Neural Correlations, Population Coding and Computation.¶
Averbeck, B. B., Latham, P. E., & Pouget, A. (2006). Neural Correlations, Population Coding and Computation. Nature Reviews Neuroscience, 7(5), 358-366.
Cited by¶
1 citation across 1 artifact.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Population Coding
- The partially-independent noise is the per-neuron spiking variability, largely independent across neurons, so it averages out in the sum — and the prime correctly flags correlated noise (shared input fluctuations) as the main thing that caps achievable precision, formalized by Fisher information.
This sourceShows how noise correlations across a population cap achievable decoding precision.
Supported in partVerified against the publisher's abstract
The review supports that correlated neuronal variability can substantially affect population-code precision, but not that correlated noise is the main cap on precision; it says correlations may also increase or not affect information.
“This is because variability in the brain is typically correlated, and although the exact effects of these correlations are not known, it is known that they can be large.”
- The partially-independent noise is the per-neuron spiking variability, largely independent across neurons, so it averages out in the sum — and the prime correctly flags correlated noise (shared input fluctuations) as the main thing that caps achievable precision, formalized by Fisher information.
Verification¶
Does it exist? Confirmed. This work's DOI resolves to a registered record, which fixes its identity. That is all it fixes.
Does it back the claim? Read against the text for 1 of 1 citation: 1 supported in part. Each verdict is shown under its citation below, with what in the work backs the sentence.
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Registry ID ref:5860768b1e7d · see in the full table