Annu. Rev. Anthropol. 1997. 26:337–57 Copyright © 1997 by Annual Reviews Inc. All rights reserved
WHAT MAKES THE HUMAN BRAIN DIFFERENT? Terrence W. Deacon Department of Anthropology, Boston University, Boston, Massachusetts 02215; e-mail:
[email protected] KEY WORDS: brain evolution, brain size, development, intelligence, encephalization, homeotic genes, allometry
ABSTRACT Despite decades of research that has revolutionized the neurosciences, efforts to explain the major features of human brain evolution are still mostly based on superficial gross neuroanatomical features (e.g. size, sulcal patterns) and on theories of selection for high-level functions that lack precise neurobiological predictions (e.g. general intelligence, innate grammar). Beyond its large size we still lack an account of what makes a human brain different. However, advances in comparative neuroanatomy, developmental biology, and genetics have radically changed our understanding of brain development. These data challenge classic ideas about brain size, intelligence, and the addition of new functions, such as language, and they provide tools with which we can test hypotheses about how human brains diverge from other primate brains.
INTRODUCTION What Is Known About Human Brain Differences? For centuries there has been little doubt that differences in the size and structure of human brains must be responsible for our unusual mental abilities. In search of these critical anatomical differences, generations of researchers have compared human brains to other mammal brains with the aid of histological and quantitative techniques. One might expect that a great deal must now be known about the structural differences between human and nonhuman brains 337 0084-6570/97/1015-0337$08.00
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but unfortunately this is far from the case. This is particularly surprising considering that the neurosciences have made incredible strides in understanding brain functions at many other levels. Although there is little doubt that human brains are unusually large for a mammal of our size (Jerison 1973, Martin & Harvey 1985), beyond this one piece of information little else is certain about the relevant anatomical differences between human and nonhuman brains. Even more disturbing is that many contemporary claims and assumptions about the nature of brain evolution in human ancestry take for granted assumptions that would be judged biologically implausible with respect to other organ systems (e.g. accretion of new structures, recapitulation, modular change). Human brain evolution is still very much studied with the classic tools of functional morphology. This is exemplified by the two principal sources of data applied to human brain evolution research: (a) quantitative analysis of brains and brain regions, and (b) comparisons of cortical surface morphology as identifiable on endocasts of fossil crania. In the 1990s, as in the 1890s, the most active area of research on brain evolution is based on studying patterns exhibited by comparative brain size data. Beyond such global approaches, however, the search for the special features of human neurobiology has not been pursued with the same level of technical sophistication as are most questions in the rest of the neurosciences. The causes of this methodological inertia include a lack of neurobiological tools suitable for studying microstructures of living human brains, the minimalistic nature of the paleoneuroanatomical record, and, of course, the intrinsic complexity of brains in general. Almost certainly there are other nonscientific causes for this inertia, including the influence of tacit assumptions about what anatomical variables are most important, about possible mechanisms of brain evolution, and about the place of human beings in some hierarchic evolutionary scheme. The methodological limitations are not so crippling as they might first appear, however, because there is a wealth of indirect neurobiological evidence that bears on these questions too. The review does not critique prior work in the field but instead emphasizes the relevance of the rapidly growing body of neurobiological, developmental, and molecular findings that can inform and constrain the study of human brain evolution, and that mostly have not been incorporated into current theoretical perspectives.
What Does Brain Size Tell Us? Our large brain size in comparison with our body size is undeniable, but the causes and consequences of this difference are far from obvious. Nevertheless, it is accepted almost as fact that large brains can process more information than small brains and that having more extra brain tissue provides intellectual ca-
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pacity over and above basic physiological needs. Despite a century of analysis of the correlates of gross and net brain size trends, however, the mechanisms behind these presumed relationships remain unexplained. What is known is that mammalian brains and bodies scale with respect to each other according to a highly regular relationship (Figure 1A) described by an allometric exponent1 between 2/3 and 3/4, depending on the species sampled and the mode of computation (e.g. see Jerison 1973, Martin 1981), and that this value can be considerably lower in samples from more confined taxonomic groups (e.g. family, genus, or species level; see Martin & Harvey 1985; Figure 1B). The developmental mechanisms underlying this regularity of segmental scaling remain a matter of intense debate, and therefore the mechanisms that were modified to produce deviations from these trends (e.g. encephalization of primates and human beings) are also unclear. The highly correlated allometry of brain and body sizes in mammals has long been thought to reflect some overarching evolutionary economy of intelligence or metabolism that holds across diverse adaptations and sizes. But theories attempting to explain this regularity have almost exclusively been based on comparative statistical studies demonstrating correlations with other physiological, ecological, taxonomic, or theoretical trends. Unfortunately, it is not possible to use correlational analyses alone to determine which, if any, of the multitude of brain size associations represent direct causal mechanisms, or even which are spurious, and the fact that there are many potentially independent correlational relationships to explain adds a further complication. One cannot, on the one hand, argue that metabolic, taxonomic, embryological, or socioecological factors are involved in producing the observed trends and, on the other hand, argue that these trends reflect comparative information processing capacities alone. The specific allometric patterns that are observed may reflect a complicated evolutionary compromise among many factors, or these factors may be indirect correlates of some more basic relationship. We cannot substantiate any conjectures about the significance of brain size trends or deviations from them without independent information concerning the mecha1 1An allometric relationship, as opposed to an isometric relationship, is one in which the sizes of two corresponding body structures do not equally change across ranges of scale, either with respect to growth or in interspecific comparisons. However, body proportions often consistently correlate with scale allowing the assessment of patterns of proportional change or difference. The assessment of allometric scaling is commonly applied to samples of log transformed data points (which linearizes geometric growth relationships) and is reported in terms of the slope and y-intercept of a best fit line (typically determined by least squares regression, major axis, or reduced major axis methods) through these points. The slope of the log transformed line is the exponent of a curve of the form Y=aXb. Differences in these parameters can thus be interpreted as reflecting systematic differences in growth rates or initial/ancestral conditions.
