In this section I define and explain the main concepts required to understand enculturation, other than the already explored concepts of integration and practice. I will develop the concepts of evolutionary continuity, behavioural and neural plasticity, transformation and innovation, or novelty and uniqueness. In particular I will emphasise the phylogenetic and ontogenetic bases for modern human cognitive capacities.
The concept of evolutionary continuity results from the fact that evolution occurs gradually with complex structures evolving over many generations. Over long periods of time these gradual changes accumulate, resulting in large differences. Consequently, changes to a phenotype occur in slow cumulative steps over long periods of time and do not appear in a single mutational step. Evolutionary continuity demands that modern human minds evolved from earlier archaic variants. Doubtless modern minds differ from archaic minds in important respects, but these differences must have evolved over long periods of time, through slow cumulative mutational changes to the genotype. Even so, we should expect some of our archaic traits to remain, and for more modern variants to be built on top of them. One obvious example of this is the evolution of the human brain.
The evolution of the human brain can, to some extent, be seen in the gradual increase of cranial capacity, but some of the most important changes have been in the reorganisation of cortical circuitry and interconnectivity (Hoffman 2014). Although the evolution of the human brain can be understood in terms of increasing encephalization and increased connectivity between brain regions, the human brain has essentially the same set of structures as any other primate brain.[14] Modern brains evolved from archaic brains and share the same evolutionary constraints as other primates: “the similarity in brain design among primates, including humans, indicates that brain systems among related species are internally constrained and that the primate brain could only evolve within the context of a limited number of potential forms” (Hoffman 2014, p. 5). Modern minds are still partly archaic.
It is important to think of evolutionary continuity as running from archaic to modern. We should try to avoid anthropomorphic tendencies to project modern cognitive capacities backwards into the hominin lineage or across to primate species. For example, humans are excellent social cognisers, but it does not follow from this that we should expect other primates to have a theory of mind.[15] The evolutionary pressures under which humans evolved and the capacities for complex social cognition might have been very different from those under which other primates evolved. Consequently, we should be searching for archaic precursors to modern cognitive capacities. For example, we might expect that given the increasing social pressures in hominid social groups there would be precursors to modern social cognition and that these precursors would have been adaptive solutions (Shultz et al. 2012). Modern human social cognition would then be an evolutionary consequence of increasing variation in the complexity of social organisation and interaction (Sterelny 2003).
I am committed to another sense of continuity: that between biology and culture. Culture is not, as a category, distinct from the biological. Although culture is sometimes thought of as floating free of our biological nature and sometimes as being highly constrained by it, I shall assume that genes and culture co-evolve[16] mutually, influencing and constraining one another. Therefore I shall accept no culture–biology dualism in this paper. Indeed I shall adopt a cultural inheritance model of cognitive evolution (of the niche construction kind). However, I shall always do so with archaic origins in mind. Archaic origins matter to cognitive evolution and they matter to the way our brains develop during the lifespan.[17]
In the “modern synthesis” there is only one line of inheritance, and that is genetic inheritance. More recently, biologists (Odling-Smee et al. 2003) have proposed that there are other lines of inheritance: ecological inheritance and cultural inheritance (Boyd & Richerson 2005). Many organisms construct the niche in which they live, mate, hunt, and die. Niche constructors modify the ancestral environment, and these modifications are bequeathed to the next generation. Modifications encompass physical alterations, such as living in mounds or constructing hives, as well as cultural artefacts, practices, and institutions. Over long periods these alterations to the niche can have profound effects on the phenotype. For example, the ubiquitous niche constructions of termites, burrows and mounds, have profoundly altered their morphology and behaviour (Turner 2000).
Humans are also ubiquitous niche-constructors. They physically alter their environment and they also epistemically, socially, and culturally engineer the environment (Sterelny 2003, 2010; Menary 2007). Humans are born into a highly structured cognitive niche that contains not only physical artefact, but also representational systems that embody knowledge (writing systems, number systems, etc.); skills and methods for training and teaching new skills (Menary & Kirchhoff 2014); and practices for manipulating tools and representations. Inherited cultural capital is a real and stable feature of the socio-cultural environment, including a great variety of knowledge systems, skills, and practices across a variety of domains of human action. As such, human cultural niches provide neonates with rich developmental niches. It is in these developmental niches that humans acquire cognitive practices.
