Publications by subject

Recent papers

Dynamic Synapses

Model Neurons

Recurrent Networks

Independent Component Analysis

Unsupervised learning

Statistics of natural images

Dynamics of receptive fields

Information Theory

Cellular Automata

Neural Networks

Statistical Physics

Particle Physics



Recent papers

• S. Sarno, V. de Lafuente, R. Romo and N. Parga
  Dopamine reward prediction error signal codes the temporal evaluation of a perceptual decision report
  Proceedings of the National Academy of Sciences 114; E10494–E10503, 2017.
  

• R. Rossi-Pool, E. Salinas, A. Zainos, M. Alvarez, J. Vergara, N. Parga and R. Romo
  Emergence of an abstract categorical code enabling the discrimination of temporally structured tactile stimuli
  Proceedings of the National Academy of Sciences, 113(49), E7966–E7975, 2016.
  

• F. Carnevale, V. de Lafuente, R. Romo, O. Barak and N. Parga
  Dynamic control of response criterion in premotor cortex during perceptual detection under temporal uncertainty
  Neuron 86; 1067–1077, 2015.
  

• F. Carnevale, V. de Lafuente, R. Romo and N. Parga
  An optimal decision population code that accounts for correlated variability unambiguously predicts a subject’s choice
  Neuron 80; 1532–1543, 2013.
  

• N. Parga
  Towards a self-consistent description of irregular and asynchronous cortical activity
  J. Statistical Physics P03010: 1742-5468, 2013.
  

• F. Carnevale, V. de Lafuente, R. Romo and N. Parga
  Internal signal correlates neural populations and biases perceptual decision reports
  Proceedings of the National Academy of Sciences 109; 18938–18943, 2012.
  

• A. Renart, J. de la Rocha, P. Bartho, L. Hollender, N. Parga, A. Reyes and K. Harris
  The asynchronous state in cortical circuits
  Science 327: 587-590, 2010.
  

• R. Moreno-Bote and N. Parga
  Response of integrate-and-fire neurons to noisy inputs filtered by synapses
  with arbitrary timescales: firing rate and correlations
  Neural Computation 22: 1528-1572, 2010.
  Supplementary Material
  

• J. de la Rocha and N. Parga
  Thalamocortical Transformations of periodic stimuli: The effect of Stimulus Velocity
  and Synaptic Short-Term Depression in the Vibrissa-Barrel System.
  J. Computational Neuroscience 25(1): 122-140, 2008.
  

• R. Moreno-Bote, A. Renart and N. Parga
  Theory of input spike auto- and cross-correlations and their effect on the response of spiking neurons
  Neural Computation 20: 1651-1705, 2008.
  

• N. Parga and L.F. Abbott
  Network model of spontaneous activity exhibiting synchronous transitions between up and down states
  Frontiers in Neuroscience 1: 57-66, 2007.
  

• A. Renart, R. Moreno-Bote, X-J Wang and N. Parga
  Mean-driven and fluctuation-driven persistent activity in recurrent networks
  Neural Computation 19: 1-46, 2007.
  
  
  

  Recent abstracts

  • A. Renart, J. de la Rocha, L. Hollender, B. Haider, A. Duque, D. McCormick, N. Parga, A.D. Reyes and K.D. Harris
    The asynchronous state in the cerebral cortex
    Computational and Systems Neuroscience 2009 (COSYNE),
    (Salk Lake City. Feb. 26 - March 1, 2009).
    

  • N. Parga, J.M. Delgado and A. Turiel
    From the scale invariant properties of natural visual stimuli to the receptive fields of simple cells
    Sensory coding and the natural environment.
    Gondon Research Conference
    (Il Ciocco, Lucca, Barga, Italy. July 27 - Aug. 1, 2008).
    

