be used to constrain the range of options available (e.g., something akin to the affordances described by Gibson (1966, 1979), and that organisms are thus required to compute all contingencies independently of the environment. May et al. (2006), however, have shown that robotic rat pups, provided with a completely random control architecture (i.e., without any rules at all, whether domain-general or domain-specific), were nevertheless able to produce the distinctive huddling behavior of real rat pups, due to the constraining influence of bodily and environmental structures. That is, rather than having to decide among a trillion different options, according to the logic described above, bodily and environmental structures allow for complex behavior to emerge without any decision-making at all. Thus, there is no reason, in principle, to suppose that humans could not be similarly scaffolded and guided by environmental constraints, in ways that would allow general-learning mechanisms to get a grip and, over time, produce functionally specialized mechanisms that help guide behavior. Indeed, this may also be one reason why human infant learning mechanisms take the form they do, with only a limited capacity at first, so as not to overwhelm the system. As Elman (1993) showed, in his classic paper on infant language learning, the training of a neural network succeeded only when such networks were endowed with a limited working memory, and then gradually "matured." More recently, Pfeifer and Bongard (2007) have reported on similar findings relating to the development of behavior in a "babybot."

Thus, while reasonable when taken at face value, many of the arguments offered in support of an evolved domain-specific computational architecture turn out to be rather Hegelian on closer inspection, rather than well-supported by empirical data. As such, the increased value of evolutionary psychology remains an open issue: it is not clear that EP offers an improvement over other computational perspectives that do not make strong claims for an evolved, domain-specific architecture of this kind.

#### **MODULES 2.0**

The contention that EP has sometimes offered Hegelian arguments should not be taken to suggest that opponents of the EP position are not guilty of the same. We do not deny that modular accounts have also been ruled out based on assertion rather than evidence, and that there have been many simplistic straw man arguments about genetic determinism and reductionism. Interestingly enough, Jerry Fodor himself, author of "The Modularity of Mind" (Fodor, 1983), asserted that it was simply impossible for "central" cognitive processes to be modular, and Fodor (2000) also presents several Hegelian arguments against the evolutionary "massive modularity" hypothesis. Indeed, the prevalence of such arguments in the field of cognitive science is Chemero's (2009) main reason for raising the issue. His suggestion is that, unlike older disciplines, cognitive science gives greater credence to Hegelian arguments because it has yet to establish a theoretical framework and a supporting body of data that everyone can agree is valid. This means that EP does not present us with the knockdown arguments against the SSSM and domain-general learning that it supposes, but neither should we give Hegelian arguments against EP any credence for the same reason.

As both Barrett and Kurzban (2006) and Frankenhuis and Ploeger (2007) have documented, many of the misrepresentations and errors of reasoning concerning the massive modularity hypothesis in EP can, for the most part, be traced precisely to the conflation of Fodor's (1983) more limited conception of modularity with that of Tooby and Cosmides (1992, 2005) and Cosmides and Tooby (1994). Criticisms relating to encapsulation, cognitive impenetrability, automaticity, and neural localization are not fatal to the EP notion of modularity because EP's claim is grounded in functional specialization, and not any specific Fodorian criterion; criticisms that argue in these terms therefore miss their mark (Barrett and Kurzban, 2006).

Given that most criticisms of the massive modularity hypothesis prove groundless from an EP point of view, it is worth considering Barrett and Kurzban's (2006) analysis in detail in order to understand exactly what the EP view of modularity entails, and whether this updated version of the modularity argument is more convincing in terms of presenting an improved alternative to standard computational models.

First and foremost, Barrett and Kurzban (2006) make clear that functional specialization *alone* is the key to understanding modularity from an EP point of view, and domain-specific abilities, and hence modules, "should be construed in terms of the formal properties of information that render it processable by some computational procedure" (Barrett and Kurzban, 2006, p. 634). That is, modules are defined by their specialized input criteria and their ability to handle information in specialized ways: only information of certain types can be processed by the mechanism in question. Natural selection's role is then "to shape a module's input criteria so that it processes inputs from the proper domain in a reliable, systematic and specialized fashion." (By "proper" domain they mean the adaptive problem, with its associated array of inputs, that the module has been designed by selection to solve; this stands in contrast to the "actual" domain, which includes the range of inputs to which the module is potentially able to respond, regardless of whether these were present ancestrally: see Sperber, 1994; Barrett and Kurzban, 2006, p. 635). Hence, the domain-specificity of a module is a natural consequence of its functional specialization (Barrett and Kurzban, 2006). Crudely speaking, then, modules are defined more in terms of their syntactic rather than semantic properties—they are not "content domains," but more like processing rules.

Barrett and Kurzban (2006) argue that their refinement of the modularity concept holds two implications. First, given that a module is defined as any process for which it is possible to formally specify input criteria, there is no sharp dividing line between domain-specific and domain-general processes, because the latter can also be defined in terms of formally specified input criteria. The second, related implication is that certain processes, like working memory, which are usually regarded as domain-general (i.e., can process information from a wide variety of domains, such as flowers, sports, animals, furniture, social rituals), can also be considered as modular because they are thought to contain subsystems with highly specific representational formats and a sensitivity only to specific inputs (e.g., the phonological loop, the visuospatial sketchpad; Barrett and Kurzban, 2006). This does, however, seem to deviate slightly

from Cosmides and Tooby's (1997) suggestion that modules are designed to solve particular adaptive problems encountered by our ancestors: what *specific* adaptive problem does "working memory" solve, given that the integration of information seems common to all adaptive problems? (see also Chiappe and Gardner, 2012).

Taken on its own terms, however, Barrett and Kurzban's (2006) definition of modularity should raise no objections from anyone committed to the computational theory of mind, nor does it come across as particularly radical with respect to its evolutionary theorizing. Thus, Barrett and Kurzban (2006) dissolve many of the problems identified with massive modularity, and suggest that most criticisms are either misunderstandings or caricatures of the EP position. When considered purely as a computational theory (i.e., leaving to one side issues relating to the EEA, and Hegelian arguments relating to the need for evolved domain-specific knowledge), the more recent EP position is thereby revealed as both reasonable and theoretically sophisticated.

#### **DEVELOPMENTAL CONSIDERATIONS: "SOFT" DEVELOPMENTAL SYSTEMS THEORY AND EP**

It is also important to note that the more recent work in EP also incorporates a strongly developmental perspective, again laying rest to criticisms that EP is overly determinist and that EP researchers are prone to simplistic claims about the innateness or "hard-wiring" of particular traits (e.g., Barrett, 2006; Frankenhuis et al., 2013). In particular, work by Barrett (2006) and Frankenhuis et al. (2013) attempts to integrate developmental systems theory (DST) into EP. This represents an encouraging move at first glance, because the aim of DST is to moves us away from a dichotomous account of development, where two classes of resources—genes and"all the rest"—interact to produce the adult phenotype, toward an account in which there is no division into two fundamentally different kinds of resources. Instead, genes are seen as just one resource among many available to the developmental process, and are not the central drivers of the process (Griffiths and Gray, 1994). Indeed, genes can play their role only if all other resources essential for development are in place. This should not be taken to mean that all resources contribute equally to each and every process, and always assume the same relative importance: the aim is not to "homogenize" the process of development, and obliterate the distinctions between different kinds of resources, but to call into question the way in which we divide up and classify developmental resources, opening up new ways to study such processes.

The EP take on DST, however, is self-confessedly"soft," and continues to maintain that standard distinction between genetic and environmental resources. As defined by Frankenhuis et al. (2013), "soft DST" regards developmental systems as "dynamic entities comprising genetic, molecular, and cellular interactions at multiple levels, which are shaped by their external environments, but distinct from them" (p. 585). Although a strongly interactionist view, the "developmental system" here remains confined to the organism alone, and it continues to treat genetic influences as fundamentally distinct from other developmental resources, with a unique role in controlling development. More pertinently, Barrett (2006) suggests that, precisely because it gets us away from any

kind of "genetic blueprint" model of growth and development, it may be "fruitful to think of developmental processes themselves in computational terms: they are designed to take inputs, which include the state of the organism and its internal and external environments as a dynamically changing set of parameters, and generate outputs, which are the phenotype, the end-product of development. One can think of this end-product, the phenotype, as the developmental target" (p. 205). Thus, once again, EP does not present us with an alternative to current computational models, because, as Barrett (2006) makes clear, the incorporation of these additional theories and models into an EP account entails a reinterpretation of such theories in fully computational terms.

#### **ANCIENT ADAPTATIONS OR THOROUGHLY MODERN MODULES?**

Another consideration we would like to raise is whether, as a result of incorporating a clearly articulated developmental component, EP researchers actually undermine some of their own claims regarding the evolved domain-specificity of our putative modular architecture. Barrett (2006), for example, uses Sperber's (1994) ideas of actual and proper domains to good effect in his developmental theorizing, distinguishing clearly between "types" of cognitive processes (which have been the target of selection) and "tokens" of these types (which represent the particular manner in which this manifests under a given set of conditions). This enables him to provide a cogent account of an evolved modular architecture that is capable of generating both novelty and flexibility. The interesting question, from our perspective, is whether the modules so produced can be still be considered adaptations to past environments, as Cosmides and Tooby (1994, 1997) insist must be the case.

For example, as Barrett (2006) notes, many children possess the concept of *Tyrannosaurus rex*, which we know must be evolutionarily novel because, as a matter of empirical fact, there has been no selection on humans to acquire this concept. Nevertheless, as Barrett (2006) argues, we can consider the possession of this concept as a token outcome that falls well within the proper type of a putative predator-recognition system. This argument is logical, sensible, and difficult to argue with, yet seems at odds with the central idea presented in much of Tooby and Cosmides (1992, 2005) work that the modular architecture of our minds is adapted to a past that no longer exists. That is, as tokens of a particular type of functional specialization, produced by a developmental process that incorporates evolutionarily novel inputs, it would seem that any such modules produced are, in fact, attuned to present conditions, and not to an ancestral past. As Barrett (2006) notes, Inuit children acquire the concept of a polar bear, whereas Shuar children acquire the concept of a jaguar, even though neither of these specific animals formed part of the ancestral EEA; while the mechanisms by which these concepts are formed, and why these concepts are formed more easily than others, may well have an evolutionary origin, the actual functional specializations produced − the actual tokens produced within this proper type − would seem to be fully modern. The notion that "our modern skulls house a stone age mind" (Cosmides and Tooby, 1997) or that, as Pinker (2003, p. 42) puts it; "our brains are not wired to cope with anonymous crowds, schooling, written language, governments, police courts, armies, modern medicine, formal social institutions, high technology and other newcomers to the human experience" are thus undermined by the token-type distinction developed in more recent EP theorizing.

One could argue, perhaps, that what Pinker means here is that our brains did not evolve to deal with such things specifically, i.e., that he is simply making Barrett's (2006) argument that these phenomena are just tokens of the various types that our brains *are* wired to cope with. But, if this is the case, then it seems that EP loses much of its claim to novelty. If it is arguing only that humans have evolved psychological mechanisms that develop in ways that attune them to their environment, this does not differ radically from computational cognitive theories in human developmental and comparative psychology more generally.

This sounds like a critical argument, but we do not mean it in quite the way it sounds. Our argument is that the theoretical EP literature presents a perfectly acceptable, entirely conventional computational theory, one that admits to novelty, flexibility, the importance of learning and development, and incorporates the idea that a species' evolutionary history is important in shaping the kinds of psychological processes it possesses and the ease with which they are acquired. Our point is that this is no different from the arguments and empirical findings offered against behaviorism toward the middle of the last century, which heralded the rise of cognitive psychology (see e.g., Malone, 2009; Barrett, 2012). Central to all cognitivist psychological theories is the idea that there are internal, brain-based entities and processes that transform sensory input into motor output, and the acknowledgment that much of this internal structure must reflect a past history of selection. EP,in this sense then, is not controversial within psychology, and is entirely consonant with current psychological theory and practice. Thus, in addition to the fact that EP is based on the same computational metaphor as standard cognitive psychology, it is also apparent that most of the evolutionary aspects of this theory, as reconceived by current authors, do not render it revolutionary within psychology, nor is there any reason to believe that the remaining social sciences should view EP as any more essential or necessary to their work than current computational models. Indeed, one could simply take the message of EP to be that, as with all species, humans are prepared to learn some things more readily than others as a result of evolving within a particular ecological niche. Seen in these terms, it is surprising that EP continues to be considered controversial within psychology, given that its more recent theoretical claims can be seen as entirely mainstream.