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Figure 1 (A) Brain and body sizes in a wide selection of mammals are plotted on a log-log graph showing the almost linear distribution of points and the relative position of the human value with respect to the others. Human beings show a greater divergence from the predicted brain size for our body size than any other species. (B) Intraordinal (within order) and interspecific trends are superimposed on the mammalian distribution to show the shifted position of the primate trend and the flatter trend characteristic of all intraspecific brain/body scaling. Encephalization is most typically assessed with respect to the prediction for an average mammal.
nisms by which brain growth and differentiation are achieved. What kinds of developmental data would be relevant? How much are currently known? To review the developmental information applicable to these questions, it is useful to approach it hierarchically, from gross comparative assessments of brain growth processes, to developmental processes underlying regional parcellation and connectional architecture, to genetic determinants of regional differentiation of neural tissue types.
BRAIN GROWTH PATTERNS Are Primates More Encephalized Than Other Mammals? One of the least-questioned facts about brain evolution are the apparent advance in relative brain size among monkeys and apes as compared with most other mammals. On average, anthropoid primate brains are twice as large as would be predicted for a typical nonprimate mammal of the same body size. This comparatively greater encephalization has prompted speculation that features of the general primate adaptation may have selected for intelligence or at least removed constraints on brain expansion. A closer look, however, at the nature of this encephalization difference suggests that it may not be that simple. The question in this case is whether it matters how this systematic proportional difference came about. Would it matter if proportionately larger brain size resulted from relatively stunted postcranial growth, as opposed to exag-
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gerated brain growth? Consider dwarfism. Some of the most encephalized animals and human beings on the planet are dwarves. To my knowledge, there is no evidence that stunted postcranial growth contributes to augmentation of any intellectual functions, and likely the opposite is true. Although it is a source of encephalization, there are no serious contenders among encephalization theories that include dwarfism as a major factor, and yet selection on postcranial body proportions appears common in evolution as well as in selective breeding. In domestic dogs, for example, there are large differences in encephalization between large and small breeds. Small dog breeds tend to be encephalized and large dogs unencephalized, because selective breeding alters body size more extensively than brain size (Kruska 1988), a feature also evident in the pattern of intraspecific brain/body scaling. To my knowledge there is no evidence that smaller, more encephalized breeds show enhanced cognitive abilities as a result, and probably the reverse is true (Coren 1995). Could this be a model for certain forms of encephalization identified in interspecific comparisons? If so, the exclusive focus on encephalization as brain evolution reflects a persistent anthropocentric bias. One obvious objection is that comparing intra- to interspecies examples of unusually high or low encephalization may not be a comparison of the same phenomenon. For example, if breed differences mostly reflect selection on postcranial features, they might not significantly correlate with differences in cognitive abilities, whereas species differences might be the result of selection influencing both brain and body size and therefore might indicate neurological differences. But comparisons of adult data alone are not sufficient to discriminate between these two possible sources of differences in relative encephalization, nor to help determine whether either effect reflects selection on brain function. An analysis that takes into account development can help. Consider the causes of encephalization in primates. Although we cannot directly analyze the forces of selection acting on primate brains and bodies throughout their phylogenetic history, we can approach this question in much the same way we might with respect to dog breeds. We recognize that small dog encephalization is secondary to postcranial reduction because we can compare these dogs to more typical dogs and their patterns of growth. A distinct difference between brain/body growth in primates and most other mammals was first systematically analyzed by Earl Count (1947). He showed that during the prenatal growth period, most mammals grow their brains and bodies according to the same pattern with the same ratio of brain size to body size at corresponding time points, irrespective of eventual adult size (see also Holt et al 1975). The sharing of a nearly identical segmental growth pattern across wide ranges of sizes and shapes is quite remarkable and suggests that most
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mammals share a very conservative embryological brain growth plan (Deacon 1990a, Finlay & Darlington 1995). The basis for this developmental regularity remains unknown, but this very conservative pattern of mammalian brain/body growth could be the major factor determining the regularity of adult brain/body patterns as well (Deacon 1990a). Similar growth curves, which are aligned during early development and merely uniformly expanded or contracted with respect to one another, could produce the pattern of brain/body allometry observed between adults of different species (Figure 2A). Below, I review genetic evidence that suggests this is the case. Although this embryonic constraint contributes to the regularity of brain/body scaling, it need not contradict additional functional arguments, but it cannot be ignored. One deviant group, however, is the primate clade. Among anthropoids (from which most data come), brains and bodies grow along a trajectory that is parallel but shifted from that of other mammals (though cetaceans and elephants are also similarly shifted) so that at every growth stage these primates have a higher ratio of brain to body size (Count 1947, Deacon 1990a, Holt et al 1975, Martin & Harvey 1985, Sacher 1982; Figure 2A). Conservatism of the growth pattern is still evident, because growth curves still resemble those of
