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Part IV PHYLOGENY OF HUMAN BRAINS AND HUMAN MINDS T he chapters in Part IV address the question of human uniqueness in brain organization and behavior. In Chapter 14, Todd Preuss focuses on molecular genetic differences between human brains and the brains of our closest relatives. Particular emphasis is given to the role of foxP2, which has, at times, been called the human language gene. Not surprisingly, the true story of foxP2 is more complex, because as Preuss puts it, “we are trying to relate a multifunctional gene to a complex, high-level phenotype.” To deal with this complexity, Preuss suggests that we need a better understanding not of single-gene variation, but of varia- tion in many genes and, particularly, brain development. Preuss also notes that human brains mature more slowly than the brains of other species, which would explain why brain metabolic activity is surprisingly high and structural plasticity unusually protracted in humans. Particularly interesting is the observation that some patterns of gene expression in the prefrontal cortex of humans are seen only during development in other species. The mechanisms underlying this heterochrony as well as their functional sequelae remain unclear. However, childhood is well known to be more protracted in humans than in other apes. Lizabeth Romanski reviews in Chapter 15 the anatomical and physi- ological organization of the ventrolateral prefrontal cortex (vlPFC) of macaque monkeys. This cortical region is of special interest because its homolog in humans includes several language-related areas (e.g., Broca’s area). In a key experiment, Romanski and her colleagues took movies of vocalizing monkeys, separated them into audio and visual streams, and 251
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252 / Part IV showed them to other monkeys with recording electrodes in their vlPFC. This experiment revealed that the majority of vlPFC neurons integrate auditory and visual information in a nonlinear manner. This finding is important because human speech perception also involves a considerable amount of audiovisual integration, as demonstrated by the McGurk effect (McGurk and MacDonald, 1976). Of course, audiovisual integration of vocalization-related stimuli is not identical to speech perception, which requires the integration of sounds and visual information with meanings. The latter type of integration still eludes the understanding of neurobi- ologists and is extremely difficult to study in monkeys. Nonetheless, the audiovisual integration that Romanski describes in monkeys is likely to have played a major role in the evolution of human language. In Chapter 16, Jessica Cantlon compares the mathematical abilities of nonhuman primates and humans, especially human children. Although we often think that mathematics requires symbols (e.g., numbers and operators), simple math can be performed without symbols. For example, one can compare two images and estimate, even without counting, which image contains more items of a particular sort. This kind of analog numeri- cal estimation can also be performed by human infants and nonhuman primates. Cantlon further reports that the analog math task activates homologous brain areas in the parietal cortex of both humans and mon- keys. Collectively, the data strongly suggest that analog math abilities evolved long before the origin of Homo sapiens. This finding is fascinating, but how did symbolic math evolve? Was it built on top of the more ancient analog skill, using the ancient circuitry with only minor modifications? Or did symbolic math evolve out of symbolic communication (i.e., language)? At this point, the answer is unknown. In the final Chapter 17, Clark Barrett dispels the notion—promulgated by some evolutionary psychologists—that adaptive specializations in the brain must be hard-wired modules. To grasp the argument, consider face- selective neurons in primate brains. Given the importance of conspecific faces in the lives of most primates, the distinct patches of face-selective neurons in monkey and human brains were likely shaped by natural selec- tion. Nonetheless, the development of face-selective neurons probably depends on extensive experience with faces. Indeed, Barrett hypothesizes that selection generated not an innate face-processing module but a set of mechanisms that, given experience with faces, will generate a large number of neurons that selectively encode faces. Given other types of experience, the same mechanisms would (and do) generate patches of neurons selective for other kinds of behaviorally important stimuli. Stated succinctly, Barrett argues that natural selection generates developmental norms of reaction rather than experience-independent specialized mod- ules. This idea extends evo-devo neurobiology into the realm of evolution- ary psychology.