Chapter 7 Neuroarchaeology

Dietrich Stout and Erin Hecht

Abstract ‘‘Neuroarchaeology’’ in the broad sense refers to any application of theory and methods to archaeological questions. This includes the interpretation of archaeological materials in terms of the cognitive operations and neural substrates they are thought to imply as well as the experimental study of archaeologically-visible behaviors using neuroscience methods. The particular strengths and interests of have led neuroarchaeologists to focus on three broad themes in neuroscience theory: grounded , executive func- tion, and social cognition. Much of the published work in neuroarchaeology has consisted of attempts to apply neuroscience perspectives on these topics to interpretations of the archaeological record. Experimental neuroarchaeology, a straightforward methodological extension of conventional experimental archae- ology, has been less common. This may change with the increasing availability of neuroscience methods for investigating complex, real-world behaviors. The use of methods to study experimental stone tool-making provides one example. Archaeology and neuroscience are united in the quest to understand human nature but remain deeply divided by disciplinary , , methods, career paths, and institutional support. Whereas the utility of neuroscience meth- ods to archaeology is clear, there has been less interest among in the potential contributions of archaeological strengths in the study of and material culture. The future of ‘‘neuroarchaeology’’ as just another niche focus within archaeology or as something more will ultimately depend on its relevance to the questions and research agendas of neuroscientists.

Keywords Archaeology Á Cognition Á Neuroscience Á Stone tools Á Brain imaging

D. Stout (&) Á E. Hecht Department of , Emory University, 1557 Dickey Drive, Atlanta, GA 30322, USA e-mail: [email protected] E. Hecht e-mail: [email protected]

Ó Springer International Publishing Switzerland 2015 145 E. Bruner (ed.), Human Paleoneurology, Springer Series in Bio-/ 3, DOI 10.1007/978-3-319-08500-5_7 146 D. Stout and E. Hecht

Introduction

The past 20 years have witnessed an explosive growth in the scale, diversity and public profile of neuroscience research, fueled in part by the development of methods like functional imaging and molecular genetics (Jones and Mendell 1999). Neuroscientists have pushed the boundaries of their field in exciting new directions and researchers in other disciplines have sought to tap into the novel insights and opportunities of this booming enterprise. This has yielded a host of hopeful interdisciplinary hybrids including (Camerer et al. 2005), (Churchland 1989), (Parasuraman and Rizzo 2006), neuroeducation (Battro et al. 2008), (Domínguez Duque et al. 2010), neuroachaeology (Malafouris 2009), and even neuroarthistory (Onians 2007), to name just a few. As might be expected, the aims and accomplishments of such attempts vary widely. Generally speaking, attempted synthesis may be lim- ited to theory or extend to include methods, and may comprise unilateral bor- rowing or bilateral collaboration. Arguably, the most productive efforts have sought to integrate theory and methods in a bilateral synergy. This has been more difficult in some cases than others. , with its natural sci- ence framework, has been particularly amenable to integration with neuroscience (Rilling 2008) but it remains a much greater challenge to integrate neuroscience with the social sciences (Dias 2010; Roepstorff and Frith 2012) including and (some forms of) archaeology. ‘‘Neuroarchaeology’’ is a term advanced by Malafouris and Renfrew (e.g. 2008) and it has specific theoretical implications that extend beyond the general sense of the neologism. It is thus useful to distinguish between Neuroarchaeology (narrow sense) and neuroarchaeology (general sense). As outlined by Malafouris (2009), Neuroarchaeology is an outgrowth of the cognitive-processual archaeology of Renfrew (1994) and is explicitly grounded in Material Engagement Theory (Malafouris 2004; Renfrew 2004). Material Engagement Theory focuses on the role of objects in mediating human behavior, cognition, and sociality and is closely aligned with approaches to cognition as extended (Clark and Chalmers 1998), grounded (Barsalou 2008), situated (Lave and Wenger 1991) and distributed (Hutchins 1995) developed in , philosophy, anthropology, and elsewhere. Neuroarchaeology explicitly (Malafouris 2009, p. 254) aims to: (1) incorporate neuroscience findings into cognitive archaeology, (2) promote ‘‘critical reflection on neuroscience’s claims on the basis of our current archaeo- logical knowledge’’, and (3) facilitate cross-disciplinary dialog. General neuroarchaeology, on the other hand, might refer to any application of neuroscience theory and methods to archaeological questions. Examples include the interpretation of archaeological materials in terms of the cognitive operations and neural substrates they are thought to imply (Henshilwood and Dubreuil 2011; Wynn et al. 2009) and the experimental study of archaeologically-visible behav- iors using neuroscience methods (Stout et al. 2011). Work in neuroarchaeology has most commonly addressed the biocultural evolution of human cognitive capacities 7 Neuroarchaeology 147 during the Paleolithic, in contrast to Neuroarchaeology which has often been more interested in the ‘‘post-evolutionary’’ effects of culture change on human cognition in more recent (Holocene) contexts. Although both Neuroarchaeologists and neuroarchaeologists have published in neuroscience journals and collaborated with neuroscientists, reciprocal interest from ‘‘mainstream’’ neuroscience has remained somewhat limited. For example Ramachandran (2000) suggested that mirror neurons might explain the Upper Paleolithic ‘‘big bang’’ of human material cultural elaboration, and Frey (2007) references the great antiquity of stone tools to illustrate the fundamental impor- tance of neuroscience research on complex tool use. Somewhat greater use of archaeological evidence is made by Peeters et al. (2009), who refer to Oldowan and Acheulean tool industries in order to speculate about the timing of the emergence of a putative human cortical specialization for tool use. Perhaps the most systematic use of archaeological evidence has been in the development of Michael Arbib’s (2011) Mirror System Hypothesis of language evolution. The relatively limited interest in archaeology among neuroscientists is unsurprising and unlikely to change so long as the neuroarchaeology research agenda is set solely by archaeologists in order to address archaeological questions. In a recent critique, Roepstorff and Frith (2012) similarly suggested that ‘‘neuroanthropology’’ is not actually a hybrid discipline but simply a new research focus within anthropology. The future of neuroarchaeology as just another niche focus within archaeology or as something more will ultimately depend on its relevance to the questions and research agendas of neuroscientists.