  • A. Renart, J. de la Rocha, N. Parga, A.D.Reyes and K.D. Harris
    The dynamics of pair-wise correlations lead to asynchronous states in recurrent densely-connected balanced cortical networks: I Theory.
    38th Annual Meeting of the Society for Neuroscience
    (Washington DC. November, 2008).
    Society for Neuroscience Abstracts
    

  • J. de la Rocha, A. Renart, N. Parga, K.D. Harris and A.D. Reyes
    The dynamics of pair-wise correlations lead to asynchronous states in recurrent densely-connected balanced cortical networks: II Numerical analysis and experiments.
    38th Annual Meeting of the Society for Neuroscience
    (Washington DC. November, 2008).
    Society for Neuroscience Abstracts
    

  • N. Parga
    Network model of low frequency oscillations exhibiting synchronous transitions between up and down states
    Noise in Life 2007: Stochastic dynamics in the Neurosciences.
    Max-Plank-Institute für Physik Komplexer Systeme
    (Dresden, Germany. November 7-9, 2007).
    

  • N. Parga
    Synchronous transitions between up and down states in a network model of spontaneous activity
    Mathematical Neuroscience Workshop.
    Centre de Recherche Mathematique, Univ de Montreal
    (Montreal, Canada. Sept 16-19, 2007).
    

  • R. Moreno-Bote and N. Parga
    Theory of spike correlations: a formal description of input and output correlations in spiking neurons
    16th Computational Neuroscience Meeting
    (Toronto, Canada. July 8-12, 2007).
    

Dynamic Synapses

• N. Parga, J. de la Rocha and A. Nevado
  Information transmition of correlated spike trains through stochastic synapses with short-term depression.
  31th Annual Meeting of the Society for Neuroscience (San Diego. December, 2001),
  Society for Neuroscience Abstracts 27.
  

• de la Rocha J., Nevado A. and Parga N
  Information transmission by stochastic synapses with short-term depression: neural coding and optimization
  Neurocomputing 44-46: 85-90 , 2002.

• J. de la Rocha, R. Moreno-Bote and N. Parga
  Correlations shape the response of a neuron with short-term plasticity
  Neurocomputing 58-60: 313-319, 2004.

• J. de la Rocha and N. Parga
  Short-term synaptic depression causes a non-monotonic response to correlated stimuli
  The Journal of Neuroscience 25(37): 8416-8431, 2005.
  

• J. de la Rocha and N. Parga
  Thalamocortical Transformations of periodic stimuli: The effect of Stimulus Velocity
  and Synaptic Short-Term Depression in the Vibrissa-Barrel System.
  J. Computational Neuroscience 25:1, 2008
  

Model Neurons

• R. Moreno, J. de la Rocha, A. Renart and N. Parga
  Mean firing rate and CV of a leaky IF neuron with exponentially correlated input
  "Tenth Annual Computational Neuroscience Meeting" (CNS2001. San Francisco -
  Pacific Grove. June 30 - July 5, 2001)
  Abstract, CNS2001
  

• R. Moreno and N. Parga
  Firing rate for a generic integrate-and-fire neuron with exponentially correlated input
  Lecture Notes in Computer Science, vol 2415: 223-228.
  Ed. J.R. Dorronsoro. Springer Verlag, Berlin-Heidelberg, 2002.
  

• R. Moreno, J. de la Rocha and N. Parga
  Response of a leaky integrate-and-fire neuron when stimulated with synapses showing short-term depression.
  32th Annual Meeting of the Society for Neuroscience (Orlando. November 2-7, 2002).
  Society for Neuroscience Abstracts 28: 752.6
  

• R. Moreno, J. de la Rocha J., A. Renart and N. Parga
  Response of Spiking Neurons to Correlated Inputs
  Physical Review Letters 89(28), 288101, 31 December 2002.
  

• R. Moreno-Bote and N. Parga
  Response of a leaky integrate-and-fire neuron to white noise input filtered by synapses with an arbitrary time constant
  Neurocomputing 58-60: 197-202, 2004.

• R. Moreno-Bote and N. Parga
  Role of synaptic filtering on the firing response of simple model neurons
  Physical Review Letters 92(2), 028102, 2004.
  

• R. Moreno-Bote and N. Parga
  Simple model neurons with AMPA and NMDA filters. The role of the synaptic time scales
  Neurocomputing 65-66: 441-448, 2005.

• R. Moreno-Bote and N. Parga
  Membrane potential and response properties of populations of cortical neurons in the high conductance state
  Physical Review Letters 94: 088103, 2005.
  

