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Entropy and Information in Neural Spike Trains
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“As previously reported,27,60 the plugin estimate of the joint Shannon information has an upward bias, which decreases with the number of samples N (Figures 1B and 2A [left]), increases with the number of discrete bins R, S of each source and target variable (Figure 2A, middle, where we keep R = S for simplicity), and decreases with the information level (Figure 2A, right).”
From Sampling bias corrections for discrete and Gaussian partial information decompositions (2026) · cites this paper as [60]
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Dimitrov, A. G., & Miller, J. P. (2001) · Network: Computation in Neural Systems · doi:10.1080/net.12.4.441.472 · Cited by 76
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Self-citationSampling bias corrections for discrete and Gaussian partial information decompositions
Lorenz, G. M., Engel, N. M., Koçillari, L., Celotto, M., Orsenigo, D., Curreli, S., Malerba, S. B., Engel, A. K., Kayser, C., Fellin, T., et al. (2026) · Patterns · doi:10.1016/j.patter.2026.101619 · Cited by 9
Metadata
- Authors
- Strong, S. P., Koberle, R., de Ruyter van Steveninck, R. R., & Bialek, W.
- Venue
- Physical Review Letters
- Publisher
- American Physical Society (APS)
- Published
- 1998-01-05
- Volume
- 80
- Issue
- 1
- Pages
- 197-200
- ISSN
- 0031-9007
- 1079-7114
- Cited by
- 791
- References
- 1
- Language
- en
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