Neuroarchaeology Theory

Archaeologists work with material remains in order to infer past human behavior. Cognitive archaeologists take this a step further in an attempt to infer mental capacities and patterns of thought from these reconstructed behaviors. Neurosci- entists work with extant organisms in order to study the genetics, structure, and function of nervous systems. Cognitive neuroscientists in particular study the neurobiological substrates of observable behaviors and the (inferred) psycholog- ical processes that support them. There is much potential overlap between cog- nitive neuroscience and cognitive archaeology, but a substantial gulf does exist between the in vivo, organism-focused, experimental methods of the former and the object-focused, reconstructive, historical methods of the latter. It is the hope of neuroarchaeology that these differences are complementary and synergistic rather than disjunctive and insurmountable. Though never without controversy, archaeology does have well developed theory and methods for inferring behavior from material remains. A review of such ‘‘Middle Range Theory’’ is well beyond the scope of this chapter, but key methods include experimental replication (Coles 1979; Saraydar 2008) and ethnographic analogy (David and Kramer 2001). Theory and methods for moving from inferred 148 D. Stout and E. Hecht behaviors to ancient cognition are much less developed, and cognitive archaeol- ogists have a long history of borrowing from psychology and in an attempt to fill this gap (e.g. Wynn 1979). In many ways, neuroarchaeology is simply the latest incarnation of this tradition. Its particular appeal is the possibility of linking ancient cognition to evolving neurobiological substrates. It is thus fairly clear what neuroscience has to offer archaeology, but what does archaeology have to offer neuroscience? The key strengths of archaeology are its evolutionary time depth and its focus on material culture. Evolutionary theory is fundamental to all biological sciences, and the value of an evolutionary perspective has already motivated productive integration between biological anthropology and neuroscience. Comparative functional and anatomical studies (in which living species are compared in order to infer ancestral conditions and identify neurocognitive specializations) are conducted by researchers with cross-cutting neuroscience and anthropology training and affiliations and are published and cited across core neuroscience and anthropology journals. Archaeology offers another source of evolutionary data that has yet to be exploited in this interdisciplinary fashion. Although the comparative method is extremely useful, it does have a weakness in its inability to resolve the sequence, context, and timing of evolutionary events since the last common ancestor of the species being compared. Comparative studies can thus identify human neural specializations for language, tool use and social cognition that are absent in chimpanzees (Rilling and Stout In press) but not when or under what conditions during the past 7–10 million years of hominin evolution these specializations emerged. As Wynn (2002) has pointed out, archaeology can help fill these gaps by documenting the chronology, , and context for the emergence of new behaviors in the 2.5 million years since the first appearance of a human material culture record (Semaw 2000). The other major strength of archaeology is precisely its focus on this material record. Archaeologists obviously have little choice but to focus on artifacts, but they have made a virtue of this necessity by thinking deeply on the role of materiality in human culture and cognition. Like the air we breathe, human material culture is so pervasive and integral to life that it is easily overlooked. According to Schiffer (1999, p. 2), one result is that ‘‘investigators have ignored what might be most distinctive and significant about our species …what makes humans unique is that we take part in diverse interactions with innumerable kinds of artifacts in the course of daily activities’’. Particularly relevant to neuroscience are the ways in which interactions with artifacts extend [or even constitute (Malafouris 2004)] human cognition and sociality. Material culture is a durable medium of action and interaction with its own intrinsic properties and dynamics (Hodder 2012) that are often neglected in the organism-focused world of neuro- science. For example, social neuroscientists have devoted considerable effort to studying social signaling via facial expressions and eye gaze but have completely ignored clothing and personal adornment. Even neuroscientists explicitly inter- ested in tool-use have often considered it sufficient to study pantomimed gestures without any actual object and have devoted almost no to the purposeful modification of artifacts that is the practical goal of most human tool use. 7 Neuroarchaeology 149

Archaeology has developed theory and methods for dealing with the central role of objects in human life that may be useful to neuroscientists, particularly as they continue to push the boundaries of their field to address more and more complex domains of naturalistic human behavior such as communication, social learning, and tool-use. The particular strengths and interests of archaeology have led neuroarchaeol- ogists to focus on overlap with three broad themes in neuroscience theory: grounded cognition, executive function, and social cognition. Much of the pub- lished work in neuroarchaeology has consisted of attempts to apply neuroscience perspectives on these topics to interpretations of the archaeological record. Figure 7.1a illustrates key brain regions discussed below.

