E pluribus Unum: Too many unique human capacities and too many theories




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E Pluribus Unum:
Too many unique human capacities and too many theories
Barbara L. Finlay

Department of Psychology

Cornell University

Corresponding author:


Barbara L. Finlay

Department of Psychology

Cornell University

Ithaca NY 14853

USA
Phone 1-607 255 6394

Fax 1-607 255 8433


blf2@cornell.edu

Plausible adaptive scenarios designed to account for the evolution of large brains in humans not only successfully account for it, they do so many times over. We have no shortage of hypotheses. Indeed, we have too many, and they are probably all correct, at least in part. The problem of accounting for human brain evolution is not choosing which one of the many ways our behavior differs from our nearest relatives is the essential one, but to develop an explanatory scheme that encompasses all of them.

In this essay, I will argue that it is the coordinated enlargement of the entire human brain that gives the best account of the rapid emergence of our diverse capabilities. However, I will first briefly review the range of proposals regarding the “first causes” of human brain enlargement.

Scenarios

Accounts of human evolution fall into various classes. Some appeal to particular behavioral adaptations, others to organizing principles particular to the human brain, and others to a release from general constraints. Each explanation has been argued to be the critical factor, or the first factor in the causal evolutionary chain. As critical human abilities are laid out, note how completely their functional domains encompass the surface of the cortex, given how we presently understand structure-function relations within the cortex.



Behavioral adaptations. The first domain is social living and various versions of the “social brain” hypothesis (Byrne & Whitten, 1988; Dunbar, 1998). The manifest benefits of coordinated group living for resource acquisition and sharing, protection from predation, and distributing the demands of raising young are the basis of the power of these arguments, though theories vary widely concerning which aspects of perception or cognition are most central to the “social brain”. Some researchers have drawn attention to the motor control aspects of facial control and oral mobility, which could have enabled concomitant perceptual changes leading to the appreciation of facial and verbal nuances (Stedman et al., 2004; Varga- Khadem et al., 1995). The hierarchical structure of kin and group relationships, and the various operations required to understand embedded and transitive relationships, have also been likened to language structure. More recently, economics has come to the fore, examining the complex system of rules, mental accounting, and reward structures required to enable “cheater detection” and barter that underlies otherwise unaccountable human altruism (Tooby & Cosmides, 1992). This form of social accounting entails more than merely immediate accounting. It also entails a “theory of mind” to represent the intention of agents (Baron-Cohen 1997) as well as a procedure for mapping events and outcomes onto their likely causal agents (Wegner, 2002). In another domain, an interesting coupling of sociality and longevity has emerged. The simple presence of another helper has been underscored by showing that grandmothers improve the reproductive success of their daughters and sons (Lahdenpera et al., 2004). However, if offspring benefit as much by the knowledge of the elders as they do from their presence (which is likely, but yet not demonstrated), additional brain space would be needed for seventy years of memories.

Another highlighted domain is finding (or making) food, including both hunting and foraging (Stanford, 1999). Hunts could have been made more profitable and less dangerous by symbolic representations that improved hunting strategies. Falk (2004), for example, has observed that the communicative but not necessarily the symbolic aspect of language (e.g., mother’s speech to infants) might allow for better gathering because females could have put babies down while still retaining contact with them. Tools, from transitory textiles to enduring stone, are also central in various applications from food gathering, hunting, and food storage to preparation. Tool invention and construction underscores the importance of manual dexterity, spatial representations of objects and their transformations, and learning and planning (Ambrose, 2001).

A final domain of human behavioral expertise is long-term planning and modulating immediate motivations in the service of long-term goals. Aiello and Weaver (1995), for example, point out in their “expensive tissue hypothesis” that the reciprocal relation of brain size and intestinal length probably required brainier primates to find fancier foods, that is, to remember the spatial and temporal layout of seasonally fruiting trees and other plants, which would have required both memory and planning. Many more analytical aspects of coordinating present wants with future needs have been discussed, particularly in the context of the special functions of the frontal lobe, working memory, and response inhibition.

Rubicons. A different kind of argument has also been made for human evolution, namely that a single organizational change might underlie diverse abilities rather than a single catalyzing and altered behavioral domain of adaptive importance. The central candidate here is, of course, language. It has been argued that a feature of grammatical structure of language (recursion) is the critical difference that enabled language, and that language is in turn the critical vehicle for most major, subsequent cognitive changes (Hauser et al., 2003). This argument can be broadened (see Deacon, 1997) to argue that it is not language specifically, but symbolic ability in general that is the essential ingredient. Connectionist theorists have also proposed a version of the Rubicon model, in which a critical amount of processing power, working memory, or long-term memory might have produced a sudden acceleration in acquisition of language specifically and cognition more generally (Elman et al., 1995).

