Publications in 2009

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119 publication entries, 9 of them (printed in bold in the list) acknowledge the project support.
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Paper (reviewed)

Bedard and Destexhe 2009Bedard, C. and Destexhe, A.Macroscopic models of local field potentials the apparent 1/f noise in brain activityBiophysical Journal (2009) 96: 2589-2603 abstract
Boucsein et al. 2009aBoucsein, C., Tetzlaff, T., Meier, M., Aertsen, A. and Naundorf, B.Dynamical response properties of neocortical neuron ensembles: multiplicative versus additive noiseJournal of Neuroscience (2009) 29(4):1006-1010
Brette et al. 2009Brette, R., Piwkowska, Z., Monier, C., Gomez Gonzalez, JF., Fregnac, Y., Bal, T. and Destexhe, A.Dynamic clamp with high resistance electrodes using active electrode compensation in vitro and in vivo. Dynamic-clamp: From Principles to Applications, Edited by Destexhe A and Bal T, Springer, new York (2009). pp. 347-382.
Brüderle et al. 2009Brüderle, D., Müller, E., Davison, A., Muller, E., Schemmel, J. and Meier, K.Establishing a novel modeling tool: A Python-based interface for a neuromorphic hardware systemFront. Neuroinform. (2009) 3:17
abstract, fulltext, BibTeX
Buesing and Maass 2009Buesing, L., and Maass, W.A Spiking Neuron as Information BottleneckNeural Computation (2010) 22(8): 1961-1992
Buesing et al. 2009Buesing, L., Schrauwen, B., and Legenstein, R. Connectivity, Dynamics, and Memory in Reservoir Computing with Binary and Analog NeuronsNeural Computation (2010) 22(5):1272-1311 abstract, fulltext
Buonomano and Maass 2009Buonomano,D., and Maass., W.State-dependent computations: Spatiotemporal processing in cortical networksNature Reviews in Neuroscience (2009) 10:113-125 fulltext
Cessac et al. 2009Cessac, B., Paugam-Moisy, H. and Viéville, T.Overview of facts and issues about neural coding by spikesJournal of Physiology-Paris (2010) 104(1-2): 5-18
Cessac et al. 2009bCessac, B., Rostro, H., Vasquez, J.C. and Viéville, T. How Gibbs distributions may naturally arise from synaptic adaptation mechanismsJ. Stat. Phys. (2009) 136 (3):565-602
Davison 2009bDavison, A.P., Brüderle, D., Kremkow, J. and Muller, E. A common language for neuronal networks in software and hardware. The Neuromorphic Engineer (2010)
abstract, fulltext
Davison et al. 2009Davison, A.P., Brüderle, D., Eppler, J., Kremkow, J., Muller, E., Pecevski, D., Perrinet, L. and Yger, P.PyNN: a common interface for neuronal network simulatorsFrontiers in Neuroinformatics (2009) 2:11
Davison et al. 2009cDavison, A.P., Hines, M. and Muller, E Trends in programming languages for neuroscience simulations.Frontiers in Neuroscience (2009) 3:3
Destexhe 2009Destexhe, A. Self-sustained asynchronous irregular states and Up/Down states in thalamic, cortical and thalamocortical networks of nonlinear integrate-and-fire neurons. J. Computational Neurosci. (2009) 27(3):493-506
abstract, fulltext
Dimova and Denham 2009Dimova, K. and Denham, M.A neurally plausible model of the dynamics of motion integration in smooth eye pursuit based on recursive Bayesian estimation.Biol Cybern. (2009) 100(3):185-201 abstract, fulltext
El Boustani et al. 2009El Boustani, S., Marre, O., Behuret, S., Baudot, P., Yger, P., Bal, T., Destexhe, A. and Fregnac, Y.Network-State Modulation of Power-Law Frequency-Scaling in Visual Cortical NeuronsPLoS Comput Biol (2009) 5(9): e1000519
Eppler 2009Eppler, J.M.PyNEST: A Python interface to NESTThe Neuromorphic Engineer (2009)
Eppler et al. 2009Eppler, J.M., Helias, M., Muller, E., Diesmann, M. and Gewaltig, M.-O.PyNEST: a convenient interface to the NEST simulatorFrontiers in Neuroinformatics (2009) 2:12