Grounded Cognition

During the 1950s the dominant paradigm of Behaviorism, which sought to understand human psychology purely in terms of observable behaviors, was supplanted by Cognitivism, which reasserted the reality and importance of internal mental states and processes in explaining overt behavior. This was the ‘‘Cognitive Revolution’’ that led to the establishment of the cognitive sciences, including (Miller 2003). Perhaps reflecting these reactionary origins, the orthodox view in the cognitive sciences has been that cognition consists of the manipulation of abstract, ‘‘amodal’’, symbols that are distinct from the ‘‘modal’’ systems of (e.g. vision, hearing), action (e.g. motor control) and interoception (e.g. body states, emotions) more directly associated with producing behavior (Barsalou 2008). By the 1990s, a further counter-reaction to this Cogn- itivist orthodoxy had emerged. Although most commonly referred to as ‘‘Embodied Cognition’’ (Wilson 2002), Lawrence Barsalou has suggested the more inclusive term ‘‘Grounded Cognition’’ to describe this emerging paradigm, which includes grounding in perceptual imagery (Barsalou 1999), motor simula- tion (Decety and Grèzes 2006), and environmental situations (Thelen and Smith 1994) as well as bodily states (Lakoff and Johnson 1980). Grounded Cognition questions the central importance of abstract symbol manipulation in human cog- nition and replaces it with an emphasis on ‘‘grounded’’ simulation in the brain’s modal systems of perception, action and interoception. For example, semantic knowledge of word meaning appears to be based at least partially on simulation, with color words activating parts of the brain involved in visual color processing, and action words activating motor cortex associated with the relevant body part (e.g. face, arm, leg) (Pulvermüller and Fadiga 2010). There is now substantial evidence that the actions of others (including speech) are understood through internal simulation using one’s own motor system, and that abstract conceptuali- zation and reasoning are supported by the concrete simulation of objects, situa- tions, and actions (review in Barsalou 2008). This move away from the classical Cognitivist view of mental processes as abstract symbol manipulation has 150 D. Stout and E. Hecht encouraged neuroarchaeologists and others to seriously consider: (1) extending the concept of ‘‘mind’’ beyond the conventional boundaries of skin and skull and (2) re-conceptualizing the relationship between perception, action, and cognition.

Extended Mind

The central roles posited for simulation and context in Grounded Cognition are consonant with archaeological insights into the importance of artifacts in shaping human experience. Artifacts are not just something people think about, they are something people think with. Malafouris (2004, 2008) in particular has drawn on Andy Clark’s (e.g. Clark 2008; Clark and Chalmers 1998) concept of an Extended Mind to argue that artifacts help to actively constitute cognitive systems, rather than simply influencing internal cognition. For example, a Mycenaean Linear B tablet may be thought of as enabling a redistribution of memory functions outside the brain and indeed as partially instantiating a new ‘‘extended’’ cognitive system that includes reading as one of its behaviors. The incorporation of bodily orna- ments, from Paleolithic shell beads to Mycenaean gold rings, into the body image might similarly be seen as extending and transforming the human sense of self. Central to this approach is a questioning of traditional boundaries between mind, body, and environment in the analysis of cognitive systems. Though largely inspired by work in (e.g. Gell 1998; Hutchins 1995) and philosophy (e.g. Merleau-Ponty 1962) this theory of human ‘‘Material Engagement’’ also draws support from neuroscientific evidence that external objects can indeed come to be represented in the brain as literal extensions of the body. Head and Holmes (1911) are commonly credited with originating the con- cept of a ‘‘body schema’’ localized in the parietal lobe, including the speculation that this internal body representation might be plastic enough to incorporate hand- held objects. This conjecture has now been amply supported by empirical findings. Working with macaque monkeys, Atsushi Iriki (Iriki et al. 1996; Maravita and Iriki 2004) used single neuron recording to show that bimodal (visual/somatosensory) neurons in the parietal cortex actually changed their response patterns when macaques learn to use a rake. For example, ‘‘distal type’’ neurons with somato- sensory and visual receptive fields centered on the hand extended their receptive field to encompass the entire length of the tool. Maravita and Iriki (2004, p. 80) suggest that this plasticity may ‘‘constitute the neural substrate of use-dependent assimilation of the tool into the body schema’’. Although single neuron recording is an invasive procedure that cannot ethically be applied to human subjects, behavioral and neuropsychological evidence strongly supports the existence of similar neural mechanisms in humans. For example, brain-damaged patients suf- fering from selective spatial awareness difficulties in near (personal) space make errors on a line bisection task when using a stick to point (i.e. an extension of the body) but perform normally using a laser pointer (Berti and Frassinetti 2000). 7 Neuroarchaeology 151

Iriki’s group has also used tracer techniques to examine anatomical changes in connectivity associated with tool training in macaques (Hihara et al. 2006). They reported the development of new projections from high order visual areas near the temporo-parietal junction to the intraparietal sulcus (see Fig. 7.1), where bimodal neurons are found, and speculate that this physical change in connectivity enables the body schema flexibility of tool-trained macaques. Tracer techniques require killing the subject, and so cannot be applied in humans, however the non-invasive technique of Diffusion Tensor Imaging (DTI, see Sect. Neuroarchaeology Meth- ods) has now provided extensive evidence of experience-dependent changes in human white matter. Examples range from learning to juggle (Scholz et al. 2009) to learning a second language (Schlegel and Rudelson 2012). Voxel Based Mor- phometry (VBM, Sect. Neuroarchaeology Methods) has similarly documented experience-dependant changes in grey matter density, and there is now widespread acceptance that even adult brains are highly plastic in response to environment and experience. For Malafouris (2010) this plasticity is yet another reason to consider the brain itself as a cultural artifact, and to focus on the broader organism-environment system as the proper unit of analysis. Archaeology has much to offer neuroscience in this regard, both in taking material culture seriously and in appreciating the full scope of human cultural and technological variation through time and space. Renfrew (2008) has argued that even in the absence of significant biological evolution, the past 60,000 years have witnessed a fundamental, culturally-driven reorganization of the and cognition. Within neuroscience (though perhaps not in the mainstream), Iriki (Iriki and Sakura 2008) has made a somewhat similar proposal that the origins of human tool use, with its intimate relation to body schema representation and sense of self, set up a unique feedback interaction between organism and environment leading to the emergence of consciousness, Theory of Mind, and eventually ‘‘scientific and technical civilization’’. These ideas about the evolution of organism-environment systems may be further related to the concept of Niche Construction in evolutionary biology (Odling-Smee et al. 2003), which recognizes that organisms alter environments in a multitude of ways that influence the selective pressures acting on their own offspring. For example, ter- mites not only build mounds but are exquisitely adapted to live in them. Over evolutionary and historical time, humans have constructed a complex diversity of cognitive, cultural and technological niches. Neuroarchaeologists would argue that it is no more possible to understand human cognition without reference to this fact than it is to explain the adaptations of beavers without reference to dams.

