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Cited by 678

The DOI matches its Crossref record; 58 of the 58 references it cites were found in a registry or an index.

Fractional differentiation by neocortical pyramidal neurons

Open access
Lundstrom, Brian N, Higgs, Matthew H, Spain, William J, Fairhall, Adrienne L·2008·Nature Neuroscience
DOI 10.1038/nn.2212
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Abstract

Neural systems adapt to changes in stimulus statistics. However, it is not known how stimuli with complex temporal dynamics drive the dynamics of adaptation and the resulting firing rate. For single neurons, it has often been assumed that adaptation has a single time scale. We found that single rat neocortical pyramidal neurons adapt with a time scale that depends on the time scale of changes in stimulus statistics. This multiple time scale adaptation is consistent with fractional order differentiation, such that the neuron's firing rate is a fractional derivative of slowly varying stimulus parameters. Biophysically, even though neuronal fractional differentiation effectively yields adaptation with many time scales, we found that its implementation required only a few properly balanced known adaptive mechanisms. Fractional differentiation provides single neurons with a fundamental and general computation that can contribute to efficient information processing, stimulus anticipation and frequency-independent phase shifts of oscillatory neuronal firing.

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Metadata

Authors
Lundstrom, B. N., Higgs, M. H., Spain, W. J., & Fairhall, A. L.
Venue
Nature Neuroscience
Publisher
Springer Science and Business Media LLC
Published
2008-10-19
Volume
11
Issue
11
Pages
1335-1342
ISSN
  • 1097-6256 (ISSN-L)
  • 1546-1726
DOI
10.1038/nn.2212
OpenAlex
W1968134101
Cited by
678
References
58
FWCI
7.47
Type
journal article
Language
en
Open access
green

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.