Using animal models to explain human behavior and cognition often has some limitations. Here we discuss one popular analogy recently proposed in numerical cognition—the origins of the number line, a cornerstone of human mathematics and geometry, which has been recently tested in newly hatched birds (Rugani, Kelly, Szelest, Regolin, & Vallortigara, 2010; Rugani, Vallortigara, Priftis, & Regolin, 2015). The mental number line is a construct illustrating the interplay between mental representations of numbers and space. Numbers can be mentally ordered such that small numbers are associated with the left side in space and large numbers with the right side (Dehaene, Bossini, & Giraux, 1993), and numerical distances represented as spatial distances in a linear manner (Siegler & Opfer, 2003). The ability to map numbers to space does not seem to be universal or invariant among humans. For instance, the basic intuition of sequential arrangement of numbers is lacking in unschooled autochthons of Papua New Guinea (Núñez, Cooperrider, & Wassmann, 2012). Directionality of this association is also flexible, and it is affected by recent cultural inventions like spatially oriented scripts (Shaki, Fischer, & Göbel, 2012; Shaki, Fischer, & Petrusic, 2009) or some less advanced cultural practices. The latter are evident in various directional body-counting systems in illiterate tribes (Ifrah, 1985; Saxe, 1981; Wassmann & Dasen, 1994) and number-space effects consistent with dominant cultural directions in preliterate children (McCrink, Shaki, & Berkowitz, 2014; Opfer & Furlong, 2011; Opfer, Thompson, & Furlong, 2010; Patro, Fischer, Nuerk, & Cress, 2016; Shaki et al., 2012; for reviews, see de Hevia, Girelli, & Macchi Cassia, 2012; McCrink & Opfer, 2014; Nuerk et al., 2015). In short, multiple cultural experiences widely influence number-space mapping in humans. Nevertheless, some recent studies with animals and infants suggested that number–space interactions might initially originate from certain biological mechanisms rather than cultural experiences (Bulf, de Hevia, & Macchi Cassia, 2016; de Hevia, Girelli, Addabbo, & Macchi Cassia, 2014; Rugani et al., 2010; Rugani, Vallortigara, Priftis, et al., 2015; Rugani, Vallortigara, & Regolin, 2015). One frequently proposed mechanism, which we wish to discuss, refers to the dominance of the right hemisphere in visuospatial processing (de Hevia et al., 2012; Rugani et al., 2010). The role of hemispheric lateralization was first postulated to account for spatial–numerical biases of birds. In a study by Rugani et al. (2010), adult nutcrackers, and newborn chicks were trained to peck the fourth or sixth element in a series of sagittally aligned equidistant 16 elements. After rotating the whole series into a horizontal position, the birds correctly identified the fourth and sixth element starting from the left end but not from the right end. To explain these findings, the authors referred to a phenomenon of “avian pseudoneglect,” systematically observed with birds as an allocation of attention to the left hemifield, while searching for grains or bisecting horizontal lines (Diekamp, Regolin, Güntürkün, & Vallortigara, 2005; Regolin, 2006). Presumably, such a bias is a direct consequence of the right hemisphere dominance in encoding relative distances between target and the endpoint element (when elements are not equidistant, spatial estimation is disrupted and lateral biases disappear; Rugani, Vallortigara, Vallini, & Regolin, 2011). Unlike in humans and many other mammals, the neuroanatomy of the avian brain is structured such that the right hemisphere takes almost entire control over visual–spatial information projected from the left hemifield: Retinal fibers in the optic chiasm are nearly fully crossed, so that visual information entering each eye is mainly projected to the contralateral hemisphere. Birds also lack corpus callosum—a structure that enhances the transfer of information between hemispheres. As a result, many cognitive functions differently lateralized in the avian brain may cause systematic and pronounced contralateral biases in their behavior from very early on (Güntürkün, 1997; Rogers, 2008). It is, however, disputable how far a similar mechanism can be generalized to other animal species. On one hand, morphological and functional similarities are often observed in animals sharing a common ancestor. For instance, a lateralized brain is a common characteristic of all vertebrates (Vallortigara, Rogers, & Bisazza, 1999). Even such a human-unique trait like speech follows the lateralization pattern for processing vocal calls in our evolutionary ancestors (e.g., Poremba et al., 2004). In a similar way, the mechanism of directional numerical ordering could be simply passed on from birds to higher-order vertebrates, including primates. However, the process of speciation is not only about continuity but also about differentiation, which enables better adaptation to the environment. The strength and directionality of lateralization patterns are in fact diversified in the animal world. For instance, certain species of fish tend to escape to the right from a predator, whereas other species do so in exactly the opposite direction (Bisazza, Cantalupo, Capocchiano, & Vallortigara, 2000); some populations of domestic horses exhibit left-sided foreleg preference, but other populations do not (McGreevy & Thomson, 2006). Even within the same species, one might observe variability in individual lateralization patterns (e.g., paw preference in dogs, Quaranta, Siniscalchi, Frate, & Vallortigara, 2004; preferential eye use in fighting fish, Cantalupo, Bisazza, & Vallortigara, 1996; and even visuospatial biases in birds, Chiandetti, 2011; Skiba, Diekamp, & Güntürkün, 2002; Wilzeck & Kelly, 2013). All these differences may arise from several different sources like, for instance, social pressure to coordinate inter-group behavior (Vallortigara & Rogers, 2005), environmental factors (e.g., lateral light exposure of a bird embryo, Rogers, 1996), or morphological traits (e.g., the presence of corpus callosum, Miu, 2005). So the specific lateralization pattern characteristic to one species is not necessarily present in the same form in its evolutionarily near relatives, or even within all members of the same species. Indeed, it could disappear or evolve in a different direction. Furthermore, there are cases in the animal world supporting the theory of convergent evolution, that is, when species from different evolutionary lineages develop independently similar features (e.g., Emery & Clayton, 2004). Based on this analogy, we might consider the possibility that some lateral biases functionally equivalent in various organisms originate from different mechanisms. In