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Cited by 280

The DOI matches its Crossref record; 60 of the 60 references it cites were found in a registry or an index.

Age matters

Open access
McCutcheon, James Edgar, Marinelli, Michela·2009·European Journal of Neuroscience

Abstract

The age of an experimental animal can be a critical variable, yet age matters are often overlooked within neuroscience. Many studies make use of young animals, without considering possible differences between immature and mature subjects. This is especially problematic when attempting to model traits or diseases that do not emerge until adulthood. In this commentary we discuss the reasons for this apparent bias in age of experimental animals, and illustrate the problem with a systematic review of published articles on long‐term potentiation. Additionally, we review the developmental stages of a rat and discuss the difficulty of using the weight of an animal as a predictor of its age. Finally, we provide original data from our laboratory and review published data to emphasize that development is an ongoing process that does not end with puberty. Developmental changes can be quantitative in nature, involving gradual changes, rapid switches, or inverted U‐shaped curves. Changes can also be qualitative. Thus, phenomena that appear to be unitary may be governed by different mechanisms at different ages. We conclude that selection of the age of the animals may be critically important in the design and interpretation of neurobiological studies.

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Crossref · 10.1111/j.1460-9568.2009.06648.x

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Metadata

Authors
McCutcheon, J. E., & Marinelli, M.
Venue
European Journal of Neuroscience
Publisher
Wiley
Published
2009-03
Volume
29
Issue
5
Pages
997-1014
ISSN
  • 0953-816X (ISSN-L)
  • 1460-9568
OpenAlex
W4211060198
Cited by
280
References
60
FWCI
5.77
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.