abstract, fulltext
Escobar et al. 2009Escobar, M.-J., Masson, G.S., Vieville, T. and Kornprobst, P.Action recognition using a bio-inspired feedforward spiking networkInternational Journal of Computer Vision (2009) 82: 284-301 abstract
Faugeras et al. 2009aFaugeras, O., Touboul, J. and Cessac, B.A constructive mean field analysis of multi population neural networks with random synaptic weights and stochastic inputsFront. Comput. Neurosci. (2009) 3:1 abstract
Franke et al. 2009Franke, F., Natora, M., Boucsein, C., Munk, M.H. and Obermayer, K.An online spike detection and spike classification algorithm capable of instantaneous resolution of overlapping spikesJ Comput Neurosci (2009)
Frégnac 2009Fregnac, Y., Baudot, P., Chavane, F., Marre, O., Monier, C., Pananceau, M. and Sadoc, G.Multiscale functional imaging: reconstructing network dynamics from the synaptic echoes recorded in a single visual cortex neuron.Bull Acad Natl Med. (2009) 193(4): 851-862. abstract
Haeusler et al. 2008Haeusler, S., Schuch, K. and Maass, W.Motif distribution, dynamical properties, and computational performance of two data-based cortical microcircuit templates.J. of Physiology (2009) 103(1-2):73-87 abstract
Hines et al. 2009Hines, M., Davison, A.P. and Muller, E.NEURON and PythonFrontiers in Neuroinformatics (2009) 3:1
abstract, fulltext
Johansson and Lansner 2008Johansson, C. and Lansner, A.Implementing plastic weights in neural networks using low precision arithmetic. Neurocomputing (2009) 72(4-6): 968-972
Johansson and Lansner 2009Johansson, C. and Lansner, A.Implementing plastic weights in neural networks using low precision arithmetic.Neurocomputing (2009) 72: 968-972 abstract
Klampfl et al. 2007bKlampfl, S., Legenstein, R. and Maass, W.Spiking neurons can learn to solve information bottleneck problems and to extract independent componentsNeural Comput. (2009) 21(4):911-59.
Kriener et al. 2009Kriener, B., Helias, M., Aertsen, A. and Rotter, S. Correlations in spiking neuronal networks with distance dependent connections.J Comput Neurosci (2009) 27: 177-200
abstract, fulltext
Lansner 2009Lansner, A.Associative memory models ? from cell assembly theory to biophysically detailed cortex simulations.Trends Neurosci (2009) 32: 178-186 abstract
Lévi et al. 2009Levi, T., Tomas, J., Lewis, N. and Fouillat, P.CMOS Resizing Methodology for Analog CircuitsIEEE Design and Test of Computers (2009) 26: 78-87
Long et al. 2009Long, P., Mercer, A., Begum, R., Stephens, G.J., Sihra, T.S. and Jovanovic JNNerve Terminal GABAA Receptors Activate Ca2+/Calmodulin-dependent Signaling to Inhibit Voltage-gated Ca2+ Influx and Glutamate ReleaseThe Journal of Biological Chemistry (2009) 284:8726-8737
Lucas-Meunier et al. 2009Lucas-Meunier, E., Monier, C. , Amar, M., Baux, G., Frégnac, Y. and Fossier, P.Involvement of nicotinic and muscarinic receptors in the endogenous cholinergic modulation of the balance between excitation and inhibition in the young rat visual cortex. Cerebral Cortex. (2009) 19 (10): 2411-2427. fulltext
Marre et al. 2009Marre, O., Yger, P., Davison, A.P and Frégnac, Y.Reliable recall of spontaneous activity patterns in cortical networksJ. of Neuroscience (2009) 29(46):14596-14606
Marre et al. 2009bMarre, O., El Boustani, S., Frégnac, Y. and Destexhe, A.Prediction of spatio-temporal patterns of neural activity from pairwise correlations.Physical Review Letters (2009) 102(13):138101 abstract
Marre et al. 2009cMarre, O., Yger, P., Davison, A. and Frégnac, Y. Reliable recall of spontaneous activity patterns in chaotic cortical networks. The Journal of Neuroscience (2009) 29(46):14596-14606.