Figure 2 (A) The common shapes but different intercepts of developmental brain/body growth curves distinguishing primate and nonprimate mammals shown in a slightly idealized comparison of four species. The left graph schematically depicts the general pattern exhibited by brain/body growth throughout life, showing a two-phase pattern caused by the cessation of brain growth earlier than the rest of the body. P, primate fetal growth pattern; NP, nonprimate pattern; the arrow indicates the primate shift. (B) Comparison of brain growth in three mammals shows all following the same growth trajectory prenatally. This demonstrates that the left-shifted primate growth is not the result of faster brain growth but reduced body growth. Note that human beings follow this pattern also.
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other mammals except for this shift. This primate shift cannot be explained in terms of postnatal growth differences and therefore must represent an independent mode of encephalization. Correspondingly, we should be suspicious of efforts to lump explanations of primate encephalization with those of encephalization in other mammal groups. So what is the likely mechanism underlying the primate shift? It could be the result of either accelerated brain growth or decelerated postcranial growth. This latter question can be resolved by comparing absolute growth rates as opposed to relative growth rates. Data for this comparison have also been available for decades (e.g. Dickerson & Dobbing 1967, Dobbing & Sands 1973, Holt et al 1975, Widdowson 1981). When brain and body growth rates are compared between species on the same time scale, primate and nonprimate species differ in total body growth rates but not brain growth rates (Figure 2B). For example, prenatal brain growth in human beings, macaques, and pigs proceeds at essentially the same rate, whereas body growth rates for macaques and human beings overlap but are significantly below those for pigs. This appears to be generalizable to most comparisons between primates, on the one hand, and ungulates, carnivores, and rodents on the other. The clear implication is that primate encephalization is the result of a shift in postcranial growth processes, not a modification of brain growth! While this has been hinted at in a number of studies over the past few years (Deacon 1990a, Holt et al 1975, Passingham 1985, Sacher 1982), there does not appear to be wide appreciation of its consequences for interpretations of primate (and human, see below) encephalization. If primates have big brains merely because they have small bodies, we cannot presume that this represents an evolutionary trend driven by cognitive demands. Indeed, primate encephalization is in this one respect analogous to the encephalization produced by dwarfism, where it does not appear to produce a cognitive advantage. But this comparison is also superficial. Unlike the way dwarfism affects postnatal brain/body growth patterns, the primate shift is the result of a cranial/postcranial growth difference that can be followed back to very early embryonic stages. Therefore, the effects of the primate shift in growth are a factor throughout all stages of brain development. This is undoubtedly an important difference, and it is the subject of the last section of this review.
Is Human Encephalization an Extension of the Primate Trend? Before considering the likely significance of the timing of brain and body growth processes on brain function, it is informative to compare human encephalization to these other forms. Here, again, the comparison of ontogenetic growth processes provides critical information. Although in texts on human
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evolution it is generally suggested that the hominid increase in brain size continues a trend characteristic of primates in general, the ontogenetic comparison demonstrates that in terms of underlying mechanism this is not the case. Human brain/body growth does not deviate from that of other primates during the prenatal phase; it merely prolongs this phase in a way consistent with size differences in general, except that the human brain/body growth curve is truncated along the postnatal phase (Figure 3). Superficially, this resembles the pattern characteristic of dwarfism: typical brain growth with truncated postnatal somatic growth. But when brain and body growth rates are compared with similar-sized primates (e.g. chimpanzees) it is apparent that for the size of the adult body, human beings do not have stunted growth. The difference is that human brains grow as though they were in an ape with a very much larger body (in excess of 1000 lbs). The locus of the ontogenetic deviation from the typical primate pattern is within the head. This is also clearly demonstrated by the fossil record. Hominid body sizes have not decreased to produce human encephalization. Stature increased significantly during the transition from Australopithecus to Homo. The difference in growth process that produces increased primate encephalization over and above that typical of most other mammals is not the same as that which produces increased human encephalization over and above the typical primate pattern. Human brains and bodies grow at a rate that would be predicted for the adult sizes reached by each, respectively, except that human brains continue to grow as though in a much larger body longer
Figure 3 Somewhat idealized graphs showing the human brain/body growth pattern as compared with the pattern seen in dwarfism (A) and with other species of primates (B) (H, human; C, chimpanzee; M, macaque monkey). Squares and diamonds indicate adult values of brain and body weight. Dwarfism and giantism diverge from more typical growth curves after most brain growth is complete. Human fetal growth follows the fetal primate trajectory, but the fetal brain growth phase is comparatively extended (dashed arrows). The triangle in (B) indicates body growth predicted in a typical ape with human brain size. Human body growth is similar to the chimpanzee pattern, but brain growth continues as if in a larger primate.