#### **AN ALTERNATIVE SUGGESTION: COGNITIVE INTEGRATION**

If our conclusion is that EP does not offer an alternative to standard computational cognitive psychology, we are left with two further questions: Is an alternative really needed? And if so, what is it? In the remainder of this paper, we tackle these questions in turn.

One reason why we might need an alternative to standard computational and representational theories of mind is because, despite claims to the contrary (e.g., Pinker, 2003), it has yet to provide a complete account of how humans and other species produce adaptive, flexible behavior in a dynamic, unpredictable

world. Although we may understand something about capacities like playing chess, engaging in formal reasoning, or natural language (i.e., tasks that involve the manipulation of symbols according to rules, and are inherently computational anyway), we still lack a good understanding of the more mundane tasks that characterize much of what we could call "everyday" intelligence, such as how we manage to negotiate uneven terrain or coordinate all the actions and objects necessary to make a pot of tea, or coordinate our social actions with others when we dance, engage in conversation smoothly and easily, or simply walk down a crowded street.

It is also interesting to note that the computational metaphor also hindered the advancement of robotics in much the same way. The MIT roboticist and inventor of the Roomba, Rodney Brooks, relates how his first formal foray into robotics was at Stanford, where they took a "classic" artificial intelligence approach, with robots that took in sensory inputs, computed solutions to a task based on these inputs, and then executed them. This made the robots operate very slowly, even to the extent that the movement of the sun across the sky, and the changes in the shadows thrown, had the ability to confuse their internal representations. Only by moving away from a classic computational "sense–represent–plan–act" approach, and eliminating the need for internal representations altogether, was progress made (Brooks, 2002; also see Pfeifer and Bongard, 2007).

In other words, the idea that cognition is, ultimately, a form of "mental gymnastics" (Chemero, 2009) involving the construction, manipulation, and use of internal representations according to a set of rules does not seem to provide an adequate account of how humans and other animals achieve most of the activities they engage in every day. Given this, the obvious alternatives to the standard computational theories of mind are the various forms of "E-cognition" (embodied, embedded, enactive, extended, and extensive) that have been gaining steady ground in recent years within cognitive science and philosophy of mind and, to a lesser extent, psychology itself, both theoretically and empirically (e.g., Clark, 1997, 2008; Gallagher, 2005; Wheeler, 2005; Menary, 2007, 2010; Pfeifer and Bongard, 2007; Chemero, 2009; Barrett, 2011; Hutto and Myin, 2013). While these approaches vary in the degree to which they reject computational and representational approaches to cognition [e.g., Clark (1997, 2008) argues for a form of "dynamic computationalism," whereas Hutto and Myin (2013) reject any suggestion that "basic minds," i.e., those that are non-linguistic, make use of representational content], they have in common the idea that body and environment contribute to cognitive processes in a constitutive and not merely causal way; that is, they argue that an organism's cognitive system extends beyond the brain to encompass other bodily structures and processes, and can also exploit statistical regularities and structure in the environment.

For reasons of space, we cannot provide a full account of these alternatives, and the similarities and differences between them. Instead, we will focus on one particular form of E-cognition, the "EM" hypothesis. Specifically, we will deal with "second-wave EM" thinking, also known as "cognitive integration," as exemplified by the work of Clark (2008), Sutton (2010), and Menary (2007, 2010). We believe this supplies the beginnings of an answer to why an alternative to standard computational theory is required, and illustrates why EP cannot provide it.

Put simply, the EM hypothesis is that external resources and artifacts, like written language and other forms of material culture, are central to the production of the modern human cognitive phenotype, and serve to augment and ratchet up the power of our evolved brains (e.g., Clark, 1997, 2008; Menary, 2007, 2010; Sutton, 2010). External resources are argued to play a role in a cognitive process in ways that are either functionally equivalent to that carried out by a biological brain such that, for the duration of that process, the external resource can be considered to be part of the cognitive system (the so-called "parity principle": Clark and Chalmers, 1998) or they play roles that are complementary to brain-based processes, and augment them accordingly (the "complementarity principle": Menary, 2007, 2010; Sutton, 2010). We can see this in everything from the way in which our ability to multiply very large numbers is enhanced by the use of pencil and paper to the fascinating literature on sensory substitution devices, where blind individuals are able to visually explore their environments via external devices that supply auditory or tactile information in ways that compensate for the loss of their visual sense (Bach-y-Rita et al., 1969, 2003; Bach-y-Rita and Kercel, 2003). The idea here, then, is not to eliminate all distinctions between different kinds of resources and consider them to be synonymous, but to reduce our prejudice that only internal processes taking place in the brain count as cognitive, and to redraw the boundaries of the cognitive system accordingly. The notion of the EM or cognitive integration therefore dissolves the boundary between brain, body, and world, and rejects the idea that the "cognitive system" of an animal is confined to its brain alone (for a review of how cognitive integration relates to the non-human animal literature, see Barrett, 2011). Instead, as Clark (1997) and Clark and Chalmers (1998) suggested, many of our cognitive states can be considered as hybrids, distributed across biological and non-biological realms. We are, as the title of one of Clark's books suggests, "natural born cyborgs" (Clark, 2003).

#### **CULTIVATING THE HYBRID HUMAN**

The human cognitive system, in particular, is extended far beyond that of other species because of the complex interaction between the biological brain and body, and the wide variety of artifacts, media and technology that we create, manipulate, and use. It is crucial to realize that the hybrid nature of human beings is not a recent phenomenon tied to the development of modern technology. On the contrary, cognitive extension is a process that has been taking place ever since the first hominin crafted the first stone tools, and has continued apace ever since. What this means today is that, as Clark (2003) puts it, "our technologically enhanced minds are barely, if at all, tethered to the ancestral realm" (p. 197) nor are they now "constrained by the limits of the on-board apparatus that once fitted us to the good old savannah" (p. 242). This stands in stark contrast to the EP position, where the only "cognitive machinery" involved is the brain itself, whose structure is tied fundamentally and necessarily to the past, untouched by our culturally constructed,

technological world. As Tooby and Cosmides (1992) put it: "what mostly remains, once you have removed from the human world everything internal to humans, is the air between them" (p. 47). Cognitive integration begs to differ in this regard, and invites us to look around and see that this simply cannot be true.

Consequently, our view is that cognitive integration promises to explain more about human psychology than EP ever could because it forces a stronger recognition of the historical, sociocultural nature of human psychology − the fact that we develop in a socially and culturally rich milieu that reflects the contingent nature of both historical and evolutionary events. Past generations structure the developmental context of those that succeed them, providing resources that are essential to the production of species-typical behavior. Importantly, however, they also enhance what can be achieved by providing ever more sophisticated forms of cognitive scaffolding that itself augments the scaffolding that previous generations bequeathed to them (Sterelny, 2003; Stotz, 2010). This can be seen as something akin to the process of ecological succession, where the engine of change is the organism's own impact on the environment; a metaphor we have stolen from Griffiths and Gray's (1994) treatment of DST. Indeed, there is a natural sympathy between DST as an approach to the study of the evolution and development of biological organisms, and the more dynamical forms of E-cognition that adopt a similar approach to the evolution, development, and functioning of cognitive systems. In particular, Stotz (2010) argues convincingly that understanding human psychology from an evolutionary perspective requires a focus on "developmental niche construction"; an idea that, as the name suggests, incorporates elements of both developmental systems and niche construction theory (see also Griffiths and Stotz, 2000). Understanding modern human psychology therefore requires an understanding of the entanglement of our technologies, cultural practices, and historical events with our evolutionary heritage, and not the reverse engineering of human cognitive architecture alone. Clark (2002)suggests that the pay-off from this kind of expanded psychology "... could be spectacular: nothing less than a new kind of cognitive scientific collaboration involving neuroscience, physiology and social, cultural and technological studies in equal measure" (p. 154).

Turning to an embodied, extended approach as an alternative to standard computational theories, including that of EP, is a step in the right direction not only because it recognizes the hybrid nature of humans, in the terms described above, but also in the sense discussed by Derksen (2005), who argues that a recognition of ourselves as part-nature and part-culture creates a distinct and interesting boundary (or rather a range of related boundaries) between humans and the natural world. As Derksen (2005) points out, the reflexive ways in which we deal with ourselves and our culture are very different from our dealings with the natural world, and a recognition of our hybrid nature allows us to explore these boundaries in their own right, and to examine how and why these may shift over time (for example, issues relating to fertility treatments, stem cell research, cloning, and organ transplantation all raise issues concerning what is "natural" versus "unnatural," and how we should conceive of human bodies in both moral and ethical terms).

To emphasize this shifting, dynamic element of the boundaries we straddle as hybrid natural-cultural beings, Derksen (2005) uses the metaphor of "cultivation." Like a gardener tending his plants, humans cultivate their nature, and in so doing elaborate their potential. As Vygotsky (1962) suggested, this makes culture something we do, rather than something that happens to us, or that we simply possess. The intersection between cognitive integration and cultivation should be clear, for cognitive integration, which naturally takes into account our historical, social, cultural, and evolutionary underpinnings in equal measure, is key to our ability to cultivate new forms of human nature (see also Bakhurst, 2011). Indeed, proponents of cognitive integration, suggest that "human nature" continually emerges in an ongoing way from human activity, and that we cannot pinpoint some fixed and unchanging essence (Derksen, 2012). As Wheeler and Clark (2008) put it: "our fixed nature is a kind of meta-nature ... an extended cognitive architecture whose constancy lies mainly in its continual openness to change" (p. 3572).

Such a view stands in contrast to the EP perspective, where the idea of a universal human nature, comprising our evolved computational architecture, is a central premise of the approach. The problem here, as we see it, is that cultural variation across time and space is seen simply as the icing on the cake of our evolved universal psychology. Humans are argued to manifest different behaviors under different conditions because our evolved architecture works rather like a jukebox that can play different records given different inputs; what Tooby and Cosmides (1992) refer to as "evoked culture." By this definition, such cultural differences fail to penetrate or alter our "human nature" in any fundamental way. Such a view also fails to account for how and why completely different modes of thinking have emerged over space and time as a consequence of the invention of different material artifacts, like the wheel, the plow, time-pieces, accounting systems, and written language. Such things are not evoked simply by exposure to local ecological conditions, and their existence fundamentally changes how we think about the world (without the invention of time-pieces, for example, the cultural importance of timeliness and punctuality so valued by, among others, the Swiss and Germans, would not, and could not, be considered any part of human nature). EP therefore leaves out the most distinctive aspect of human cognitive life—the way in which material culture is both a cause and consequence of our psychological and cultural variability—whereas cognitive integration makes this the central element to understanding why humans think and act in the ways that they do (Menary, 2010; Sutton, 2010; Malafouris, 2013).

Finally, as Derksen (2005, 2007) argues, a view of human nature as a matter of cultivation, as a form of ongoing human activity, renders the idea of unification between the biological and social sciences wrongheaded on its face: the very diversity of disciplines in which we engage reflects the disunity, the boundary between nature and culture, that characterizes our humanity, and not the fundamental"psychic unity"of humankind that EP assumes. Consequently, there is a very real need to collaborate and confront each other along disciplinary boundaries, but not dissolve, ignore, or erase them (Derksen, 2005, 2007). Such sentiments are echoed by those involved in the study of cognitive integration, who similarly call for this kind of multidisciplinary pluralism in our approach to the study of human nature and the mind (Derksen, 2005, 2007; Menary, 2007; Clark, 2008; Wheeler and Clark, 2008; Menary, 2010; Sutton, 2010). Simply put, our hybrid selves can be studied in no other way.

