Publications of P.

Select a view.
77 publication entries, 47 of them (printed in bold in the list) acknowledge the project support.
Jump to:
Review
Book chapter
Conference contribution: poster
PhD Thesis
Web publication
Other

Paper (reviewed)

Adhikari et al. 2012Adhikari, M.H., Quilichini, P.P., Roy, D., Jirsa, V.K. and Bernard, C. Brain State Dependent Postinhibitory Rebound in Entorhinal Cortex InterneuronsJ Neurosci. (2012) 32(19):6501-6510
doi:10.1523/JNEUROSCI.5871-11.2012
abstract, (fulltext)
Antolik and Davison 2013Antolik, J. and Davison, A.P.Integrated workflows for spiking neuronal network simulationsFront. Neuroinform. (2013) 7:34
doi:10.3389/fninf.2013.00034
fulltext
Arduin et al. 2013Arduin, P.-J., Fregnac, Y., Shulz, D. E. and Ego-Stengel, V. "Master" Neurons Induced by Operant Conditioning in Rat Motor Cortex during a Brain-Machine Interface TaskThe Journal of Neuroscience (2013) 33(19): 8308-8320
doi:10.1523/JNEUROSCI.2744-12.2013
fulltext
Bakker et al. 2015Bakker, R., Tiesinga, P. and Kötter, R.The Scalable Brain Atlas: Instant Web-Based Acces to Public Brain Atlases and Related ContentNeuroinformatics February (2015) 13(3):353-366
doi:10.1007/s12021-014-9258-x
abstract, fulltext
Baudot et al. 2013Baudot, P., Levy, M., Marre, O., Monier, C., Pananceau, M. and Fregnac, Y. Animation of natural scene by virtual eye-movements evokes high precision and low noise in V1 neuronsFront. Neural Circuits (2013) 7:206
doi:10.3389/fncir.2013.00206
fulltext
Bazhenov et al. 2011Bazhenov, M., Lonjers, P., Skorheim, S., Bedard, C. and Destexhe, A.Non-homogeneous extracellular resistivity affects the current-source density profiles of up/down state oscillationsPhil. Trans. R. Soc. A (2011) 369:3802-3819
doi:10.1098/rsta.2011.0119
abstract, fulltext
Berthet and Lansner 2014Berthet, P. and Lansner, A.Optogenetic Stimulation in a Computational Model of the Basal Ganglia Biases Action Selection and Reward Prediction ErrorPLoS ONE (2014) 9(3): e90578
doi:10.1371/journal.pone.0090578
fulltext
Berthet et al. 2012Berthet, P., Hellgren-Kotaleski, J. and Lansner, A.Action selection performance of a reconfigurable Basal Ganglia model with a Hebbian-Bayesian Go-NoGo connectivityFront. Behav. Neurosci. (2012) 6:65
doi:10.3389/fnbeh.2012.00065
fulltext
Blackman et al 2014A. V. Blackman, S. Grabuschnig, R. Legenstein, and P. J. SjöströmA comparison of manual neuronal reconstruction from biocytin histology or 2-photon imaging: morphometry and computer modelingFrontiers in neuroanatomy (2014) : 8
doi:10.3389/fnana.2014.00065
abstract, fulltext
Brüderle et al. 2011Brüderle, D., Petrovici, M. A., Vogginger, B., Ehrlich, M., Pfeil, T., Millner, S., Grübl, A., Wendt, K., Müller, E., Schwartz, M.-O., de Oliveira, D. H., Jeltsch, S., Fieres, J., Schilling, M., Müller, P., Breitwieser, O., Petkov, V., Muller, L., Davison, A. P., Krishnamurthy, P., Kremkow, J., Lundqvist, M., Muller, E., Partzsch, J., Scholze, S., Zühl, L., Mayr, C., Destexhe, A., Diesmann, M., Potjans, T. C., Lansner, A., Schüffny, R., Schemmel, J. and Meier, K. A comprehensive workflow for general-purpose neural modeling with highly configurable neuromorphic hardware systemsBiological Cybernetics (2011) 104(4-5): 263-296
doi:10.1007/s00422-011-0435-9
abstract, fulltext