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than would be expected for our postcranial growth. This human pattern is distinct from dwarfism or the primate postcranial reduction. Comparing the evolutionary causes and correlates of encephalization across each of these major species differences runs the risk of analogizing entirely unrelated phenomena. Quite different growth processes are responsible for the encephalization of chimpanzees, Chihuahuas, and human beings with respect to their respective phylogenetic contexts. Unless we can say with certainty that only the resulting size relationships matter for questions of brain organization and brain function, we are not justified in using cross-species correlations between encephalization and other adaptational variables to extrapolate the causes of human brain evolution. Until we understand the functional consequences of these developmental differences, we can only treat such correlations as interesting coincidences. Assumptions about the significance of differences in encephalization, about the relevance or irrelevance of total brain size, and even about the centrality of encephalization to human cognitive evolution are all placed in doubt by these differences. We need an explanation of the mechanisms behind these different modes of growth and an account of their effects on brain organization before we can go beyond merely correlative stories. The deviation in size of the human brain is the most robust clue to what is unique, but it is not clear that increased relative brain size itself is the only or even the primary feature that is represented by this difference. The question is whether encephalization achieved by substantially different modifications of brain and body growth produces different neural architectures with different functional consequences. There are good reasons to suspect that it does.
DEVELOPMENTAL NEUROBIOLOGY How Species-Specific Are Neural Circuit Plans? Although quantitative differences in overall brain size stand out as obvious markers of primate and human evolutionary trends, it has long been assumed that species behavioral and cognitive differences might also be mediated by the presence or absence of distinctive brain structures and by species-specific differences of connection patterns. Beyond general questions of brain growth, the obvious question is, What is the level of detail and specificity of the information that distinguishes patterns of cells and connections in one species brain from another? Is there developmental evidence demonstrating species-unique developmental signals that are responsible for unique adult structures? Many structural and connectional details seem highly similar in the brains of different mammals, and have suggested that there is considerable connectional conservatism across mammals. Only recently have we begun to discover why.
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Figure 4 Evidence for conserved axonal guidance and Darwinian competitive processes in brain development. (A) Transplanting cortical cells from a pig fetus into an adult rat brain shows that both species use the same signals to guide axon growth to targets. Top: normal connections (Isacson & Deacon 1996). Bottom: Despite placing the graft into an inappropriate location, axons find appropriate targets. (B) During normal development of cortical output connections, axons are initially overproduced and nonspecific (top), and are later culled (bottom) (O’Leary 1992). (C) Removing inputs destined for specific thalamic targets can allow other inputs to take over the vacated region and induce this part of the thalamus to transmit different sensory information to the cortex, thus changing its functional organization (Frost & Metin 1985, Sur et al 1988).
Although common sense suggests that quite different signals might underlie different species’ neural circuit designs, recent studies of axonal growth and guidance suggest otherwise. In fact, initial axonal growth from one brain structure into others may be even more conservative in evolution than the trends in brain and body growth. Although few of the molecular details are currently known, already there is evidence that highly conserved proteins (such as the netrins and homeotic gene products) guide axons along specific pathways in distantly homologous structures in animals as different as roundworms, insects, and mammals (e.g. Friedman & O’Leary 1996, Kennedy et al 1994, Colamarino & Tessier-Lavigne 1995). Further indirect evidence for conservative connectional signaling has been provided by transplantation experiments where tissue from one species’ brain is allowed to grow in another species’ brain. Experiments in which Japanese quail embryos were dissected and part of their very immature neural tissue was grafted into the corresponding regions of embryonic chicken brains (lacking this part) have shown that not only do the grafts link up with the host brain but that individual animals born with such a chimeric brain behave in ways that indicate that the neural connections have
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conferred appropriate function (Balaban et al 1988, Le Douarin 1993). Further evidence that the same or highly similar signals are used to initially guide different species’ neural output branches to their appropriate targets is also provided by experiments transplanting pig fetal neurons into adult rat brains. Using species-specific markers for axons, we have demonstrated that pig axons from a variety of neuronal cell types and implanted into a number of different brain structures can use rat host guidance cues to grow axons to targets that are appropriate for the transplanted cell type (Isacson & Deacon 1996). Although not highly precise in their target specificity, axons can take elaborate routes to grow around and past nontarget structures through developmentally anomalous pathways to terminate in target structures (Figure 4A). This provides an unexpected challenge to brain evolution theories. If axon guidance signals are highly conserved from species to species, they are not likely to account for significant differences. One might counter that only these early, generic, and not highly specific growth signals are conserved and that species differences are more likely at the microscopic level, with genetic variants producing fine differences in network patterning. However, there is also evidence that much of the fine wiring of the brain that produces the complex topographies of sensory analyzers and high-level cognitive differences is not prefigured in specific genetic instructions.