particular, biological origins of left-to-right numerical ordering in chicks are well justified, whereas less obvious are the origins of similar biases in rhesus monkeys (Drucker & Brannon, 2014) or preschool children (Opfer et al., 2010). The direction of numerical ordering as assessed by counting can at least be modulated in preschoolers by cultural immersion (Shaki et al., 2012), whereas pre-cultural onset of this behavior has never been proved. In monkeys who live in laboratories, and who are in contact with people, cultural immersion might also influence spatial–numerical biases (apart from or instead of biological factors). Zookeepers or animal researchers might exhibit unintentionally certain culture-specific biases while ordering things in a cage, marking territory with a line, and so on (cf. Tversky, Kugelmass, & Winter, 1991; Vaid, 1995). Whether monkeys are really able to internalize such spontaneous culturally oriented behavior of humans and transmit it to numerical tasks is as yet an open question, which could optimally be tested in cross-cultural or controlled training settings. Taken together, variability in functional lateralization in the animal world and variety of possible mechanisms explaining the same behavioral biases should both be taken into account before one concludes that left-to-right numerical ordering is evolutionary inherited. Recently, another form of number-space processing in humans, quantity-to-space mapping, has been found in infants (e.g., attentional preference for left/right side after presentation of small/large number of objects; Bulf et al., 2016; see also de Hevia et al., 2014). The right-hemisphere explanation was again adopted to explain these findings. This generalization faces in our view at least two problems. First, it is unclear whether left-sided attentional bias emerges in human infants at all. Although pseudoneglect in human adults is a widespread phenomenon (Jewell & McCourt, 2000), there is no direct evidence for its early onset in infancy. Leftward biases in visuospatial orienting are even hard to observe in preschoolers (e.g., Chokron & De Agostini, 1995). Moreover, lateral neglect in young children with brain injury appears equally frequently after damage to the left and right hemisphere, suggesting that “both hemispheres may be critical in the development of visuospatial attention before the typical adult pattern of right hemisphere dominance emerges“ (Smith & Chatterjee, 2008, p. 1286). Finally, the idea of early onset of pseudoneglect in humans cannot easily be reconciled with other directional tendencies present in infancy. One contentious example is a systematic tendency of neonates to turn their head rightward while supine (Turkewitz, Gordon, & Birch, 1965), which could stimulate their left eye, but also enables more perceptual input from the right side of the body. Systematic attentional biases in infancy could be further suppressed by multi-directional experiences like following the parents’ gaze (Hood, Willen, & Driver, 1998), being cradled by a mother preferentially on her left arm (De Château, 1983), or an advantage of a given hand in some motoric tasks (Streri & de Hevia, 2015). Altogether, there are reasons to suspect that the emergence of spatial-visual asymmetries in humans is a process stretched over a longer period of time. Therefore, it might not be powerful enough to determine the direction of numerical representation already in infancy. This is in contrast to birds, whose spatial asymmetries arise spontaneously from early-developing anatomical constraints specific to this particular species. Even if this conclusion is wrong and spatial–visual biases emerge already in infancy, the right-hemispheric explanation would face another problem: It seems to suggest that the role of the right hemisphere in forming a number–space link is not restricted to visuospatial analysis of inter-item distances in ordinal tasks (Rugani et al., 2011); rather it may organize a more general left-to-right reference frame onto which numerical quantities are sequentially mapped. However, it is unclear how this mechanism could exactly work: Why are small and large quantities associated with the left and right hemispaces, respectively, instead of both being processed predominantly in the left hemifield? Rugani, Salva, & Retolin (2014), Rugani, Vallortigara, Priftis, et al. (2015), and Rugani, Vallortigara, & Regolin (2015) acknowledge this limitation while discussing their recent studies, in which chicks approached a larger set of objects more often on the right side, and a smaller set on the left side. If leftward attentional shift alone guided chicks’ behavior in this task, the birds would be always biased to the left. This pattern demonstrates that processing of quantities is not functionally lateralized, but the lateral bias depends on which relative numerical magnitude is currently processed. Thus, pseudoneglect alone might not directly explain quantity-based effects, neither in human infants nor even in chicks. Some, as of yet unknown, additional mechanism supporting conceptual magnitude-to-space linkage (like experience of increasing magnitudes while moving rightward, Patro, Nuerk, & Cress, 2016) has to be assumed. Altogether, in our view, the hemispheric explanation faces some problems when transferred from chicks to human infants. More empirical tests are needed to clarify whether the human number line can be constructed independently of any cultural experience (like in birds). Because culture does not need to be very advanced to affect our behavior, optimal experimental settings should minimize the effect of implicit learning by studying human neonates or provide cross-cultural variation by studying infants from different reading societies. Some neuroimaging studies could also help to clarify the potential role of the right hemisphere in number-space mapping. In different species, lateralized behavior might be determined by different hemispheric organization, the developmental course of this organization, or active immersion in cultural surroundings and high susceptibility to social learning. Thus, a direct transfer of spatial-numerical mapping mechanisms from chicks to humans cannot be assumed; it must be appropriately tested. It is true that we can learn something about the human genome from the fruit fly (Ashburner et al., 2000), but the fact that female spiders eat their male spiders after sex (Elgar, 1992) cannot be (luckily) easily transferred to humans. Thus, we have to look carefully at single cases and to assess each time whether it is reasonable to explain human cognition based on animal models.
No takes yet. Share an insight, caveat, or question.
Patro et al. (2016) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: