What is a moment? Transient synchrony as a collective mechanism for spatiotemporal integration.

By John J. Hopfield, Carlos D. Brody. Proceedings of the National Academy of Sciences of the United States of America, 2001

296 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/406d968077fdb21f7d44e5b0c095ff1d66bcd329

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cellular and Molecular Neuroscience

1. Filip Ponulak
2. Andrzej J. Kasinski
3. Wolfgang Maass
4. Emilio Salinas
5. David John Cameron MacKay
6. Terrence J. Sejnowski
7. E. D. Di Paolo
8. Henry Markram

In Cognitive Neuroscience

1. Filip Ponulak
2. Andrzej J. Kasinski
3. Wolfgang Maass
4. Jean-Jacques E. Slotine
5. Henry Markram
6. E. D. Di Paolo
7. Terrence J. Sejnowski
8. Wei Wang

In Electrical and Electronic Engineering

1. Filip Ponulak
2. Andrzej J. Kasinski
3. Wolfgang Maass
4. Henry Markram
5. E. D. Di Paolo
6. David John Cameron MacKay
7. Terrence J. Sejnowski
8. Jean-Jacques E. Slotine

Citations in the corpus

• Spike-Timing Dependent Plasticity for Evolved Robots (2002, background): “They can perform novel kinds of computations such as the recognition of temporal patterns using transient synchrony (Hopfield & Brody, 2001) and real-time computation without stable states in high-dimensional ‘‘liquids’’ of transient activity, (Maass, Natschläger, & Markram, 2002).”
• Introduction to spiking neural networks: Information processing, learning and applications. (2011, background): “One of the first spiking models of supervised speech recognition has been proposed in Hopfield and Brody (2000, 2001).”
• On partial contraction analysis for coupled nonlinear oscillators (2004, background): “2000; Strogatz 1994, 2000), biology (Collins and Stewart 1993a; Murray 1993; Strogatz and Stewart 1993), neuro-science (Brody and Hopfield 2003; Hopfield and Brody 2001; Kopell 2000; Manoret et al. 1999; Neuenschwan-der et al. 2002; Singer 1999; Wolf 2001; Yen et al. 1999), robotics (Bay John and…”
• Information Theory, Inference, and Learning Algorithms (2004, background): “The problem of finding a large subset of variables that are approximately equal can be solved with a neural network approach (Hopfield and Brody, 2000; Hopfield and Brody, 2001).”
• Correlated neuronal activity and the flow of neural information (2001, background): “For example, according to a recent theoretical proposa”
• Supervised Learning in Spiking Neural Networks with ReSuMe: Sequence Learning, Classification, and Spike Shifting (2010, methodology): “In the past decade, spiking neural networks have been successfully applied to various classification tasks (Bohte et al., 2002; Ghosh-Dastidar & Adeli, 2007; G¨utig & Sompolinsky, 2006; Hopfield & Brody, 2001; Maass et al., 2002; Maass, Natschlaeger, & Markram, 2004; Muresan, 2002).”
• The neural representation of time. (2004, background): “Alternatively, the dynamics of time-varying physiological events might be used to represent and produce temporal information [47,49 ,50].”
• On the computational power of circuits of spiking neurons (2004, background): “A network was presented in [15] that could solve this task with an error(4) of 0.”