Developing Brains Adapt Themselves to Bodies It has long been suspected that during the earliest stages of development, brains are particularly sensitive to experiences. It has also been known that young brains are remarkably more resilient in recovering from major injury. Both ideas are summed up by the claim that immature brains are far more plastic than mature brains. However, what began as investigations into the mechanisms of this plasticity has led to findings that have changed our whole understanding of how brains develop. This plasticity is an artifact of a developmental process that employs a great deal of information that is extrinsic to any individual neural cell to determine location and function within the vast network of other neurons. In general terms, evolution has eliminated any redundant architectonic information that it could from the mammalian genome in favor of using free structural information ubiquitously present in the developmental context itself. This has allowed brains to be much more responsive to adaptive challenges driving major changes in morphology. Theoretically, one might have predicted that every mutation that resulted in a modification of limb architecture, an increase or decrease in muscle mass, or a change in the size or relative position of a sensory organ, would require at least one (and possibly many) corresponding mutations of the peripheral and
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central nervous systems to keep it from being malfunctional. In contrast, however, it appears that no such matching pattern of mutations is necessary, and may be relatively rare. Developing neural systems adapt to the body much as species adapt to a surrounding ecosystem by utilizing overproduction, unspecified variation, competition, selective elimination, and perpetuation of only a fraction of the original variants. There are two levels of this process that are crucial to matching the central nervous system to the needs of an unprespecified body (Cowan et al 1984, Deacon 1990b, Finlay et al 1987, Purves 1988, Wilczynski 1984). The first involves the initial overproduction of neurons that are later selectively culled away by programmed cell death (apoptosis). The second involves a related overproduction and underspecification of axonal growth and connectivity that is also subsequently pruned as axons compete with one another for limited synaptic targets (Figure 4B). Both are highly reminiscent of Darwinian selection processes and are variants of processes that are also used elsewhere in the developing embryonic body. The importance of neuronal overproduction and programmed cell death was first demonstrated by investigations of motor neuron development in the spinal cord and in spinal ganglia (see reviews in Katz & Lasek 1983, Purves 1988, Williams & Herrup 1988). Early in fetal development, far more motor neurons are produced than will persist into maturity. All grow axons into the
Figure 5 (A) Stereoscopic vision in mammals is supported by interdigitated cortical maps of the visual field from each eye. Segregation of inputs (different shades of gray in cortex) develops in response to patterning of inputs during development. (B) Spontaneous emergence of an analogous interdigitated visual field mapping in the optic tectum of a frog with a transplanted third eye (Law & Constantine-Paton 1981).
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periphery, guided by relatively generic signals to a predefined class of target muscles. Once in the periphery, axons compete for connection with individual muscle fibers, which ultimately will allow only terminals from one motor neuron to develop mature neuromuscular junctions. In the ensuing competition for muscle contacts, a large fraction of motor neurons will fail to maintain any contacts, and this will eventually set in motion processes within the cell that cause it to self-destruct. Elimination of the unconnected cells produces a precise matching of muscle and motor neuron populations, post hoc. In evolutionary terms, this allows variations of neural and muscular systems to occur almost irrespective of each other (i.e. without the need for high-level regulation of different gene systems with respect to one another) and yet guarantees coordination of function. Thus, novel adaptive responses, produced by mutations that shift the distribution of muscle masses within the body, would not require any corresponding neural mutations to match, and vice versa. Over the past decade, it has become evident that programmed cell death is a widespread phenomenon that probably plays an analogous role in matching neural populations throughout the developing brain. But this contributes more than just a matching and population sculpting function. Coupled with its corollary—axonal competition—it is a major factor in neural network pattern formation. Axonal overproduction and pruning of connections have been shown to play critical roles in circuit patterning all levels of CNS development and in the delineation of major subdivisions of cortical and subcortical structures (Figure 4B). Thus, for example, severing the optic tract at a point before complete innervation of the thalamus causes axons from other sensory systems to innervate the newly available targets and consequently alters cortical areal topography and connectivity (e.g. Frost & Metin 1985, O’Leary 1992, Sur et al 1988; Figure 4C). The power of this “connectional Darwinism” to drive pattern formation is perhaps most vividly demonstrated by the neural adaptation for binocular visual perception. Crucial to both primate and carnivore vision is the ability to see depth by integrating information about binocular disparity, i.e. the difference in angle of gaze to the same object from each eye. The perceptual experience of depth is computed on line in the visual cortex of these mammals because of complex overlapping interdigitated projection maps arriving from each eye. This composite map is like a system of zebra stripes in which the alternating white and black bands represent the input from each eye, respectively, and in which adjoining black and white regions are receiving information about the same position in the visual field (see Figure 5A). The extent of overlap and interdigitation depends on the relative convergence of the eyes in the head, so the map pattern differs for different species and ranges from essentially no overlap in many rodent brains to nearly complete overlap in the human brain.
