TY - JOUR
T1 - What is a moment? 'Cortical' sensory integration over a brief interval
AU - Hopfield, J. J.
AU - Brody, Carlos D.
PY - 2000/12/5
Y1 - 2000/12/5
N2 - Recognition of complex temporal sequences is a general sensory problem that requires integration of information over time. We describe a very simple 'organism' that performs this task, exemplified here by recognition of spoken monosyllables. The network's computation can be understood through the application of simple but generally unexploited principles describing neural activity. The organism is a network of very simple neurons and synapses; the experiments are simulations. The network's recognition capabilities are robust to variations across speakers, simple masking noises, and large variations in system parameters. The network principles underlying recognition of short temporal sequences are applied here to speech, but similar ideas can be applied to aspects of vision, touch, and olfaction. In this article, we describe only properties of the system that could be measured if it were a real biological organism. We delay publication of the principles behind the network's operation as an intellectual challenge: The essential principles of operation can be deduced based on the experimental results presented here alone. An interactive web site (http://neuron.princeton.edu/-moment) is available to allow readers to design and carry out their own experiments on the organism.
AB - Recognition of complex temporal sequences is a general sensory problem that requires integration of information over time. We describe a very simple 'organism' that performs this task, exemplified here by recognition of spoken monosyllables. The network's computation can be understood through the application of simple but generally unexploited principles describing neural activity. The organism is a network of very simple neurons and synapses; the experiments are simulations. The network's recognition capabilities are robust to variations across speakers, simple masking noises, and large variations in system parameters. The network principles underlying recognition of short temporal sequences are applied here to speech, but similar ideas can be applied to aspects of vision, touch, and olfaction. In this article, we describe only properties of the system that could be measured if it were a real biological organism. We delay publication of the principles behind the network's operation as an intellectual challenge: The essential principles of operation can be deduced based on the experimental results presented here alone. An interactive web site (http://neuron.princeton.edu/-moment) is available to allow readers to design and carry out their own experiments on the organism.
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U2 - 10.1073/pnas.250483697
DO - 10.1073/pnas.250483697
M3 - Article
C2 - 11095747
AN - SCOPUS:0034610280
SN - 0027-8424
VL - 97
SP - 13919
EP - 13924
JO - Proceedings of the National Academy of Sciences of the United States of America
JF - Proceedings of the National Academy of Sciences of the United States of America
IS - 25
ER -