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Dryad

Data from: Brain size does not predict learning strategies in a serial reversal learning test

Cite this dataset

Boussard, Annika et al. (2020). Data from: Brain size does not predict learning strategies in a serial reversal learning test [Dataset]. Dryad. https://doi.org/10.5061/dryad.5mkkwh72s

Abstract

Reversal learning assays are commonly used across a wide range of taxa to investigate associative learning and behavioural flexibility. In serial reversal learning, the reward contingency in a binary discrimination is reversed multiple times. Performance during serial reversal learning varies greatly at the interspecific level, as some animals adapt a rule-based strategy that enables them to switch quickly between reward contingencies. Enhanced learning ability and increased behavioural flexibility generated by a larger relative brain size has been proposed to be an important factor underlying this variation. Here we experimentally test this hypothesis at the intraspecific level. We use guppies (Poecilia reticulata) artificially selected for small and large relative brain size, with matching differences in neuron number, in a serial reversal learning assay. We tested 96 individuals over ten serial reversals and found that learning performance and memory were predicted by brain size, whereas differences in efficient learning strategies were not. We conclude that variation in brain size and neuron number is important for variation in learning performance and memory, but these differences are not great enough to cause the larger differences in efficient learning strategies observed at higher taxonomic levels. 

Funding

Svenska Research Council , Award: 2016-03435

Knut and Alice Wallenberg Foundation, Award: 102 2013.0072

Svenska Research Council, Award: 2016-03435