

Cereb Cortex. 2004 Oct;14(10):1059-70. Epub 2004 Apr 27.

PMID:
15115747
48.

Climbing neuronal activity as an event-based cortical representation of time.

Reutimann J, Yakovlev V, Fusi S, Senn W.

J Neurosci. 2004 Mar 31;24(13):3295-303.

49.

Hyperpolarization-activated current Ih disconnects somatic and dendritic spike initiation zones in layer V pyramidal neurons.

Berger T, Senn W, Lüscher HR.

J Neurophysiol. 2003 Oct;90(4):2428-37. Epub 2003 Jun 11.

50.

Neocortical pyramidal cells respond as integrate-and-fire neurons to in vivo-like input currents.

Rauch A, La Camera G, Luscher HR, Senn W, Fusi S.

J Neurophysiol. 2003 Sep;90(3):1598-612. Epub 2003 May 15.

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