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High-Fidelity Coding with Correlated Neurons

Figure 4

Heterogeneous neural populations.

A, B. Histogram of the error suppression (error in the homogeneous, 2-Pool model divided by the error in the fully heterogeneous model) for variability values and , respectively. All suppression values are greater than one. C. Value of the error suppression (geometric mean) versus the degree of population variability; neurons, , , , . (With these parameters, correlation suppresses the error probability by a factor of 4350 relative to the matched independent population.)

Figure 4

doi: https://doi.org/10.1371/journal.pcbi.1003970.g004