Chossat et al. 2011Chossat, P., Faye, G., Faugeras, O.Bifurcations of hyperbolic planforms Journal of Nonlinear Science (2011) 21(4): 465-498
doi:10.1007/s00332-010-9089-3
abstract, fulltext, BibTeX
Dagnino et al. 2015Dagnino, B., Gariel-Mathis, M.-A. and Roelfsema, P. R. Microstimulation of area V4 has little effect on spatial attention and on the perception of phosphenes evoked in area V1Journal of Neurophysiology (2015) 113(3): 730-739
doi:10.1152/jn.00645.2014
abstract
Davison 2012Davison, A. P.Automated Capture of Experiment Context for Easier Reproducibility in Computational Research Computing in Science and Engineering (2012) 14: 48-56
doi:10.1109/MCSE.2012.41
abstract, fulltext
Deco at al. 2014bDeco, G., McIntosh, A.R., Shen, K., Hutchison, R.M., Menon, R.S., Everling, S., Hagmann, P. and Jirsa, V.K.Identification of Optimal Structural Connectivity Using Functional Connectivity and Neural ModelingThe Journal of Neuroscience (2014) 34(23): 7910-7916
doi:10.1523/JNEUROSCI.4423-13.2014
fulltext
Deco et al. 2013Deco,G., Ponce-Alvarez, A., Mantini, D., Romani, G.L., Hagmann, P. and Corbetta, M.Resting-state functional connectivity emerges from structurally and dynamically shaped slow linear fluctuationsJ. Neurosci. (2013) 33: 11239-11252
doi:10.1523/JNEUROSCI.1091-13.2013
abstract, (fulltext)
Deco et al. 2014Deco, G., Ponce-Alvarez, A., Hagmann, P., Romani, G.L., Mantini, D. and Corbetta, M.How local excitation-inhibition ratio impacts the whole brain dynamicsJ. Neurosci. (2014) 34: 7886-7898
doi:10.1523/JNEUROSCI.5068-13.2014
abstract, (fulltext)
DeFelipe et al. 2013DeFelipe, J., Lopez-Cruz, P.L., Benavides-Piccione, R., Bielza, C., Larranaga, P., Anderson, S., Burkhalter, A., Cauli, B., Fairen, A., Feldmeyer, D., Fishell, G., Fitzpatrick, D., Freund, T.F., Gonzalez-Burgos, G., Hestrin, S., Hill, S., Hof, P.R., Huang, J., Jones, E.G., Kawaguchi, Y., Kisvarday, Z., Kubota, Y., Lewis, D.A., Marin, O., Markram, H., McBain, C.J., Meyer, H.S., Monyer, H., Nelson, S.B., Rockland, K., Rossier, J., Rubenstein, J.L.R., Rudy, B., Scanziani, M., Shepherd, G.M., Sherwood, C.C., Staiger, J.F., Tamas, G., Thomson, A., Wang, Y., Yuste, R. and Ascoli, G.A.New insights into the classification and nomenclature of cortical GABAergic interneuronsNature Reviews Neuroscience (2013) 14: 202-216
doi:10.1038/nrn3444
(fulltext)
Devor et al. 2013Devor, A., Bandettini, P., Boas, D., Bower, J., Buxton, R., Cohen, L., Dale, A., Einevoll, G., Fox, P., Franceschini, M., Friston, K., Fujimoto, J., Geyer, M., Greenberg, J., Halgren, E., Hamalainen, M., Helmchen, F., Hyman, B., Jasanoff, A., Jernigan, T., Judd, L., Kim, S.-G., Kleinfeld, D., Kopell, N., Kutas, M., Kwong, K., Larkum, M., Lo, E., Magistretti, P., Mandeville, J., Masliah, E., Mitra, P., Mobley, W., Moskowitz, M., Nimmerjahn, A., Reynolds, J., Rosen, B., Salzberg, B., Schaffer, C., Silva, G., So, P., Spitzer, N., Tootell, R., Essen, D. V., Vanduffel, W., Vinogradov, S., Wald, L., Wang, L., Weber, B. and Yodh, A. The challenge of connecting the dots in the B.R.A.I.N.Neuron (2013) 80: 270-274
doi:10.1016/j.neuron.2013.09.008
abstract
Djurfeldt et al. 2014Djurfeldt, M., Davison, A.P. and Eppler, J.M. Efficient generation of connectivity in neuronal networks from simulator-independent descriptionsFront. Neuroinform. (2014) 8:43
doi:10.3389/fninf.2014.00043
fulltext