Mayr et al. 2009Mayr, C. and Partzsch, J. and Schüffny, R.Transient responses of activity-dependent synapses to modulated pulse trains Neurocomputing (2009) 73(1-3): 99-105
abstract, BibTeX
Mayr et al. 2009bMayr, C. and Partzsch, J. and Schüffny, R.On the Relation Between Bursts and Dynamic Synapse Properties: a Modulation-based AnsatzComputational Intelligence and Neuroscience (2009) :ID 658474
fulltext, BibTeX
Naud09Gerstner, W. and Naud, R.How Good are Neuron Models?Science (2009) 326(5951): 379-380
abstract, fulltext
Nawrot et al. 2009Nawrot, M.P., Schnepel, P., Aertsen, A. and Boucsein, C.Precisely timed signal transmission in neocortical networks with reliable intermediate-range projectionsFrontiers in Neural Circuits (2009) 3 (1): 1-11
Nikolic et al. 2010Nikolic, D., Haeusler, S., Singer, W. and Maass, W.Distributed Fading Memory for Stimulus Properties in the Primary Visual CortexPLoS Biol (2009) 7(12): e1000260
Pecevski et al. 2009Pecevski, D., Natschläger, T. and Schuch, K. PCSIM: a parallel simulation environment for neural circuits fully integrated with Python Frontiers in Neuroinformatics (2009) 3:11 fulltext
Pospischil et al. 2009Pospischil, M., Piwkowska, Z., Bal, T. and Destexhe, A.Extracting synaptic conductances from single membrane potential tracesNeuroscience (2009) 158: 545-552 fulltext
Potjans et al. 2009Potjans, W., Morrison, A. and Diesmann, M.A spiking neural network model of an actor-critic learning agentNeural Computation (2009) 21: 301-339 abstract, fulltext
Rochefort 2009Rochefort, N.L., Buzás, P., Quenech'du, N., Koza, A., Eysel, U.T., Milleret, C. and Kisvárday, Z.F. Functional Selectivity of Interhemispheric Connections in Cat Visual CortexCerebral Cortex (2009) 19(10):2451-2465
Sandström et al. 2009Sandström, M., Lansner, A., Hellgren Kotaleski, J. and Rospars, J.-P.Modeling the response of a population of olfactory receptor neurons to an odorant." doi: 10.1007/s10827-009-0147-5J Comput Neurosci (2009) abstract, fulltext
Steimer et al. 2008Steimer, A., Maass, W. and Douglas, R.Belief-propagation in networks of spiking neuronsNeural Computation (2009) 21(9): 2502-2523
Stepanyants et al. 2009Stepanyants, A., Martinez, L. M., Ferecskó, A. S. and Kisvárday, Z. F. The fractions of short- and long-range connections in the visual cortexPNAS (USA) (2009) 106:3555-3560.
