D. Amit

发表

Saturation Level of the Hopfield Model for Neural Network

A. Crisanti, D. Amit, H. Gutfreund, 1986 .

Statistical mechanics of neural networks near saturation

D. Amit, H. Gutfreund, H. Sompolinsky, 1987 .

Retrospective and prospective persistent activity induced by Hebbian learning in a recurrent cortical network

D. Amit, N. Brunel, G. Mongillo, 2003, The European journal of neuroscience.

Quantitative study of attractor neural networks retrieving at low spike rates: II. Low-rate retrieval in symmetric networks

D. Amit, M. Tsodyks, 1991 .

The Hebbian paradigm reintegrated: Local reverberations as internal representations

D. Amit, 1995, Behavioral and Brain Sciences.

Optimised network for sparsely coded patterns

D. Amit, C. P. Vicente, 1989 .

Model of global spontaneous activity and local structured activity during delay periods in the cerebral cortex.

D. Amit, N. Brunel, 1997, Cerebral cortex.

Effective neural response function for collective population states.

D. Amit, M. Mascaro, Massimo Mascaro, 1999, Network.

Modeling brain function: the world of attractor neural networks, 1st Edition

Daniel J. Amit, D. Amit, 1989 .

Persistent delay activity in cortex: a Galilean phase in neurophysiology?

D. Amit, 1994 .

Learning attractors in an asynchronous, stochastic electronic neural network.

D. Amit, Stefano Fusi, P. Del Giudice, 1998, Network.

Constraints on learning in dynamic synapses

D. Amit, Stefano Fusi, 1992 .

Universal Memory Mechanism for Familiarity Recognition and Identification

D. Amit, S. Hochstein, S. Romani, 2008, The Journal of Neuroscience.

Spin-glass models of neural networks

D. Amit, H. Gutfreund, H. Sompolinsky, 1987 .

Perceptron learning with sign-constrained weights

D. Amit, K. Y. Wong, C. Campbell, 1989 .

Attractor neural networks with biological probe records

Daniel J. Amit, Moshe Abeles, D. Amit, 1990 .

The eye and the hand: neural mechanisms and network models for oculomanual coordination in parietal cortex.

D. Amit, M. Mascaro, R. Caminiti, 2003, Cerebral cortex.

Field Theory, the Renormalization Group and Critical Phenomena

Victor Martin-Mayor, Daniel J Amit, D. Amit, 1984 .

Multiple-object working memory--a model for behavioral performance.

D J Amit, D. Amit, A. Bernacchia, 2003, Cerebral cortex.

Associative memory neural network with low temporal spiking rates.

A Treves, D J Amit, D. Amit, 1989, Proceedings of the National Academy of Sciences of the United States of America.

Neural Networks — Achievements, Prospects, Difficulties

D. Amit, D. J. Amit, 1987 .

Low firing rates: an effective Hamiltonian for excitatory neurons

Alessandro Treves, D J Amit, D. Amit, 1989 .

Metastable states in asymmetrically diluted Hopfield networks

Alessandro Treves, D J Amit, D. Amit, 1988 .

Mean-field analysis of selective persistent activity in presence of short-term synaptic depression

Daniel J. Amit, Sandro Romani, Gianluigi Mongillo, 2006, Journal of Computational Neuroscience.

Search for fMRI BOLD signals in networks of spiking neurons

D. Amit, S. Romani, 2007, The European journal of neuroscience.

In defence of single-electrode recordings

Daniel J. Amit, D. Amit, 1992 .

Memory of Ordinal Number Categories in Macaque Monkeys

D. Amit, S. Hochstein, E. Zohary, 2006 .

The correlation function in Wilson's theory of phase transitions: Above and below the transition

D. Amit, A. Shcherbakov, 1973 .

Correlation length in Wilson's theory of phase transitions

D. Amit, 1972 .

Theory of a low-density bose liquid☆

D. Amit, E. Gross, 1967 .

Psychology, Neurobiology and Modeling: The Science of Hebbian Reverberations

D. Amit, 1994 .

Crossover at a bicritical point: Asymptotic behavior of a field theory with quadratic symmetry breaking

D. Amit, Y. Goldschmidt, 1978 .

Selective delay activity in the cortex: phenomena and interpretation.

Gianluigi Mongillo, Daniel J Amit, D. Amit, 2003, Cerebral cortex.

Universal ratios in first-order transitions induced by fluctuations

D. Amit, G. Parisi, 1983 .

Changeover from a critical line to a tricritical point in the large N-limit

D. Amit, C. Dominicis, 1973 .

Particle-Hole Excitations and Self Energy of Quasi-Particles in a Fermi Liquid

D. Amit, 1968 .

FUNCTIONAL INTEGRALS IN QUANTUM FIELD THEORY

D. Amit, V. Martin-Mayor, 1993 .

Modelling Brain Function: The World of Attractor Neural Networks

D. Amit, 1989 .

Spin-glass models of neural networks AUGUST 1985

D. Amit, H. Gutfreund, 2011 .

Learning in Neural Networks with Material Synapses

Daniel J. Amit, Stefano Fusi, D. Amit, 1994, Neural Computation.