El Boustani et al. 2012El Boustani, S., Yger, P., Frégnac, Y. and Destexhe, A.Stable Learning in Stochastic Network StatesThe Journal of Neuroscience (2012) 32(1): 194-214
doi:10.1523/JNEUROSCI.2496-11.2012
fulltext
Faye and Chossat 2012Faye, G. and Chossat, P.Bifurcation Diagrams and Heteroclinic Networks of Octagonal H-PlanformsJournal of Nonlinear Science (2012) 22(3): 277-325
doi:10.1007/s00332-011-9118-x
abstract, fulltext, BibTeX
Faye and Chossat 2013Faye, G. and Chossat, P.A spatialized model of textures perception using structure tensor formalismAIMS Journal on Networks and Heterogeneous Media (2013) 8(1): 211-260
doi:10.3934/nhm.2013.8.211
abstract, (fulltext)
Faye et al. 2011Faye, G., Chossat, P. and Faugeras, O.Analysis of a hyperbolic geometric model for visual texture perceptionThe Journal of Mathematical Neuroscience (2011) 1:4
doi:10.1186/2190-8567-1-4
fulltext, BibTeX
Faye et al. 2012Faye, G., Rankin, J and Chossat, P.Localized states in an unbounded neural field equation with smooth firing rate function: a multi-parameter analysisJournal of Mathematical Biology (2012) :
doi:10.1007/s00285-012-0532-y
abstract, fulltext, BibTeX
Galtier et al. 2012Galtier, M., Faugeras, O. and Bressloff, P. Hebbian Learning of Recurrent Connections: A Geometrical PerspectiveNeural Computation (2012) 24(9): 2346-2383
doi:10.1162/NECO_a_00322
(fulltext)
Garcia et al. 2014Garcia, S., Guarino, D., Jaillet, F., Jennings, T.R., Pröpper, R., Rautenberg, P.L., Rodgers, C., Sobolev, A., Wachtler, T., Yger, P. and Davison, A.P.Neo: an object model for handling electrophysiology data in multiple formatsFront. Neuroinform. (2014) 8:10
doi:10.3389/fninf.2014.00010
abstract, fulltext
Hennequin et al. 2014Hennequin, G., Vogels, T.P. and Gerstner, W.Optimal Control of Transient Dynamics in Balanced Networks Supports Generation of Complex MovementsNeuron (2014) 82: 1394-1406
doi:10.1016/j.neuron.2014.04.045
fulltext
Hennequinet al 2012Hennequin, G., Vogels, T.P. and Gerstner, W.Non-normal amplification in random balanced neuronal networksPhysical Review E (2012) 86: 011909
doi:10.1103/PhysRevE.86.011909
fulltext
Indiveri et al. 2011Indiveri, G., Linares-Barranco, B., Hamilton, T. J., van Schaik, A., Etienne-Cummings, R., Delbruck, T., Liu, S.-C., Dudek, P., Häfliger, P., Renaud, S., Schemmel, J., Cauwenberghs, G., Arthur, J., Hynna, K., Folowosele, F., Saïghi, S., Serrano-Gotarredona, T., Wijekoon, J., Wang, Y. and Boahen, K. Neuromorphic silicon neuron circuitsFront. Neurosci. (2011) 5:73
doi:10.3389/fnins.2011.00073
fulltext
Kerr et al.Kerr, C.C., van Albada, S., Neymotin, S.A., Chadderdon, G.L., Robinson, P.A., and Lytton, W.W.Cortical information flow in Parkinson's disease: a composite network/field modelFront Comput Neurosci. (2013) 7:39
doi:10.3389/fncom.2013.0003
fulltext
Kooijmans et al. 2014Kooijmans, R.N., Self,M.W., Wouterlood,F.G., Beliën, J.A.M. and Roelfsema P.R.Inhibitory Interneuron Classes Express Complementary AMPA-Receptor Patterns in Macaque Primary Visual CortexThe Journal of Neuroscience (2014) 34(18): 6303-6315
doi:10.1523/JNEUROSCI.3188-13.2014
fulltext
Krishnamurthy et al. 2012Krishnamurthy, P., Silberberg, G. and Lansner, A.A cortical attractor network with Martinotti cells driven by facilitating synapsesPLoS ONE (2012) 7(4): e30752