Symes and Wennekers 2009Symes, A. and Wennekers, T.Spatiotemporal dynamics in the cortical microcircuit: a modelling study of primary visual cortex layer 2/3Neural Networks (2009) 22(8): 1079-92
Wohrer and Kornprobst 2008Wohrer, A. and Kornprobst, P.Virtual Retina : A biological retina model and simulator, with contrast gain controlJ Comput Neurosci. (2009) Apr;26(2):219-49 abstract, fulltext


Destexhe and Bal 2009Destexhe, A. and Bal, T.Dynamic-Clamp: From Principles to ApplicationsEditors of the book. Springer (2009) Series in Computational Neuroscience , Vol. 1, ISBN: 978-0-387-89278-8 abstract
Masson and Ilg 2009Masson, G.S. and Ilg, U.J.Dynamics of visual motion processing: Neuronal, Behavioral, and Computational ApproachesEditors of the book. Springer (2009) ISBN: 978-1-4419-0780-6 abstract

Book chapter

Brette 2009Brette, R., Piwkowska, Z., Monier, C., Gomez, J., Frégnac, Y., Bal, T. and Destexhe, A.Dynamic clamp with high resistance electrodes using active electrode compensation in vitro and in vivoDynamic Clamp. From Principles to Applications. A. Destexhe and T. Bal editors. Springer. (2009) P. 347-382 abstract
Destexhe and Huguenard 2007Destexhe, A. and Huguenard, J.R. Modeling voltage-dependent channelsIn: Computational Modeling Methods for Neuroscientists, Edited by DeSchutter, E., MIT Press, Cambridge, USA (2009): 107-138 abstract
Destexhe and Rudolph-Lilith 2008Destexhe, A. and Rudolph-Lilith, M.Synaptic "noise": Experiments, computational consequences and methods to analyze experimental dataIn: Stochastic Processes in Neuroscience, Edited by Lord, G. and Laing, C., Oxford University Press, Oxford UK (2009). abstract
Jancke et al. 2009Jancke, D., Chavane, F. and Grinvald, A.Stimulus localization by neuronal populations within early visual cortex - Linking perception to the underlying functional architecture In: Dynamics of visual motion processing. Eds: Ilg, U.J. and Masson, G.S. Springer Verlag (2009)
Lansner et al. 2009Lansner, A., Benjaminsson, S. and Johansson, C.From ANN to biomimetic information processingBiologically Inspired Signal Processing for Chemical Sensing. S. G. Marco, Agustín, Ed, Springer. (2009) 188: 37-50. abstract
Masson et al. 2009Masson, G.S., Montagnini, A. and Ilg, U.J.When the brain meets the eye: Tracking object motionIn: Dynamics of visual motion processing. Eds: Ilg, U.J. and Masson, G.S. Springer Verlag (2009)
Piwkowska 2009 reviewPiwkowska, Z., Destexhe, A. and Bal, T.Associating living cells and computational models: from basics to present applications of the dynamic-clampDynamic Clamp. From Principles to Applications. A. Destexhe and T. Bal editors. Springer. New York. (2009) P. 1-30 abstract
Piwkowska et al. 2009Piwkowska, Z., Pospischil, M., Rudolph-Lilith, M., Bal, T. and Destexhe, A.Testing methods for synaptic conductance analysis using controlled conductance injection with dynamic clamp. Dynamic Clamp. From Principles to ApplicationsA. Destexhe and T. Bal editors. Springer. New York. (2009) P. 115-140 abstract
Sadoc et al. 2009Sadoc, G., Le Masson, G., Foutry, B., Le Franc, Y., Piwkowska, Z., Destexhe, A. and Bal, T.Recreating in vivo like activity and investigating the signal transfer capabilities of neurons: Dynamic-clamp applications using real-time NEURONDynamic-clamp: From Principles to Applications, Edited by Destexhe A and Bal T, Springer, New York,(2009). P. 287-320 abstract

Conference contribution: poster

Arduin et al. 2009Arduin, P.J., Ego-Stengel, V., Shulz, D. and Frégnac, Y. Graded control of a prosthesis by operant conditioning of single-units in rat motor cortexCongrčs FRM/IRME/ICM Interfaces Cerveau-Machine, Fondation pour la Recherche Médicale Paris VIIe, France. November 05 2009.