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Given the complexity of this map structure and the precision with which it must be formed in order to function, it would seem to be a candidate for precisely prespecified organization. Shortly after this functional architecture was discovered, however, it soon became evident that its pattern could be significantly modified by simply manipulating extrinsic signals. For example, blocking visual signals from one eye during a critical period during early development could substantially bias the map so that the uncovered eye would be far more extensively represented, and if blocked long enough (or if one eye was removed), the entire primary visual cortex could become dedicated to one eye. Varieties of other developmental manipulations in animals and, more recently, computer simulations have demonstrated that this complex map architecture can be induced to develop under quite general conditions. All that is necessary are weakly topographic connection patterns and a Darwinian-like competition between axons that is biased with respect to the degree of synchrony of input signals from the two eyes. This signal patterning is provided by the only slightly different images projecting onto the two retinas. The power of this developmental selection process to generate complex architecture is most unequivocally demonstrated in cases where the possibility of genetic instruction can be ruled out. One remarkable example is provided by a study in which additional—or third—eyes were implanted into the heads of embryonic frogs, between their existing eyes (Law & Constantine-Paton 1981). During development it was found that this extranumery eye extended axons to the optic tectum (a dorsal midbrain cortical-like structure that serves as the primary visual center in frogs) along with axons from the two normal eyes. During development this extra eye relayed information that was partially redundant with information from the closest normal eye. The result was the production of a pattern of connection with interdigitated eye-specific stripes, analogous to the ocular dominance stripes in mammal cortices (Figure 5B). Normal frogs, however, have essentially no normal binocular overlap and not even any phylogenetic history (so far as we know) of binocularity. The stripe pattern emerged de novo merely in response to the generic features of the competitive process and the systematic biases produced by input signals.
How Do Deviations in Brain Size Affect Brain Development? How these two developmental processes might interact with relative size factors to produce brain differences is demonstrated by an animal with an extreme sensory adaptation that alters the proportions of different sensory inputs from an early stage in development. The blind mole rat (Spalax) lives underground its entire life and develops only tiny vestigial eyes. Recently, anatomical studies have demonstrated that ascending neural connections from the auditory and tactile sensory systems have essentially displaced visual connections in the
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major visual nuclei and visual cortex of this rodent (Doron & Wollberg 1994, Heil et al 1991). It is probably the case that the diminutive visual projections are simply outcompeted during early development by these other projections to produce a substantially different functional recruitment of brain structures than in a typical rodent. This demonstrates the power of quantitative reorganization of body structure to drive correlated neuronal reorganization. Even more subtle variations of the size of external receptor systems can alter normal cortical organization (e.g. Killackey et al 1994). Depending on the extent, distribution, and timing of growth differences, we should expect that critical competitive processes will be biased differently. For example, the reduction in somatic growth that is mostly exhibited postnatally in dwarfism occurs largely after most neural developmental adaptation processes have been completed and so can be expected to have only a modest effect on the distribution of cell populations and connection patterns, whereas changes in somatic proportions that occur earlier in development (as in the blind mole rat or as in primates), should have far more significant effects on brain organization. Currently, there is insufficient comparative neural morphological information to determine whether patterns of neural connections directly correlate with patterns of brain and body growth. We are therefore not in a position to offer more than theoretical predictions based on quite general principles and analogies to experimental conditions. However, these new developmental data provide some very important clues for guiding future research into more detailed assessments of brain structure evolution. In fact, this represents a research topic that would benefit from combining the methods of modern developmental neurobiology with traditional quantitative morphology of brain structure and growth processes. Despite a limited empirical database from which to predict the links between allometric growth trends and brain structure patterns, it may be possible to offer some educated guesses about what to expect in response to large-scale allometric deviations. The effects of primate and human encephalization are cases in point. Consider, for example, that primate cranial/postcranial proportions are shifted from those characteristic of most other mammals from the very earliest stages of fetal growth. Because of this, disproportions in cell death patterns and axonal recruitment patterns likely ramify throughout the developing primate nervous system. In very general terms, primates ought to have proportionately less of their brains dedicated to projection systems that are directly associated with sensory and motor functions, when compared with nonprimates with similar-size brains. Nonsystematic claims to the effect that primate brains contain a smaller proportion of primary sensory and motor cortex than nonprimates have been around for generations, but systematic analysis of this
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and of the possible correlation with growth and body proportion relationships awaits future work. Nor are there systematic behavioral data sufficient to determine whether primates as a group exhibit different cognitive biases as a result (perhaps causing them to be less stimulus-driven during learning), as distinct from some sort of general intelligence advantage. Finally, with respect to the human brain, the uniqueness of the pattern of human brain/body growth suggests that the pattern of internal reorganization of human brains is unlike that correlated with either form of increased encephalization due to postcranial reduction (i.e. dwarfism and the primate shift in growth). Because human brain/body proportions do not deviate from the general primate pattern during the major portion of prenatal development, it is likely that human/primate brain differences are less substantial than primate/nonprimate differences. However, the more prolonged immaturity of the brain with respect to body growth likely produces more widespread reorganization than does dwarfism. But unlike dwarfism or primate body reduction, in human beings it is the brain that is the locus of the change in growth and not postcranial structures. To appreciate this difference we are forced to go beyond simple growth and size comparisons and to consider the primary ontogenetic mechanisms underlying them.