Cognitive practices are products of cultural evolution, evolving over faster timescales than biological evolution. Writing systems, for example, are only thousands of years old; consequently, it is highly unlikely that there is a “reading gene” or even an innate specialised “reading module.” This is important: cognitive capacities for reading and writing, mathematics, and other culturally recent forms of cognition could not be biological adaptations (that evolved over long periods of time). The timescales for their evolution are too short. It follows that the capacity for culturally recent forms of cognition must be acquired through learning and training.
Although there are no innate specialized modules for these recent forms of cognition, cortical circuits with which we are endowed through evolution are transformed to perform new culturally recent cognitive functions, even though they evolved to perform different functions. Recent cognitive innovations aside, there are good reasons to expect that evolution has driven us to think by interacting with the environment and that this is adaptive (Sterelny 2003 2012; Menary 2007; Wheeler & Clark 2008). However, it is the scaffolding of cultural practices that orchestrates the interactions—as in the case of written language and mathematics.
Structured socio-cultural niches have had profound evolutionary consequences in the hominin lineage. Structured niches have co-evolved with human phenotypic and developmental plasticity. We have evolved to be a behaviourally plastic species (Sterelny 2012) as well as a cultural species. In this co-evolution we have developed all manner of skills, practices, and activities. Why, though, are we so peculiarly behaviourally plastic? One good answer to this question is that human behavioural and developmental plasticity is an adaptive response to the variability and contingency of the local environment (Finlayson 2009; Sterelny 2003, 2012; Davies 2012). This is an alternative to the view that we are adapted to a pleistocene hunting and gathering environment—a view relied upon by many evolutionary psychologists (Barkow et al. 1992).
Critical to a co-evolutionary account of cultural practices is the evolution of human plasticity. Given that there is such a variety of cultural activity, we need an account of human evolution that will allow for variability in human behaviour. Second, we need a model that explains how innovations in our cultural niche are inherited and propagated, leading to changes in behaviour over time. The niche construction model explains how both of these causal factors could come into play. In the sub-sections below, I outline the importance of behavioural and neural plasticity, the concept of transformation, and those of novelty and uniqueness.
In evolutionary terms, humans are capable of developing a wide range of skills that allow them to cope with a wide variety of environments (and their contingencies). For example, even where skills are (broadly) of the same type, such as hunting, they will vary in how they cope with the differences in local environments—think of the differences in environments between Aboriginal hunters in the Pilbara desert, hunter-gatherers in the Central American rainforests, and Inuit seal-hunters (Sterelny 2003, p. 167).
Development is extended in modern humans relative to other species. Humans take a long time to learn how to walk and talk, and much, much longer to develop fine-grained manual and cognitive skills such as reading and writing. Other primates have much faster developmental timescales. While this might make humans more dependent on their caregivers for longer, it also allows them to refine skills and acquire a greater array of them before entering adulthood.
Through cultural inheritance, knowledge, skills, and artefacts are passed on to the next generation, but learning environments and learning techniques are also passed on so that the next generation can acquire and be transformed by the inherited cultural capital. This last point is important for our purposes, because developmentally plastic humans need scaffolded learning environments in which to develop.[18]
How, though, are we capable of acquiring these new cultural capacities in development? Through neural plasticity. Rather than the process of synaptogenesis or lesion-induced plasticity,[19] the kind of plasticity I will discuss here is what I call learning driven plasticity (see Menary 2014). Learning driven plasticity (LDP) can result in both structural and functional changes in the brain. Structurally, LDP can result in new connections between existing cortical circuits. Functionally, LDP can result in new representational capacities (the ability to represent public symbolic representations such as alphabets and numerals) and new cognitive abilities, such as mathematics,[20] reading, and writing (Dehaene 2009; Ansari 2012). It should come as no surprise that learning drives structural and functional changes in the brain, given the extended developmental period in humans and the late development of the cortex (Thatcher 1991). The brain changes, not just because of maturation, but also because of learning:
[w]hen children learn to read, they return from school ‘literally changed’. Their brains will never be the same again. (Dehaene 2009, p. 210)
Famously, Dehaene argues that a region of the occipito-temporal junction (which he calls the VWFA, visual word form area) that is part of a wider network for recognising faces, objects, and even abstract shapes (such as chequer patterns), alters its function to recognise written symbols in alphabets and even logographic scripts such as kanji (Dehaene 2009). This is due to the plasticity of that area of the brain, where the functional shift is due to scaffolded learning.[21] “Scanning of ‘ex-illiterate’ adults who learned to read during adulthood has demonstrated that the VWFA is highly plastic, even in adults, and quickly enhances its response to letter strings as soon as the rudiments of reading are in place” (Dehaene & Cohen 2011, p. 259). Even those who are not convinced that a specialised region for “word recognition” is acquired once we learn to read admit that the occipito-temporal junction is part of a reading and writing circuit (e.g., Price & Devlin 2011).
