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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
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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.