doi:10.1371/journal.pone.0030752
fulltext
Lundqvist et al. 2011aLundqvist, M., Herman, P. and Lansner, A.Theta and gamma power increases and alpha/beta power decreases with memory load in an attractor network modelJ Cogn Neurosci (2011) 23:3008-3020
doi:10.1162/jocn_a_00029
abstract
Lundqvist et al. 2012Lundqvist, M., Herman, P. and Lansner, A.Variability of spike firing during theta-coupled replay of memories in a simulated attractor networkBrain Res (2012) 1434:152-161
doi:10.1016/j.brainres.2011.07.055
fulltext
Markram et al. 2011Markram, H., Gerstner, W. and Sjoestoem, P.J.A history of spike-timing-dependent plasticityFront. Syn. Neurosci. (2011) 3:4
doi:10.3389/fnsyn.2011.00004
abstract, fulltext
Petrovici et al. 2014Petrovici, M. A., Vogginger, B., Müller, P., Breitwieser, O., Lundqvist, M., Muller, L., Ehrlich, M., Destexhe, A., Lansner, A., Schüffny, R., Schemmel, J. and Meier, K. Characterization and Compensation of Network-Level Anomalies in Mixed-Signal Neuromorphic Modeling PlatformsPLoS ONE (2014) 9(10): e108590
doi:10.1371/journal.pone.0108590
abstract
Pfeil et al. 2012Pfeil, T., Grübl, A., Jeltsch, S., Müller, E., Müller, P., Petrovici, M., Schmuker, M., Brüderle, D., Schemmel, J. and Meier, K. Six networks on a universal neuromorphic computing substrateFront. Neurosci. (2013) 7:11
(Pre-print: http://arxiv.org/abs/1210.7083)
doi:10.3389/fnins.2013.00011
abstract
Pooresmaeili and Roelfsema 2014Pooresmaeili, A. and Roelfsema, P. R. A Growth-Cone Model for the Spread of Object-Based Attention during Contour GroupingCurrent Biology (2014) 24(24): 2869-2877
doi:10.1016/j.cub.2014.10.007
abstract
Pooresmaeili et al. 2014Pooresmaeili, A., Poort, and Roelfsema, P.R.Simultaneous selection by object-based attention in visual and frontal cortexPNAS (2014) 111(17): 6467-6472
doi:10.1073/pnas.1316181111
fulltext
Poort et al. 2012Poort, J., Raudies, F., Wannig, A., Lamme, V.A.F., Neumann, H. and Roelfsema, P.R.The role of attention in figure-ground segregation in areas V1 and V4 of the visual cortex.Neuron (2012) 75: 143-156
doi:10.1016/j.neuron.2012.04.032
abstract, (fulltext)
Rankin et al. 2012Rankin, J., Tlapale, E., Veltz, R., Faugeras, O. and Kornprobst, P. Bifurcation analysis applied to a model of motion integration with a multistable stimulusJournal of Computational Neuroscience (2013) 34(1): 103-124
doi:10.1007/s10827-012-0409-5
fulltext, BibTeX
Rankin et al. 2013aRankin, J., Tlapale, E., Veltz, R., Faugeras, O. and Kornprobst, P. Bifurcation analysis applied to a model of motion integration with a multistable stimulus Journal of Computational Neuroscience (2013) 34(1): 103-124
doi:10.1007/s10827-012-0409-5
fulltext
Rankin et al. 2013bRankin, J., Meso, A. I., Masson, G.S., Faugeras, O. and Kornprobst, P. Bifurcation study of a neural field competition model with an application to perceptual switching in motion integrationJournal of Computational Neuroscience (2013) September: 1-21
doi:10.1007/s10827-013-0465-5
fulltext
Rombouts et al. 2015Rombouts, J.O., Bohte, S.M. and Roelfsema, P.R.How Attention Can Create Synaptic Tags for the Learning of Working Memories in Sequential TasksPLoS Comput Biol (2015) 11(3): e1004060
doi:10.1371/journal.pcbi.1004060
fulltext
Rombouts et al. 2015bRombouts, J. O., Bohte, S. M., Martinez-Trujillo, J. and Roelfsema, P. R. A learning rule that explains how rewards teach attentionVisual Cognition (2015) 33:179-205