Which Genes Are Most Relevant? Perhaps the most revolutionary information about brain evolution and growth has come from the study of gene expression during early development. Over the past decade, the use of a molecular technique called in situ hybridization to identify specific localized RNA production in embryos has demonstrated that a diverse class of regulatory genes, generally called homeotic genes, interact to produce the initial segmental patterning of the body by specifying cell fates, and major growth fields. (For an overview of current research and theory in developmental genetics, including a discussion of homeotic gene function and evolution, see Raff 1996.) Perhaps the most remarkable feature of homeotic genes is their conservatism of both nucleotide sequences and developmental functions. Homeotic genes in animals as diverse as flies and human beings exhibit high levels of sequence homology, are responsible for determining body structures in corresponding locations in the developing body, and to a certain extent can even substitute for each other in cross-species transgenic experiments (for example, substituting mammal genes in mutant fly embryos to restore developmental functions). An important characteristic of homeotic genes is that they subdivide the developing body both in the dorsal-ventral axis and in the anterior-posterior axis, and into semiregular segments from anterior to posterior, providing the initial subdivision grid within which later embryonic construction will take place. The overlapping patchwork of different gene ex-
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pression domains defines each subdivision in terms of an explicit combination of genes expressed only at that site, and this in turn appears to specify regional cell differentiation. It may be possible to take advantage of the conservatism of this positional expression of homeotic genes to home in on the genes behind some of these major morphological shifts in brain growth and morphology. This approach has been successful in identifying homeotic genes associated with mutations involving other morphological abnormalities. For example, a recent study of human synpolydactyly (which produces extra digits and abnormal growth and attachment of the digits) took advantage of the known expression of the Hox13 genes localized to the hand during its formation in other vertebrates to narrow the genetic search to that region of the genome. This ultimately led to the discovery that mutations of this gene are responsible for the morphological abnormality. By analogy, identifying the embryological locus of differences in brain-body growth relationships or brain structure relationships may provide the crucial clues to the underlying genetic differences that produce them. Of particular relevance to the problem of brain size differences are homeotic genes that play critical roles in establishing the boundary between head structures and postcranial structures and between the midbrain and brain stem. This locus in the developing embryo has long been known to roughly correspond to the site of the initiation of neural tube formation (identified with the Spemann organizer, which is the point in the developing early embryo where mesodermal tissue initiates the formation of the neural tube from ectodermal tissue, and without which no nervous system would form). At the midbrain/ brain stem transition there is a dichotomy of developmental geometry: Behind this point, there is a regular linear pattern of gene expression. In front of it there is a less linear pattern which forms the head (partly organized with respect to more localized mesodermal structures called placodes). Not surprisingly, this point in the embryonic body seems to be a critical juncture with respect to control of cranial/postcranial growth patterns. A few homeotic genes, initially identified by their role in fly head formation, appear to play particularly direct roles in determining where this transition between brain and brainstem will occur during development. Two relevant examples are designated Otx1 and Otx2 in mammals and are expressed in the brain—just in front of the midbrain/hindbrain division—at the time these embryonic decisions are made (Simeone et al 1992). Studies with frog and mouse embryos in which expression of an Otx gene is modified demonstrate its potential role in brain size determination. In frog embryos, the Otx2 homologue (called X-Otx2; X for Xenopus) is initially expressed throughout the undifferentiated embryo, then progressively restricted in its expression to more and more rostral regions. Its expression, however, can be manipulated by ex-
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Figure 6 (A) Regions of the developing human embryonic brain that must have undergone additional early stem cell production to produce the adult pattern of shifted proportions of enlarged dorsal forebrain structures. The overlapping expression regions of Otx and Emx genes are indicated by dashed lines above the embryonic brain to show the correspondence with expanded regions (+). The arrow indicates the boundary between brain and brainstem with Hox genes expressed below (both dorsally and ventrally) and Otx and Emx genes expressed above (mostly restricted to dorsal structures). (B) Schematic diagram showing how the adult human brain diverges from allometric prediction for a “typical” primate brain. Structures indicated with “=” are roughly predictable from human body size, whereas structures indicated by “+” are greater than predicted (correspondences with embryonic brain gene expression patterns are indicated by relative lightness/darkness). The proportions of one peripheral input—the eye—with respect to the brain are shown to exemplify how this disproportion is reflected in connectional disproportions and developmental axonal competition (dark gray arrows—reduced—compared to light gray arrows—enlarged—to indicate relative numbers of projections).
