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Weighting of sensory cues reflects changing patterns of visual investment during ecological divergence in Heliconius butterflies

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DataONE2024-07-03 更新2024-07-27 收录
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Integrating information across sensory modalities enables animals to orchestrate a wide range of complex behaviours. The relative importance placed on one sensory modality over another reflects the reliability of cues in a particular environment and corresponding differences in neural investment. As populations diverge across environmental gradients, the reliability of sensory cues may shift, favouring divergence in neural investment and the weight given to different sensory modalities. During their divergence across closed-forest and forest-edge habitats, closely related butterflies Heliconius cydno and H. melpomene evolved distinct brain morphologies, with the former investing more in vision. Quantitative genetic analyses suggest selection drove these changes, but their behavioural effects remain uncertain. We hypothesised that divergent neural investment may alter sensory weighting. We trained individuals in an associative learning experiment using multimodal colour and odour cues. W..., , , # Weighting of sensory cues reflects changing patterns of visual investment during ecological divergence in *Heliconius* butterflies ## Provenance for this README * File name: README_sensoryweighting.Rmd * Authors: José Borrero * Other contributors: Daniel Shane Wright, Richard M. Merrill * Date created: 2024-04-08 * Date modified: 2024-07-02 ## Dataset Version and Release History * Current Version: * Number: 2.0.0 * Date: 2024-07-02 * Persistent identifier: DOI: [https://doi.org/10.5061/dryad.7m0cfxq0h](https://doi.org/10.5061/dryad.7m0cfxq0h) * Summary of changes: # Differences Between Current and Previous Versions In this version, we have made the following changes and additions compared to the previous version: 1. Subsections Added to Section 1: * 1.3 GLMM 75% Model naive trained, conflict, and color: Included details on the Generalized Linear Mixed Model (GLMM) used to analyze naive, trained, conflict, and color treatments. * 1.4 GLMM total feedin...
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2024-07-04
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