dorsal/arxiv
View SchemaWeak pairwise correlations imply strongly correlated network states in a neural population
| Authors | Elad Schneidman, Michael J. Berry II, Ronen Segev, William Bialek |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0512013 |
| URL | https://arxiv.org/abs/q-bio/0512013 |
| DOI | 10.1038/nature04701 |
Abstract
Biological networks have so many possible states that exhaustive sampling is impossible. Successful analysis thus depends on simplifying hypotheses, but experiments on many systems hint that complicated, higher order interactions among large groups of elements play an important role. In the vertebrate retina, we show that weak correlations between pairs of neurons coexist with strongly collective behavior in the responses of ten or more neurons. Surprisingly, we find that this collective behavior is described quantitatively by models that capture the observed pairwise correlations but assume no higher order interactions. These maximum entropy models are equivalent to Ising models, and predict that larger networks are completely dominated by correlation effects. This suggests that the neural code has associative or error-correcting properties, and we provide preliminary evidence for such behavior. As a first test for the generality of these ideas, we show that similar results are obtained from networks of cultured cortical neurons.
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"abstract": "Biological networks have so many possible states that exhaustive sampling is\nimpossible. Successful analysis thus depends on simplifying hypotheses, but\nexperiments on many systems hint that complicated, higher order interactions\namong large groups of elements play an important role. In the vertebrate\nretina, we show that weak correlations between pairs of neurons coexist with\nstrongly collective behavior in the responses of ten or more neurons.\nSurprisingly, we find that this collective behavior is described quantitatively\nby models that capture the observed pairwise correlations but assume no higher\norder interactions. These maximum entropy models are equivalent to Ising\nmodels, and predict that larger networks are completely dominated by\ncorrelation effects. This suggests that the neural code has associative or\nerror-correcting properties, and we provide preliminary evidence for such\nbehavior. As a first test for the generality of these ideas, we show that\nsimilar results are obtained from networks of cultured cortical neurons.",
"arxiv_id": "q-bio/0512013",
"authors": [
"Elad Schneidman",
"Michael J. Berry II",
"Ronen Segev",
"William Bialek"
],
"categories": [
"q-bio.NC",
"q-bio.QM"
],
"doi": "10.1038/nature04701",
"title": "Weak pairwise correlations imply strongly correlated network states in a neural population",
"url": "https://arxiv.org/abs/q-bio/0512013"
},
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