AUTHOR=Agrillo Christian , Miletto Petrazzini Maria Elena , Tagliapietra Christian , Bisazza Angelo TITLE=Inter-Specific Differences in Numerical Abilities Among Teleost Fish JOURNAL=Frontiers in Psychology VOLUME=3 YEAR=2012 URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2012.00483 DOI=10.3389/fpsyg.2012.00483 ISSN=1664-1078 ABSTRACT=

Adults, infants and non-human primates are thought to possess similar non-verbal numerical systems, but there is considerable debate regarding whether all vertebrates share the same numerical abilities. Despite an abundance of studies, cross-species comparison remains difficult because the methodology employed and the context of species examination vary considerably across studies. To fill this gap, we used the same procedure, stimuli, and numerical contrasts to compare quantity abilities of five teleost fish: redtail splitfin, guppies, zebrafish, Siamese fighting fish, and angelfish. Subjects were trained to discriminate between two sets of geometrical figures using a food reward. Fish initially were trained on an easy numerical ratio (5 vs. 10 and 6 vs. 12). Once they reached the learning criterion, they were subjected to non-reinforced probe trials in which the set size was constant but numerical ratios varied (8 vs. 12 and 9 vs. 12). They also were subjected to probe trials in which the ratio was constant, but the total set size was increased (25 vs. 50) or decreased (2 vs. 4). Overall, fish generalized to numerosities with a 0.67 ratio, but failed with a 0.75 ratio; they generalized to a smaller set size, but not to a larger one. Only minor differences were observed among the five species. However, in one species, zebrafish, the proportion of individuals reaching the learning criterion was much smaller than in the others. In a control experiment, zebrafish showed a similar lower performance in shape discrimination, suggesting that the observed difference resulted from the zebrafish’s difficulty in learning this procedure rather than from a cross-species variation in the numerical domain.