We have evolved to be phenotypically and developmentally plastic. This is in no small part due to the plasticity of our brains. Our developmentally plastic brains exhibit learning-driven plasticity. When the brain is coupled to a highly scaffolded learning environment it is profoundly transformed, structurally and functionally, and consequently we are cognitively transformed in the profoundest way.
The transformation thesis can be given a simple formulation: cognitive transformations occur when the development of the cognitive capacities of an individual are sculpted by the cultural and social niche of that individual. Cognitive transformations result from our evolved plasticity and scaffolded learning in the developmental niche. In the previous sub-sections an account was given of the effects of cultural inheritance and niche construction on hominid evolution. The result is phenotypic plasticity, and in the cognitive case the co-evolution of neural plasticity and scaffolded learning. However, the point of the transformation thesis is to drill down into the process of acquiring knowledge, skills, and cognitive abilities via learning-driven plasticity and scaffolded learning. It does this by showing how transformations are a result of the role of cognitive practices in development. Practices structure the niche; they transform plastic brains via learning driven plasticity and result in new cognitive abilities.
During the learning and training of a skill, such as flaking an arrowhead, or a shot in tennis or cricket, we are guided by the norms for the correct actions that make up the skilled practice. A parallel case can be made for cognitive abilities such as mathematics. The neophyte mathematician gains mastery over the cognitive norms[22] by which numerals, operators, and other symbols are created and manipulated. Vygotsky expresses this in the claim that children, “master the rules in accordance with which external signs must be used” (Vygotsky 1981, pp. 184–185). Initially the child masters the creation and deployment of spoken linguistic signs (and later written signs) through the scaffolding of parents and caregivers. However, this process is not simply a matter of gaining new representations; it is also one of gaining new abilities.
Neophytes go through a process of dual-component transformation: they learn how to understand and deploy public symbolic representations and they learn how to create and manipulate inscriptions of those symbols in public space (Menary 2010). In so doing, they learn mathematical and linguistic concepts and they learn how to manipulate inscriptions to complete cognitive tasks. When learning the manipulative techniques, the first transformation is one of the sensory-motor abilities for creating and manipulating inscriptions: we learn algorithms like the partial products algorithm[23] and this is an example of the application of a cognitive practice. This is something we learn to do on the page and in the context of a learning environment, in public space, before we do it in our heads. Our capacities to think have been transformed, but in this instance they are capacities to manipulate inscriptions in public space. This is a way of showing that the transformation of our cognitive capacities has recognisably public features. This ought not to be a surprise, given that the cognitive niche is socially and culturally constructed and is structured by socio-cultural practices. Symbol systems, such as those for written language and mathematics, are not impermanent scaffolds that we shrug off in adulthood, but are permanent scaffolds that indelibly alter the architecture of cognition.[24]
The transformatory position is quite different from that held by Clark or Sterelny. In particular it holds that our basic cognitive capabilities are transformed in development and that the dual component transformation results in a distinct functional redeployment of neural circuitry and new abilities to bodily manipulate structures in public space. Cognitive tasks can be completed by manipulating written symbols in public space or by off-line strategies for completing algorithms, or a combination of both. This conclusion sits happily with the idea that thought is interactive and governed by practices.
The main difference between the position outlined here and Clark’s (e.g., 2008), is that Clark does not explain cognitive extension in terms of the transformation of basic cognitive resources during development in a socio-cultural niche (although he does acknowledge the importance of symbolically structured niches). Rather, he thinks that basic biological resources are not really transformed but simply dovetail to external symbols (Clark 2008, 2011). Sterelny (2010) concentrates on cognitive scaffolding, but does not think that the manipulation of symbols in public space is constitutive of cognitive processing. The enculturated approach of CI answers questions that are problematic for both Clark and Sterelny:
How do we learn to complete cognitive tasks that require the manipulation of symbols in public space?
Assuming that cognitive processing criss-crosses between neural space and public space, how does it do this?