Perception and Action

In line with the name we have chosen for our species, Homo sapiens, accounts of human uniqueness and cognitive evolution often focus on ‘‘higher order’’ capac- ities for abstract thought, problem solving and symbol use. Grounded Cognition 152 D. Stout and E. Hecht

Fig. 7.1 Functional . a Cortical regions discussed in the text. Prefrontal regions adapted from Badre and d’Esposito 2009. b Regions specifically implicated in stone tool-making. Adapted from Stout and Chaminade (2012). Blue circles indicate regions activated by both Oldowan and Acheulean toolmaking; red circles indicate regions activated by Acheulean toolmaking only. Both technologies activate bilateral inferior and superior parietal cortex and intraparietal sulcus, as well as left ventral premotor cortex. Acheulean tool-making specifically activates the right hemisphere homologue of Broca’s area in the inferior frontal gyrus, right ventral premotor cortex and dorsal premotor cortex bilaterally. Abbreviations: FPC frontopolar cortex; mPFC medial prefrontal cortex; mid-DLPFC mid-dorsolateral prefrontal cortex; PMd dorsal premotor cortex; pre-PMd/caudal PFC pre-dorsal premotor/caudal prefrontal cortex; dIPS/SPL dorsal intraparietal sulcus/superior parietal lobule; aIPS anterior intraparietal sulcus; IPL inferior parietal lobule; TPJ temporo-parietal junction; PMv ventral premotor cortex; IFG inferior frontal gyrus 7 Neuroarchaeology 153 suggests that such higher order capacities are firmly based in the brain’s modal systems for perception and action. This in turn suggests that much of the story of human cognitive evolution may actually concern changing capacities for concrete sensation and action in the world, as opposed to abstract internal representation. This perspective has been most fully developed in the work of Blandine Bril and colleagues on the kinematic organization of stone knapping behaviors. Bril’s work on stone knapping is empirical and experimental (see below), but in this section we will focus on the broader theoretical framework (e.g. Bril and Roux 2005a), which has its foundations in Ecological Psychology (Gibson 1986; Reed 1996) and the Dynamical Systems approach to cognition and action (Bernstein 1996; Thelen and Smith 1994). Broadly speaking, Ecological Psychology contends that behavior and cognition can only be properly understood as properties of integrated organism-environment systems. For Gibson (1986) this includes the concept of ‘‘direct perception’’, which rejects the conventional view that percep- tion occurs through the production of internal representations based on limited sensory input (e.g. patterns of light falling on the retina). Gibson instead charac- terizes perception as an active process of engagement with the environment, so that perceptual information and indeed the very act of perception are not located ‘‘in the head’’ but rather are constituted by the dynamics of the organism-envi- ronment system. Gibson’s ‘‘anti-representational’’ stance has remained contro- versial, but elements of his work have been widely adopted. This includes especially his concept of ‘‘affordance’’. An affordance is a possibility for action that exists in the relationship between an organism and some aspect of its envi- ronment. It is critical to emphasize that an affordance is a relational property—the same vertical wall may afford walking for a spider but not a human. In neuro- science, the concept has been used to understand evidence of motor involvement in object perception by recognizing that perception occurs for action (Fagg and Arbib 1998; Grèzes and Decety 2002) and cannot be easily separated from it. Even the perception of space can be altered by motor planning and activity—for example distances appear greater if there is more resistance to movement (Kirsch et al. 2012). Such findings have led to a questioning of conventional distinctions between sensory and motor systems in the brain, and to the concept of ‘‘active perception’’ (Pulvermüller and Fadiga 2010). As Gibson (1986, p. 223) put it: ‘‘We must perceive in order to move, but we must move in order to perceive’’. Bruner (2010) considered the relevance of such sensorimotor integration, and particularly visuospatial integration in frontoparietal neural networks, to classi- cally ‘‘cognitive’’ functions such as and general intelligence. He argues that multisensory integration in upper parietal areas supports the formation of goal-oriented spatial frames for action guiding the allocation of attention and generation of intentions. This interpretation is particularly interesting in light of paleoneurological evidence presented by Bruner that modern human brains are distinguished from other hominin taxa by a differential enlargement of the upper parietal region. The Dynamical Systems approach is closely related to Ecological Psychology and similarly opposed to mainstream, representational accounts of cognition. 154 D. Stout and E. Hecht