#### **ACKNOWLEDGMENTS**

Louise Barrett is supported by the Canada Research Chairs (Tier 1) Program and NSERC Discovery grants. Thomas V. Pollet is supported by NWO (Veni, 451.10.032). Gert Stulp is supported by an NWO Rubicon grant. We are grateful to Maarten Derksen for reading and commenting on an earlier draft of the manuscript, and for the comments of our two reviewers. Thanks also to Danielle Sulikowski for inviting us to contribute to this research topic.

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**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 20 May 2014; accepted: 21 July 2014; published online: 12 August 2014. Citation: Barrett L, Pollet TV and Stulp G (2014) From computers to cultivation: reconceptualizing evolutionary psychology. Front. Psychol. 5:867. doi: 10.3389/fpsyg.2014.00867*

*This article was submitted to Evolutionary Psychology and Neuroscience, a section of the journal Frontiers in Psychology.*

*Copyright © 2014 Barrett, Pollet and Stulp. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

### Our computational nature: comment on Barrett et al.

#### *John Klasios\**

*York University, Toronto, ON, Canada \*Correspondence<EMAIL_ADDRESS>
#### *Edited by:*

*J. Michael Williams, Drexel University, USA*

#### *Reviewed by:*

*Aaron T. Goetz, California State University, Fullerton, USA*

**Keywords: evolutionary psychology, computationalism, human nature, computers, cognitive science**

#### **A commentary on**

#### **From computers to cultivation: reconceptualizing evolutionary psychology**

*by Barrett, L., Pollet, T. V., and Stulp, G. (2014). Front. Psychol. 5:867. doi: 10.3389/fpsyg.2014.00867*

I argue that Barrett et al. (2014) have misinterpreted evolutionary psychologists' notion of computation. Barrett et al. seemingly presume that the notion of computation deployed by evolutionary psychologists (e.g., Pinker, 1997; Tooby and Cosmides, 2005) is tantamount to positing a *physical* architecture whose form of computation proceeds via the syntactic-like transformations of spatially discrete representational symbols or sentence-like structures—i.e., in the manner of a Turing machine. But this is simply not the notion of computation that evolutionary psychologists advocate (in spite of the fact that a Turing machine architecture, for instance, is nonetheless compatible with it).

The notion of computation is philosophically complex, with many different meanings and a multifaceted history (Piccinini, 2012). By "computation," evolutionary psychologists fundamentally mean to say that the brain evolved to compute in the generic sense of the term. This more generic notion of computation, and its relation to a physical substrate, is outlined by Pinker (2005):

"Computation" . . . does not refer to what a commercially available digital computer does but to a more generic notion of mechanical rationality . . . . In this conception, a computational system is one in which knowledge and goals are represented as *patterns* in bits of matter ("representations"). (p. 2, emphasis added)

The misunderstanding of what evolutionary psychologists mean by computation also leads Barrett et al. to view various other conceptions of cognition i.e., embodied, embedded, extended, enactive—as alternatives to the computational approach when, in actuality, they can easily be seen as complementary to it. For evolutionary psychologists are primarily focused on the functional level of analysis of psychological adaptations rather than their physical instantiations (i.e., their causal–physical basis in the brain, body, and wider environment). And this focus on the functional level of analysis allows researchers to investigate psychological adaptations in a manner that abstracts away from their instantiations in the brain, body, and larger context (i.e., ecological) in which they are embedded. The modular, computational framework of evolutionary psychology is quite compatible with, and can be meaningfully situated within, an overall physical and causal account that is highly complex, widely distributed, and highly diffuse. So, far from invalidating or highlighting a "prejudice" inherent to computationalism or evolutionary psychology, the supposed alternative approach that Barrett et al. advocate is rather a difference of focus and emphasis. For there is nothing within the theoretical approach of evolutionary psychology that in principle denies the existence of the kinds of "E-cognition" that Barrett et al. draw attention to. At a pragmatic level, different research programs will simply find it profitable to have differing explanatory focuses and emphases.

Barrett et al. also raise skepticism regarding the relationship between psychological adaptations and their neurobiological underpinnings. But it is important to note that the form–function fit that evolutionary psychologists focus on qua adaptationists pertains most directly to aspects of "psychological design" rather than to properties of the neurobiological realization of those designs. Thus, the reverse-engineering approach accordingly homes in on the psychological level of analysis and not the neurobiological one (or at least not primarily). More generally, at this stage of the game it is premature to draw overly strict conclusions on precisely how psychological adaptations may or may not be instantiated in the brain—e.g., if and how they are "multiply realizable" by neurobiological bases, and whether to interpret neuroimaging results according to a regionally-focused or network-wide perspective, etc. (e.g., Klein, 2012; Colombo, 2013).

Barrett and colleagues' discussion of human nature is also problematic. For instance, they endorse Wheeler and Clark's (2008) conception of human nature as "a kind of meta-nature . . . an extended cognitive architecture whose constancy lies mainly in its continual openness to change" (p. 3572) and lead the reader to believe that it is necessarily at variance with the notion of human nature alluded to by evolutionary psychologists. On the contrary, however, evolutionary psychologists recognize this underlying constancy and refer to it as our underlying "developmental programs" (e.g., Tooby et al., 2003). For evolutionary psychologists, human nature is tantamount to the ontogenesis of our species-typical psychological adaptations. On this view, human nature is envisioned as being expressed through development in ways that are guided, generative, and constrained. The precise details of how guided, generative, and constrained this underlying nature is are of course a complex empirical matter that has barely just commenced, scientifically speaking. At any rate, abstractly modeling postulated psychological adaptations in computational terms is an invaluable method of investigation (see Barrett, 2006, 2007; Bechtel, 2007; Tooby and Cosmides, 2008; Frankenhuis et al., 2013; Levy and Bechtel, 2013).

Indeed, evolutionary psychologists argue that our developmental programs should be computationally mapped in ever-increasing detail, ultimately yielding a high-resolution map of human nature. Barrett et al. claim that human nature can be "cultivated," shaped, and refracted (etc.). But the extent to which this is possible is ultimately an empirical question, and the more we can understand the nature of our developmental programs, the less need we will have for such vague notions. And in any case, however much we can cultivate our developmental programs, they are fundamentally a product of past selection and thus cannot be adapted—in the *adaptationist* sense—to present and future conditions (e.g., Tooby and Cosmides, 1990).

Barrett et al. also crucially omit certain aspects of evolutionary psychologists' treatment of culture. To wit, Barrett et al. imply that evolutionary psychologists cannot account for the way in which material artifacts, beliefs, and so forth, interact with the underlying developmental programs undergirding our species-typical cognitive architecture. To the contrary: evolutionary psychologists' notion of epidemiological culture refers both to the transmission of culture between individual minds and its impact on the cognitive architecture of those minds (Tooby and Cosmides, 1992; Sperber, 1996). Furthermore, models of epidemiological culture can, in principle, be as complex and dynamic as need be. Hence, the allegations by Barrett et al. that evolutionary psychology is inconsistent with or fails in principle to account for such cultural phenomena are baseless.

#### **ACKNOWLEDGMENT**

comments. Thanks to Aaron Goetz for the useful

#### **REFERENCES**

**Conflict of Interest Statement:** The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 20 September 2014; accepted: 05 November 2014; published online: 21 November 2014.*

*Citation: Klasios J (2014) Our computational nature: comment on Barrett et al. Front. Psychol. 5:1348. doi: 10.3389/fpsyg.2014.01348*

*This article was submitted to Evolutionary Psychology and Neuroscience, a section of the journal Frontiers in Psychology.*

*Copyright © 2014 Klasios. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

### The uniquely predictive power of evolutionary approaches to mind and behavior

#### *Ian D. Stephen\*, Mehmet K. Mahmut , Trevor I. Case , Julie Fitness and Richard J. Stevenson*

*Department of Psychology, Macquarie University, Sydney, NSW, Australia \*Correspondence<EMAIL_ADDRESS>
#### *Edited by:*

*Danielle Sulikowski, Charles Sturt University, Australia*

#### *Reviewed by:*

*Gad Saad, Concordia University, Canada*

**Keywords: evolutionary psychology, e-cognition, ethology, explanatory power, proximate/ultimate**

#### **INTRODUCTION**

Barrett et al. (2014) argue that the primary contribution of evolutionary psychology (EP), as defined by the Santa Barbara school (Cosmides and Tooby, 1987; see also Laland and Brown, 2011) is the conception of the mind as a collection of separate, domain-specific mental modules that evolved to solve specific adaptive problems. This, they argue, means that EP does not represent a true alternative to computational models of mind and is therefore not a significant advance on more traditional cognitive approaches. Instead, they recommend that e-cognition, and in particular the concept of the extended mind, can best enhance our understanding of human mind and behavior. While we appreciate Barrett et al.'s enthusiasm for an interesting and relatively new approach to understanding mind and behavior, we argue here that, independent of the veracity of the concept of massive modularity (which is an empirical question; Barrett et al., 2014; Burke, 2014; Stephen, 2014), an evolutionary approach provides a substantial advance in the understanding of mind and behavior. Here, we make two main arguments. First, we argue that a full understanding of mind, brain and behavior requires the consideration of all four of Tinbergen's levels of explanation, which can only be achieved by approaching the problem through the lens of evolution (independent of the assumption of massive, domain-specific modularity, or of any other model). Second, we argue that the embodied cognition approach advocated by Barrett et al. (2014) is actually better understood as an extension of traditional *causal* (mechanistic), and *ontogenetic* (developmental) approaches than as a revolutionary approach in its own right, and therefore is best examined through the lens of evolution.

#### **THE VALUE OF EVOLUTIONARY APPROACHES TO MIND AND BEHAVIOR**

In what is now widely considered the foundational document of human ethology, Niko Tinbergen makes the case that behavior can be addressed at four different explanatory levels (Tinbergen, 1963). In addition to the *causal* (or mechanistic) and *ontogenetic* (developmental) levels of explanation that are typical of modern psychology, Tinbergen proposed that a full understanding of behavior requires that we consider two additional, evolutionary levels of explanation. The *phylogenetic* level considers the evolutionary history of the behavior, and the *functional* level considers what he calls the survival value, or what modern evolutionists would call the fitness value or selective value of the behavior (though more recently, O'Brien and Gallup, 2011, have suggested that the role of culture represents a fifth level of explanation). While Barrett et al. (2014) assert that the primary advance offered by EP is the conception of the mind as massively modular, we suggest that the defining feature of evolutionary approaches to psychology is simply the application of the evolutionary concepts of selection and fitness to human behavior. This approach allows us to address human psychology through Tinbergen's *phylogenetic* and *functional* levels of explanation, providing novel hypotheses and a more thorough understanding of the subject. Despite rarely being acknowledged directly, these principles are applied in a range of evolutionary approaches to mind and behavior (e.g., Stephen, 2013).

This application of evolutionary concepts to psychology is not reliant on the assumption of massive, domain-specific modularity, since predictions derived from such an assumption are often identical to those derived from evolutionary approaches based on plasticity, domaingenerality, and cultural evolution. What changes is merely the level on which selection is assumed to act. Whereas a Santa-Barbara school Evolutionary Psychologist would think of selection as acting upon genes coding for domain-specific, yet flexible, mental modules, a more domaingeneral evolutionary approach would see selection as acting upon the behaviors themselves. In either case, the behaviors and cognitions selected for and against remain the same (Burke, 2014; Stephen, 2014). Indeed, the majority of research in this area does not make direct assumptions about massive modularity or lack thereof (Burke, 2014; Stephen, 2014). The question of whether the mind is massively modular and domain-specific or plastic and culturally selected remains, then, an important empirical question (Barrett et al., 2014), but one that is tangential to the issue of whether evolution offers a useful contribution to the study of mind and behavior (Stephen, 2014).

