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Items: 28

1.

SpykeTorch: Efficient Simulation of Convolutional Spiking Neural Networks With at Most One Spike per Neuron.

Mozafari M, Ganjtabesh M, Nowzari-Dalini A, Masquelier T.

Front Neurosci. 2019 Jul 12;13:625. doi: 10.3389/fnins.2019.00625. eCollection 2019.

2.

Deep learning in spiking neural networks.

Tavanaei A, Ghodrati M, Kheradpisheh SR, Masquelier T, Maida A.

Neural Netw. 2019 Mar;111:47-63. doi: 10.1016/j.neunet.2018.12.002. Epub 2018 Dec 18. Review.

PMID:
30682710
3.

Optimal Localist and Distributed Coding of Spatiotemporal Spike Patterns Through STDP and Coincidence Detection.

Masquelier T, Kheradpisheh SR.

Front Comput Neurosci. 2018 Sep 18;12:74. doi: 10.3389/fncom.2018.00074. eCollection 2018.

4.

Emergence of Binocular Disparity Selectivity through Hebbian Learning.

Chauhan T, Masquelier T, Montlibert A, Cottereau BR.

J Neurosci. 2018 Oct 31;38(44):9563-9578. doi: 10.1523/JNEUROSCI.1259-18.2018. Epub 2018 Sep 21.

5.

First-Spike-Based Visual Categorization Using Reward-Modulated STDP.

Mozafari M, Kheradpisheh SR, Masquelier T, Nowzari-Dalini A, Ganjtabesh M.

IEEE Trans Neural Netw Learn Syst. 2018 Dec;29(12):6178-6190. doi: 10.1109/TNNLS.2018.2826721. Epub 2018 May 8.

PMID:
29993898
6.

Representation learning using event-based STDP.

Tavanaei A, Masquelier T, Maida A.

Neural Netw. 2018 Sep;105:294-303. doi: 10.1016/j.neunet.2018.05.018. Epub 2018 Jun 1.

PMID:
29894846
7.

Convis: A Toolbox to Fit and Simulate Filter-Based Models of Early Visual Processing.

Huth J, Masquelier T, Arleo A.

Front Neuroinform. 2018 Mar 7;12:9. doi: 10.3389/fninf.2018.00009. eCollection 2018.

8.

STDP-based spiking deep convolutional neural networks for object recognition.

Kheradpisheh SR, Ganjtabesh M, Thorpe SJ, Masquelier T.

Neural Netw. 2018 Mar;99:56-67. doi: 10.1016/j.neunet.2017.12.005. Epub 2017 Dec 23.

PMID:
29328958
9.

Object Categorization in Finer Levels Relies More on Higher Spatial Frequencies and Takes Longer.

Ashtiani MN, Kheradpisheh SR, Masquelier T, Ganjtabesh M.

Front Psychol. 2017 Jul 25;8:1261. doi: 10.3389/fpsyg.2017.01261. eCollection 2017.

10.

Visual stimulation quenches global alpha range activity in awake primate V4: a case study.

Deneux T, Masquelier T, Bermudez MA, Masson GS, Deco G, Vanzetta I.

Neurophotonics. 2017 Jul;4(3):031222. doi: 10.1117/1.NPh.4.3.031222. Epub 2017 Jun 28.

11.

STDP Allows Close-to-Optimal Spatiotemporal Spike Pattern Detection by Single Coincidence Detector Neurons.

Masquelier T.

Neuroscience. 2018 Oct 1;389:133-140. doi: 10.1016/j.neuroscience.2017.06.032. Epub 2017 Jun 29.

12.

Humans and Deep Networks Largely Agree on Which Kinds of Variation Make Object Recognition Harder.

Kheradpisheh SR, Ghodrati M, Ganjtabesh M, Masquelier T.

Front Comput Neurosci. 2016 Aug 31;10:92. doi: 10.3389/fncom.2016.00092. eCollection 2016.

13.

Deep Networks Can Resemble Human Feed-forward Vision in Invariant Object Recognition.

Kheradpisheh SR, Ghodrati M, Ganjtabesh M, Masquelier T.

Sci Rep. 2016 Sep 7;6:32672. doi: 10.1038/srep32672.

14.

Rank Order Coding: a Retinal Information Decoding Strategy Revealed by Large-Scale Multielectrode Array Retinal Recordings.