doi:10.1080/13506285.2015.1010462
abstract
Sanz Leon et al. 2012Sanz Leon, P., Vanzetta, I., Masson, G.S. and Perrinet, L.U.Motion Clouds: model-based stimulus synthesis of natural-like random textures for the study of motion perceptionAJP - JN Physiol (2012) 107 (11): 3217-3226
doi:10.1152/jn.00737.2011
abstract, (fulltext)
Savin et al. 2014Savin, C., Dayan, P. and Lengyel, M.
Optimal Recall from Bounded Metaplastic Synapses: Predicting Functional Adaptations in Hippocampal Area CA3PLoS Comput Biol (2014) 10(2): e1003489
doi:10.1371/journal.pcbi.1003489
fulltext
Schmuker et al. 2014Schmuker, M., Pfeil, T. and Nawrot, M. P. A neuromorphic network for generic multivariate data classificationPNAS (2014) 111(6): 2081-2086
doi:10.1073/pnas.1303053111
abstract, fulltext
Self et al. 2013Self, M.W., van Kerkoerle, T., Supèr, H. & Roelfsema, P.R. Distinct roles of the cortical layers of area V1 in figure-ground segregationCurr. Biol. (2013) 23: 2121-2129
doi:10.1016/j.cub.2013.09.013
abstract
Self et al. 2014Self, M.W., Lorteije, J.A.M., Vangeneugden, J., van Beest, E.H., Grigore, M.E., Levelt, C., Heimel, J.A. and Roelfsema, P.R.Orientation-Tuned Surround Suppression in Mouse Visual CortexThe Journal of Neuroscience (2014) 34(28): 9290-9304
doi:10.1523/JNEUROSCI.5051-13.2014
fulltext
Simoncini et al. 2012Simoncini, C., Perrinet, L.U., Montagnini, A., Mamassian, P. and Masson G.S.More is not always better: pooling motion information differently for perception or actionNature Neuroscience (2012) 15: 1596-1603
doi:10.1038/nn.3229
fulltext
Takerkart et al. 2014Takerkart, S., Katz, P., Garcia, F., Roux, S., Reynaud, A. and Chavane, F.Vobi One: a data processing software package for functional optical imaging.Front. Neurosci. (2014) 8:2
doi:10.3389/fnins.2014.00002
fulltext
Taouali et al. 2015Taouali, W., Benvenuti, G., Wallisch, P., Chavane, F. and Perrinet, L. U. Testing the Odds of Inherent versus Observed Over-dispersion in Neural Spike CountsJournal of Neurophysiology (2015)
doi:10.1152/jn.00194.2015
abstract
Tully et al. 2014Tully, P. J., Hennig, M. H. and Lansner, A.Synaptic and Nonsynaptic Plasticity Approximating Probabilistic InferenceFront. Synaptic Neurosci. (2014) 6:8
doi:10.3389/fnsyn.2014.00008
fulltext
van Kerkoerle et al. 2014van Kerkoerle, T., Self, M.W., Dagnino, B., Gariel-Mathis, M.-A., Poort, J., van der Togt, C. and Roelfsema, P.R.Alpha and gamma oscillations characterize feedback and feedforward processing in monkey visual cortexPNAS (2014) 111(40): 14332-14341
doi:10.1073/pnas.1402773111
abstract, fulltext
Vella et al. 2014Vella, M., Cannon, R.C., Crook, S., Davison, A.P., Ganapathy, G., Robinson, H.P.C., Silver, R.A. and Gleeson, P.libNeuroML and PyLEMS: using Python to combine procedural and declarative modelling approaches in computational neuroscienceFrontiers in Neuroinformatics (2014) 8: 38
doi:10.3389/fninf.2014.00038
abstract
Vogels et al 2013T. P. Vogels, R. C. Froemke, N. Doyon, M. Gilson, J. S. Haas, R. Liu, A. Maffei, P. Miller, C. J. Wierenga, M. A. Woodin, F. Zenke and H. SprekelerInhibitory synaptic plasticity: spike timing-dependence and putative network functionFrontiers In Neural Circuits (2013) : 7
doi:10.3389/fncir.2013.00119
fulltext