Irrespective, then, of the unit of selection, we suggest that an evolutionary approach can offer unique insights into understanding and predicting behavior. Indeed, most of the added value brought by an evolutionary approach is reflected in the two neglected aspects (for psychology at least) of Tinbergen's ethological approach to behavior. Evolutionary psychologists are perhaps with good reason shy of admitting that consideration of function may be useful when thinking about behavior. Much of this concern relates to *a posteriori* reasoning, and the criticism of "just so stories." However, a consideration of function *a priori* can be a powerful aid to theorizing and hypothesis generation. In research on disgust, for example, the principal driver behind studying this emotion's relationship with the immune system was based upon the idea that disgust *functions* to aid disease avoidance (Stevenson et al., 2011). Without a consideration of the functional value of this emotion, such avenues of enquiry would not have been envisaged.

A further benefit of an evolutionary approach is in consideration of the phylogenetic origin of a particular behavior. This seems to be a more neglected line of reasoning within human EP, but it can be highly instructive. Again, take disgust as an illustrative example.  This "tail" extends into other mammals (and beyond) and has been termed "distaste." Distaste functions primarily as a specific defense against consuming bitter (poisonous) food. However, mammals and indeed all animals face similar pathogen threats to humans, and it would be surprising if we did not also share some of the same basic behaviors to avoid getting sick. In fact, a very extensive set of disease avoidant behaviors have been documented in animals (e.g., Hart, 2011) but surprisingly, almost no research has explored whether the emotion of disgust plays a role in animal disease avoidance. Not only, then, can the idea of phylogenetic continuity act to stimulate new avenues for research, it can also act to complement the functional approach. For example, if animals do use disgust to assist disease avoidance, this would be consistent with the functional interpretation of disgust in humans. Further, Schaller and Murray's (2008) finding of regional personality differences corresponding to pathogen prevalence offers a clear illustration of the use of evolutionary theorizing to generate novel predictions across multiple levels to draw a connection between traditionally disparate domains. Crucially, *none* of this theorizing relies upon a commitment to any particular theory of the unit of selection.

Intra-species color cues may be taken as another example of a *phylogenetic* approach that has advanced our understanding of human behavior. Color is frequently used to convey information in non-human animals. For example, male hooded vultures have highly vascularized, exposed skin on their heads, which flush red during antagonistic encounters, and male ostriches show redder necks during the mating season, suggesting that this hemoglobin-based coloration is a cue to dominance and fertility (Negro et al., 2006). A *phylogenetic* approach allows us to make predictions about the kinds of perceptual biases and behaviors that we expect to see in humans and other species. We know that the majority of mammals have only dichromatic vision that precludes the differentiation of red from green (Carroll et al., 2001), whereas old world, and some new world, primates have trichromatic vision. The *phylogenetic* approach thus allows us to predict that we may see red cues in primates, including humans and old world monkeys, but not in nonprimate mammals, and new world monkeys with dichromatic vision (Changizi et al., 2006). This is indeed what we see. The red coloration of mandrills' faces increases with higher position in the dominance hierarchy and with higher testosterone (Setchell and Dixson, 2001). During antagonistic confrontations, the less red male is more likely to back down (Setchell and Wickings, 2005), and female mandrills prefer to mate with redder faced males, irrespective of alpha status (Setchell, 2005). Similarly, in humans, we see redder facial skin in men interpreted as appearing more aggressive, dominant, attractive (Stephen et al., 2012), and healthy (Stephen et al., 2009a,b). Indeed, it has been suggested that one evolved function of trichromatic vision in primates may be to enable individuals to identify color-based social cues (Changizi et al., 2006).

This prediction of human psychological traits based on *phylogenetic* approaches, then, allows enhanced predictive power and greater understanding of the psychology of humans.

#### **e-COGNITION'S PROXIMAL EXPLANATORY NATURE**

Barrett et al. (2014) suggest that an alternative to the standard computational theories of mind (in which they include Santa Barbara school EP) is the various e-cognition approaches. They focus on one form, the extended mind hypothesis (e.g., Clark and Chalmers, 1998), which holds that the boundaries of cognition extend well beyond the central nervous system, so that the body and the environment form a coupled system that governs behavior. The main benefit of such an approach, according to Barrett et al. (2014), is that it encompasses the complex array of external features (e.g., written language, visual aids, etc.) that shape human behavior in the current environment.

While we agree that e-cognition approaches offer potentially interesting ways of understanding behavior, we would also argue that they are essentially elaborations of the computational models of mind that Barrett et al. (2014) criticize, representing extensions of Tinbergen's (1963) *causal* (mechanistic), and *ontogenetic* (developmental) levels of explanation. Extending the boundary of cognition to include objects that are not typically considered as part of the cognitive system (e.g., a shopping-list memory aid) does not address a *functional* or *phylogenetic* level of analysis, any more than does a standard computational approach. This can only be achieved by studying behavior through the evolutionary concepts of selection and fitness. As such, Barrett et al.'s suggested alternative to EP—ecognition—does not represent a true alternative to computational models of mind, but rather an extension of these approaches that should be best approached through the lens of evolutionary theory. In this way, Barrett et al.'s (2014) conception of e-cognition as an alternative to evolutionary approaches to cognition and behavior mischaracterizes e-cognition as an ultimate explanatory framework, when it should properly be considered proximal (see Scott-Phillips et al., 2011, for similar arguments in response to previously proposed alternative ultimate explanatory frameworks, such as cultural evolution and epigenetics).

#### **CONCLUSIONS**

Accordingly, we argue that evolutionary approaches provide significant additional predictive and explanatory value above standard computational models by allowing researchers to address the *phylogenetic* and *functional* levels of explanation. Evolutionary approaches to mind and behavior, then, go well beyond existing approaches in their potential to provide an understanding, not necessarily of the how, but of the why, humans behave as they do in an unpredictable world. Consider, for example, the richness and complexity of human emotion: forged over the course of human evolution and responding to present day triggers, the passions drive behavior—albeit often to dysfunctional ends within modern societies (e.g., Fitness and Case, 2003). Understanding such diverse emotions as anger, jealousy, hate, love, disgust, or shame as evolution's executioners (Wright, 1995) provides us with an answer to the question of the "why" of behavior that cannot be addressed by only *causal* and *ontogenetic* levels of analysis. In short, e-cognition accounts, along with other approaches that do not hold the evolutionary principles of selection and fitness as central represent only extensions of the more proximate explanations of mind and behavior, rather than providing the fuller understanding of cognition and behavior that ensues from *phylogenetic* and *functional* level of explanations. Further, one extraordinary achievement of evolutionary approaches to mind and behavior has been to demonstrate the commonalities shared by human beings across time and space as a function of the adaptive problems they have always faced, and continue to face, as social animals who depend upon one another for their survival. Certainly, humans today are confronted with a material, technological world that could not be imagined by humans who lived thousands of years ago. However, a baby from our recent evolutionary past miraculously transported through time to a modern Western environment would still crave attachment and belonging, experience, and respond to the world and others through her senses and feelings, and learn through language how to interpret, communicate, and function more or less adaptively in that environment, just as babies raised in regions geographically distant from their ancestral homelands do today. No doubt she would also help her parents program their latest iPhone along the way.

#### **REFERENCES**

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 07 October 2014; accepted: 11 November 2014; published online: 28 November 2014.*

*Citation: Stephen ID, Mahmut MK, Case TI, Fitness J and Stevenson RJ (2014) The uniquely predictive power of evolutionary approaches to mind and behavior. Front. Psychol. 5:1372. doi: 10.3389/fpsyg.2014.01372*

*This article was submitted to Evolutionary Psychology and Neuroscience, a section of the journal Frontiers in Psychology.*

*Copyright © 2014 Stephen, Mahmut, Case, Fitness and Stevenson. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

### The not-always-uniquely-predictive power of an evolutionary approach to understanding our not-so-computational nature

Gert Stulp<sup>1</sup> \*, Thomas V. Pollet <sup>2</sup> and Louise Barrett <sup>3</sup>

*<sup>1</sup> Department of Population Health, London School of Hygiene & Tropical Medicine, London, UK, <sup>2</sup> Department of Social and Organizational Psychology, VU University Amsterdam, Amsterdam, Netherlands, <sup>3</sup> Department of Psychology, University of Lethbridge, Lethbridge, AB, Canada*

Keywords: evolutionary psychology, cognition, cognitive integration, modules, extended mind

#### Introduction

#### Edited by:

*Danielle Sulikowski, Charles Sturt University, Australia*

#### Reviewed by:

*Darren Burke, University of Newcastle, Australia*

> \*Correspondence: *Gert Stulp<EMAIL_ADDRESS>
#### Specialty section:

*This article was submitted to Evolutionary Psychology and Neuroscience, a section of the journal Frontiers in Psychology*

Received: *17 February 2015* Accepted: *25 March 2015* Published: *21 April 2015*

#### Citation:

*Stulp G, Pollet TV and Barrett L (2015) The not-always-uniquely-predictive power of an evolutionary approach to understanding our not-so-computational nature. Front. Psychol. 6:419. doi: 10.3389/fpsyg.2015.00419* We thank Klasios (2014)<sup>1</sup> and Stephen et al. (2014)<sup>2</sup> for their commentaries on our paper (Barrett et al., 2014) 3 . Criticisms like these can only help to improve the quality of arguments offered on both sides. Both Klasios's and Stephen et al.'s commentaries generate misconceptions, however, about the aim of our article and our stated position. Before we respond more generally to their arguments, we want to correct these mistaken impressions.

First, Klasios states that we misinterpret the EP notion of computation. This is simply false. We do not argue that EP posits a physical architecture. Our characterization of the EP view (p. 3) is that it "relies heavily on analogies to computational algorithms, functions, inputs, and outputs" and that its research strategy "involves . . . hypothesizing the kinds of algorithmic "design features" that any psychological adaptation would require in order to solve such a problem." The notion of a physical architecture was raised in response to Robert Kurzban's implied suggestion that psychological adaptations are analogous to morphological (i.e., physical) adaptations, and can be reverse engineered in the same way. We disputed Kurzban's argument precisely because there are no grounds for positing a particular kind of physical architecture that could serve to support such an analogy (see also Peters, 2013).

Second, Stephen et al. (2014) present our argument as stating that the primary contribution of an evolutionary approach to psychology is the idea of massive modularity when, in fact, we stated merely that the modularity of evolved adaptations is the primary distinction between EP and standard computational theories. We do not consider modularity to be the primary contribution of an evolutionary approach to human behavior, as should be clear from our previous work (e.g., Barrett et al., 2001; Pollet et al., 2009; Stulp and Barrett, 2014), as well as our argument in the original paper.

Both these misconceptions perhaps arise because of a failure to appreciate that we were addressing the specific question posed for this research topic: is EP the obvious alternative to standard computational approaches to the mind? Our answer was that one evolutionary approach to psychology (i.e., the "Santa Barbara School" of Evolutionary Psychology, which we refer to as EP throughout this piece) was not an alternative approach, nor could it be,

<sup>1</sup>http://journal.frontiersin.org/article/10.3389/fpsyg.2014.01348/full <sup>2</sup>http://journal.frontiersin.org/article/10.3389/fpsyg.2014.01372/full

<sup>3</sup>http://journal.frontiersin.org/article/10.3389/fpsyg.2014.00867/full

precisely because it is a computational theory. As such, it could only be distinguished from other cognitive approaches via the manner in which it applied evolutionary thinking. A large part of our paper was then devoted to why we felt the particular evolutionary approach adopted—namely, modular psychological adaptation—fell short. Other evolutionary approaches are not vulnerable to this criticism, and so we did not include these in our analysis. Thus, nowhere do we dispute Stephen et al.'s main point that evolutionary theory is useful for explaining human behavior and that, using Tinbergen's integrative approach, one can generate unique predictions (see also Barrett and Stulp, 2013).