Portelli G, Barrett JM, Hilgen G, Masquelier T, Maccione A, Di Marco S, Berdondini L, Kornprobst P, Sernagor E.

eNeuro. 2016 Jun 3;3(3). pii: ENEURO.0134-15.2016. doi: 10.1523/ENEURO.0134-15.2016. eCollection 2016 May-Jun.

15.

Microsaccades enable efficient synchrony-based coding in the retina: a simulation study.

Masquelier T, Portelli G, Kornprobst P.

Sci Rep. 2016 Apr 11;6:24086. doi: 10.1038/srep24086.

16.

Oscillations can reconcile slowly changing stimuli with short neuronal integration and STDP timescales.

Masquelier T.

Network. 2014 Mar-Jun;25(1-2):85-96. doi: 10.3109/0954898X.2014.881574. Review.

PMID:
24571100
17.

Network bursting dynamics in excitatory cortical neuron cultures results from the combination of different adaptive mechanisms.

Masquelier T, Deco G.

PLoS One. 2013 Oct 11;8(10):e75824. doi: 10.1371/journal.pone.0075824. eCollection 2013. Erratum in: PLoS One. 2013;8(11). doi:10.1371/annotation/b7f972c2-57df-44c4-9d54-9f194222d762.

18.

Neural variability, or lack thereof.

Masquelier T.

Front Comput Neurosci. 2013 Feb 25;7:7. doi: 10.3389/fncom.2013.00007. eCollection 2013.

19.

STDP and STDP variations with memristors for spiking neuromorphic learning systems.

Serrano-Gotarredona T, Masquelier T, Prodromakis T, Indiveri G, Linares-Barranco B.

Front Neurosci. 2013 Feb 18;7:2. doi: 10.3389/fnins.2013.00002. eCollection 2013.

20.

STDP allows fast rate-modulated coding with Poisson-like spike trains.

Gilson M, Masquelier T, Hugues E.

PLoS Comput Biol. 2011 Oct;7(10):e1002231. doi: 10.1371/journal.pcbi.1002231. Epub 2011 Oct 27.

21.

Relative spike time coding and STDP-based orientation selectivity in the early visual system in natural continuous and saccadic vision: a computational model.

Masquelier T.

J Comput Neurosci. 2012 Jun;32(3):425-41. doi: 10.1007/s10827-011-0361-9. Epub 2011 Sep 21.

PMID:
21938439
22.

The timing of vision - how neural processing links to different temporal dynamics.

Masquelier T, Albantakis L, Deco G.

Front Psychol. 2011 Jun 30;2:151. doi: 10.3389/fpsyg.2011.00151. eCollection 2011.

23.

On spike-timing-dependent-plasticity, memristive devices, and building a self-learning visual cortex.

Zamarreño-Ramos C, Camuñas-Mesa LA, Pérez-Carrasco JA, Masquelier T, Serrano-Gotarredona T, Linares-Barranco B.

Front Neurosci. 2011 Mar 17;5:26. doi: 10.3389/fnins.2011.00026. eCollection 2011.

24.

The role of rhythmic neural synchronization in rest and task conditions.

Deco G, Buehlmann A, Masquelier T, Hugues E.

Front Hum Neurosci. 2011 Feb 7;5:4. doi: 10.3389/fnhum.2011.00004. eCollection 2011.

25.

Oscillations, phase-of-firing coding, and spike timing-dependent plasticity: an efficient learning scheme.

Masquelier T, Hugues E, Deco G, Thorpe SJ.

J Neurosci. 2009 Oct 28;29(43):13484-93. doi: 10.1523/JNEUROSCI.2207-09.2009.

26.

Competitive STDP-based spike pattern learning.

Masquelier T, Guyonneau R, Thorpe SJ.

Neural Comput. 2009 May;21(5):1259-76. doi: 10.1162/neco.2008.06-08-804.

PMID:
19718815
27.

Spike timing dependent plasticity finds the start of repeating patterns in continuous spike trains.

Masquelier T, Guyonneau R, Thorpe SJ.

PLoS One. 2008 Jan 2;3(1):e1377. doi: 10.1371/journal.pone.0001377.

28.

Unsupervised learning of visual features through spike timing dependent plasticity.

Masquelier T, Thorpe SJ.

PLoS Comput Biol. 2007 Feb 16;3(2):e31. Epub 2007 Jan 2.

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