Bal et al. 2009Bal, T., Béhuret, S., Deleuze, C., Gomez, L., Piwkowska, Z., Wolfart, J., Debay, D., Brette, R., El Boustani, S., Marre, O., Baudot, P., Yger, P., Rudolph, M., Le Masson, G., Sadoc, G., Destexhe, A., and Frégnac, Y. Hybrid biological-artificial neuronal networks. Colloque ANR Interface Physique-Chimie-Biologie, Fréjus, France. 2009
Belhadj et al. 2009Belhadj, B., Tomas, J., Bornat, Y., Daouzli, A., Malot, O. and Renaud, S. Digital Mapping of a Realistic Spike Timing Plasticity Model for Real-time Neural SimulationsIn XXIV Conference on Design of Circuits and Integrated Systems, (DCIS 2009) Zaragoza, Spain, 2009.
Belhadj et al. 2009bBelhadj, B., Tomas, J., Bornat, Y., Malot, O. and Renaud, S. Token-passing communication protocol in hardware based real-time spiking neural networksIn Proceedings of SPIE, Bioengineered and Bioinspired Systems, Microtechnologies for the New Millenium, SPIE'09 Dresden, Germany, 2009.
Boucsein et al. 2009bBoucsein, C., Rau, F., Nawrot, M.P. and Aertsen, A.Photo-activation of neuronal tissue using a spatial light modulator (DMD)T27-4C, NWG Annual Meeting, Göttingen (2009)
Brémaud and Thomson 2009Brémaud, A. and Thomson, A. M.Complex short term dynamics in stochastic models of neocortical synaptic connectionsSociety for Neuroscience 2009: 822.19
Brüderle et al. 2009cBrüderle, D., Kremkow, J., Bauer, A., Perrinet, L.U., Aertsen, A., Masson, G.S., Meier, K. and Schemmel, J.Matching Network Dynamics Generated by a Neuromorphic Hardware System and by a Software SimulatorBernstein Conference on Computational Neurosciences (2009)
Buhry et al. 2009Buhry, L., Saďghi, S., Salem, W.B. and Renaud, S. Adjusting Neuron Models in Neuromimetic ICs using the Differential Evolution Algorithm4th International IEEE EMBS Conference on Neural Engineering, Antalya, Turkey, 29 April-2 May 2009, pp 681-684
Carelli et al. 2009Carelli, P., Pananceau, M., Kopysova, I. and Fregnac, Y. Mapping the horizontal synaptic association field with apparent motion in the cat visual cortex. American Society for Neuroscience Abstract. 35: 558.22, Chicago, USA. 2009
Daouzli et al. 2009Daouzli, A., Saďghi, S., Rudolph, M., Destexhe, A. and Renaud, S. Convergence in an Adaptive Neural Network: The Influence of Noise Inputs CorrelationIWANN'2009, Vol. 1, pp. 140-148, Salamanca, Spain, 10-12 June 2009, Springer abstract
El Boustani et al. 2009bEl Boustani, S., Yger, P., Frégnac, Y. and Destexhe, A. A mean-field based formalism to investigate structure-function correlations in sensory neocortex using VSD imaging. American Society for Neuroscience Abstract. 35: 352.19, Chicago, USA. 2009
Faugeras et al. 2009bFaugeras, O., Touboul, J. and Cessac B.A constructive mean-field analysis of multi population neural networks with random synaptic weightsCOSYNE 09 (2009)
Fournier et al. 2009Fournier, J., Monier,C., Levy, M., Pananceau, M. and Y. FrégnacControl of the "Effective" receptive field organization by the spatio-temporal statistics of the visual input.American Society for Neuroscience Abstracts, 35: 353.19. Chicago, USA. 2009
Frégnac 2009aFrégnac, Y. Complexity based computing : From Biology to Brain Models.Facets II Thinktank Meeting (Orgs. K. Meier and Y. Frégnac). Leysin. (Invited conference). 2009
Frégnac 2009bFrégnac, Y. Multi-scale analysis and complexity in sensory cortical networks.CNRS - Max Planck Gesellshaft Symposium. (Org. M. Giurfa). (Invited conference). 2009
Frégnac 2009cFrégnac, Y. Bruit, Information an Cortical Dynamics.In ?Signal and Neurons? Conférence-Débat. (Orgs. H. Korn and O. Macchi). French Academy of Sciences. (Invited Plenary conference).2009
Frégnac 2009dFrégnac, Y. 'Noise' and information propagation in sensory cognitive networks.5th Cajal Winter School. (Org. Franceso Artigas) Benasque, Spain (Invited Keynote conference). 2009
Frégnac 2009eFrégnac, Y. Stimulus-driven Coordination of Cortical Cell Assemblies and Propagation of Gestalt Belief in V1. In « Dynamic Coordination in the Brain: From Neurons to Mind », Thinktank Dahlem Konferenzen. Ernst Strüngmann Forum (Orgs. Ch. Von der Malsburg, B. Philipps and W. Singer). Aug 16-21, 2009, Frankfurt/M, Germany. 2009 (Invited position paper)
Frégnac 2009fFrégnac, Y. Concepts in dynamics of cortical sensory networks : signal, noise or chaos ? Brain Machine Interface (Org. F. Clarac). Paris, 5 Novembre 2009. (Invited conference).