Review

Crook et al. 2012Crook, S. M., Bednar, J. A., Berger, S., Cannon, R., Davison, A. P., Djurfeldt, M., Eppler, J., Kriener, B., Furber, S., Graham, B., Plesser, H. E., Schwabe, L., Smith, L., Steuber, V. and van Albada, S.Creating, documenting and sharing network modelsNetwork: Computation in Neural Systems (2012) 23(4): 131-149
doi:10.3109/0954898X.2012.722743
abstract, fulltext

Book chapter

Crook et al. 2013Crook., S. M., Davison, A. P. and Plesser, H. E. Learning from the past: approaches for reproducibility in computational neuroscienceIn: J.M. Bower (Ed.), 20 Years of Computational Neuroscience, Springer, ISBN 978-1-4614-1423-0
doi:10.1007/978-1-4614-1424-7_4
abstract
Davison et al. 2014Davison, A.P., Mattioni, M., Samarkanov, D. and Telenczuk, B.Sumatra: A Toolkit for Reproducible ResearchIn: Implementing Reproducible Research (2014), edited by V. Stodden, F. Leisch and R.D. Peng, Chapman & Hall/CRC: Boca Raton, Florida., pp. 57-79 abstract

Conference contribution: poster

Medathati, K.N.V., Rankin, J., Kornprobst, P. and Masson, G.S. A retinotopic neural fields model of perceptual switching in 2D motion integrationAnnual Bernstein Conference 24-27 september 2013, Tuebingen, Germany
Antolik and Davison 2013bAntolik, J. and Davison, A.P.Mozaik: a framework for model construction, simulation, data analysis and visualization for large-scale spiking neural circuit modelsNeuroinformatics 2013, Stockholm, Sweden, August (2013)
doi:10.3389/conf.fninf.2013.09.00018
abstract
Bachmannet al 2013Bachmann, C. ; Tetzlaff, T. ; Kunkel, S. ; Bamberger, P. ; Morrison, A.
Computational characteristics of recurrent neural networks under the influence of Alzheimer's disease
10th Göttingen Meeting of the German Neuroscience Society, Göttingen, Germany, 03/13/2013 - 03/16/2013
Bachmannet al 2013bBachmann, C., Tetzlaff, T., Kunkel, S., Bamberger, P. and Morrison, A.
Effect of Alzheimer's disease on the dynamical and computational characteristics of recurrent neural networks
22nd Annual Computational Neuroscience Meeting, CNS*2013, Paris, France, 07/13/2013 - 07/18/2013
Davison et al. 2013Davison, A.P., Djurfeldt, M., Eppler, J.M., Gleeson, P., Hull, M. and Muller, E.B.An integration layer for neural simulation: PyNN in the software forestNeuroinformatics 2013, Stockholm, Sweden, August (2013).
doi:10.3389/conf.fninf.2013.09.00020
abstract
Davison et al. 2013bDavison, A.P., Brizzi, T., Guarino, D., Manette, O.F., Monier, C., Sadoc, G. and Frégnac, Y.Helmholtz: a customizable framework for neurophysiology data management Neuroinformatics 2013, Stockholm, Sweden, 27 Aug - 29 Aug, (2013)
doi:10.3389/conf.fninf.2013.09.00025
abstract
Deneux et al. 2012Deneux, T., Sanz-Leon, P., Masquelier, T., Masson, G. S., Deco, G. and Vanzetta, I. (2012) The spatiotemporal structure of ongoing and evoked activity investigated using optical imaging of voltage sensitive dyes in awake monkey V4AREADNE Meeting, Juin 2012, Santorini, Greece (2012)