Release from constraints. Constraints, defined as resource limitations, are fundamental to any evolutionary argument. Rather than the generalized form of constraint, I use the term to mean independent changes in some feature of morphology or life history that indirectly permitted increases in brain size or behavioral complexity. Examples include Falk’s “radiator hypothesis” (1990), which suggests that a change in brain circulation following upright posture allowed enough brain cooling to allow for rapid brain expansion. Similar arguments have been made that a change in jaw morphology might also have permitted cranial expansion.
How Brains Change

Mammalian brains tend to change in a highly coordinated but not necessarily proportionate fashion. The cortex is probably as large as it should be in humans (as predicted from cortex size in other mammals), as are the subdivisions of the cortex. Which brain structures have enlarged at the fastest rate is strongly predicted by the order of neurogenesis, which is a measure of the rate at which precursor pools can proliferate before they become committed to their particular neuronal fate. This order is highly conserved across all mammalian radiations, such that a simple formula can be written to transform any mammal’s developmental schedule to any other (Finlay et al., 2001). The duration of precursor genesis of each brain part can be directly linked in turn to the basic axes and segments of the embryonic brain. The structures that become disproportionately large when brains enlarge are those that lie on the most anterior and lateral parts of the original basal and alar axes, particularly in the forebrain. Which parts of the brain enlarge in response to evolutionary pressures can therefore be predicted by a structural variable that explains a vast majority of the variance, but not a functional one. The traditional view that strict structure-function links are the basis for selection (for example, selection on auditory cortex size in an animal advantaged by speech) is not supported by the preponderance of data on brain change. No mammal has found it advantageous to enlarge any brain structure preferentially over the cortex.

The observation of predictable but disproportionate growth can be over-interpreted to infer that a late-generated, disproportionately enlarging structure such as the cortex might have no functional specializations and, hence, must be a general-purpose processing device in light of the fact that the cortex varies in evolution as a unit. The decoupling of tight structure-function links in the evolution of brain parts, however, merely requires that there be mechanisms for introducing functions into structures that have been made larger by rule, either in evolutionary time, developmental time, or “real” time. In the case of evolutionary time, variability that produced general brain enlargement could have been coupled with mutation or variability that directed new function into the space available through, say, a difference in connectivity or in the time constants of neurotransmitters. This would have resulted in a larger, functionally specialized region not necessarily different from the larger functionally specialized area arising from the more traditionally conceived selection processes that have been proposed to be produced in a different sequence.

Introducing new functions into multimodal regions such as the cortex in developmental or real time, however, implies an initial architecture that can be adapted to various functions. Innumerable examples of functional plasticity in most regions of the cortex indicate that this is true, one notable example being the activation of the visual cortex by Braille reading in the early and late blind (see Burton et al., 2002). In fact, an evolutionary history characterized by predictable/disproportionate structural proliferation would favor the survival of those animals possessing mechanisms to reallocate functions into quiescent regions of the brain. Any single one of the perceptual, cognitive, or motor modifications of human/primate behavior mentioned above could have provided the initial leverage to increase brain size. However, the possibility of dynamic reallocation of brain structure to function over every time scale now becomes even more important, particularly when one considers how behavior and/or culture transforms human niches.



Particulars of history and generalities of mechanism

I am now prepared to argue that all of the theories listed at the outset of this chapter are probably true in part, given that each one can be plausibly linked to greater fitness in our ancestors. The mechanism might allow them to all be true is the coordinated enlargement of the brain. Certainly, there must have been some sequence in the accretion of cognitive abilities, but we are unlikely to be able to determine anything but the grossest outlines of any particular sequence. Arguments over what the exact first step was in hominid evolution are not of great interest, and they distract attention from the startling range of behavioral changes that have accumulated in short evolutionary time.

I conclude the chapter with a cautionary tale about an evolved feature in primates that we have learned a fair amount about at all levels of analysis and for which we have developed a plausible evolutionary history. This is trichromatic color vision (often erroneously called “color vision”). Trichromacy appears to have evolved at least three times, once in Old World monkeys (our direct ancestors) and twice in New World Monkeys (Jacobs, 1998). It does not appear in other mammals.

