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Times Cited: 769
Times Cited
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L F Abbott, P Dayan. Neural Comput 1999
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The variable discharge of cortical neurons: implications for connectivity, computation, and information coding.
M N Shadlen, W T Newsome. J Neurosci 1998
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Stimulus dependence of neuronal correlation in primary visual cortex of the macaque.
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Matthew A Smith, Adam Kohn. J Neurosci 2008
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Correlated firing in macaque visual area MT: time scales and relationship to behavior.
W Bair, E Zohary, W T Newsome. J Neurosci 2001
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The effect of noise correlations in populations of diversely tuned neurons.
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Learning and attention reveal a general relationship between population activity and behavior.
A M Ni, D A Ruff, J J Alberts, J Symmonds, M R Cohen. Science 2018
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How Can Single Sensory Neurons Predict Behavior?
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State dependence of noise correlations in macaque primary visual cortex.
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Population coding in neuronal systems with correlated noise.
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The asynchronous state in cortical circuits.
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Effects of noise correlations on information encoding and decoding.
Bruno B Averbeck, Daeyeol Lee. J Neurophysiol 2006
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Direction-Selective Circuits Shape Noise to Ensure a Precise Population Code.
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Feedback determines the structure of correlated variability in primary visual cortex.
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Decoding the activity of neuronal populations in macaque primary visual cortex.
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Stimulus onset quenches neural variability: a widespread cortical phenomenon.
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Adaptive coding of visual information in neural populations.
Diego A Gutnisky, Valentin Dragoi. Nature 2008
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The spatial structure of correlated neuronal variability.
Robert Rosenbaum, Matthew A Smith, Adam Kohn, Jonathan E Rubin, Brent Doiron. Nat Neurosci 2017
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Inferring decoding strategies from choice probabilities in the presence of correlated variability.
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Correlation between neural spike trains increases with firing rate.
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Functional specificity of local synaptic connections in neocortical networks.
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Co-cited is the co-citation frequency, indicating how many articles cite the article together with the query article. Similarity is the co-citation as percentage of the times cited of the query article or the article in the search results, whichever is the lowest. These numbers are calculated for the last 100 citations when articles are cited more than 100 times.