4 fish [60]. Since both guppies and mosquitofish appear to discriminate 3 from 4 fish [22,37] there might be taxonomic or ecological differences in the numerical abilities among fish species. Other explanations are however possible. Since poeciliids do not form tight shoals, during the experiment, all stimulus fish of one group are usually simultaneously visible to the subject. Angelfish, by contrast, are characterized by a wide lateral body surface and tend to form coherent and synchronized schools; thus, as the number of individuals increases some individuals could often block the sight of other shoalmates, making it difficult for a subject to accurately estimate group numerosity. Some recent studies found that accuracy was affected by numerical ratio for both small and large numbers leading some researchers to question the existence of two separate numerical systems [16,65]. It is unclear why some studies find that performance in the range 1–4 is independent of ratio and some do not. A possible explanation for this literature inconsistency, recently proposed by some authors (e.g. [26,66,67]), is that small quantities may be represented by both analog magnitude and object-file mechanisms, and that recruitment of one or the other system may depend on context and previous experience. In line with this hypothesis, a recent study found that, unlike controls, a sample of participants with an expertise that requires years of training in estimation of magnitudes showed the typical signature of the analog magnitude system, ratio effect, in the small number range too [Agrillo and Piffer, unpublished]. However that may be, the lack of a ratio effect in the 1–4 numerical range does not necessarily entail the existence of a separate system. As pointed out by Gallistel and Gelman [9], the difference in ratio effect between large and small numbers could occur because there is so little error in the analog magnitude representations of 1, 2, 3, and 4 that they are highly distinguishable from one another, and thus coarse behavioral measures of the underlying processes (as they often are with both human and non-human experiments), fail to evidence a ratio dependence when in fact such a relationship may exist. Our results do not help to clarify this issue, being compatible with both hypotheses. However, even assuming the existence of a single system of analog magnitude with a different ratio sensitivity in the range 1–4 and beyond it, the similarity in human and guppy experiments in the steepness of the slope in both ranges is again strongly suggestive of similar systems of numerical representation. References 1. Burr D, Ross J (2008) A visual sense of number. Curr Biol 18: 425–428. 2. Nieder A (2005) Counting on neurons: The neurobiology of numerical competence. Nat Rev Neurosci 6: 177–190. 3. Feigenson L, Dehaene S, Spelke ES (2004) Core systems of number. Trends Cogn Sci 8: 307–314. 4. Xu F, Spelke ES (2000) Large number discrimination in 6-month-old infants. Cognition 74: B1–B11. 5. Aoki T (1977) On the counting process of patterned dots. Toh Psychol Folia 36: 15–22. 6. Atkinson J, Campbell FW, Francis MR (1976) The magic number 460: a new look at visual numerosity judgements. Perception 5: 327–334. 7. Trick LM, Pylyshyn ZW (1994) Why are small and large numbers enumerated differently: A limited-capacity preattentive stage in vision. Psychol Rev 101: 80–102. 8. Dehaene S (1997) The number sense. New York: Oxford University Press. 9. Gallistel CR, Gelman R (1992) Preverbal and verbal counting and computation. Cognition 44: 43–74. 10. Nieder A, Dehaene S (2009) Representation of number in the brain. Ann Rev Neurosci 32: 185–208. 11. Kahneman D, Treisman A, Gibbs BJ (1992) The reviewing of object files - object-specific integration of information. Cogn Psychol 24: 175–219. 12. Meck WH, Church RM (1983) A mode control model of counting and timing processes. J Exp Psych: Anim Behav Proc 9: 320–334. 13. Whalen J, Gallistel CR, Gelman R (1999) Nonverbal counting in humans: The psychophysics of number representation. Psychol Sci 10: 130–137. Similar Numerical Systems in Humans and Guppies Other studies have provided evidence to support strong similarities between teleosts and primates. Swordtails, mosquito- fish, angelfish and climbing perch appear to adhere to Weber’s Law when discriminating between two large quantities [22,23,38,68] and mosquitofish trained to discriminate between large sets of geometric figures were found to be equally efficient in discriminating 4 vs. 8 items or 100 vs. 200 items, exactly like the college students tested with the same stimuli [36]. Naturally, as with most comparative data, it is always possible that a strong similarity in cognitive abilities is the product of convergent evolution and that similar performance reflect very dissimilar underlying mechanisms. It might seem surprising to discover similar numerical abilities in humans and in guppies, especially when considering that the brain size of a guppy is less than a thousandth of that of primates. However, it is clear from recent literature that the cognitive abilities of fish have been greatly underestimated and that teleosts are capable of complex behaviors such as individual recognition, transmission of cultural traditions, cooperation, copying behavior and deception, which have traditionally been associated with the evolution of large cortical areas in mammals and birds [69,70]. On the other hand, it is also possible that a cognitive function such as numerical discrimination, which is apparently complex, may actually be based on relatively simple neural circuits, as suggested by a recent neural network study [71]. On a more general note, the evolution of numerical abilities in animal species is still a largely unexplored field and future research is needed to understand the origin of the quantitative systems shown by vertebrates. If numerical abilities have evolved many times independently in different taxa it would be challenging to understand which selective constraints have shaped them in a converging fashion. On the other hand, the results of this comparative study admits the possibility of common mechanisms between primates and basal vertebrates, suggesting that the evolutionary emergence of numerical abilities may be very ancient, possibly dating back to before the teleost-tetrapod divergence. 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Demeyere N, Lestou V, Humphreys GW (2010) Neuropsychological evidence for a dissociation in counting and subitizing. Neurocase 16: 219–237. 19. Hyde DC, Spelke ES (2009) All numbers are not equal: An electrophysiological investigation of small and large number representations. J Cogn Neurosci 21: 1039–1053. 20. Vetter P, Butterworth B, Bahrami B (2011) A candidate for the attentional bottleneck: Set-size specific modulation of right TPJ during attentive enumeration. J Cogn Neurosci 23: 728–736. 21. Piazza M, Mechelli A, Butterworth B, Price CJ (2002) Are subitizing and counting implemented as separate or functionally overlapping processes? Neuroimage 15: 435–446. 22. Agrillo C, Dadda M, Serena G, Bisazza A (2008) Do fish count? Spontaneous discrimination of quantity in female mosquitofish. Anim Cogn 11: 495–503. PLoS ONE | www.plosone.org 7 February 2012 | Volume 7 | Issue 2 | e31923