Frégnac 2009gFrégnac, YReading out the neural code by listening to the synaptic echoes of the visual world in a single cell.Rare Diseases II: Hearing and Sight Loss. ESF-UB Conference in Biomedicine. (orgs. C. Petit and J-A. Sahel). Sant Feliu de Guixols (Costa Brava), Spain. 22 - 27 November 2009. (Invited Keynote conference).
Frégnac 2009hFrégnac, YIntegrative and Computational Neurosciences: interdisciplinarity of Sciences confronted to Brain Complexity. In 'Challenges for the XXIst century'. French Academy of Sciences (Invited Plenary conference). fulltext
Frégnac 2009iFrégnac, Y. Multi-scale analysis and complexity in visual cortex.In Symposium ?Organisation and Plasticity of the visual cortex " Orgs. C. Levelt and T. Pizzorusso . Scuola Normale Superiore in Pisa 18-19th May 2009. Italy. (Invited conference).
Kaplan et al. 2009Kaplan, B., Bruederle, D., Schemmel, J. and Meier, K.High-Conductance States on a Neuromorphic Hardware SystemProceedings of the 2009 International Joint Conference on Neural Networks, Atlanta, USA (2009): 2593-2599 abstract, fulltext
Karube and Kisvarday 2009Karube, F. and Kisvarday, F.Axonal distribution and functional topography of layer 6 pyramidal cells in the primary visual cortex of the cat (Area 18)Frontiers in Systems Neuroscience. Conference Abstract: 12th Meeting of the Hungarian Neuroscience Society (2009). doi: 10.3389/conf.neuro.01.2009.04.201 fulltext
Kilias et al. 2009Kilias, A., Garbers, C., Aertsen, A. and Egert, U.Finding Information in Neuronal Data: An open source framework for the analysis of neuronal activity dataG-Node Symposium on Neuroinformatics at CNS09, 22 July 2009, Berlin, Germany
Klampfl and Maass 2009Klampfl, S. and Maass, W. Replacing supervised classification learning by Slow Feature Analysis in spiking neural networksProc. of NIPS 2009, Advances in Neural Information Processing Systems (2010) 22: 988-996. MIT Press, 2010 abstract
Klampfl et al. 2009Klampfl, S., David, S. V., Yin, P., Shamma, S. A. and Maass, WIntegration of stimulus history in information conveyed by neurons in primary auditory cortex in response to tone sequences39th Annual Conference of the Society for Neuroscience, 2009
Kremkow et al 2009Kremkow, J., Perrinet, L.U., Monier, C., Frégnac, Y., Masson, G.S. and Aertsen, A.Control of the temporal interplay between excitation and inhibition by the statisitics of visual input.Annual Meeting Computational Neuroscience Society (CNS?O9). 18-23 Juillet 2009, Berlin, Germany. 2009
Kremkow et al. 2008bKremkow, J., Perrinet, L., Aertsen, A. and Masson, G.S.Functional consequences of correlated excitation and inhibition induced by feed-forward inhibitionOral presentation at Neurocomp 2008
Kremkow et al. 2009aKremkow, J., Perrinet, L., Monier, C., Frégnac, Y., Masson, G.S. and Aertsen, A.Control of the temporal interplay between excitation and inhibition by the statistics of visual inputOral presentation at Eighteenth Annual Computational Neuroscience Meeting CNS*2009