Rather than modeling cognition as the manipulation of discrete, amodal symbols, mental processes are seen as arising from continuous variation in coupled per- ceptual, motor, cognitive and environmental systems that converge on dynamically stable states (attractors) corresponding to adaptive behavior (Barsalou 2008; Thelen and Smith 1994; van Gelder 1998). Like connectionism, this is an ‘‘emergentist’’ perspective which understands cognition as arising from the com- plex interaction of a large number of simple noncognitive processes (McClelland et al. 2010). As the name implies, the Dynamical Systems approach focuses on patterns of change through time, rather than static cognitive states or ‘‘architec- tures’’, and especially on the parameters constraining these patterns. Such influ- ences are often conceptualized geometrically in terms of a ‘‘dynamical landscape’’ with features such as gradients or basins of attraction (van Gelder 1998). It is recognized that human behavior displays a vast number of degrees of freedom (independent dimensions of variation): the joints of the human body, for example, encompass approximately 100 degrees of freedom for movement whereas at the level of individual muscles this number is closer to 1,000 (Bril and Roux 2005a). A central question for the Dynamic Systems approach is thus how this vast com- plexity is controlled and coordinated. A classic example is provided by Bernstein (1996), who described the arm motions of blacksmiths striking a chisel with a hammer. Surprisingly, Bernstein found that the movement trajectories of indi- vidual joints in the arms of these expert craftsmen were highly variable but nev- ertheless produced a highly consistent trajectory of the hammer head. From this perspective, control emerges from the discovery of effective movement synergies that coordinate action with respect to a goal (or ‘‘attractor’’) without limiting the degrees of freedom that allow for adaptive flexibility and dynamic stability. Insofar as the discovery of effective synergies changes an organism’s possibilities for action in its environment, it may be considered as a form of experience-dependent affordance perception. These theoretical considerations, informed by experimental kinematic results, have led Bril and colleagues to suggest that early (i.e. Oldowan) stages of hominin technological evolution were enabled by changing perceptual-motor, rather than cognitive, capacities (Bril and Roux 2005b) and furthermore that the difficulty of discovering the appropriate movement synergies (i.e. the cryptic nature of task affordances) implies that ‘‘the recurrence of a learning situation which allows the transmission of the skill, possibly by providing the opportunities for first-hand experience, is likely to have been a prerequisite to the emergence of controlled flaking found in some Early Stone Age sites’’. (Nonaka et al. 2010, p. 165). Influenced in part by the work of Bril (e.g. Roux et al. 1995), Stout reached similar conclusions on the basis of functional brain imaging (Stout and Chaminade 2007) and ethnographic (Stout 2002, 2005) evidence. Supporting neuroscientific evi- dence of human perceptual-motor specializations relevant to tool-making comes from histological studies of occipital visual cortex in humans versus other primates (Preuss et al. 1999) and fMRI experiments showing human parietal cortex responses to 3D form (Vanduffel et al. 2002) and hand-held tools (Peeters et al. 2009, 2013) that are absent in macaques. Similarly, the emphasis placed by Bril 7 Neuroarchaeology 155 and others on the social and environmental facilitation or ‘‘scaffolding’’ of affor- dance perception/skill acquisition is supported a wide array of research on apprenticeship learning and related topics across disciplines ranging from devel- opmental and comparative psychology to anthropology and (Fragaszy 2011; Ingold 2001; Lave and Wenger 1991; Rogoff 1990; Tomasello 1999; Vygotsky 1978; Zukow-Goldring and Arbib 2007). The key to understanding the perception-action perspective and its application in neuroarchaeology is to rec- ognize that it does not deny the relevance of ‘‘mental’’, ‘‘cognitive’’, or even ‘‘representational’’ levels of analysis (cf. Bril and Roux 2005a) but rather rejects the conventional mind-body dualism which would see cognitive ‘‘competence’’ as separable from motor ‘‘performance’’ (Thelen and Smith 1994). As Nonaka et al. (2010, p. 166) conclude, increasing control in early stone tool-making ‘‘is indic- ative of the emergence of a system, of which learning situation, behavior of an organism, and other biological processes (e.g., genetic activity, neural activity) are components, that stabilizes the transmission of the detection of the constraints and opportunities for action in the environment across generations’’.

Executive Function

Interest in the Grounded Cognition perspectives discussed above should not be seen as precluding research focused more directly on the ‘‘higher order’’ capacities for planning, problem solving, and conceptualization that have traditionally been seen as defining uniquely human cognition. The goal of emergentist perspectives is not impose a purely ‘‘bottom-up’’ approach but rather to seek accounts than span levels (McClelland et al. 2010). Functions such as planning that may provide ‘‘top-down’’ control of cognitive processes are generally considered under the headings of ‘‘cognitive control’’ (e.g. Stout 2010) or ‘‘executive function’’ (e.g. Coolidge and Wynn 2001) and are classically associated with prefrontal cortex. Such functions have been of great interest to researchers across (the study of mental processes, especially using psychometric experiments and formal model- ing), cognitive (the study of brain function, especially through work with brain-damaged patients), and cognitive neuroscience (discussed above). This diverse history is reflected in an equally diverse range of partially overlapping terminology and theoretical frameworks that can be quite confusing. In cognitive archaeology, Frederick Coolidge and Thomas Wynn (e.g. Coolidge and Wynn 2005, 2009; Wynn and Coolidge 2004) have applied the multi-com- ponent Working Memory model of Baddeley (e.g. 2003) which derives from cognitive psychology. As discussed by Coolidge et al. (this volume) this model includes a ‘‘central executive’’ responsible for ‘‘attention, active inhibition, deci- sion making, planning, sequencing, temporal tagging, and the manipulation, updating, maintenance, and integration of multimodal information’’. Working memory capacity, including especially amodal attention regulation, has been linked to ‘‘fluid intelligence’’ (i.e. novel problem solving ability) (e.g. Engle et al. 1999). 156 D. Stout and E. Hecht

