The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.
Intrinsic biophysical diversity decorrelates neuronal firing while increasing information content
Open accessAbstract
Although examples of variation and diversity exist throughout the nervous system, their importance remains a source of debate. Even neurons of the same molecular type have notable intrinsic differences. Largely unknown, however, is the degree to which these differences impair or assist neural coding. We examined the outputs from a single type of neuron, the mitral cells of the mouse olfactory bulb, to identical stimuli and found that each cell's spiking response was dictated by its unique biophysical fingerprint. Using this intrinsic heterogeneity, diverse populations were able to code for twofold more information than their homogeneous counterparts. In addition, biophysical variability alone reduced pair-wise output spike correlations to low levels. Our results indicate that intrinsic neuronal diversity is important for neural coding and is not simply the result of biological imprecision.
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Cites
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Cited by
The benefits of noise in neural systems: bridging theory and experiment
McDonnell, M. D., & Ward, L. M. (2011) · Nature Reviews Neuroscience · doi:10.1038/nrn3061 · Cited by 772
Multiple models to capture the variability in biological neurons and networks
Marder, E., & Taylor, A. L. (2011) · Nature Neuroscience · doi:10.1038/nn.2735 · Cited by 451
Neuronal organization of olfactory bulb circuits
Nagayama, S., Homma, R., & Imamura, F. (2014) · Frontiers in Neural Circuits · doi:10.3389/fncir.2014.00098 · Cited by 411
Early Olfactory Processing in Drosophila: Mechanisms and Principles
Wilson, R. I. (2013) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-062111-150533 · Cited by 394
Variability, compensation, and modulation in neurons and circuits
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Metadata
- Authors
- Padmanabhan, K., & Urban, N. N.
- Venue
- Nature Neuroscience
- Published
- 2010-08-29
- Volume
- 13
- Issue
- 10
- Pages
- 1276-1282
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- OpenAlex
- W2119024215
- Cited by
- 310
- References
- 48
- FWCI
- 11.95
- Type
- journal article
- Language
- en
- Open access
- green
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
