The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.
The log-dynamic brain: how skewed distributions affect network operations
Open accessAbstract
We often assume that the variables of functional and structural brain parameters — such as synaptic weights, the firing rates of individual neurons, the synchronous discharge of neural populations, the number of synaptic contacts between neurons and the size of dendritic boutons — have a bell-shaped distribution. However, at many physiological and anatomical levels in the brain, the distribution of numerous parameters is in fact strongly skewed with a heavy tail, suggesting that skewed (typically lognormal) distributions are fundamental to structural and functional brain organization. This insight not only has implications for how we should collect and analyse data, it may also help us to understand how the different levels of skewed distributions — from synapses to cognition — are related to each other.
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Metadata
- Authors
- Buzsáki, G., & Mizuseki, K.
- Venue
- Nature Reviews Neuroscience
- Published
- 2014-02-26
- Volume
- 15
- Issue
- 4
- Pages
- 264-278
- ISSN
- 1471-003X (ISSN-L)
- 1471-0048
- OpenAlex
- W2042076346
- Cited by
- 981
- References
- 55
- FWCI
- 5.92
- Type
- journal article
- Language
- en
- Open access
- green
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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.