Coolidge and Wynn (2005) hypothesized that a recent (60,000–130,000 years ago) genetic mutation affecting the central executive of working memory might be responsible for the emergence of fully modern behavior and cognition in the archaeological record (but see Powell et al. (2009) and d’Errico and Stringer (2011) for an alternative account of the emergence of modern behavior). Mithen (1996) made a somewhat similar proposal based on concepts of functional modularity versus ‘‘cognitive fluidity’’ derived from (e.g. Karmil- off-Smith 1992). Mithen proposed that evolution of a novel capacity for fluid integration across multiple ‘‘specialized intelligences’’ explained the emergence of modern behavior. Stout (2010, 2011); Stout et al. (2008) focused on earlier (Lower Paleolithic) time periods using cognitive neuroscience models of hierarchical information processing in prefrontal cortex (e.g. Badre and D’Esposito 2009; Koechlin and Jubault 2006) to suggest a gradual evolution of executive function as well as possible links with the emergence of language (Stout and Chaminade 2012). Insofar as there is a core concept running across these various theories and applications, it is that executive functions have to do with the selection and organization of adaptive behavior. This is thought to require a variety of con- stituent capacities loosely falling into categories such as the integration of infor- mation across time and input modes or domains, the allocation of attention, and the parsing/production of hierarchical structure (e.g. nesting of behavioral sub-goals). The frontal lobes appear critical to these capacities, although it is increasingly recognized that control processes are distributed across functional circuits inte- grating frontal and parietal brain regions (Dosenbach et al. 2008). Questions about how to sub-divide or ‘‘fractionate’’ executive function into psychologically real components, and whether these components are functionally localized to different portions of frontal cortex remain controversial and at the forefront of research. A prevailing view in cognitive neuroscience is that frontal cortex function is organized along a posterior to anterior gradient of increasing abstraction (see Fig. 7.1). As reviewed by Badre and D’Esposito (2009), cognitive ‘‘abstraction’’ has been defined in various ways, including: 1. Domain generality: integrating information across input domains (e.g. spatial and object domains) 2. Relational integration: proceeds from 1st order relations (properties such as color), to 2nd order relations (relations between properties, e.g. judge same vs. different), 3rd order relations (relations among relations, e.g. verify X is to Y as A is to B), and so on. 3. Temporal abstraction: maintenance of general action goals (e.g. make a sandwich) over extended periods of time in contrast to concrete goals (e.g. slice bread) that are more frequently updated. 4. Policy abstraction: the degree to which goals are generalized across sub-goals. For example, ‘‘grasp knife’’ is a relatively concrete action that might be sub- ordinated to the increasingly abstract goals of ‘‘cut bread’’, ‘‘make sandwich’’, and ‘‘prepare lunch’’ or incorporated into an entirely different activity such as 7 Neuroarchaeology 157

‘‘open package’’. Conversely, the abstract goal ‘‘prepare lunch’’ on a particular day might not involve any knives or sandwiches at all. Brain imaging experiments designed using these various definitions have consistently documented increasingly anterior frontal involvement as abstraction increases, suggesting that this is indeed a fundamental organizing principle of frontal cortex. However defined, capacities for abstract cognition supported by anterior frontal cortex are clearly important for the planning and execution of complex adaptive behavior, which is commonly impaired in patients with frontal damage (Stuss and Alexander 2007). Research in comparative neuroanatomy has identified evolutionary changes in the organization and interconnectivity of human anterior frontal cortex that may support uniquely human capacities for abstract cognitive control (Teffer and Semendeferi 2012; Reyes and Sherwood, this volume). The inferior frontal gyrus (IFG) in particular has been linked with human capacities for language, tool use, and social learning, making it of special interest to neuroarchaeologists. IFG includes Broca’s area and has long been associated with speech production and syntactic processing (Broca 2006 [1861]; Hagoort 2005). More recently, IFG has been shown to participate in a range of non- linguistic behaviors from object manipulation to sequence prediction, visual search, arithmetic and music (Fadiga et al. 2009; Fink et al. 2006; Schubotz and von Cramon 2003). It has been proposed that this superficial behavioral diversity stems from an underlying computational role of IFG in the processing of hierar- chically structured information (i.e. policy abstraction) (Koechlin and Jubault 2006), leading to speculation that this function may have evolved first in the context of manual praxis before being co-opted to support other behaviors such as language (Pulvermüller and Fadiga 2010). Neuroarchaeological studies of stone tool-making (see below) have reported IFG activation consistent with this idea.

Social Cognition

Michael Tomasello (Tennie et al. 2009; Tomasello 1999; Tomasello et al. 2005)is a leading advocate of the influential hypothesis that human cognitive and behav- ioral uniqueness is largely the product of cumulative cultural evolution rather than (neuro)biological evolution. On this view, an underlying change in human social cognition enabled the high-fidelity cultural learning which subsequently did ‘‘the actual work in creating many, if not all, of the most distinctive and important cognitive products and processes of the species Homo sapiens’’. (Tomasello 1999, p. 11). Importantly, this cultural mechanism of cognitive change implies a potentially faster (‘‘historical’’) rate of change compared to biological evolution. It is thus appealing to conjecture that a single change in social cognition might explain the apparent increase in rates of cultural change that some archaeologists see as marking the initial emergence of ‘‘modern human behavior’’ in the African 158 D. Stout and E. Hecht

