ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2020
Information-Limiting Correlations in Large Neural Populations.
Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers.
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54 citing papers in PubMed, 106 citations in OpenAlex.
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4 authors at 1 institution in 1 country.
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Abstract
Understanding the neural code requires understanding how populations of neurons code information. Theoretical models predict that information may be limited by correlated noise in large neural populations. Nevertheless, analyses based on tens of neurons have failed to find evidence of saturation. Moreover, some studies have shown that noise correlations can be very small, and therefore may not affect information coding. To determine whether information-limiting correlations exist, we implanted eight Utah arrays in prefrontal cortex (PFC; area 46) of two male macaque monkeys, recording >500 neurons simultaneously. We estimated information in PFC about saccades as a function of ensemble size. Noise correlations were, on average, small (∼10
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.