Gorchetchnikov et al. 2011Gorchetchnikov, A., Cannon, R., Clewley, R., Cornelis, H., Davison, A., De Schutter, E., Djurfeldt, M., Gleeson, P., Hill, S., Hines, M., Kriener, B., Le Franc, Y., Lo, C.-C., Morrison, A., Muller, E., Plesser, H.E., Raikov, I., Ray, S., Schwabe, L. and Szatmary, B.NineML: declarative, mathematically-explicit descriptions of spiking neuronal networksFront. Neuroinform. Conference Abstract: 4th INCF Congress of Neuroinformatics
doi:10.3389/conf.fninf.2011.08.00098
abstract
Lodi et al. 2013Lodi, M., Somogyi, P. and Kisvarday, Z. Synaptic targets of GABAergic fusiform cells in the cat primary visual cortexXVIII. Hungarian Vision Symposium, Pécs (2013)
Meso et al. 2013Meso, A., Rankin, J., Kornprobst, P. and Masson, G.S.Multi-stability in motion perception combines multiple underlying neural mechanismsCoSyne meeting. 1-4 March 2013, Salt-Lake City, USA.
Plesser et al. 2011Plesser, H.E., Crook, S. and Davison, A.P.Reproducible models and reliable simulations: Current trends in computational neuroscienceSIAM Computational Science and Engineering 2011, Reno, Nevada, February 2011
Raikov et al. 2011Raikov, I., Cannon, R., Clewley, R., Cornelis, H., Davison, A., De Schutter, E., Djurfeldt, M., Gleeson, P., Gorchetchnikov, A., Plesser, H.E., Hill, S., Hines, M., Kriener, B., Le Franc, Y., Lo, C.-C., Morrison, A., Muller, E., Ray, S., Schwabe, L. and Szatmary, B. NineML: the network interchange for neuroscience modeling languageBMC Neuroscience 2011, 12(Suppl 1):P330
doi:10.1186/1471-2202-12-S1-P330
abstract
Suzukiet al 2013Suzuki, M. ; Yamane, Y. ; Ito, J. ; Strokov, S. ; Fujita, I. ; Maldonado, P. ; Grün, S. ; Tamura, H.
Factors affecting human gaze behavior: an analysis with complex natural scenes with superimposed object images
36th European Conference on Visual Perception, ECVP2013, Bremen, Germany, 08/25/2013 - 08/29/2013
Teeters et al. 2013Teeters, J.L., Benda, J., Davison, A.P., Eglen, S., Gerhard, S., Gerkin, R.C., Grewe, J., Harris, K., Jackson, T., Moucek, R., Pröpper, R., Sessions, H.L., Smith, L.S., Sobolev, A., Sommer, F.T., Stoewer, A. and Wachtler, T. Considerations for developing a standard for storing electrophysiology data in HDF5Neuroinformatics 2013, Stockholm, Sweden, 27 Aug - 29 Aug, (2013)
doi:10.3389/conf.fninf.2013.09.00069
abstract

PhD Thesis

Arduin 2011Arduin, P.-J.Operant conditionning of neurons in the rat motor cortex for a graded control of a prosthetic devicePh. D. thesis (2011)

Web publication

Benjaminsson et al. 2011Benjaminsson, S., Silverstein, D., Herman, P., Melis, P., Slavnic, V., Spasojevic, M., Alexiev, K. and Lansner, A.Visualization of output from Large-Scale Brain SimulationsPartnership for Advanced Computing in Europe (PRACE), Project ID: PRPC06 fulltext

Other

Chorley et al. 2014Chorley, P., Diesmann, M., Helias, M. and Grün, S. Correlated rate vector dynamics in motor cortexINM Retreat, Jülich, Germany, 07/01/2014 - 07/02/2014


 
. 
 

26 August 2016