• R. Moreno-Bote and N. Parga
  Auto- and Cross-correlograms for the spike response of LIF neurons with slow synapses
  Physical Review Letters 96: 028101, 2006.
  

• R. Moreno-Bote, A. Renart and N. Parga
  Theory of input spike auto- and cross-correlations and their effect on the response of spiking neurons
  Neural Computation 20: 1651-1705, 2008.
  

Recurrent Networks

• Parga N. and Rolls E.
  Transform invariant recognition by association in a recurrent network
  Neural Computation 10:1507-1525, 1998 .

• Renart A., Parga N. and Rolls E. T.
  Backprojections in the cerebral cortex: implications for memory storage
  Neural Computation 11 (6): 1349-1388, 1999.

• Renart A., Parga N. and Rolls E. T.
  Associative memory properties of multiple cortical modules
  NETWORK 10: 237-255, 1999.

• Elliffe M.C.M., Rolls E.T., Parga N. and Renart A.
  A recurrent network of transformation invariance by association
  Neural Networks, 13(2): 225-237, 2000.

• Renart A., Parga N. and E.T. Rolls
  Connected cortical recurrent networks
  Proceedings of the
  5th INTERNATIONAL WORK-CONFERENCE ON ARTIFICIAL AND
  NATURAL NEURAL NETWORKS (IWANN '99) vol I, pp. 163 - 170 (Alicante. June 2-4, 1999).
  Eds. J. Mira and J.V. Sanchez-Andres. Lecture Notes in Computer Science, Springer Verlag

• Renart A., Parga N. and E.T. Rolls
  A recurrent model of the interaction between PF and IT
  cortex in delay memory tasks
  "Advances in Neural Information Processing Systems 12", (NIPS99), pp. 171-177.
  Eds. S. Solla, T. Leen and K-R Mueller. Cambridge, MA: MIT Press (2000)
  

• Renart A., Moreno R., de la Rocha J., Parga N. and E.T. Rolls
  A model of the IT-PF network in object working memory
  which includes balanced persistent activity and tuned inhibition
  Neurocomputing 38-40: 1525-1531 , 2001.
  

• Renart A., Parga N. and E.T. Rolls
  A model of the interaction between infero-temporal
  and pre-frontal cortex in object memory and visual search tasks.
  30th Annual Meeting of the Society for Neuroscience (New Orleans, November 4 - 9, 2000),
  Society for Neuroscience Abstracts 26; 201.11, pp. 547.
  

• A. Renart, R. Moreno, X-J Wang and N. Parga
  Balanced persistent activity in recurrent network models of working memory.
  32th Annual Meeting of the Society for Neuroscience (Orlando. November 2-7, 2002).
  Society for Neuroscience Abstracts 28: 187.2
  

• A. Renart, R. Moreno-Bote, X-J Wang and N. Parga
  Mean-driven and fluctuation-driven persistent activity in recurrent networks
  Neural Computation 19: 1-46, 2007.
  

Independent Component Analysis

• Nadal J.-P. and Parga N.
  Nonlinear neurons in the low-noise limit: a factorial code maximizes information transfer
  NETWORK 5: 565-581, 1994.

• Nadal J.-P. and Parga N.
  Redundancy Reduction and Independent Component Analysis:
  Conditions on Cumulants and Adaptive Approaches
  Neural Computation 9:1421-1456, 1997.

• Nadal J.-P. and Parga N.
  I.C.A.: conditions on cumulants and information theoretic approach
  Proceedings of ESANN97, 1997 (Bruges, Belgium).
  Eds.

• Nadal J.-P. and Parga N.
  Analyse en composantes indépendantes et séparation de sources :
  approches basées sur la théorie de l'information et recherche de conditions minimales (in french)
  Proceedings of ``SEIZIÈME COLLOQUE GRETSI SUR LE TRAITEMENT DU SIGNAL ET DES IMAGES''
  (GRETSI'97) (Grenoble, France. September 15 - 19, 1997).
  Eds.