Empirical and theoretical active memory: The proper context

Daniel J. Amit, D. Amit, 1995, Behavioral and Brain Sciences.

Next-to-Leading Terms in the Correlation Function inside the Scaling Regime

D. Amit, É. Brézin, J. Zinn-Justin, 1974 .

First order transitions induced by fluctuations in general φ4-theories

D. Amit, Hadasa H Iacobson, 1981 .

Spike-Driven Synaptic Plasticity: Theory, Simulation, VLSI Implementation

Davide Badoni, Daniel J. Amit, Stefano Fusi, 2000, Neural Computation.

Kosterlitz-thouless transition and self-duality in three dimensions☆

D. Amit, R. Savit, E. Rabinovici, 1982 .

Breaking of scale invariance in π6 theory: Tricriticality and critical end-points

D. Amit, E. Rabinovici, 1985 .

On dangerous irrelevant operators

D. Amit, L. Peliti, 1982 .

Renormalisation group analysis of the phase transition in the 2D Coulomb gas, Sine-Gordon theory and XY-model

D. Amit, S. Grinstein, Y. Goldschmidt, 1980 .

Phase transition in HeII films

D. Amit, 1968 .

Structure of adsorbed film of a bose liquid

D. Amit, 1970 .

Generalized Landau theory for continuous phase transitions

D. Amit, M. Luban, 1968 .

New form for the thermodynamic potential of He II near Tλ

D. Amit, 1968 .

VORTEX RINGS IN A BOSE FLUID

D. Amit, E. Gross, 1966 .

The properties of models of simple neural networks

Daniel J. Amit, D. Amit, 1987 .

Vortex structure under pressure in a bose liquid

D. Amit, 1966 .

Multi-item working memory--a behavioral study.

Shaul Hochstein, Volodya Yakovlev, Tanya Orlov, 2005, Cerebral cortex.

Dynamics of a recurrent network of spiking neurons before and following learning

Nicolas Brunel, Daniel J. Amit, D. Amit, 1997 .

Paradigmatic Working Memory (Attractor) Cell in IT Cortex

Daniel J. Amit, Volodya Yakovlev, Stefano Fusi, 1997, Neural Computation.

Optimizing One-Shot Learning with Binary Synapses

Yali Amit, Daniel J. Amit, Sandro Romani, 2008, Neural Computation.

Mean Field and Capacity in Realistic Networks of Spiking Neurons Storing Sparsely Coded Random Memories

Daniel J. Amit, Gianluigi Mongillo, Giancarlo La Camera, 2004, Neural Computation.

E ective neurons and attractor neural networks in cortical environment

Daniel J. Amit, Misha Tsodyks, D. Amit, 1992 .

Quantitative Study of Attractor Neural Network Retrieving at Low Spike Rates: I

Daniel J. Amit, Misha Tsodyks, D. Amit, 1991 .

Effective interaction calculations of energy levels and wave functions in the nuclear 1p shell

D. Amit, A. Katz, 1964 .

EXPANSIONS OF THE FREE ENERGY NEAR A PHASE TRANSITION.

D. Amit, 1969 .

Cross-over behavior of the nonlinear σ-model with quadratically broken symmetry

D. Amit, L. Peliti, Y. Goldschmidt, 1978 .

Statistical Physics: An Introductory Course

D. Amit, Y. Verbin, 1999 .

The O(n)-symmetric model between two and four dimensions

D. Amit, Shang‐keng Ma, R. Zia, 1981 .

When the Landau criterion fails qualitatively

D. Amit, S. Alexander, 1975 .

Asymptotic behavior of the "true" self-avoiding walk

Daniel J. Amit, Giorgio Parisi, L. Peliti, 1983 .

Renormalization of the Potts model

D. Amit, 1976 .

The Ginzburg criterion-rationalized

D. Amit, 1974 .

The Wilson theory and the Ginzburg critical region

D. Amit, Y. Imry, D. Bergman, 1973 .

The phase transition in the continuous Potts model

D. Amit, A. Shcherbakov, 1974 .

Universality in the percolation problem—Anomalous dimensions of φ4 operators

D. J. Wallace, D. Amit, R. Zia, 1977 .

Exactly soluble limit of phi3 field theory with internal Potts symmetry

D. Amit, D. Roginsky, 1979 .

Functional integral approach to the magnetic impurity problem: The superiority of the two-variable method

D. Amit, H. Keiter, 1973 .

Path-Integral Approach to the Magnetic-Impurity Problem. I

D. Amit, C. Bender, 1971 .

Coupling of Density and Spin Fluctuations to Quasiparticles in a Fermi Liquid

D. Amit, H. Wagner, J. W. Kane, 1968 .

On the Renormalization of the Susceptibility of a Fermi Liquid

D. Amit, 1969 .

Self-consistent treatment of a phase transition

D. Amit, M. Zannetti, 1973 .

Field theory description of continuous phase transitions

D. Amit, M. Zannetti, 1973 .

Spike-Driven Synaptic Dynamics Generating Working Memory States

Daniel J. Amit, Gianluigi Mongillo, D. Amit, 2003, Neural Computation.