Kremkow et al. 2009bKremkow, J., Perrinet, L., Masson, G. S. and Aertsen, A.Functional consequences of correlated excitation and inhibition on single neuron integration and signal propagation through synfire chainsIn Proceedings of the 32th Göttingen Neurobiology Conference
Kremkow et al. 2009dKremkow, J., Laurent, L.U., Reynaud, A., Aertsen, A., Masson, G.S. and Chavane, F.Dynamics of cortico-cortical interactions during motion integration in early visual cortex: a spiking neural network model of an optical imaging studyAnnual Meeting Computational Neuroscience Society (2009)
Legenstein et al. 2009Legenstein, R., Maass, W., Chase, S.M. and Schwartz, A.B.Functional network reorganization in motor cortex can be explained by reward-modulated Hebbian learningProc. of NIPS 2009: Advances in Neural Information Processing Systems (2009) 22: 1105-1113 abstract
Levy et al. 2009Levy, M., Truchard, A., Sadoc, G., Ohzawa, I., Fregnac, Y. and Freeman, R.Dynamics of nonlinear suppression in Cat V1 Simple cells.American Society for Neuroscience Abstracts 35: 353.10. Chicago, USA. 2009
Levy et al. 2009bLevy, M., Truchard, A., Sadoc, G., Ohzawa, I., Fregnac, Y. and Freeman, R.Dynamics of nonlinear suppression in Cat V1 Simple cells.Annual Meeting Computational Neuroscience Society (CNS'O9). 18-23 Juillet 2009, Berlin, Germany. 2009
Liebe et al. 2009Liebe, S., Hoerzer, G., Logothetis, N.K., Maass, W. and Rainer, G.Long range coupling between V4 and PF in theta band during visual short-term memory39th Annual Conference of the Society for Neuroscience, 2009
Nessler et al. 2009Nessler, B., Pfeiffer, M. and Maass, W. STDP enables spiking neurons to detect hidden causes of their inputsNIPS 2009 abstract
Partzsch and Schüffny 2009Partzsch, J. and Schüffny, R.On the routing complexity of neural network models - Rent's Rule revisitedESANN (2009): 595-600 abstract
Pecevski et al. 2009bPecevski, D., Natschläger, T. and Schuch, K.PCSIM: A Parallel Simulation Environment for Neural Circuits Fully Integrated with Python39th Annual Conference of the Society for Neuroscience, 2009
Perrinet and Masson 2009Perrinet, L.U. and Masson, G.S.Decoding the population dynamics underlying ocular following response using a probabilistic frameworkEighteenth Annual Computational Neuroscience Meeting (2009) Chicago
Perrinet et al. 2009Perrinet, L., Voges, N., Kremkow, J. and Masson, G.S.SDecoding center-surround interactions in population of neurons for the ocular following responseProceedings of COSYNE Conference (2009)
Reynaud et al. 2009Reynaud, A., Masson, G.S. and Chavane, F.Cortical origin of contrast response function contextual modulation in V1 population activity measured with voltage-sensitive dye imagingJournal of Vision (2009) 9(8):749, 749a.VSS, Naples FL.