• Nadal J.-P. and Parga N.
  Sensory coding: information maximization and redundancy reduction
  Proceedings of the ``SUMMER SCHOOL on NEURONAL INFORMATION PROCESSING:
  FROM BIOLOGICAL DATA TO MODELLING AND APPLICATIONS''
  (Cargese, Corse du Sud, France. June 30 - July 12, 1997)
  Eds. G. Burdet, P. Combe and O. Parodi. World Scientific, Series in Mathematical Biology and Medicine, Vol. 7 (1999), pp 164-171.

• Nadal J.-P. and Parga N.
  Neural codes and Independent Component Analysis: information theoretic approach and conditions on cumulants
  Proceedings of TAINN'97
  (Ankara, Turkey. May, 1997)
  Eds.

• Nadal J.-P., Brunel N. and Parga N.
  Nonlinear feedforward networks with stochastic ouputs:
  infomax implies redundancy reduction
  NETWORK 9: 1-11, 1998.

• Parga N. and Nadal J.-P.
  Blind source separation with time dependent mixtures
  Signal Processing 80 (10), 2000.

• Turiel A. and Parga N.
  Wavelet based decomposition of natural images in independent resolution levels.
  Proceedings of the "Intl Workshop on INDEPENDENT COMPONENT ANALYSIS and BLIND SIGNAL SEPARATION"
  (Helsinki, Finland, 9-22 June, 2000).

Unsupervised learning

• Nadal J.-P. and Parga N.
  Duality between learning machines: a bridge between supervised and unsupervised learning
  Neural Computation 6: 489-506, 1992.

• Del Giudice P., Campa A., Parga N. and Nadal J.-P.
  Maximization of mutual information in a linear noisy network: a detailed study
  NETWORK 6:449-468, 1995.

• Del Giudice P., Campa A., Parga N. and Nadal J.-P.
  Neural Networks as Optimal Information Processors
  Intl. Journal of Mod. Phys. C5:885-862, 1994.

• Campa A., Del Giudice P. and Parga N.
  Noisy Information Transmission: A Stability Analysis
  Proceedings of the "Third Workshop on Neural Networks: from Biology to High Energy Physics", 1994 (Elba, Italy).
  Intl. Journal of Neural Systems, Supplement 1995, pp 147-152

• Del Giudice P., Campa A., Parga N. and Nadal J.-P.
  Mutual Information in a Linear Noisy Network
  Proceedings of the 1995 IEEE Workshop: "Neural Networks for Signal Processing V".
  Eds. F. Girosi, J. Makhoul, E. Manolakos and E. Wilson. pp. 181

• Nadal J.-P. and Parga N.
  Information transmission by networks of non linear neurons
  Proceedings of the "Third Workshop on Neural Networks: from Biology to High Energy Physics", 1994 (Elba, Italy).
  Intl. Journal of Neural Systems, Supplement 1995, pp. 153-157

Statistics of natural images

• Turiel A., Mato G., Parga N. and Nadal J.-P.
  The self-similarity properties of natural images resemble those of turbulent flows
  Phys. Rev. Lett., 80: 1098-1101, 1998.

• Turiel A., Mato G., Parga N. and Nadal J.-P.
  Self-similarity properties of natural images
  NIPS97 (Denver. Dec 1 - Dec 6, 1997).
  Eds. Michael I. Jordan, Michael J. Kearns, and Sara A. Solla, Cambridge, MA: MIT Press (1998)

• Turiel A. and Parga N.
  The multifractal structure of contrast changes in natural images: from sharp edges to textures
  Neural Computation 12: 853-883, 2000.

• Turiel A., Parga N., Ruderman D.L. and Cronin T.W.
  Multiscaling and information content of natural color images
  Physical Review E62: 1138-1148, 2000.

• Nevado A., Turiel A. and Parga N.
  Scene dependence of the non-gaussian scaling properties of natural images
  Network 11 (2):131-152, 2000.

• Turiel A. and Parga N.
  The multifractal wavelet filter of natural images
  Physical Review Letters 85: 3325-3328, 2000.

• Turiel A. and Parga N.
  Wavelet based decomposition of natural images in independent resolution levels.
  Proceedings of the "Intl Workshop on INDEPENDENT COMPONENT ANALYSIS and BLIND SIGNAL SEPARATION"
  (Helsinki, Finland, 9-22 June, 2000).

• A. Turiel, J-P. Nadal and N. Parga
  An algorithm for image representation as independent levels of resolution
  Lecture Notes in Computer Science, vol 2415: 1213-1218.
  Ed. J.R. Dorronsoro. Springer Verlag, Berlin-Heidelberg, 2002.
  

• N. Parga, J. M. Delgado and A. Turiel
  A model for learning optimal filters in the representation of visual scenes.
  32th Annual Meeting of the Society for Neuroscience (Orlando. November 2-7, 2002).
  Society for Neuroscience Abstracts 28: 260.19
  

• N. Parga, J. M. Delgado and A. Turiel
  Predicting Receptive Fields in V1 from Natural Scene Properties.
  33th Annual Meeting of the Society for Neuroscience
  (New Orleans. November 8-12, 2003).
  Society for Neuroscience Abstracts 29

• A. Turiel, J.-P. Nadal and N. Parga
  Orientational minimal redundancy wavelets: from edge detection to perception
  Vision Research 43: 1061-1079 , 2003

• A. Turiel, J.M. Delgado and N. Parga
  Learning efficient internal representations from natural image collections
  Neurocomputing 58-60: 915-921, 2004.

• Turiel and N. Parga
  Role of statistical symmetries in sensory coding: an optimal scale invariant code for vision
  Journal of Physiology - Paris 97(4-6): 491-502 , 2004

Dynamics of receptive fields

• Mato G. and Parga N.
  Dynamic changes in receptive fields induced by cortical reorganization
  In: "Information Theory and the Brain".
  Eds. Baddeley R., Hancock P. and Foldiak P.
  Cambridge University Press, 2000, pp. 122:138.

Information Theory

• Nadal J.-P. and Parga N.
  Information processing by a perceptron in an unsupervised learning task
  NETWORK 4: 295-312, 1993.

• Nadal J.-P. and Parga N.
  Information Processing by a Perceptron
  Proceedings of the "Second Workshop on Neural Networks: from Biology to High Energy Physics", 1992 (Elba, Italy).
  International Journal of Neural Systems, Supplement 1993, pp 41-50

• Korutcheva E., Parga N. and Nadal J.-P.
  Information processing by a noisy binary channel
  NETWORK, 8:405, 1997.

• Turiel A., Korutcheva E. and Parga N.
  The mutual information of a stochastic binary channel: the validity of the replica symmetric ansatz
  Journal of Physics A 32 (10): 1875-1894, 1999

• Dominguez D.R.C., Maravall JM., Turiel A., Ciria C., and Parga N.
  Numerical simulation of a binary communication channel:
  comparison between a replica calculation and an exact solution
  Europhysics Letters 45 (6)739-744, 1999.

Neural Networks

• N. Parga and M.A. Virasoro
  The ultrametric organization of memories in a neural network
  Journal de Physique 47: 1857, 1986.

• N. Parga
  Neural Networks as Models of Associative Memories
  Computer Physics Comm. 55: 77, 1989.

• N. Parga
  Spin Glasses and Neural Networks
  Nuclear Physics B (Proc. Suppl.) 10A: 332, 1989.

• G. Mato and N. Parga
  Generalization properties of multilayered neural networks
  Journal of Physics A25: 5047, 1992.

• G. Mato and N. Parga
  Sequences in Neural Networks with Temporal Association
  Zeitschrift für Physik B84: 483, 1991.

• G. Mato, C. Moukarzel and N. Parga
  Optimal storage capacity of double-layered neural networks
  "Neural Networks: from Biology to High Energy Physics", pp. 39
  Eds. O. Benhar, C. Bosio, P. del Giudice and E. Tabet; ETS editrice Pisa, 1991.

• S. Bacci, G. Mato and N. Parga
  Dynamics of a neural network with hierarchically stored patterns
  Journal of Physics A23: 1801, 1990.

• S. Bacci, J. Alfaro, C. Wiecko and N. Parga
  Numerical analysis of a neural network with hierarchically organized patterns
  Journal de Physique 50: 757, 1989.

Cellular Automata

• E. Miranda and N. Parga
  Ultrametricity in the Kauffman Model: a Numerical Test
  Journal of Physics A21: L357, 1988.

• E. Miranda and N. Parga
  Noise effects in the Kauffman model
  Europhysics Letters 10: 293, 1989.

• E. Miranda and N. Parga
  On the use of spin-glass concepts in random automata networks
  Europhysics Letters 6: 297, 1988.

• C. Moukarzel and N. Parga
  On the evaluation of magnetisation fluctuations with Q2R cellular automata
  Journal of Physics A22: 943, 1989.

• C. Moukarzel and N. Parga
  Q2R simulations of two-dimensional spin glasses
  Journal of Physics A25: 765, 1992.

Statistical Physics

• N. Parga, G. Parisi and M. Virasoro
  A numerical investigation of the overlap distribution among pure states in the spin-glass phase
  Journal de Physique Lettres 45: L1063, 1984.

• N. Parga and H. Van Himbergen
  Renormalization group studies of phase diagrams of Ising and XY-model films of variable thickness
  Annals of Physics 134: 286, 1981.

• N. Parga and H. Van Himbergen
  Critical behavior of the double layer classical XY model
  Solid State Communications 35: 607, 1980.

• J. Cardy and N. Parga
  On the jump in the superfluid density of helium film
  Journal of Physics C13: 571, 1980.

• J. Cardy and N. Parga
  Renormalization group for the transfer matrix
  Journal of Physics A15: L115, 1982.

• N. Parga and G. Parisi
  On the locally stable states of the Sherrington-Kirkpatrick model
  ICTP-preprint, Trieste, IC/85/133, 1985.

• C. Moukarzel and N. Parga
  On the evaluation of magnetisation fluctuations with Q2R cellular automata
  Journal of Physics A22: 943, 1989.

• C. Moukarzel and N. Parga
  Q2R simulations of two-dimensional spin glasses
  Journal of Physics A25: 765, 1992.

• R. Jengo and N. Parga
  Stochastic quantization and mean field approximations
  Physics Letters B134: 221, 1984.
  

• J. Alfaro, R. Jengo and N. Parga
  Evaluation of critical exponents based on stochastic quantization
  Physical Review Letters 54: 369, 1985.
  

• N. Parga
  Overlap distributions and taxonomy analysis of spin glass states with equal weights
  Journal de Physique 48: 499, 1987.
  

• S. Bacci and N. Parga
  Ultrametricity, Frustration and the Graph Coloring Problem
  Journal of Physics A22: 3023, 1989.
  

• C. Moukarzel and N. Parga
  The REM zeros in the complex temperature and magnetic field planes
  Physica A185: 305, 1992.
  

Particle Physics

• M.B. Gavela and N. Parga
  Ward identities and chiral anomalies in stochastic quantization
  Nuclear Physics B275 [FS17]: 546, 1986.
  

• M.B. Gavela and N. Parga
  Ward identities and physical interpretation of anomalies in stochastic quantization
  Physics Letters B174: 319, 1986.
  

• N. Parga, A. Schwimmer and E. Rabinovici
  Patterns of two-dimensional supersymmetry breaking. A Monte-Carlo study
  Nuclear Physics B255: 383, 1985.
  

• G. Aldazabal, E. Dagotto, A. González-Arroyo and N. Parga
  Wilson loop Langevin equations for U(1) lattice gauge theory
  Physics Letters 125B: 305, 1983.
  

• G. Aldazabal, A. González-Arroyo and N. Parga
  The stochastic quantization of U(N) and SU(N) lattice gauge theory and Langevin equations for the Wilson loops
  Journal of Physics A18: 2975, 1985.
  

• G. Aldazabal, N. Parga, A. González-Arroyo and M. Okawa
  Large N reduced models and stochastic quantization
  Physics Letters 129B: 90, 1983.
  

• N. Parga
  Finite temperature behavior of topological excitations in lattice compact QED
  Physics Letters 107B: 442, 1982.
  

• N. Parga, D. Toussaint and J.R.Fulco
  Strong-coupling expansion in the large-N limit
  Physical Review D20: 887, 1979.
  

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