The first question is hard for Clark since he does not think that our basic cognitive resources get transformed, at least in the way that I have presented here. The second question is hard for Sterelny because he limits himself to a scaffolded view of cognition rather than an extended view. Consequently, manipulations of symbols in public space are not cognitive processes for Sterelny.[25]
CI as a process of enculturation requires a robust transformation thesis. A robust transformation thesis is warranted by phenotypic and neural plasticity, in particular by learning driven plasticity. Novel and unique public systems of representation drive the transformation of our existing cognitive abilities.
Sometimes symbols and tools provide us with novel functions: they radically extend our capabilities in some sphere. Take the humble hand axe. Very crude hand tools have been discovered dating as far back as 2.6 mya (million years ago; Toth & Schick 2006), since then there has been evidence of a hominid capacity for cumulative cultural inheritance “which was ultimately to transform Homo sapiens into the richly cultural species we are today” (Whiten et al. 2011). However, the capacity for developing novel functions and transmitting them to the next generation with high fidelity appears to be a more recent innovation, as evidenced by the long periods of relative stability in technological development in the early hominids and archaic humans. It also appears to be an innovation unique to the homonin lineage (Whiten et al. 2011). The Oldowan period begins in the lower paleoloithic with Homo Habilis around 2.6 mya, being taken up by Homo Erectus and Ergaster and ending at about 1.8 mya (Lycett & Gowlett 2008). The tool types and process of manufacture remain consistent during this period, with some refinement and novelty (Lycett & Gowlett 2008), where the main tool types were choppers and scrapers or mode 1 tools (Semaw et al. 2003).
Homo Habilis is unique in that it is the first hominid to make tools that were made to endure and be re-usable (it is likely that earlier anthropocines used naturally-occurring objects as tools that were disposable; Jeffares 2010).
Oldowan toolmaking involves the production of sharp-edged flakes by striking one stone (the core) with another (the hammerstone). Effective flake detachment minimally requires visuomotor coordination and evaluation of core morphology (e.g., angles, surfaces) so that forceful blows may reliably be directed to appropriate targets (Stout et al. 2008, p. 1940).
There is a clear transition to Achulean technology at around 1.7 mya with the appearance of Erectus/Ergaster. The main innovation for Achulean technology was the bifacial handaxe—a handheld cutting tool with two cutting sides. The real explosion in novelty occurs in the upper paleoloithic period, from 50,000 years ago (ya) to 10,000 ya (or to just before the advent of agriculture and the neolithic period), with genuine novelty in tool production and use and cultural diversification. In this period we begin to see evidence of art, including paintings and sculpture, fishing, jewellery, burial, evidence of musical activity, and all the hallmarks of behaviourally modern humans. It is in this period that the combination of inherited cultural capital, with phenotypic and learning-driven plasticity, complex social relations and language results in an explosion of cultural and behavioural diversity.
It is also in this period that we begin to find evidence of proto-numerical and writing systems as novel representational innovations. Simple tally notch systems on bone fragments have been dated to between 35,000 and 20,000 ya, and may have been used for a variety of purposes, the most obvious being to keep track of economic exchanges. However, it is far easier and more economical to keep track of larger amounts using a single symbol, rather than a one-to-one correspondence of marks with things.
The complex social and economic pressures that required tracking exchanges involving increasingly large numbers would be the kind of socio-economic pressures that produced symbolisation of quantity. Social and cultural pressures can drive evolutionary novelty, in this case symbolisation and uniqueness—symbolic representations are unique in both type and property, no other animal produces written symbols to represent concepts. Symbols have unique properties that allow for operations—addition, subtraction, multiplication, division, and so on that are much harder (if not unlikely) without them.
Early symbolic number systems date from between 3000–4000 BCE, but genuinely abstract symbol systems are even more recent—about 1000–2000 BCE. The invention of symbol systems is too recent to be a genetic endowment, but is inherited as cultural capital and acquired through high-fidelity social learning (which is in turn dependent upon neural plasticity).
The phylogeny of hominid tool-use is one of hard-won innovation and retention. Modern humans have developed high-fidelity modes of transmitting cultural capital vertically and horizontally. The socio-cultural pressures that led to humans innovating symbolic representational systems are unique and very recent. Fortunately, modern human minds are flexible enough to both innovate and reliably acquire those innovations in ontogeny.[26] This flexibility makes modern human minds unique, and in the case of mathematical cognition unique amongst all our primate relatives.
The next section outlines mathematical cognition as a case of enculturation, and there I will explore the example of mathematical cognition by deploying the concepts refined in the first two sections.