Neural computation by concentrating information in time.

Proceedings of the National Academy of SciencesPublished 1 April 1987Open access

David W. Tank, J. J. Hopfield

DOI10.1073/pnas.84.7.1896

Citations362

TL;DR

An analog model neural network that can solve a general problem of recognizing patterns in a time-dependent signal is presented and can be understood from consideration of an energy function that is being minimized as the circuit computes.

Abstract

An analog model neural network that can solve a general problem of recognizing patterns in a time-dependent signal is presented. The networks use a patterned set of delays to collectively focus stimulus sequence information to a neural state at a future time. The computational capabilities of the circuit are demonstrated on tasks somewhat similar to those necessary for the recognition of words in a continuous stream of speech. The network architecture can be understood from consideration of an energy function that is being minimized as the circuit computes. Neurobiological mechanisms are known for the generation of appropriate delays.

Keywords

Computer ScienceNeuroscience

Springer series in information sciencesSelf-Organization and Associative Memory

8,770 Citations1989Teuvo Kohonen

Proceedings of the National Academy of SciencesNeurons with graded response have collective computational properties like those of two-state neurons.

6,955 Citations1984J. J. Hopfield

A model for a large network of "neurons" with a graded response (or sigmoid input-output relation) is studied and collective properties in very close correspondence with the earlier stochastic model based on McCulloch - Pitts neurons are studied.

View PDF

Biological Cybernetics“Neural” computation of decisions in optimization problems

6,040 Citations1985J. J. Hopfield, David W. Tank

Results of computer simulations of a network designed to solve a difficult but well-defined optimization problem-the Traveling-Salesman Problem-are presented and used to illustrate the computational power of the networks.

The Journal of PhysiologyProperties and distribution of ionic conductances generating electroresponsiveness of mammalian inferior olivary neurones in vitro.

891 Citations1981R. Llinás, Yosef Yarom

The electrophysiological properties of the high‐ and low‐threshold Ca spikes described in inferior olivary neurones were analysed in detail and it was demonstrated that the duration of the after‐depolarization is determined by an interplay between inward Ca current and both voltage‐dependent and Ca‐dependent K currents.

Physical Review LettersTemporal Association in Asymmetric Neural Networks

575 Citations1986Haim Sompolinsky, Ido Kanter

A neural network model which is capable of recalling time sequences and cycles of patterns is introduced and may be also useful in understanding the generation of rhythmic patterns in biological motor systems.

Proceedings of the National Academy of SciencesSequential state generation by model neural networks.

336 Citations1986David Kleinfeld

This work shows how sequences of neural output activity can be generated by a class of model neural networks that make defined sets of transitions between selected memory states, and presents a scheme for the recognition of externally generated sequences by these networks.

View PDF

Proceedings of the National Academy of SciencesNeural map of interaural phase difference in the owl's brainstem.

165 Citations1986W. E. Sullivan, M. Konishi

KybernetikA model of associative memory in the brain

67 Citations1973Kunihiko Fukushima

A model of associative memory for time varying spatial patterns is proposed and simulated on a digital computer, and shows an ability for associatives memory similar to that of the brain.