What can developmental and comparative cognitive neuroscience tell us about the adult human brain?

An oft-repeated dictum in biology holds that ontogeny recapitulates phylogeny. Despite failures of Haeckl’s principle to predict in strict form the morphological, behavioral, or cognitive stages an organism passes through during development, the underlying sentiment continues to inform contemporary approaches to mind and brain. For example, studies of behavior and cognition in developing humans provide an anchor for understanding both intellectual primitives and the nature of representation in animal minds. Conversely, comparative studies of cognition in animals serve to address seemingly intractable questions concerning the roles of innate capacities, culture and language in the development of mature human cognition. And both comparative and developmental studies shed light on the neural mechanisms that subserve the most complex and distinctive cognitive abilities of adult humans, such as the capacity for abstract thought. Both developmental and comparative approaches to cognition provide uniquely powerful data that can inform the search for homologies in brain and mind. Homologous features of cognition are defined as those psychological and neurobiological traits that evolved in the common ancestor of related phyletic groups that emerge from shared developmental pathways and serve closely related behavioral functions. Nothing in this definition requires that such traits emerge early in development: the developmental pathways that produce homologous patterns of sexual or parental behavior, for example, may be long. Nevertheless, a central discovery of developmental and comparative research on cognitive neuroscience, over the last decades, is that the cognitive traits that humans share with other animals tend to emerge early in human development. This conclusion stems from research probing the behavioral and neurobiological signatures of specific cognitive abilities in human children and nonhuman animals. Consider, for example, the sense of number. Even in adults, sensitivity to numerosity—a fuzzy sense of number—follows psychophysical principles that characterize the number sense in preverbal infants and animals. Most importantly, the number sense follows Weber’s Law in that sensitivity improves with numerical distance and declines with numerical magnitude, as if the underlying representation of numerosity (at least for collections of objects or events greater than 2 or 3) were encoded on a ratio scale (i.e., logarithmically). Moreover, non-human animals, human infants, and human adults represent number abstractly, detecting the common cardinal values of visuo-spatial arrays of objects and temporal sequences of sounds or actions (Meck & Church, 1983; Izard, Sann, Spelke & Streri, in press; Jordan & Brannon, 2006; Jordan, MacLean, & Brannon, 2008; Barth et al., 2005). And finally, numerical representations enter into arithmetic operations of ordering, addition, and subtraction for animals, infants, and adults (Cantlon & Brannon, 2006, 2007; Brannon, 2002; McCrink & Wynn, 2004; Barth et al., 2005). These three behavioral signatures of number sense are joined by evidence of common brain mechanisms for representing number in non-human animals, human children, and adults. Brain imaging studies show activation of parietal cortex in both adult humans and children when they make numerical discriminations (Piazza et al 2004; Cantlon, Brannon, Carter, and Pelphrey, 2006), and neurons in the fundus of the intraparietal sulcus in macaque monkeys show approximately logarithmic tuning functions for numerosity (Nieder and Miller 2003). In both types of experiments, responses to number are independent of sensory modality and stimulus format, providing evidence for abstract numerical representations (Diester and Nieder 2007). And these quantity representations are transformed by the operations of numerical comparison and arithmetic. The above studies also begin to shed light on the neural mechanisms by which abstract concepts of number are formed and used. Studies of humans and monkeys implicate the intraparietal sulcus as an important locus of numerical processing. Yet this cannot be the whole story, since a wide array of animals, including birds, fish, and insects, without a cerebral cortex—let alone a parietal lobe—can discriminate number and do so in a way that obeys Weber’s Law (e.g., Gross et al 2009; Rugani, Regolin, and Vallortigara, 2008; Agrillo et al 2009). Number is such a fundamental aspect of the world that its core representation may depend on mechanisms that evolved early in the history of animal life: mechanisms whose operation was amplified by the higher brain systems that emerged later in evolution. Further studies of the underlying neurobiological mechanisms of numerical representation will be instrumental in reconstructing this evolutionary history and enriching understanding of how the human brain represents number abstractly. The goal of this issue is to evaluate critically the case for cognitive homology in five domains considered fundamental to adult human cognition. Specifically, we have invited reviews of the literature on cognitive development, comparative cognition, and where these studies are sufficiently advanced, neural mechanism, by leading experts in their respective fields. We focus on the principles governing spatial cognition, tool use and physical cognition, social cognition, economic decision making, and numerical thinking as a precursor for symbolic representation. On balance, these reviews favor the hypothesis that both animals and preverbal children are endowed with biological primitives of adult human cognition in all these domains. Yet, uncertainties remain regarding the specific mechanisms that mediate these processes. Further, some of these reviews begin to shed light on unique features of cognition in humans and in other species that have confronted distinct selective pressures that propelled their development along diverging evolutionary paths. Together, these reviews point the way forward to both new approaches to understanding the development and comparative expression of cognition, as well as the kinds of neurobiological data that will be necessary to adjudicate current hypotheses regarding cognitive homologies and differences in these domains.

[1]  Ken Cheng,et al.  Whither geometry? Troubles of the geometric module , 2008, Trends in Cognitive Sciences.

[2]  Hilary Barth,et al.  Abstract number and arithmetic in preschool children. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[3]  E. Spelke,et al.  Newborn infants perceive abstract numbers , 2009, Proceedings of the National Academy of Sciences.

[4]  C. Gallistel The organization of learning , 1990 .

[5]  Elizabeth M Brannon,et al.  The development of ordinal numerical knowledge in infancy , 2002, Cognition.

[6]  R. Church,et al.  A mode control model of counting and timing processes. , 1983, Journal of experimental psychology. Animal behavior processes.

[7]  K. Cheng A purely geometric module in the rat's spatial representation , 1986, Cognition.

[8]  Marco Dadda,et al.  Use of Number by Fish , 2009, PloS one.

[9]  Elizabeth M Brannon,et al.  Basic Math in Monkeys and College Students , 2007, PLoS biology.

[10]  E. J. Carter,et al.  Functional Imaging of Numerical Processing in Adults and 4-y-Old Children , 2006, PLoS biology.

[11]  J. Tautz,et al.  Number-Based Visual Generalisation in the Honeybee , 2009, PloS one.

[12]  J. Fodor The Modularity of mind. An essay on faculty psychology , 1986 .

[13]  Philippe Pinel,et al.  Tuning Curves for Approximate Numerosity in the Human Intraparietal Sulcus , 2004, Neuron.

[14]  Elizabeth M. Brannon,et al.  Monkeys match and tally quantities across senses , 2008, Cognition.

[15]  K. Wynn,et al.  Large-Number Addition and Subtraction by 9-Month-Old Infants , 2004, Psychological science.

[16]  J. Cantlon,et al.  Shared System for Ordering Small and Large Numbers in Monkeys and Humans , 2006, Psychological science.

[17]  Giorgio Vallortigara,et al.  Discrimination of small numerosities in young chicks. , 2008, Journal of experimental psychology. Animal behavior processes.

[18]  E. Miller,et al.  Coding of Cognitive Magnitude Compressed Scaling of Numerical Information in the Primate Prefrontal Cortex , 2003, Neuron.

[19]  Andreas Nieder,et al.  Semantic Associations between Signs and Numerical Categories in the Prefrontal Cortex , 2007, PLoS biology.

[20]  Elizabeth M Brannon,et al.  The multisensory representation of number in infancy. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[21]  Antoine Wystrach,et al.  Ants Learn Geometry and Features , 2009, Current Biology.