Publications in Computational Neuroscience
1- D. Hansel and H. Sompolinsky (1990).
Learning from examples in a single layer neural network.
Europhysics Letters, 11:677.
2- E. Barkai, D. Hansel and I. Kanter (1990).
Statistical mechanics of a multilayer perceptron. Physical Review Letters, 65:2312.
3- E. Barkai, D. Hansel and H. Sompolinsky (1990).
Broken symmetries inmultilayered perceptrons. Physical
Review A, 45:4146.
4- D. Hansel, G. Mato and C. Meunier (1992). Memorization without
generalization in a multilayered neural
network. Europhys. Lett., 20:471.
5- D. Selingson, M. Griniasty, D. Hansel and N. Shoresh (1992).
Computing with a difference neuron. Network, 3:187.
6- D. Golomb, D. Hansel, B. Shraiman and
H. Sompolinsky (1992).
Clustering in globally coupled phase
oscillators. Physical Review A, 45:3516
7- D. Hansel and H. Sompolinsky (1993).
A solvable model of
spatiotemporal chaos. Phys. Rev. Letters, 71:2710.
8- D. Hansel, G. Mato and C. Meunier (1993).
Clustering and slow switching
in globally coupled phase oscillators. Phys. Rev. E, 48:3470.
9- D. Hansel and G. Mato (1993).
Patterns of synchrony of a Hodgkin-Huxley
neural network at weak coupling Physica A, 200:662.
10- D. Hansel, G. Mato and C. Meunier (1993).
Phase dynamics for weakly coupled Hodgkin-Huxley neurons.
Europhysics Letters, 23:367.
11- D. Hansel, G. Mato and C. Meunier (1993).
Phase reduction and neural modeling.
Concepts Neurosci. 4:192.
12- D. Hansel, G. Mato and C. Meunier (1995).
Synchronization in excitatory neural networks.
Neural Computation 7: 307
13- D. Hansel (1996).
Synchronized chaos in local cortical
circuits. Int. J. of Neur. Systems 7: 403.
14- H. Bergman, A. Raz, A. Feingold, A. Nini, I. Nelken,
D. Hansel, H. Ben-Pazi et A. Reches.
Physiology of MPTP Tremor (1998)
Movement Disorders 13:32.
15- Hansel, D. and Sompolinsky, H. (1998).
Modeling Feature Selectivity in Local Cortical Circuits. In
Methods in Neuronal Modeling: From Synapse to Networks.
Koch, C. and Segev, I. Eds. (MIT Press, Cambridge, MA, 1998), Chapter 13, second edition.
introduction (ps file)
16- Ben-Yishai, R., Hansel, D. and Sompolinsky, H. (1997).
Traveling Waves and the Processing of Weakly Tuned Inputs in a
Cortical Network Model.J. Comp. Neurosci. 4, 57-79.
17- Hansel, D. and Sompolinsky, H. (1996).
Chaos and Synchrony in a Model of a Hypercolumn in Visual Cortex.
J. Comp. Neurosci. 3:7-34
18- Hansel, D. and Sompolinsky, H. (1992).
Synchronization and computation in a chaotic neural network.
Physical Review Letters, 68:718.
19- D. Hansel, G. Mato, C. Meunier and L. Neltner (1998).
On numerical simulations of integrate-and-fire neural networks.
Neural Computation, 10:467.
20- D. Hansel and D. Golomb (2000).
The number of synaptic input and the synchrony of large sparse neural
networks. Neural Computation, in press.
21- L. Neltner, D. Hansel, G. Mato and C. Meunier (2000).
Synchrony in heterogeneous neural networks
Neural Computation, in press.
all figures for this paper
22- O. Shriki, H. Sompolinsky and D. Hansel (1999).
Modeling neuronal networks in cortex by rate
models using the frequency-current response properties of
cortical cells submitted.
23- C. van Vreeswijk and D. Hansel (2000)
Patterns of synchrony in neural networks with spike adaptation.
submitted.
all figures for this paper
Abstracts
1- M.L. Monnet, D. Hansel, G. Mato et C. Meunier (1995)
Des proprétés cellulaires aux propriétés collectives
des réseaux ; 2ieme Colloque de la Société
des Neurosciences, Lyon.
2- J. Goldberg, D. Hansel, and C. van Vreeswijk (1996)
Israel J. of Med. Sci. 32:S22.
The role of adaptation in synchrony and rhythmogenesis.
3-D. Hansel, {\it Etats collectifs des grands syst\`emes
de neurones: synchronisme, fluctuations, correlations}; 2ieme
Colloque de la Soci\'et\'e des Neurosciences, Lyon, (1995).
4- L. Neltner, D. Hansel, G. Mato and C. Meunier (1997).
Recurrent excitatory and inhibitory interactions in neural synchronization
Neural Coding 97, (Versailles).
5- D. Golomb et D. Hansel (1998). Synchrony of large sparse
neuronal networks, Workshop on Computational Neuroscience,
(IMA, Minneapolis, USA).
6- D.Golomb and D. Hansel (1998). Synchrony in sparse
inhibitory cortical neuronal networks,Soc. Neurosci.
7- D. Hansel (1995). Chaos and synchrony in a model
of hypercolumn in visual cortex ; Cortical dynamics in Jerusalem.
8- R. Ben-Yishai, D. Hansel and H. Sompolinsky (1995).
Traveling waves and coding of movement in a cortical
network module . Proceedings of the annual meeting of
the Israel Society for Neurosciences Israel J.
31: 772.
9- H. Sompolinsky, D. Hansel and R. Ben-Yshai (1996).
Recurrent networks and sensory processing in visual cortea
National Institute of Health, Bethesda, USA.
10- D. Hansel (1997). The role of spike adaptation in shaping
spatio-temporal patterns of neural activity SIAM conference on
Aplication of Dynamical Systems.
11- D. Hansel (1998). Spatio-temporal patterns
of neural activity in large networks of neurons with
spike adaptation neuronal networks
Workshop on Computational Neuroscience, Institute
of Applied Mathematics, (Minneapolis, USA).
12- D. Hansel (1997).
The role of adaptation in shaping spatiotemporal activity patterns in cortex
Neural Coding 97, (Versailles).
13- O. Shriki, D. Hansel and H. Sompolinsky (1998).
Modeling neuronal networks in cortex
by rate models using the current-frequency response properties of
cortical cells, Soc. Neurosci.
14- D. Hansel, H. Sompolinsky and O. Shriki (1998). A model
of the orientation tuning of synaptic conductances in primary visual
cortex Soc. Neurosci.
15- J. Goldberg, H. Sompolinsky, D. Hansel and H. Bergman
(1999). Network model of parkinsonian neuronal oscillations in
the cortico-baso-cortical loop . Frontiers in Computational Neuroscience,
Eilat.
16- D. Hansel, H. Sompolinsky and O. Shriki (1999). A model
of the orientation tuning of synaptic conductances in primary visual
cortex , Frontiers in Computational Neuroscience, Eilat.
17- O. Shriki, D. Hansel and H. Sompolinsky (1999).
Modeling neuronal networks in cortex
by rate models using the current-frequency response properties of
cortical cells Frontiers in Computational Neuroscience, Eilat.
Other publications