Rostro-Gonzalez et al. 2009Rostro-Gonzalez, H., Cessac, B., Vasquez, J.C. and Viéville, T.Back-engineering of spiking neural networks parametersPoster at Eighteenth Annual Computational Neuroscience Meeting: CNS*2009 Berlin, Germany. 18-23 July 2009
Roux et al. 2009Roux, S., Suchanek, D., Aertsen, A. and Boucsein, C. Visual evoked activity in V1 of anesthetized rats: from gratings to natural imagesNWG Annual Meeting (Göttingen) (2009), T16-9C
Roux et al. 2009aRoux, S., Suchanek, D., Aertsen, A. and Boucsein, C. Visual evoked activity in V1 of anesthetized ratsSFN Annual Meeting (Chicago) (2009), abstr. 353
Sari et al. 2009Sari, K., Fuyuki, K., Fournier, J., Cyril, M., Fregnac, Y. and Kisvarday, Z.A combined approach to unravel single cell function using complex visual stimuli, intracellular staining and intrinsic signal optical imaging in the cat primary visual cortex Frontiers in Systems Neuroscience. Conference Abstract: 12th Meeting of the Hungarian Neuroscience Society (2009). doi: 10.3389/conf.neuro.01.2009.04.202 fulltext
Schemmel 2009Schemmel, J.VLSI Implementations of Very Large Scale Neuromorphic Circuitstalk on the ESSCIRC/BIECS 09, Athens, Greek fulltext
Schrauwen et al 2009Schrauwen, B., Buesing, L. and Legenstein, R.On Computational Power and the Order-Chaos Phase Transition in Reservoir ComputingIn Proc. of NIPS 2008, Advances in Neural Information Processing Systems, volume 20. MIT Press, 2009 fulltext
Vasquez et al. 2009Vasquez, J. C., Cessac, B., Rostro-Gonzalez, H. and Viéville, T. How Gibbs Distributions may naturally arise from synaptic adaptation mechanismCNS (2009), Berlin
Viéville and Cessac 2009Viéville, T. and Cessac, B. Parametric Estimation of spike train statisticsCNS 09 Berlin
Yavuz et al.Yavuz, E., Monier, C., and Frégnac, Y. Blind Signal Separation Methods for VSDIOral Presentation for FACETS Workshop « Macroscopic Aspects of Neuronal Activity: VSD, LFP and Macroscopic Models ». Marseille/France November 30, 2009.
Yger et al. 2009Yger, P., El Boustani, S., Frégnac, Y. and Destexhe, A. A mean-field based formalism for modeling and analysis of voltage-sensitive dye imaging data. American Society For Neurosciences (SFN), 35: Chicago, USA. 2009
Yger et al. 2009Yger, P., El Boustani, S., Marre, O., Davison, A.P., Destexhe, A. and Frégnac, Y.Spatial organization of evoked neuronal dynamics in 2D recurrent networks, with or without structured stimulation.Eighteenth Annual Computational Neuroscience Meeting CNS (2009) 10: 94 abstract
Yger et al. 2009bYger, P., Brüderle, D., Eppler, J., Kremkow, J., Pecebski, D., Perrinet, L., Schmucker, M., Muller, E. and Davison, A.NeuralEnsemble: Towards a meta-environment for network modeling and data analysisIn Proceedings of the 32th Göttingen Neurobiology Conference

Web publication

Chossat and Faugeras 2009Chossat, P. and Faugeras, O.Hyperbolic planforms in relation to visual edges and textures perception fulltext


Brüderle 2009Brüderle, D.Neuroscientific Modeling with a Mixed-Signal VLSI Hardware SystemPh.D. thesis at the University of Heidelberg (2009) fulltext
Cessac 2009Cessac, B.Neural Networks as dynamical systemsarXiv:0901.2203v2 abstract, fulltext
Friedmann 2009Simon FriedmannExtending a Hardware Neural Network Beyond Chip BoundariesDiploma thesis (English), University of Heidelberg (2009) HD-KIP 09-41 fulltext
Kremkow 2009Kremkow, J.Correlating excitation and inhibition in visual cortical circuits: Functional consequences and biological feasibilityPhD thesis (2009) Université de la Méditerranée and Albert-Ludwigs-Universitat, Freiburg.
Wohrer et al. 2009Wohrer, A., Kornprobst, P. and Antonini, M.Retinal filtering and image reconstructionINRIA Research Report 6960 (2009)


3 August 2011