Middle Stone Age. As mentioned in the introduction, for example, V.S. Rama- chandran has suggested that developments in the mirror neuron system of action understanding may have enabled enhanced imitation learning leading to a cultural ‘‘big bang’’ in human evolution. So-called ‘‘mirror neurons’’ were first described in the in the inferior frontal and parietal cortex of macaque monkeys (Rizzolatti and Craighero 2004). These are neurons that respond both to observed actions and the self-performance of a similar action. Neurons with similar properties are thought to exist in humans (Kilner et al. 2009) and to provide a mechanism of action understanding through internal simulation or ‘‘motor resonance’’. It has further been proposed that this basic mechanism of action understanding is the foundation for more sophisticated forms of social cognition, including the understanding of intentions (Wolpert, et al. 2003) and Theory of Mind (Gallese et al. 2009). The location of mirror neurons in human Broca’s area and its macaque homolog has also suggested potential links to language evolution (Rizzolatti and Arbib 1998). Michael Arbib’s Mirror System Hypothesis proposes that a primitive anthropoid action understanding system underwent successive evolutionary modifications to support imitation, pantomime, manual ‘‘protosign’’ and ultimately vocal language, thus providing a neural underpinning for earlier ‘‘gestural hypotheses’’ (Hewes 1973) of language origins. It is important to note that macaque monkeys have mirror neurons but do not imitate, so any account of human imitation and cumulative culture invoking the mirror neurons must include evolutionary changes to this system. For example, human mirror neurons respond to pantomimed grasping movements lacking an object, whereas monkey mirror neurons do not (Gallese et al. 2004). These functional differences may be related to the pattern of increasing white matter connectivity of ‘‘core’’ fronto-parietal mirror system regions and related temporal- parietal regions seen across (non-imitating) macaques, (infrequently imitating) chimpanzees, and humans (Hecht et al. 2012). Although some have linked mirror neurons and motor resonance to the on- togentic development of Theory of Mind, others are less convinced that simula- tion-based mechanisms can fully account for human understanding of other minds (Saxe 2005). Indeed, the very term ‘‘Theory of Mind’’ implies an actual theory or a set of beliefs about how minds work (Gopnik and Wellman 1992). The debate between ‘‘Simulation Theory’’ and ‘‘Theory Theory’’ is complex and unresolved, but for current purposes does draw attention to brain regions outside the mirror system that are widely thought to be involved in the representation and attribution of mental states: the temporo-parietal junction (TPJ) and the medial prefrontal cortex (Fig. 7.1). As reviewed by Frith and Frith (2006), TPJ appears to be involved in visual perspective taking while medial prefrontal cortex is specifically involved in ‘‘mentalizing’’—thinking about the mental states of oneself and of others. Henshilwood and colleagues (2011) have suggested that evolutionary changes in TPJ may explain the emergence of major innovations in the South African archaeological record after 77,000 years ago. Specifically, they argue (p. 378) that innovations such as personal ornamentation, finely-made stone points, and 7 Neuroarchaeology 159 engraved objects reflect an awareness of and concern for the appearance of arti- facts to others that is ‘‘best explained by reorganization in modern H. sapiens of the temporoparietal areas implicated in higher theory of mind and attentional flexibility’’.

Neuroarchaeology Methods

One of the core challenges for neuroarchaeology is to reconcile the historically situated and interpretive approach of archaeology with the experimental ethos of neuroscience. Cognitive archaeologists are interested in understanding the impli- cations of highly complex real-world behaviors like stone tool-making or artifact- mediated social signaling, whereas cognitive neuroscientists are motivated to pursue tightly controlled laboratory paradigms that can provide rigorous tests of well-defined hypotheses. In discussing the interface between neuroscience and anthropology, Roepstorff and Frith (2012, pp. 104–105) suggest that anthropo- logical perspectives may be useful in providing a theoretical background but that ‘‘once one gets into the necessary nitty-gritty details of experimental design and subsequent data analysis, the anthropological intervention seems rarely very useful in its own right… When one, as an anthropologist, tries, out of the best of intentions, to go down the experimental route, one runs the risk of experiencing a double failure. On the one hand, one may be selling out on what anthropology is good at but, on the other hand, one is not gaining the rigor and/or style which is required for other experimentalists to take one seriously’’. To the extent that this critique of neuroanthropology is also true of neuroar- chaeology, it suggests that the most appropriate roles for the neuroarchaeologist are to apply neuroscience findings to the interpretation of archaeological materials, as reviewed in the previous section, and perhaps to try to exert some influence over the broader theoretical framing of neuroscience research (cf. Malafouris 2009). However, archaeology does differ from (sociocultural) anthropology in having a well-established experimental component. seeks to recreate past processes (Fig. 7.2) in order to test hypotheses about the relationship between material remains and the processes (natural and human) that produce them. For example, researchers might test the influence of furnace temperature on the chemical composition of slag left behind by ore smelting or the effect of angle and force of percussion on flake detachment during stone tool production. Experimental archaeological concern with the detailed study and description of behavioral processes presents an opportunity for profitable integration with neu- roscience research methods. The future of such an ‘‘experimental neuroarchaeol- ogy’’ will lie in the truly interdisciplinary development of methods to study complex real-world behaviors rigorously, in detail, and on multiple levels (e.g. functional anatomy, cognitive processes, action organization, kinematics, ). 160 D. Stout and E. Hecht

Fig. 7.2 Stone tool-making (‘‘knapping’’). Making an Acheulean-style handaxe, one example of the kind of complex, naturalistic behavior of interest to archaeologists

