Memory Performance Influences Male Reproductive Success in a Wild Bird

Shaw, Rachael C.; MacKinlay, Regan D.; Clayton, Nicola S.; Burns, Kevin C.

doi:10.1016/j.cub.2019.03.027

Cited by 48 publications

(76 citation statements)

References 35 publications

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“…To assess spatial discrimination performances, we used the same two-well apparatus as that in the visual discrimination task (above), but instead of encircling each well with a particular color, both wells were unmarked and identical, differing only in their location on the apparatus (e.g., Pravosudov et al 2005 ; Sanford and Clayton 2008 ; Sewall et al 2013 ; Shaw et al 2015 ; Shaw et al 2019 ). The correct well was furthest from the bird and the incorrect well was closest to the bird.…”

Section: Methodsmentioning

confidence: 99%

“…General cognitive abilities (learning, memory, executive function) underpin critical behaviors, such as foraging ( Raine and Chittka 2008 ; Pasquier and Grüter 2016 ), mate choice ( Shohet and Watt 2009 ; Araya-Salas et al 2018 ), and predator avoidance ( Turner et al 2006 ). Importantly, performances in cognitive tasks have associated fitness consequences in wild populations (reproduction: [ Ashton et al 2018 ; Branch et al 2019 ; Shaw et al 2019 ]; survival: [ Maille et al 2016 ; Madden, Hall, et al 2018 ; Sonnenberg et al 2019 ; Langley et al 2020 ]). Although this variation and the associated fitness implications are indicative of the evolutionary potential of these traits, investigation into their heritable component has received little attention in behavioral ecology.…”

Section: Introductionmentioning

confidence: 99%

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Heritability and correlations among learning and inhibitory control traits

et al. 2020

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To understand the evolution of cognitive abilities, we need to understand both how selection acts upon them and their genetic (co)variance structure. Recent work suggests that there are fitness consequences for free-living individuals with particular cognitive abilities. However, our current understanding of the heritability of these abilities is restricted to domesticated species subjected to artificial selection. We investigated genetic variance for, and genetic correlations among four cognitive abilities: inhibitory control, visual and spatial discrimination, and spatial ability, measured on >450 pheasants, Phasianus colchicus, over four generations. Pheasants were reared in captivity but bred from adults that lived in the wild and hence, were subject to selection on survival. Pheasant chicks are precocial and were reared without parents, enabling us to standardize environmental and parental care effects. We constructed a pedigree based on 15 microsatellite loci and implemented animal models to estimate heritability. We found moderate heritabilities for discrimination learning and inhibitory control (h2 = 0.17–0.23) but heritability for spatial ability was low (h2 = 0.09). Genetic correlations among-traits were largely positive but characterized by high uncertainty and were not statistically significant. Principle component analysis of the genetic correlation matrix estimate revealed a leading component that explained 69% of the variation, broadly in line with expectations under a general intelligence model of cognition. However, this pattern was not apparent in the phenotypic correlation structure which was more consistent with a modular view of animal cognition. Our findings highlight that the expression of cognitive traits is influenced by environmental factors which masks the underlying genetic structure.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Heritability and correlations among learning and inhibitory control traits

et al. 2020

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“…This improved orientation contributes to the animal's fitness. For instance, the spatial learning ability and spatial memory of food-hoarding birds are positively correlated with their survival and reproduction [11][12]. Spatial learning in vertebrates and invertebrates takes place in the hippocampus and mushroom body, respectively [13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Non-spatial information on the presence of food elevates search intensity in ant workers, leading to faster maze solving in a process parallel to spatial learning

et al. 2020

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Experience can lead to faster exploitation of food patches through spatial learning or other parallel processes. Past studies have indicated that hungry animals either search more intensively for food or learn better how to detect it. However, fewer studies have examined the contribution of non-spatial information on the presence of food nearby to maze solving, as a parallel process to spatial learning. We exposed Cataglyphis niger ant workers to a food reward and then let them search for food in a maze. The information that food existed nearby, even without spatial information, led to faster maze solving compared to a control group that was not exposed to the food prior to the experiment. Faster solving is probably achieved by a higher number of workers entering the maze, following the information that food is present nearby. In a second experiment, we allowed the ants to make successive searches in the maze, followed by removing them after they had returned to the nest and interacted with their naïve nestmates. This procedure led to a maze-solving time in-between that displayed when removing the workers immediately after they had reached the food and preventing their return to the colony, and that of no removal. The workers that interacted upon returning to the nest might have transferred to naïve workers information, unrelated to spatial learning, that food existed nearby, and driven them to commence searching. Spatial learning, or an increase in the correct movements leading to the food reward relative to those leading to dead-ends, was only evident when the same workers were allowed to search again in the same maze. However, both non-spatial information on the presence of food that elevated search intensity and spatial learning led to faster maze solving. OPEN ACCESSCitation: Bega D, Samocha Y, Yitzhak N, Saar M, Subach A, Scharf I (2020) Non-spatial information on the presence of food elevates search intensity in ant workers, leading to faster maze solving in a process parallel to spatial learning. PLoS ONE 15 (2): e0229709. https://doi.org/10.We collected 59 colonies of Cataglyphis niger from the Tel-Baruch sand dunes in Tel Aviv, Israel (32.132N, 34.788E), a public land. These sand dunes are an enclave of a disturbed natural Non-spatial information and maze solving in ants PLOS ONE | https://doi.

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“…Intra-species variation in animal cognition (i.e., how animals perceive, process, retain, and act on cues from their environment, Shettleworth 2010 ) is commonly observed (Dukas 2004 ; Thornton and Lukas 2012 ) and can have fitness consequences (Dukas 2004 ; Shaw et al 2019 ). Nevertheless, the underlying mechanisms behind this variation, such as the role of genes, remain largely unknown (Dukas 2004 ; Croston et al 2015 ).…”

Section: Introductionmentioning

confidence: 99%

The relationship between monoaminergic gene expression, learning, and optimism in red junglefowl chicks

et al. 2020

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Intra-species cognitive variation is commonly observed, but explanations for why individuals within a species differ in cognition are still understudied and not yet clear. Cognitive processes are likely influenced by genetic differences, with genes in the monoaminergic systems predicted to be important. To explore the potential role of these genes in association with individual variation in cognition, we exposed red junglefowl (Gallus gallus) chicks to behavioural assays measuring variation in learning (discriminative learning, reversal learning, and cognitive flexibility) and optimism (measured in a cognitive judgement bias test). Following this, we analysed prefrontal cortex gene expression of several dopaminergic and serotonergic genes in these chicks. Of our explored genes, serotonin receptor genes 5HT2A and 5HT2B, and dopaminergic receptor gene DRD1 were associated with measured behaviour. Chicks that had higher 5HT2A were less flexible in the reversal learning task, and chicks with higher 5HT2B also tended to be less cognitively flexible. Additionally, chicks with higher DRD1 were more optimistic, whilst chicks with higher 5HT2A tended to be less optimistic. These results suggest that the serotonergic and dopaminergic systems are linked to observed cognitive variation, and, thus, individual differences in cognition can be partially explained by variation in brain gene expression.

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Memory Performance Influences Male Reproductive Success in a Wild Bird

Cited by 48 publications

References 35 publications

Heritability and correlations among learning and inhibitory control traits

Heritability and correlations among learning and inhibitory control traits

Non-spatial information on the presence of food elevates search intensity in ant workers, leading to faster maze solving in a process parallel to spatial learning

The relationship between monoaminergic gene expression, learning, and optimism in red junglefowl chicks

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