Blockage of eye-closure-generated generalized paroxysms by mental activity

D. Amit, Y. Amit, R. Amit, 2006, Journal of Pediatric Neurology.

Is the time ripe for integration of scales?

Daniel J. Amit, D. Amit, 1996, Behavioral and Brain Sciences.

Architecture of attractor neural networks performing cognitive fast scanning

Marius Usher, Daniel J. Amit, Dov Sagi, 1990 .

Prosopagnosia in high capacity neural networks storing uncorrelated classes

Miguel Angel Virasoro, D. Amit, Amit, 1990 .

Global Spontaneous Activity and Local Structured (learned) Delay Period Activity in Cortex

Nicolas Brunel, Daniel J. Amit, D. Amit, 1996 .

Neural potentials as stimuli for attractor neural networks

Daniel J. Amit, Giorgio Parisi, Stam Nicolis, 1990 .

Multi-level approaches to discrete-state and stochastic problems

Achi Brandt, Daniel J. Amit, Dorit Ron, 1986 .

Attractor neural networks and biological reality: associative memory and learning

Daniel J. Amit, D. Amit, 1989, Future Gener. Comput. Syst..

Conversion of Temporal Correlations Between Stimuli to Spatial Correlations Between Attractors

Daniel J. Amit, M. Griniasty, M. V. Tsodyks, 1999, Neural Computation.

Electronic implementation of an analogue attractor neural network with stochastic learning

Davide Badoni, Daniel J. Amit, Stefano Fusi, 1995 .

Modeling brain function: Symmetric Neural Networks at Low Memory Loading

D. Amit, 1989 .

The Eye And The Hand: Neural Mechanisms And Network Model For Oculomanual Coordination

Daniel J. Amit, Roberto Caminiti, Massimo Mascaro, 2003 .

Abstracts of the 15th Annual Meeting of the Israel Society for Neuroscience Eilat, Israel, December 3–5, 2006

Leslie G. Ungerleider, D. Amit, H. Seung, 2006, Neural Plasticity.

Retrieval phase diagrams for attractor neural networks with optimal interactions

D. Amit, K. Y. Wong, H. Horner, 1990 .

Neurophysiology of a VLSI spiking neural network: LANN21

Paolo Del Giudice, Daniel J. Amit, Stefano Fusi, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Constraints on learning in dynamic synapses

Daniel J. Amit, Stefano Fusi, D. Amit, 1992, Network: Computation in Neural Systems.

Statistical Physics: An Introductory Course

D. Amit, Y. Verbin, 1999 .

The interaction space of neural networks with sign-constrained synapses

D J Amit, D. Amit, K. Y. Wong, 1989 .

Non-linear σ-model and CP(n−1) at 2 + ε dimensions

D. Amit, G. Kotliar, 1980 .

Storing infinite numbers of patterns in a spin-glass model of neural networks.

Sompolinsky, Gutfreund, D. Amit, 1985, Physical review letters.

Spin-glass models of neural networks.

Sompolinsky, Gutfreund, D. Amit, 1985, Physical review. A, General physics.

Correlations of cortical Hebbian reverberations: theory versus experiment

N Brunel, D J Amit, M V Tsodyks, 1994, The Journal of neuroscience : the official journal of the Society for Neuroscience.

Neural networks counting chimes.

D J Amit, D. Amit, 1988, Proceedings of the National Academy of Sciences of the United States of America.

Learning internal representations in an attractor neural network with analogue neurons

Nicolas Brunel, Daniel J. Amit, D. Amit, 1995 .

Learning in realistic networks of spiking neurons and spike‐driven plastic synapses

Sandro Romani, Gianluigi Mongillo, Daniel J Amit, 2005, The European journal of neuroscience.

Serial memory strategies in macaque monkeys: behavioral and theoretical aspects.

Shaul Hochstein, Volodya Yakovlev, Tanya Orlov, 2002, Cerebral cortex.

Mean--eld Ising Model and Low Rates in Neural Networks

D. Amit, 2007 .

Simulation in neurobiology: theory or experiment?

Daniel J. Amit, D. Amit, 1998, Trends in Neurosciences.

Impact of spatiotemporally correlated images on the structure of memory

Alberto Bernacchia, Daniel J Amit, D. Amit, 2007, Proceedings of the National Academy of Sciences.