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A computational neuroscience framework for quantifying warning signals

Lookup NU author(s): Matthew Wheelwright, Dr John Skelhorn, Professor Candy Rowe

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Publication metadata

Author(s): Penacchio O, Halpin CG, Cuthill IC, Lovell PG, Wheelwright M, Skelhorn J, Rowe C, Harris JM

Publication type: Article

Publication status: Published

Journal: Methods in Ecology and Evolution

Year: 2024

Volume: 15

Issue: 1

Pages: 103-116

Print publication date: 01/01/2024

Online publication date: 11/12/2023

Acceptance date: 13/11/2023

Date deposited: 23/11/2023

ISSN (electronic): 2041-210X

Publisher: Wiley-Blackwell Publishing Ltd

URL: https://doi.org/10.1111/2041-210X.14268

DOI: 10.1111/2041-210X.14268

Data Access Statement: All the hyperspectral images are available at https://arts.st-andrews.ac.uk/lepidoptera/. The data, Matlab and 503 R code that support the findings of this study—including a full description of the Matlab functions involved in 504 the computational pipeline to compute the metrics—are openly available at Dryad, Dataset, 505 https://doi.org/10.5061/dryad.x3ffbg7kd. (Link for private 506 access: https://datadryad.org/stash/share/r7UMw-SMbQe6brENF_lc-lohuNMhNLXMNPBAHfzK-lY)


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Funding

Funder referenceFunder name
BB/N005945/1
BB/N00602X/1Biotechnology and Biological Sciences Research Council (BBSRC)
BB/N006569/1
BB/N007239/1
BBSRC
Maria Zambrano Fellowship, NextGeneration EU (ALRC)

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