### The Not-Always-so-Uniquely Predictive Ability of Evolutionary Theory

We do want to add, however, that evolutionary theory may not always be as uniquely predictive as Stephen et al.'s examples suggest. With respect to disgust, we read (p. 2): "the principal driver behind studying this emotion's relationship with the immune system was based upon the idea that disgust functions to aid disease avoidance (Stevenson et al., 2011)" and that such "avenues of enquiry would not have been envisaged" without evolutionary theorizing. Their confidence in the latter statement is perhaps misplaced, however, as Stevenson et al.'s (2011) research drew explicitly on earlier findings by Bosch et al. (2001) that were obtained without any reference to either disgust or evolutionary theory (as acknowledged by Stevenson et al., p. 900). At best, then, we might say that, in this case, the functional explanation represents a plausible post-hoc account and further clarification of an already established phenomenon, rather than that the functional perspective made unique predictions that allowed the phenomenon to be identified in the first place.

Similarly, in their second example, Stephen et al. predict that species with trichromatic vision (i.e., the ability to distinguish red from green) will make use of red coloration as cues and signals more than dichromats. Again, the prediction that animals unable to see red will not make use of red coloration, whereas those animals that can see red potentially might do so, is in itself not a very strong evolutionary prediction, given that one could just as easily formulate such a prediction solely on an understanding of extant species' visual systems. It is, however, important to note that we are not denying the importance of evolutionary theory. Our point is simply that we should not overstate its power to generate unique predictions and empirical findings that would otherwise not occur. Similarly, most findings in evolutionary psychology are, as the authors of many of these articles themselves note, consistent with evolutionary predictions, but do not rule out other potential explanations.

### Ultimately Proximate?

Stephen et al.'s second point is that we have confused proximate and ultimate levels of explanation. Specifically, they state that "Barrett et al.'s (2014) conception of e-cognition as an alternative to evolutionary approaches to cognition and behavior mischaracterizes e-cognition as an ultimate explanatory framework, when it should properly be considered proximal" (p. 2). We believe this criticism is unwarranted for several reasons. First, we raised E-cognition as an alternative to the standard cognitivist, computational approach to psychology, and not to a functional evolutionary approach. We do not dispute that phylogenetic and functional levels of explanation can provide additional "explanatory value above standard computation models" (p. 3). Our actual argument was that E-cognition, and cognitive integration in particular, could fill some of the gaps left open by current information-processing approaches, and we said nothing to suggest that this should occur to the exclusion of evolutionary theory. Rather, our point was that, to take Stephen et al.'s example, seeking answers to how and why humans can program things like iPhones (and obviously conceive of and manufacture them in the first place) seems crucial to achieving a "fuller understanding of cognition and behavior" (p. 3) than we currently possess. Stephen et al. must surely agree that such a full understanding goes well beyond the phylogenetic and functional levels of explanation, and our closing plea for explanatory pluralism was made precisely for this reason. Klasios, while (surprisingly) using this point against us, actually agrees on this when he states that "[a]t a pragmatic level, different research programs will simply find it profitable to have differing explanatory focuses and emphases" (p. 1).

Second, nowhere did we "mischaracterize" E-cognition as an ultimate framework, in just the same way that no one argues that information-processing theories represent an ultimate framework. Both are guiding theories that take a particular stance on the nature of cognitive processes and, in that sense, both can be seen as more proximate than ultimate. Some E-cognition theories may stand on their own without referring to evolutionary theory, in the same way that most information-processing-theories similarly lack this explicit connection. That said, Stephen et al. perhaps jumped the gun by stating that E-cognition is a proximate and not an ultimate approach, without providing any reason as to why this is the case. Indeed, some forms of E-cognition are fundamentally evolutionary. For instance, certain aspects of the extended mind argument have been made in an explicitly evolutionary way, captured by Clark's (2005) "007 Principle" and Rowlands' (2003) "barking dog principle." Both of these suggest that a thrifty evolutionary process will not build internal resources (especially expensive neural tissue) if the structure of the environment itself can be exploited in a way that can bear some of the cognitive burden. Distributed, extended cognition is thus the process by which internal resources are replaced or complemented by reliable external structures, with the idea that organisms that pursue this route will achieve higher fitness. This is supported by analogies from other species (for example, the manner in which the physics of a cricket's body automatically filters out extraneous sounds; a process that would otherwise need to be performed by neural tissue: Barrett, 2011) and so the extended mind also adopts the phylogenetic perspective for which Stephen et al. advocate.

#### Openness to Change Rather than Constancy as a Constant

Klasios, in contrast, believes that our suggestion for E-cognition as an alternative to standard computational approaches stems from our flawed understanding of computation, and that "there is nothing within the theoretical approach of evolutionary psychology that in principle denies the existence of . . . 'E-cognition'" (p. 1). We disagree strongly with this point, and tackle it in conjunction with Klasios's assessment that "our discussion of human nature is also problematic" (p. 1). The latter assertion seems to be based on a misreading of Wheeler and Clark (2008) statement that our extended cognitive architecture's "constancy lies mainly in its continual openness to change" (p. 3572, emphasis added). While we take "change" to be the key here, Klasios takes it to be "constancy," arguing that EP recognizes "this underlying constancy and refers to it as our underlying 'developmental programs'" (p. 1). Klasios' apparent misunderstanding of Wheeler and Clark's position leads nicely into a consideration the fundamental differences between E-cognition and computational theories.

It is important to note that we completely agree that some varieties of E-cognition can be seen as complementary to computational theories, given that they raise no objections to a rulesand-representations approach (as we explicitly addressed in our paper; p. 10). The EP position on psychological phenomena as adaptations, however, does not, in fact, gel very well with E-cognition, since the latter argues for the deep intertwining of brain, body and environment, whereas EP emphasizes a disjunction between these elements. EP's premise is that cognitive processes occur in the brain alone, and that our psychology is adapted to a past (environment) that in large part no longer exists, hence we are often mismatched to the modern world (e.g., Tooby and Cosmides, 1990). In this view, our psychological processes may often operate in opposition to the world around us, whereas the E-cognition view is that body and environment should be considered as integral parts of the cognitive system. We can see this even more clearly in Klasios's suggestion that EP deals only with a functional level of explanation that "abstracts away from instantiations in brain, body and the larger context in which they are embedded" (p. 1). In addition to the fact that

#### References

the concept of an "abstracted adaptation" is entirely unclear to us, this position is fundamentally at odds with an E-cognition view which holds that no such abstraction is possible because cognitive processes are precisely a function of a brain embedded in a body embedded in an environment, all of which make crucial, often constitutive, contributions to those cognitive processes (e.g., Clark, 1997).

Klasios goes on to suggest that we misrepresent the EP view on human nature by neglecting Sperber's notion of epidemiological culture (see e.g., Sperber, 1996), which, according to Klasios, is equivalent to an E-cognition approach. Sperber's (1996) argument is, however, focused more strongly on how existing (evolved) psychological structures influence the kinds of cultural patterns produced (as captured in his notion of "cultural attractors"), with less emphasis placed on how culture actively alters our psychology. This is perhaps to be expected given that Sperber (1996) adheres to a standard EP view of psychological adaptations (modules) to past environments (also note that epidemiological or transmitted culture is given far less prominence in Tooby and Cosmides' conception of culture than Klasios suggests). Sperber's more recent position is that cultural phenomena "invade and inflate" our evolved mental modules, often resulting in "mismatches" between evolved function and current usage (Sperber and Hirschfeld, 2004), whereas cognitive integration argues that our psychology is never fixed but continually transformed as it incorporates various kinds of cultural artifacts (including the iPhone).

#### Conclusion

Again, we would like to thank John Klasios and Ian Stephen and colleagues for engaging in this discussion and providing us with the opportunity to clarify our position. We hope our original paper and this reply continue to spark debate on our computational nature or lack thereof.

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2015 Stulp, Pollet and Barrett. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

## Evolved computers with culture. Commentary: From computers to cultivation: reconceptualizing evolutionary psychology

Gregory A. Bryant\*

*Department of Communication, University of California, Los Angeles, Los Angeles, CA, USA*

Keywords: computational theory of mind, domain specificity, evolutionary psychology, cultural learning, e-cognition

#### **A commentary on**

**From computers to cultivation: reconceptualising evolutionary psychology** by Barrett, L., Pollet, T., and Stulp, G. (2014). Front. Psychol. 5:867. doi: 10.3389/fpsyg.2014.00867

Barrett et al. review recent developments in evolutionary psychology (EP) and conclude that EP offers little in way of theoretical advancement over standard computational theory of mind (CTM) accounts, because traditional approaches in psychology implicitly accept that cognition is evolved. To Barrett et al., historical resistance to EP is surprising given that EP assumes the traditional computational-representational model of cognition. Across cognitive psychology, however, evolutionary approaches are sometimes accepted, but often mostly ignored. Vision and auditory perception researchers are typically functionalist, and as a result have made advances exceeding other areas of cognitive science—these scholars are often friendly to EP at least in some form. But many other areas have neither adopted a functionalist perspective nor currently accept the research program of EP. Certainly, most researchers in cognitive psychology do not attempt to reverse engineer computational solutions to adaptive problems as EP does. Not coincidentally, many cognitive psychologists study what EP would consider nonfunctional by products.

Still, it is true that EP has largely embraced cognitive psychology (though actual cognitive research is still surprisingly rare) and has integrated it with theories from evolutionary biology. Barrett et al. suggest that the adoption of the CTM constitutes a weakness for EP and they instead propose that various forms of e-cognition (i.e., embodied, embedded, enactive) offer a viable alternative to computational approaches. But as Klasios (2014) pointed out in his recent commentary, Barrett et al. fail to recognize that "cognitive integration" is information processing, and in its most basic sense, is necessarily computational. As Gallistel and King (2009) recently put it, describing the mind as a case of digital computation "is the only game in town" (p. 24). There is no scientific alternative to the notion that the neural coding of events in the world involves the probabilistic transformation of information. If one admits that much, logical entailments prevent the kind of rejection of the CTM that Barrett et al. endorse.

Notions of e-cognition can be provocative, and on the surface can seem like an advancement in our ideas about human cognition. However, there are some fundamental problems in the current presentation and the ideas in general. By suggesting that our cognition is shaped by cultural artifact use, I believe Barrett et al. point the causal arrow mostly backwards. That is not to say that artifacts cannot, in principle, affect brain organization, but the evidence to date seems to favor the idea that cultural phenomena are generally tailored to our brains and bodies, not the reverse (Claidiere and Sperber, 2007). For instance, the authors use the example of time-pieces contributing to culturally

#### Edited by:

*Danielle Sulikowski, Charles Sturt University, Australia*

> Reviewed by: *Thom Scott-Phillips, Durham University, UK*

> > \*Correspondence: *Gregory A. Bryant<EMAIL_ADDRESS>
#### Specialty section:

*This article was submitted to Evolutionary Psychology and Neuroscience, a section of the journal Frontiers in Psychology*

Received: *23 March 2015* Accepted: *08 April 2015* Published: *22 April 2015*

#### Citation:

*Bryant GA (2015) Evolved computers with culture. Commentary: From computers to cultivation: reconceptualizing evolutionary psychology. Front. Psychol. 6:498. doi: 10.3389/fpsyg.2015.00498* evolved values associated with timeliness, and they attribute timeliness as being part of our human nature, essentially arguing that extended artifacts like time-pieces have altered our cultural cognitive machinery. There is no question that inventions like time-pieces feed back into practices and beliefs—the more we advance the technology, the more we allow ourselves to be manipulated by it. But timeliness is a byproduct of social coordination, cooperation, and reciprocity. If an individual demands that her associate pay attention to the time—an ability afforded by a time-piece—and then the associate does not abide when able to do so, he is implicitly discounting the value of the relationship. The human nature component in this example is not the timeliness per se, but the use of culturally evolved norms as a means to coordinate social interactions.

Admittedly, the ways neural coding schemes relate to various phenomena in the world, external to the brain itself, constitute hard empirical questions that will almost certainly need to incorporate many complexities suggested by various forms of e-cognition. These issues will likely be resolved, however, within a framework that involves, at its theoretical core, computational mechanisms implemented in the brain. Even if some of the external phenomena that e-cognition proponents describe constituted legitimate examples of extended phenotypic traits (Dawkins, 1982), their implementation would still land squarely in the neural circuitry of the brain interfacing with motor systems. For example, written language is learned by people quite effectively and writing systems are shaped by both cultural and cognitive factors, including visual processing and memory systems. There is evidence of a brain area that, when given certain input, reliably develops expertise for visual words (Dehaene, 2009), showing amazing flexibility in how brain structure interacts with culture (Barrett, 2012). But our understanding of the psychology of reading is purely computational. Similarly, we don't need a special theory of beaver cognition because of beaver dams—we just need to explain the evolved cognitive and behavioral processes that allow beavers to build them.

Evolutionary behavioral scientists who study culture often rely on the concept of domain generality, presumably because cultural phenomena seemingly incorporate so many aspects of our cognition and environment. Of course, culture is deeply interconnected with many facets of our cognitive processing, but that does not require a system that is infinitely flexible and unconstrained by past selection. Rather, culture is rooted in a suite of cognitive and communicative abilities that allow us to transmit rich information vertically and horizontally, and the outputs of such processes feedback iteratively into an evolutionarily dynamic cultural knowledge system rooted in adaptive computational design. Cultural transmission often follows certain patterns resulting in stable psychological and communicative strategies that have all the hallmarks of domain specificity: (i) our attention is directed in specific ways to particular relevant agents, (ii) motivational systems drive the spreading of specific kinds of information, and iii) cultural learning systems are content sensitive.

The authors acknowledge the idea that there is no defensible dividing line between domain specific and domain general mechanisms (Barrett and Kurzban, 2006), but then they fail to properly appreciate this in their treatment of certain culturally learned information, such as the special status of incest taboos in cultural transmission. In the example given, Barrett et al. fail to acknowledge the possibility that unconscious processes guiding incest avoidance (Lieberman et al., 2007) were driving the mating decisions described by Durham (2002) despite variations over time in the local cultural rules. Overall, they emphasize examples of domain-general mechanisms potentially solving problems that some evolutionary psychologists consider only manageable by highly specialized domain-specific systems but seem to momentarily forget that just because a mechanism works across content domains, it is still functionally specialized. The scope of a mechanism is independent from whether it has design features (i.e., functional specialization) (Barrett and Kurzban, 2006). Cognitive mechanisms, including associative learning processes and various decision making systems sensitive to local information, can operate on representations across multiple domains and subsequently feed into more specialized systems—cognition is hierarchically structured, and evolutionarily conserved (Barrett, 2012). So where is the argument exactly?

Despite these disagreements—some apparent, some real— Barrett et al. seem to illustrate that the historical gap between behavioral ecology and evolutionary psychology is closing, not widening. Many evolutionary psychologists are developing a greater appreciation for cultural evolution and behavioral flexibility, and behavioral ecologists are more concerned now with cognitive adaptations and experimental psychology methodology. Both fields have led the behavioral sciences in cross-cultural fieldwork, and to a great extent, we share a theoretical foundation. Don Symons's question (1987) still looms, however: If we're all Darwinians, what's the fuss about?

#### References

Dawkins, R. (1982). The Extended Phenotype. Oxford: WH Freeman. Dehaene, S. (2009). Reading in the Brain. New York, NY: Viking.

Symons, D. (1987). "If we're all Darwinians, what's the fuss about?" in Sociobiology and Psychology, eds C. B. Crawford, M. F. Smith, and D. L. Krebs (Hillsdale, NJ: Erlbaum), 121–146.

**Conflict of Interest Statement:** The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2015 Bryant. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

## Evolved biocultural beings (who invented computers)

Louise Barrett <sup>1</sup> \*, Thomas V. Pollet <sup>2</sup> and Gert Stulp<sup>3</sup>

*<sup>1</sup> Department of Psychology, University of Lethbridge, Lethbridge, AB, Canada, <sup>2</sup> Department of Social and Organizational Psychology, VU University Amsterdam, Amsterdam, Netherlands, <sup>3</sup> Department of Population Health, London School of Hygiene and Tropical Medicine, London, UK*

Keywords: evolutionary psychology, extended mind, cognition, culture, embodied cognition

#### Introduction

Many thanks to Bryant (2015) for keeping the conversation lively, and engaging in further debate on our paper (Barrett et al., 2014). Although Bryant raises several interesting points, it appears that, as with our previous commentators, there was some misunderstanding of our aim, which simply was to answer the question posed for us: does evolutionary psychology represent an alternative to computational theories of mind? To reiterate, we suggested that Santa Barbara-style EP could not be an alternative given that it already is a computational theory of mind. Bryant (2015) apparently considers this question ill-posed, given his assertion that viewing "the mind as a case of digital computation" is "the only game in town." Our friendly suggestion here is that perhaps he needs to get out a little more, and sample more fully the alternatives on offer.

#### Edited by:

*Danielle Sulikowski, Charles Sturt University, Australia*

#### Reviewed by:

*Michael Stirrat, University of Stirling, UK*

\*Correspondence: *Louise Barrett<EMAIL_ADDRESS>
#### Specialty section:

*This article was submitted to Evolutionary Psychology and Neuroscience, a section of the journal Frontiers in Psychology*

Received: *29 April 2015* Accepted: *09 July 2015* Published: *22 July 2015*

#### Citation:

*Barrett L, Pollet TV and Stulp G (2015) Evolved biocultural beings (who invented computers). Front. Psychol. 6:1047. doi: 10.3389/fpsyg.2015.01047*

#### Not the Only Metaphor in Town

"Freud often compared the brain to hydraulic and electro-magnetic systems. Leibniz compared it to a mill, and I am told the ancient Greeks thought the brain functions like a catapult. At present, obviously, the metaphor is the digital computer."

∼ John Searle

To assert that there is no alternative to digital computation is a philosophically weak position, not least because the history of science provides ample evidence of prominent ideas eventually shown to be wrong: phlogiston and the luminiferous aether were also "the only game in town" once upon a time. The brain has been likened to many other cultural tools that were, unsurprisingly, considered to be of great significance in their time; the computational metaphor is one in a long line of metaphors that reflect the most advanced technology of their day. There is no reason to imagine that we have finally managed to hit on the correct one, as opposed to the one that just reflects something about the times in which we live (Barrett, 2011).

Our main point, though, is that digital computation really isn't the only game in town. Among other work cited in our original paper, Chemero (2009) provides the most recent and comprehensive treatment of a non-computational-representational approach to mind (see also Anderson (2014, 2015) for a more neuroscientifically-focused account that similarly concludes the best way to understand the brain may be in enactive and ecological terms). Furthermore, this approach is not restricted to philosophical theorizing but also includes empirical work (see Dotov et al., 2010, as well as the examples given in Chemero, 2009). There have also been earlier incarnations of a non-representational approach to cognition (e.g., Rosch et al., 1992; Thelen and Smith, 1994; Kelso, 1997) along with Gibson's (1979) anti-representational theory of perception (see Barrett, 2011 for a review). Given Bryant's (2015) assertion of no scientific alternative to computation, he implies either that such genuinely non-computational-representational approaches do not qualify as science, or else he has misunderstood them. Although all we need do to counter Bryant's position is point to these scientifically credible alternatives, in what follows we consider briefly some of the arguments against a strong computational position. We then go on to discuss his other assertions regarding the relationship between culture and cognition.

It is telling that Bryant (2015) adopts a rather "Hegelian" approach in his commentary (see Chemero, 2009, and our original article), asserting the necessity of digital computation and information processing (conceived in terms of Shannon information theory: G. Bryant, Pers. Comm.), rather than providing arguments or evidence for it. As Wallace (2007) discusses, echoing Searle (1990) before him, the notion of the brain as engaged in digital computation is not a scientific discovery, like the moons of Saturn, but is instead a claim: a claim that looking at the brain in this particular way is useful. As Wallace (2007) argues, Shannon's theory was a pragmatic solution to an explicitly human engineering problem, and was never intended as a scientific theory of cognition. Using Shannon information to model human cognition is fundamentally flawed because, as Wallace (2007) discusses, human cognitive systems violate the assumptions under which Shannon information applies. Wallace (2007) further notes that use of terms like "information processing" to describe brain function can lead to a dualist position. Such thinking pervades Klasios's (2014) commentary, for example, when he argues that EP deals only with information processing and not neural activity as such, giving rise to the brain possessing two distinct qualities: the material activity of its neurons and, as Wallace (2007) calls it, the non-material, "mysterious world of information."

Bryant's argument rests on the notion that adopting an information theoretic view is, in essence, a functionalist perspective, asking what role a given process plays, rather than the specific manner in which it is brought about or implemented. This is entirely reasonable—such a position has helped avoid a particular kind of "neural chauvinism" that suggests there is something inherently special about biological brains, so excluding any form of artificial intelligence from consideration. In addition, cognitive integration is often characterized as a form of "extended functionalism" (e.g., Wheeler, 2010) precisely because it attempts to expand the bounds of the cognitive system beyond the biological brain. That said, it is also apparent that understanding neural implementation is crucial to generating well-founded hypotheses about brain function. Neurobiological data are particularly useful for guiding evolutionary theories by constraining our hypotheses with respect to what brains can reasonably be expected to achieve (see Colombo, 2013 and Peters, 2013). Bryant and Klasios both stick to the classical cognitivist EP party line, justifying a strategy of studying the computational-algorithmic levels alone, but we think that EP, and evolutionary approaches more generally, would benefit from using neurobiological data to inform their theoretical stance, thus grounding our knowledge in living biological systems; we are, after all, attempting to explain how such living biological systems work. Such a stance is also a natural element of the embodied perspective we endorse, which argues that the way brains are put together will matter for cognition (that is, the way that neurons, glia, neurotransmitters and neuromodulators actually go about doing their job) and how adaptive behavior in the world is generated.

From our perspective, then, it seems well-worth considering the radical non-representational/non-computational alternative proposed by Chemero (2009), as well as related work on cognitive integration. As Chemero (2009) himself points out, and as we acknowledged in our original article, embodied/dynamical approaches do not entail a rejection of all representational theories of mind. Clark (1997), for example, argues that there are certain "representation-hungry" (i.e., linguistic) processes that do not seem amenable to an account grounded in coordinated sensorimotor processes alone. Thus, there is some effort being made to reconcile embodied and dynamical approaches with computational/ representational theories (e.g., Barsalou's, 1999 "perceptual symbol systems" and Clark's, 1997 "dynamic computationalism"). At a minimum, however, the recognition of alternatives to computational-representational theories of mind make it possible to ask some penetrating questions about the nature of representation in a computational model of mind, and whether such representations are, in fact, doing all of the cognitive work, all of the time (Barrett, 2011). Thus, when Bryant (2015) asserts that cognitive integration is a computational theory he is not wrong, but nor is he right. More specifically, the issue of whether cognition is extended can be viewed as orthogonal to whether cognition should be viewed as computation (see Sutton, 2014): the issue at stake is where the bounds of the cognitive system should be drawn, and whether bodily resources, material artifacts, and other aspects of the environment can be considered constitutive parts of the cognitive system or simply causally related to them. We argued for the constitutive approach, because this follows naturally from a radical embodied view that treats cognitive processes as products of the interaction between brain, body, and environment and not the brain alone (see also Chemero, 2009; Barrett, 2011; Hutto and Myin, 2013). Even if one wishes to adhere to a computational framework, however, cognitive integration can and does represent an alternative approach to standard cognitive psychology because it views cultural artifacts (in the human case) and other environmental resources as an integral part of cognitive systems (a point made in both Barrett et al., 2014, and reiterated in Stulp et al., 2015); cognitive integration does not view the brain alone as the part that does all the heavy-lifting. To counter this, as Bryant (2015) and Klasios (2014) do, simply by insisting that brains compute is to precisely miss this point.