What permitted the profusion of this ability? Adequate selection pressure for the ability would appear to have always been available. Any animal evolving in visually complex forested environments, could take advantage of the obvious benefits of greater chromatic acuity in discriminating fruits and foliage, as well as more subtle and general benefits in scene segmentation. So far, there doesn’t seem to be anything genetically different about the brains of trichromat primate species (especially considering that there are species of New World monkeys in which individuals can be dichromats or trichromats by chance, depending on which opsin photopigments are produced in their retinas). The difference in photopigments is very tiny, involving the substitution of one or two amino acids in critical spots that then change the best absorption of the opsin molecule. These changes are best understood in terms of the normal jitter seen in protein composition in genetic drift. What allows this genetic jitter to be useful to primates is the presence of a second visual system feature that only primates possess (see Finlay et al., 2005). This is the specialization for high-acuity central vision, the fovea, where the high density of cones and ganglion cells in central gaze has a one-to-one convergence ratio, unlike the several-to-one ratio in other mammals. The changed opsin absorption of a population of cones can thus find its way undiluted into the central nervous system, where general-purpose comparators allow its application to the diverse uses of color vision.

What, then, is the cautionary tale? We can certainly understand the evolution of trichromacy in general terms of multiple uses of color vision in complex environments, the ability of the visual cortex to extract difference signals of all sorts, and normal drift in gene transcription. The causal domains invoked include levels of analysis ranging from adaptive behavior to the genome. The causal forces of all these features are inadequate to account for the emergence of trichromacy, however, without the presence of a feature of visual organization, the fovea, which antedates trichromacy, is independent of it, and is adaptive even without it.

Trichromacy is trivial in complexity in comparison to understanding human cognition, and the evolutionary history of trichromacy could never have been deduced from the types of information typically used to speculate about human cognitive evolution. We will never know details of sequence, and we should stop arguing about it. What we can hope to know is how the multifunctional human cortex can be situated in a broader view of how brains change in evolutionary time.



References


Aiello LC, Wheeler P (1995) The expensive-tissue hypothesis: the brain and digestive system in human and primate evolution. Current Anthropology 36:199-221.

Ambrose. S. (2001) Paleolithic Technology and Human Evolution Science 29: 1748-1750

Baron-Cohen, S. (1997) Mindblindness: An Essay on Autism and Theory of Mind

1997 Cambridge, MA : MIT Press

Burton H, Snyder AZ, Conturo TE, Akbudak E, Ollinger JM, Raichle ME (2002) Adaptive changes in early and late blind: A fMRI study of Braille reading. Journal of Neurophysiology 87:589-607.

Byrne, R.W., & Whitten, A. (1988). Machiavellian intelligence: social expertise and the evolution of intellect in monkeys, apes and humans. Oxford: Clarendon Press.

Deacon, T. (1997) The Symbolic Species New York: W.W. Norton and Co.

Dunbar R (1998) The social brain hypothesis. Evolutionary Anthropology:179-190.

Elman JL, Bates EA, Johnson MH, Karmiloff-Smith A, Parisi D, Plunkett K (1996) Rethinking innateness: A connectionist perspective on development. Cambridge, MA: MIT Press.

Falk, D. (1990). Brain evolution in Homo: the “radiator theory”. Behavioural and Brain Sciences, 13: 333 - 381.

Finlay BL, Darlington RB, Nicastro N (2001) Developmental structure in brain evolution. Behavioural and Brain Sciences 24:263-307.

Finlay BL, Silveira, LCL, and Reichenbach, A. (2005) Comparative aspects of visual system development In “The Visual System of Primates” Kremers, J and Silveira, LCL eds New York: John Wiley and Sons. Pp 37-72

Jacobs GH (1998) Photopigments and seeing - Lessons from natural experiments - The Proctor Lecture. Invest Ophthalmol Visual Sci 39:2205-2216.

Hauser MD, Chomsky N, Fitch WT (2002) The faculty of language: What is it, who has it, and how did it evolve? Science 298:1569-1579.

Lahdenpera, M, Lummaa, V, Helle, S, Tremblay, M, Russell, AF (2004) Fitness benefits of prolonged post-reproductive lifespan in women. Nature 428, 178 - 181

Stanford, C.B. (1999). The Hunting Apes. Princeton University Press.

Stedmann, HH, Kozyaki, BW, Nelson A, Thesier, DM, Sui, LT, Lowi, DW, Bridges, CR, Shrager, JB, Miugh-Purvis, N, Mitchell, MA (2004) Myosin gene mutation correlates with anatomical changes in the human lineage Nature 428, 415 - 418

Tooby, J. & Cosmides, L. 1992 The psychological foundations of culture. In The adapted mind: Evolutionary psychology and the generation of culture (ed. J. Barkow, L. Cosmides, & J. Tooby), pp. 19-136. NY: Oxford University Press.

Vargha-Khadem F, Watkins K, Alcock K, Fletcher P, Passingham R (1995) Praxic and nonverbal cognitive deficits in a large family with a genetically transmitted speech and language disorder. Proc Natl Acad Sci USA 92:930-933.

Wegner, D. (2002) The illusion of conscious will. Csmbridge MA:MIT Press





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