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The genetics of numeracy and the evolutionary basis of number; can fish count?

School of Biological & Chemical Sciences

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Prof Caroline Brennan No more applications being accepted Funded PhD Project (European/UK Students Only)

About the Project

It has long been recognized that non-human animals can discriminate collections of objects on the basis their numerousness. This ability is thought to be based on the existence of an evolutionarily conserved system for approximating numerical magnitude. However, there is currently no evidence that the same neural mechanisms underlie representation of numerousness among vertebrates nor that the same genes are involved. Here we use behavioural and genetic analysis of wildtype and mutant zebrafish, coupled with analysis of human genome data, to test the hypotheses that the ability to represent numerousness is genetically controlled and has an evolutionarily conserved neural basis.

What underlies the ability to count and where did it come from?
Current hypotheses propose that, driven by pressure from the rise of agriculture and trading, the ability to accurately represent the number of objects in a set (numerosity) and to carry out simple arithmetic developed from an evolutionarily conserved system for approximating numerical magnitude. According to this hypothesis the ability to assess numerosities would have an evolutionarily conserved genetic and neural basis, and one might expect at least some aspects of the neurobiology underlying ability to perform approximate numerical tasks and to accurately represent number to be shared. However, although a wide range of species are able to approximate numerosities, there is no evidence for a shared genetic basis with other species, and the suggestion that other species may be able to perform exact numerical tasks is controversial. The research proposed here will test the broad hypothesis that the ability to represent numerosity is genetically regulated and has an evolutionarily conserved genetic and neural basis. We will also examine the possibility that exact numerical abilities are present in fish without pressure from trade or the possession of symbolic means for counting, at least for small numerosities.
As shoaling animals, zebrafish use numerosity to guide behaviour and decisions. Using automated operant conditioning we train zebrafish to perform numerical tasks and identify genetic variants influencing performance. Our general hypothesis predicts that genes found to influence human performance of exact numerical tasks will influence zebrafish performance of approximate tasks and vice versa.

The project is a collaboration between human geneticists (Silvia Parachini, Brian Butterworth) and fish behavioural scientists (Caroline Brennan, Giorgio Vallorgitara). The successful applicant will be working in close association with post-doctoral scientists involved in the project both in the UK and Italy and be expected to spend some time in the laboratory of Prof Vallorgitara to gain training in behavioural methods used to assess numerosity.

This project tests the hypotheses that the ability to represent numerousness:
i) is genetically regulated and ii) has an evolutionarily conserved neural basis.
We test whether numerosity is genetically regulated by evaluating human genome data for genetic variants associated with numerical skills and by screening zebrafish mutants for families that show heritable differences in numerosity. We test whether the neural bases are evolutionarily conserved by determining whether the same genes are involved in human and fish numerosity and whether the gene products are present in homologous regions of the brain.

Funding Notes

The studentship to start around May 2017 is funded by the Leverhulme Trust and will cover tuition fees at the Home/EU rate and provide an annual tax-free maintenance allowance for 36 months.

Applications are welcome from candidates holding a 2:1 or above in a relevant degree. Experience in the use of the zebrafish and/ or behavioural analysis would be desirable.


Neider, A. J Comp Physiol 2013. 199(1): p. 1-16; Dadda, M., et al., Cognition, 2009. 112(2): p. 343-8 ; Stancher, G., et al., Anim Cogn, 2013. 16(2): p. 307-12; Gomez-Laplaza, L.M. and R. Gerlai, Anim Cogn, 2011. 14(4): p. 565-74..;Agrillo, C., et al., Anim Cogn, 2008. 11(3): p. 495-503.;Bisazza, A., et al.. PLoS One, 2010. 5(11): p. e15516.;Potrich, D., et al., J Comp Psychol, 2015. 129(4): p. 388-93.
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