#### Loops, Not Arrows

Bryant (2015) also suggests that we have got our causal arrow largely pointing backwards. According to Bryant, culture is primarily shaped by our brains and bodies, and not vice versa (although he then goes onto suggest something very similar to our position where "the outputs of such processes feedback iteratively into an evolutionarily dynamic cultural knowledge system," which points to a tension—if not an outright contradiction—in his argument). Of course, human brains are involved in the creation and use of artifacts and other forms of cultural representation, and hence brains must be involved in the shaping of culture—this is not at odds with anything we said in our original paper. The argument from the extended mind, however, is that, by extending our cognition beyond the biological brain, we become capable of feats that would otherwise be impossible. Malafouris' (2013) recent analysis of how physical artifacts allowed us to make the transition from numerosity to a formal concept of number and hence mathematics is another good example (see also Menary, 2007). Our position, then, is that we did not get the causal arrow backwards because there is no arrow. Instead, there are loops of continual reciprocal causation, with social activities and material culture both shaping and being shaped by the brain in an ongoing cycle.

By seizing on our example of timeliness as ultimately reflecting concerns about coordination and cooperation, Bryant (2015) over-simplifies and trivializes our position. Perhaps we made our point too flippantly. What we were attempting to convey was the idea that, through our invention of hours, minutes, and seconds, along with devices to measure their passing, our specific concept of time as a fourth dimension (and so on through to the concept of space-time that characterizes Einstein's theory of relativity), has fundamentally transformed aspects of human thought and practice. There seems no way that our use of time can be reduced entirely to the demands of social coordination and cooperation. Indeed, it is interesting to note that both Basu and Waymire (2006) and Mullins et al. (2013) make exactly the reverse argument to Bryant (2015) suggesting that large-scale human cooperation was dependent on material culture, namely writing and record-keeping (although these authors argue that this allowed us to "transcend" our evolved psychology, we would suggest this represents an example of how human psychology is inherently extensive and integrated with environmental and cultural resources). Although timeliness could be a by-product of social norms and customs as Bryant suggests, the concept of time is not: our invention of various ingenious ways to measure time and how we use these to shape our lives, permit us to go far beyond anything that our Pleistocene ancestors were capable of. Of course, humans are not "infinitely flexible and unconstrained by past selection," but one has to admit there is something about the sheer inventiveness of modern human behavior that quite clearly reflects the manner in which cultural artifacts augment, enhance, and extend our evolved biological brains.

#### Functional Fuzziness

Bryant (2015) identifies one last failing on our part concerning the relationship between domain-generality and specificity, with reference to our argument on incest taboos. Namely, he suggests that we did not consider the possibility that unconscious mechanisms guide our behavior under such circumstances. Far from failing to acknowledge this, however, we cited Westermarck (1921) in precisely this context. It is odd that Bryant picks up on an aspect of our argument that was made explicit in our original piece, but ignores its substance, which was to counter the idea put forward by Cosmides and Tooby (1994) that incest avoidance requires innate domain-specific knowledge because such knowledge could not, even in principle, be learned. Instead, Bryant attempts to shift the emphasis, making the point that "just because a mechanism works across content domains, it is still functionally specialized. The scope of a mechanism is independent from whether it has design features." To the extent that we understand this statement, it seems to promote a rather fuzzy notion of functional specialization, and deny the very motivation for EP-style "design thinking" in the first place: that is, the notion that specialized tasks require specialized mechanisms, and cannot be solved effectively by general-purpose mechanisms that apply across several domains. Such a statement also raises an empirical worry for, if it is true that a mechanism's scope is independent of its design features, how does one go about identifying evolved functionally-specialized mechanisms applied to a new domain as opposed to evolved domain-general mechanisms operating on one of the several tasks to which they are well-suited? There seems to be no means of distinguishing the two. Consequently, when Bryant asks: where is the argument here? We would suggest that, not only is there an argument to be had, but it is one that cuts to the very heart of the EP project.

#### Why All the Fuss?

Summing up, Bryant (2015) suggests the gap between human behavioral ecology and EP is closing, but notes that Symons (1987) question remains: if we're all Darwinians, what's all the fuss about? For us, the fuss is about the rather restrictive view of human psychology promoted by EP, and the failure of some of its assumptions to withstand close scrutiny; a topic that occupied two-thirds of our original paper. More broadly, we think it is worth considering whether we should continue to base our model of the mind on inanimate computation (a notion that has human intentionality built into it at source) or whether we should pursue a truly evolutionary route that grounds psychology (of both human and non-humans) in living biological systems a view that further permits the study of humans as hybrid embodied-extended biocultural beings who invent all kinds of things and so continually reinvent themselves. For us, this is another good reason why some Darwinians should continue to make a fuss.

### Funding

LB is supported by NSERC Canada Research Chairs and Discovery Grant Programs; TP is supported by The Netherlands Organisation for Scientific Research (Veni scheme; 451.10.032); GS is supported by The Netherlands Organisation for Scientific Research (Rubicon Post-Doctoral Fellowship).

#### References

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2015 Barrett, Pollet and Stulp. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

### Extended evolutionary psychology: the importance of transgenerational developmental plasticity

#### *Karola Stotz\**

*Department of Philosophy, Macquarie University, Sydney, NSW, Australia*

#### *Edited by:*

*Danielle Sulikowski, Charles Sturt University, Australia*

#### *Reviewed by:*

*Darren Burke, University of Newcastle, Australia Luc-Alain Giraldeau, UQAM, Canada*

#### *\*Correspondence:*

*Karola Stotz, Department of Philosophy, Macquarie University, Sydney, 2109 NSW, Australia e-mail<EMAIL_ADDRESS>
What kind mechanisms one deems central for the evolutionary process deeply influences one's understanding of the nature of organisms, including cognition. Reversely, adopting a certain approach to the nature of life and cognition and the relationship between them or between the organism and its environment should affect one's view of evolutionary theory. This paper explores this reciprocal relationship in more detail. In particular it argues that the view of living and cognitive systems, especially humans, as deeply integrated beings embedded in and transformed by their genetic, epigenetic (molecular and cellular), behavioral, ecological, socio-cultural and cognitive-symbolic legacies calls for an extended evolutionary synthesis that goes beyond either a theory of genes juxtaposed against a theory of cultural evolution and or even more sophisticated theories of gene-culture coevolution and niche construction. Environments, particularly in the form of developmental environments, do not just select for variation, they also create new variation by influencing development through the reliable transmission of non-genetic but heritable information. This paper stresses particularly views of embodied, embedded, enacted and extended cognition, and their relationship to those aspects of extended inheritance that lie between genetic and cultural inheritance, the still gray area of epigenetic and behavioral inheritance systems that play a role in parental effect. These are the processes that can be regarded as transgenerational developmental plasticity and that I think can most fruitfully contribute to, and be investigated by, developmental psychology.

**Keywords: extended inheritance, parental effects, developmental niche, developmental plasticity, embodied cognition, extended cognition, extended evolutionary synthesis**

#### **INTRODUCTION**

There exist two quite different stances toward the evolution of human cognitive capacities. The nativist stance, favored for instance by Evolutionary Psychologists (EP), attributes the origin of behavioral, social and cognitive capacities such as folk psychology, mind-reading and general reasoning capacities to the sudden appearance of genetically determined mental modules or representational systems. This approach, which subscribes to the computational theory of mind, has been polemically dubbed the "Rational Bubble stance (which) confounds cultural symbolic achievements with individual cognitive competences" and belongs to a class of views that have in recent years come under increasing criticism as a quite unrealistic model of cognitive growth (McGonigle and Chalmers, 2008, p. 143). An alternative view, now sometimes called the *e*mbodied, *e*mbedded, *e*nactive, extended (4E) cognition approach, is united by its opposition to traditional cognitivism and methodological individualism (Menary, 2010). Despite the differences between the separate views they all seem to agree on the necessity to place active agency at the center of cognition and the importance of cognition's scaffolding through developmental, ecological, and cultural niche construction. In addition this approach presupposes only very simple and modest biological preadaptations, e.g., in the perceptual realm or general developmental plasticity (Donald, 2000a,b; Griffiths and Stotz, 2000; Tomasello, 2000; Sterelny, 2003; Wheeler and Clark, 2008; Stotz, 2010).

There is natural affinity between one's view of the nature of the mind and an understanding of how the mind developed and evolved. The Modern Synthesis—the evolutionary theory to which EP is entirely wed—almost exclusively invokes natural (including kin and sexual) selection as the driving force, genetic mutations as the creative force and genetic transmission as the only mechanism of heredity. When applied to cognition, the Modern Synthesis invites the decomposition of the mind into separately evolved cognitive traits, called mental modules, each selected to solve a particular evolutionary problem in the human ancestor's "environment of evolutionary adaptedness" (Cosmides and Tooby, 1997). The origin of these modules is explained with the appearance of certain genetic factors that code for them. Strictly speaking the modern synthesis can be understood as a theory of genes, which arguably is poorly equipped to provide a more fully-fledged explanation of the transformation of form, other than the occurrence of genetic mutations and recombinations, which somehow translate into phenotypic modifications.

There is, however, a growing consensus that we need explanatory resources that go beyond inner logical representations or the dynamics of neural networks on the on hand, and the received view of evolution on the other. Physical, social and cultural life transforms individual characteristics and abilities in daily interactions, during individual development and the evolution of the lineage. The view of organisms, especially humans as deeply integrated beings embedded in and transformed by their genetic, epigenetic, behavioral, ecological, socio-cultural and cognitive-symbolic *legacies* calls for an "extended evolutionary synthesis" (Pigliucci, 2007, 2009; Pigliucci and Müller, 2010) that goes beyond either a theory of genes juxtaposed against a theory of cultural evolution or more sophisticated theories of gene-culture coevolution and niche construction. Environments, particularly in the form of developmental environments, do not just *select for* variation, they also *create* new variation by influencing development through the reliable transmission of non-genetic but heritable information (Piaget, 1978; Gilbert and Epel, 2009; Stotz, 2010; Griffiths and Stotz, 2013). Organisms, and humans in particular, are actively engaged with and manipulate their physical and social environment and that of their descendants, which in turn not only participates in the production of selection pressures, but almost more importantly in the production of heritable phenotypic variation; therefore organisms actively contribute to their own evolution. There is a strong interconnection between be highly embodied, embedded and extended cognitive systems and the kind of developmental and evolutionary processes that bring them about (Sterelny, 2010; Stotz, 2010).

The next section will explore the alternative views of evolutionary theory that provide much richer explanatory resources for (evolutionary) psychology. It will probe which updates to the conceptual structure of evolutionary theory would be needed for its most fruitful application to problems in psychology. The next two sections will explore in more detail two issues that are of particular importance for psychology. Section Beyond Innate and Learned: the Concept of Experience criticizes the conceptual poverty created by the simplistic dichotomy between innate or genetically determined development and acquired learning. It introduces another concept, experience, as a step to bridge between and integrate development and learning. Section Extended Inheritance discusses in more detail the diverse mechanisms of non-genetic inheritance that comprise the central extension to the Modern Synthesis.

The alternative conceptions of mind and cognitions to the traditional cognitivist and computationist approach, namely 4E cognition, will stand at the center of Section Embodied, Embedded, Enacted and Extended Organisms, Extended Synthesis and Extended Evolutionary Psychology. In this final section I look in more detail at how this alternative view of the mind is related to the extended view of evolution that I have promoted here, particularly those parts of the new synthesis that I deem to have special explanatory potential for many areas of psychology. A radically different perspective to the view that sees a disembodied mind being passively molded by natural selection and genetic mutations is presented. It conceives living beings as non-linearly coupled organism-environment systems, that come with cellular, social, ecological and cultural legacies bequeathed to them from earlier generations, and who's actions substantially influence the evolutionary process.

