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Fig 1

ID

ZDB-FIG-191230-1325

Publication

Diana et al., 2019 - Bayesian inference of neuronal assemblies

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Fig 1

Validation.

(A) Simulated activity of N = 500 neurons organized in A = 5 assemblies. Time sequences of length M = 1000 for all neurons have been generated from the model with λ_μ(0) = 0.08, λ_μ(1) = 0.6 and p_μ = 0.1 for asynchrony, synchrony and activity equal for all assemblies. We used this activity matrix as input to our inference algorithm to recover the five assemblies. (B) (top) log-likelihood over the course of 300 iterations of the Monte Carlo sampler and (bottom) number of transitions per iteration divided by the number of neurons N (different colors correspond to different initializations of neuronal memberships). (C) Assignments of cells to assemblies at four stages of the sampling. Cells initially assigned to O(N) assemblies are progressively grouped until the original assemblies are recovered.

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Acknowledgments

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