ternal signals or by direct insertion of the gene product into the embryo. In embryos with higher than normal levels, this brain/body boundary develops further back, and in embryos with lower than normal levels it develops further forward on the body axis, producing relatively larger or smaller head and brain structures, respectively (Boncinelli & Mallamaci 1995). A parallel effect is seen in transgenic mouse embryos in which both Otx2 alleles have been damaged. These embryos exhibit significant reduction and abnormalities of the developing head and brain (Matsuo et al 1995). Of course, the Otx genes are not the only genes involved. The expression of other genes and many other correlated molecules also contribute, and they may also influence expression of Otx. Nevertheless, genes such as Otx and their local interactions will likely provide the critical clues to the mechanisms underlying shifts in brain/body proportions.
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Although we are a considerable way away from possessing sufficient comparative genetic information of this sort to answer some of the encephalization questions posed by primate and human evolution, the distinctiveness of the embryological growth patterns in each case does point to molecular correlates likely to be involved in some way. To discover which homeotic genes are involved, we need to precisely identify the locus of the divergent growth trend and then use this to narrow the search to the appropriate gene expression domain. For example, the pattern of the primate deviation from the typical mammalian brain/body growth trend suggests that a shift in the cranial/postcranial transition, such as produced by increased Otx2 gene expression (as in experimental frogs), might be relevant, or perhaps that postcranial homeotic gene expression might be involved in body segment reduction. In human development, the locus of the difference is the brain, but does it involve the whole brain? If a more precise localization of the differences in cell production can be identified within the human brain, a better match with homeotic gene expression might be possible. This again is where morphometric studies and neural development may be able to provide complementary data. Quantitative analyses of existing brain structure data in primates have suggested that human brain enlargement is not equally distributed among all structures, even when corrected for brain size. Although different analyses have provided conflicting predictions, and a systematic study of necessary breadth has not been done, data comparing human and nonhuman primate brain structure volumes suggest that dorsal brain structures (including cerebral cortex and cerebellar cortex) may have enlarged out of proportion to ventral brain structures (Deacon 1988, 1997). It may not be just coincidence that the Otx genes, as well as others implicated in brain size and normal forebrain development by experimental studies (Matsuo et al 1995, Simeone et al 1992), are differentially expressed in dorsal forebrain structures (Figure 6). Further examination of the expression of these and related genes in human as compared with other primate embryos may help to isolate the mechanisms underlying this critical human adaptation.
CONCLUSIONS In summary, the developmental linkage between comparative brain morphometry and the competitive processes that influence the specification of axonal connectivity suggests that what is uniquely different about human brains is not just their quantitative organization, but more importantly the consequent shifts in connectivity among brain regions. Following the analogue of animals like the blind mole rat—whose central nervous system is radically modified by changes of the relative quantity of peripheral inputs—we can predict that these
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human disproportions of forebrain structures have produced a reorganization of connectivity from the inside out, so to speak. Two significant predictions include (a) an increased central projection onto visceromotor systems such as control laryngeal and respiratory muscles (essential for speech) and (b) an increased prefrontal cortex with more extensive and more widespread connections (likely crucial for symbolic learning and an increasing predominance of cognitive “executive” functions) (Deacon 1997). Because these neurological consequences are coupled to quantitative changes, it may also be possible to use allometric evidence from fossil material to estimate the evolutionary appearance and development of these functional capacities. For over a century scientists have studied brain evolution as a problem of gross functional morphology. Recent developments in the neurosciences provide a wealth of new information about brain development that challenges and augments this classic approach. Presumed functional correlates of brain size differences, theories of encephalization, and the plausibility of highly modular species-specific changes all must be carefully reexamined in the context of this information. Although well-accepted claims about brain evolution in our lineage may be put in question as a result, the value of comparative morphological analysis takes on a new significance as a guide to more detailed developmental and molecular studies of the brain. Achieving this new synthesis of quantitative morphology, developmental biology, and genetics is key to unlocking the mystery of what makes human brains human. Visit the Annual Reviews home page at http://www.AnnualReviews.org.
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