#### **TOWARD AN EXTENDED EVOLUTIONARY SYNTHESIS KINDS OF EVOLUTIONARY PSYCHOLOGY**

This section doesn't attempt to review, discuss and criticize in detail the main kinds of evolutionary psychology. There is an extraordinary amount of literature out there doing just that. This presents just a minimalist overview, and as such necessarily presents a bit of a caricature, the three waves of attempts to integrate psychology with evolutionary theory in the last four decades. In the seventies Edward O. Wilson attempted a "New Synthesis" under the name of Sociobiology, which viewed social behavior as the product of evolution and therefore reasoned that it should be explained in terms of adaptive success. Its arguably quite radical gene centrism, promoted particularly through Richard Dawkins' notion of the selfish gene, became the subject of intense criticism. Not entirely without intellectual connections, the nineties saw the emergence of the Santa Barbara school of Evolutionary Psychology. It applies knowledge and principles from mainstream evolutionary theory to psychology and "good old-fashioned" Artificial Intelligence/cognitive science in order to understand the design of the human mind: "In this view, the mind is a set of information-processing machines that were designed by natural selection to solve adaptive problems faced by our hunter-gatherer ancestors" (Cosmides and Tooby, 1997). This highly successful new field attracted a large number of followers over the years, but at the same time has been subjected to very vocal criticisms. Against EP's dismissal of the critics as politically motivated anti-evolutionists, many critics were biologists, philosophers of biology and psychologists motivated by a different vision of a more scientifically rigorous and a more sophisticated evolutionary psychology (see for instance Barrett et al., 2014).

The beginning of the century saw the appearance of evolutionary developmental psychology, applying evolutionary thinking to human developmental psychology: "Evolutionary developmental psychology is the study of the genetic and ecological mechanisms that govern the development of social and cognitive competencies common to all human beings and the epigenetic (gene-environment interactions) processes that adapt these competencies to local conditions" (Geary and Bjorklund, 2000, p. 57). This new field takes its inspiration from evolutionary developmental biology and so-called epigenetic theories of evolution going back to Gilbert Gottlieb in accepting a role for development, particularly developmental plasticity, in evolution (Bjorklund, 2006).

Which kind of evolutionary theory you apply matters deeply to which kind of (evolutionary) psychology you get. Therefore what follows will be a very short analysis of which kind of amendments or extensions should be included to widen the scope of problems that can be successfully addressed by evolutionary theory. Again, I have to refer to the cited literature for a much more thorough and detailed criticism and further amendment than I could present here; the present paper focuses on those new developments that in my view are most relevant for an extended evolutionary psychology.

This section asks what are the implications of recent scientific developments for the mechanisms of evolution. These developments include discoveries in molecular genetics, notably "molecular epigenesist" or "distributed specificity" of gene products, new discoveries of exogenetic heredity, and the revival of notions of epigenesis and developmental plasticity and their implications for evolution. Together with many others I have argued that these developments necessitate an extension of the conventional, neo-Darwinian theory of evolution, the so-called "Modern Synthesis." Some may argue that the referral to the Modern Synthesis presents something like a straw man argument because many practitioners have, in the intervening decades, assimilated new conceptual and methodological developments into their thinking, often perhaps without being aware to what extent some of these violate the underlying assumptions on which the original synthesis was based. Several of these assumptions are now more than three quarters of a century old, and many of the relevant theories and concepts have undergone major revisions. So the point of the call for an "extended synthesis" may be as much to think through the implications of changes that have occurred or are occurring as to call for more change (Pigliucci, 2007, 2009; Craig, 2010; Pigliucci and Müller, 2010; Stotz, 2010; Gissis and Jablonka, 2011; Griffiths and Stotz, 2013).

#### **MOLECULAR EPIGENESIS**

As stated above, the Modern Synthesis was in its core a theory of genes, but the gene that figures in it was the classical gene of Gregor Mendel and Thomas Hunt Morgan, a theoretical entity of heritable factors that permitted practitioners the "genetic analysis" of observed inheritance patterns. The knowledge of how genes conferred specificity within an organism and hence had observable phenotypic effects wasn't yet a molecular reality. Historians of molecular biology credit Francis Crick with having supplemented the existing idea of *stereochemical specificity*, embodied in the three-dimensional structure of biomolecules and underlying the well-known lock-and-key model of interaction between biomolecules, with the idea of *informational specificity*, embodied in the linear structure of nucleic acids (such as genes and other genetic elements) that determine the linear structure of a gene product (Sarkar, 1996). This idea is present in Crick's statements of his Sequence Hypothesis and the Central Dogma:

Griffiths and Stotz (2013) have termed this encoding of specificity "Crick information." If a cause makes a specific difference to the order of elements in a biomolecule, it contains Crick information for that molecule. This definition embodies the essential idea of Crick's sequence hypothesis, without in principle limiting the location of biological information to nucleic acid sequences as Crick does. An important idea behind Crick information is that this causally grounded notion of biological information can be extended to apply to factors other than DNA, using research results from molecular biology. Crick's Sequence Hypothesis and Central Dogma were based on a very simple picture of how the specificity of bio-molecules is encoded in living cells. We now know that, at least in eukaryotes, coding regions are surrounded by a large number of non-coding sequences that regulate gene expression. The discrepancy between the number of coding sequences and the sometimes vastly higher number of gene products leads to the insight that the informational specificity in coding regions of DNA must be amplified by other bio-molecules in order to specify the whole range of products. Different mechanisms of gene regulation together co-specify the final product of the gene in question, first by *activating* the gene so it can get transcribed, second by *selecting* a chosen subset of the entire coding sequence (alternative splicing), and thirdly by *creating* new sequence information through the insertion, deletion or exchange of single nucleotide letters of the RNA message (RNA editing). Thus specificity, and hence Crick information, is distributed between a myriad of factors other than the original coding sequence: Non-coding DNA sequences with regulatory functions, diverse gene products such as transcription, splicing and editing factors (usually proteins), and non-coding RNAs (Stotz, 2006a,b). This leads to the second substantive use of information in contemporary molecular biology, namely in representations of genomic regulatory networks (GRNs) as implementing computations (Kauffman, 1969; Davidson and Levine, 2005).

Specificity turns out to be not inherent in any single biomolecule in these large networks but induced by regulated recruitment and combinatorial control (Ptashne and Gann, 2002). And it is here that we will find that the networks cannot be reduced to DNA sequences and gene products, because many of the latter need to be recruited, activated or transported to render them functional. These processes, the recruitment, activation, location or transportation of transcription, splicing and editing factors, allow the environment to have very *specific* effects on gene expression. I believe that this is a way to give a more precise meaning to the distinction between "instructive vs. permissive environmental causes" (Gilbert, 2003; Gilbert and Epel, 2009). Many regulatory gene products serve to relay environmental (Crick) information to the genome. While in embryology and morphogenesis it is often acknowledged that environmental signals play a role in the organization of global activities; they are rarely seen to carry information for the precise determination of the nucleic acid or amino acid chains in gene products. But this is precisely what occurs. Not just morphogenesis at higher levels of organization, but even the determination of the primary sequence of gene products is a creative process of "molecular epigenesist" that cannot be reduced to the information encoded in the genome alone (Stotz, 2006b; Griffiths and Stotz, 2013).

Section Beyond Innate and Learned: the Concept of Experience will argue that these developments warrant the introduction of another concept in psychology, namely "experience," beside the concepts of development and learning, to accommodate the many different avenues by which an organism reacts to and interacts with the environment.

#### **NON-GENETIC INHERITANCE**

Evolution is defined as changes in gene *frequencies*, because only the base sequence was deemed hereditary. The idea that developmental outcomes could be transmitted to the next generation was for almost a century discredited as raising the specter of Lamarckism. The molecular discoveries of epigenetic mechanisms, which produce effects on gene expression that were not just heritable from one cell to the other but in certain cases also from parent germline to offspring germline, however, have rendered ideas of non-genetic or exogenetic inheritance respectable. Parents beget their children not just gene *sequences* but also instructions over gene *expression* and other functional states. In addition, many aspects of the environment and individual experiences of a developing organism are there by evolutionary design: "genes *inherit* a rich and supportive environment, a fact few dispute but few discuss with any urgency" (West and King, 1987, p. 552, italics added). Evolution has designed not only a reactive genome, but also a "developmental niche" co-constructed by the parental and offspring generations to which the genome reacts to reconstruct life-cycles (see Section Developmental Niche Construction).

Since the development of molecular epigenetics has brought the existence of exogenetic inheritance to the attention of a much larger field, the idea is slowly gaining wider acceptance. The main points of debate today concern the scope and potential mechanisms of transgenerational transfer of non-genetic information, and its importance for evolutionary dynamics. Epigenetic inheritance proper, transmitted through the germline, and behaviorally transmitted transgenerational epigenetic effects (see Section Extended Inheritance) differ in several important ways from genetic inheritance: epigenetic variations may be less stable, because these variations are in principle reversible, and many organisms have developed safeguards against their transgenerational transmission. These features are not necessarily a disadvantage: in comparison to genetic inheritance, epigenetic mechanisms are more sensitive to the environment, which might make them more directed, more predictable, and also more flexible. These are all features which potentially render them more adaptive in the short term than blind genetic variation, particularly in variable environmental conditions (Jablonka and Lamb, 1995; Holliday, 2006). Exogenetic inheritance systems often transfer information involved in 'adaptive transgenerational plasticity' (see Section Transgenerational Developmental Plasticity: Parental Effects):

*...* because the parental phenotype responds to some aspect of its environment that correlates with a feature that is of adaptive relevance to the offspring. This correlational information can be exploited by developmental processes because of the continuity between parental and offspring phenotypes (*...*). In genetic inheritance systems, on the other hand, correlational information requires a process of selection that builds up gene frequency differences between environments. (Uller, 2012).

#### **DEVELOPMENTAL PLASTICITY AND EVOLUTION**

There are now a variety of scientific fields interested in the extent to which development influences evolution, and the ideas about which mechanisms are evolutionarily relevant differ greatly: The most radical position asserts that environmentally induced and developmentally regulated variation in exogenetic, developmental resources may be transmitted directly to the next generation either from germ or soma cell to germ cell, or from soma to soma, in order to create heritable variation in the phenotype (Griffiths and Gray, 1994; Jablonka and Lamb, 1995, 2005; Stotz, 2008, 2010; Stotz and Allen, 2008; Badyaev and Uller, 2009; Gilbert and Epel, 2009; Danchin et al., 2011; Bonduriansky, 2012; Uller, 2012).

Some biologists insist that only epigenetic inheritance transmitted through the gametes should be called a proper inheritance system, while the transmission from soma to germline or soma to soma is described as "transgenerational epigenetic effects" (Youngson and Whitelaw, 2008). Bonduriansky (2012) has argued that this resistance stems from the forceful association between genes and biological inheritance created by transmission genetics. For others less impressed by those historical developments transgenerational epigenetic effects are parental effects mediated via epigenetic mechanisms, which fall under the behavioral inheritance system (e.g., Meaney, 2001; Danchin et al., 2011; Griffiths and Stotz, 2013). Some evolutionary developmental biologists, traditionally reluctant to accept the existence of nongenetic inheritance, now embrace the importance of epigenetics for evolution, but see it as an extension of the genetic inheritance system since it works via the modification of the chromatin system, which forms part of the chromosome (Hallgrimsson and Hall, 2011).

According to others, phenotypically plastic responses during the lifetime (phenotypic accommodation) may uncover the existence, or facilitate the production, of suitable genetic change. Such genetic variation may lead via natural selection to either genetic assimilation (also known as the Baldwin effect), or genetic accommodation, in other words the genetic inheritance of either decreased or increased responsiveness to environmental conditions (Waddington, 1953a,b; West-Eberhard, 2003). Others argue that a group of conserved core processes of organisms facilitate the generation of phenotypic variation out of underlying genetic variation, called "facilitated variation" (Kirschner and Gerhart, 2010). Approaches closely related to the idea of facilitated variation maintain that evolution should be understood as a succession of developmental life cycles rather than change in gene frequencies, and it is therefore developmental mechanisms that provide the necessary causal explanations for how genetic change translates into phenotypic modifications (Hall, 1999).

Lastly, there are those within the niche construction (Odling-Smee et al., 2003) and the gene-culture coevolution approaches (Boyd and Richerson, 1985) who maintain that individual behavior and hence development influences evolution mainly by affecting the future selection pressure of the population through ecological and cultural niche construction activities. These modified selection pressures then feed back to evolutionary processes.

#### **SUMMARY**