The work of Blandine Bril, discussed above, provides one good example. Bril, trained as a movement scientist, has working with colleagues in archaeology and to elucidate the foundations of stone knapping skill. This had included studies of traditional stone bead knappers in India (Bril et al. 2000, 2005), experimental subjects re-creating early (Oldowan) tools (Bril et al. 2010; Nonaka et al. 2010; Rein et al. 2013), and chimpanzees cracking nuts (Bril et al. 2009, 2012), published across journals ranging from Animal Cognition, Human Move- ment Science, and the Journal of Experimental Psychology to the American Journal of Physical Anthropology and the Journal of Human Evolution. Bril has used a variety of motion recording methods, including accelerometers directly attached to hammers, multi-camera video for 3D motion reconstruction, and the Flock of Birds magnetic marker system, to measure inter-individual (e.g. skill related) variation in percussive gestures and outcomes. In one interdisciplinary 7 Neuroarchaeology 161 study (Nonaka et al. 2010), Bril’s group combined movement science with lithic analysis methods from archaeology to compare knapping intentions, outcomes and associated kinematic variation across subjects with different levels of experience. Such work is obviously of interest to archaeologists, but also helps to reveal interactions between experience, perception, action and cognition that are of interest to neuroscientists. Experimental neuroarchaeologists are interested in the relationship between human brains, behavior and evolution. Whereas archaeologists bring to the table an evolutionary time depth and a relatively sophisticated body of theory and method for dealing with the material outcomes of behavior, neuroscientists have developed a powerful array of techniques for relating behavior to the brain. These include techniques for studying brain anatomy as well as physiology (used to infer function). These techniques may be used in comparative studies of human and non-human primates, or in human experimental subjects replicating archaeologi- cally attested prehistoric behaviors. A review of neuroscience methods for studying brain structure and function is presented in the Appendix 1 of this book. Each of these different techniques is applicable for addressing different aspects of a given topic, so different techniques can often be used productively in combination. For example, of the structural techniques discussed here, the ones most commonly used to investigate neuroar- chaeological questions about brain anatomy are structural MRI and DTI. These two techniques work well as complementary approaches, since structural MRI can be used to compare anatomical differences in gray matter (e.g., using voxel-based morphometry or measurements of sulcal variability), and DTI can identify dif- ferences in white matter (e.g., using tractography or measurements of fractional anisotropy). Of the functional techniques discussed here, the ones that have been used most extensively to investigate neural correlates of archaeologically-relevant behaviors in modern humans are fMRI and FDG-PET. These two techniques also fit together well as complementary approaches. FDG-PET can be used in natu- ralistic behavioral situations, which allows reliable localization of the general brain regions associated with the actual behavior under study [e.g., actual, active flint-knapping (Stout and Chaminade 2007; Stout et al. 2008)]. However, the spatial and temporal resolution of this technique is rather poor. Follow-up fMRI experiments can provide greater spatial and temporal detail about activations associated with a version of the behavior modified for the scanner [e.g., watching videos of flint-knapping and pressing a button to indicate cognitive judgments about the actions (Stout et al. 2011)]. FDG-PET is also the only functional neu- roimaging technique that can be used in awake, behaving, unrestrained great apes and has been used to study chimpanzee brain activations during archaeologically- relevant behaviors like communication and executed/observed grasping (Rilling et al. 2007; Taglialatela et al. 2008; Parr et al. 2009; Taglialatela et al. 2009; Hopkins et al. 2010; Taglialatela et al. 2011). This information in chimpanzees can then be compared to other functional imaging studies in macaques and humans in order to trace the evolution of functional adaptations in the primate lineage and to identify functional responses that are unique to humans. 162 D. Stout and E. Hecht

Some of the techniques discussed here, like histology and intracranial neural recordings, are considered ‘‘gold standards’’ for assessing brain anatomy and function but cannot be used in living humans or great apes. This limits or precludes their direct use in most neurarchaeology experiments, but they can still be important sources of information for designing or interpreting experiments in humans and great apes. For example, comparative MRI and DTI studies often draw on histological analyses of cytoarchitecture and connectivity, which provide cellular-level information about interspecies differences. Similarly, functional neuroimaging studies in humans and chimpanzees are often designed to investigate neural systems that were originally identified using cellular recordings in maca- ques. For example, macaque mirror neurons were discovered in this manner, and were found not to respond to manual actions that do not involve objects [e.g., mimed grasping movements (Rizzolatti et al. 1996)]. Functional imaging studies in chimpanzees and humans, though, do show activation in homologous regions during the observation of mimed grasping movements, suggesting an actual functional difference in this system that may be relevant to the evolution of manual actions (Hecht et al. 2013). A few cutting-edge techniques were not discussed here because they are still in the nascent stages of development, but may ultimately be useful for addressing neuroarchaeological questions. Near-infrared spectroscopy (NIRS) is a functional neuroimaging method that uses changes in the absorbance of near-infrared light by brain tissue just under the skull to measure to changes in the oxygenation of hemoglobin as a proxy for neural activity (Ferrari and Quaresima 2012). It has spatial resolution as high as fMRI and temporal resolution as high as EEG, can be used in semi-naturalistic conditions since the detection device is worn on the head, and is much cheaper and more portable than an MRI scanner. A very recent technique called CLARITY exposes post-mortem brain tissue to a series of agents that render most of the tissue transparent, allowing 3D imaging of cells or axons that are labeled with different agents (Chung et al. 2013). So far, this technique has been used on whole mouse brains and slices of human brain. Its extension to comparative human/chimpanzee neuroanatomy could provide a new source information that combines the strengths of both structural MRI and histology. Neuroscience is a techniques-driven field. It has undergone multiple method- ology-driven revolutions in the past, from the invention of the Golgi staining method at the end of the nineteenth century which enabled visualization of single neurons by pioneers like Ramon y Cajal, to the invention of MR imaging at the end of the twentieth century which enabled the study of real-time function in living human brains. The techniques described in this chapter have all been broadly used in neuroscience and psychology but are just beginning to be applied to neuroar- chaeology, so there is the potential for rapid advancement in this field. The cre- ative application of these techniques to archaeological issues, modifications or improvements to these techniques, or the invention of novel techniques, or all have the potential to drive significant future discoveries. 7 Neuroarchaeology 163

Case Study: The Neuroarchaeology of Stone Tool-Making

Stone tool-making (‘‘knapping’’) occupies a special place in Paleolithic archae- ology generally and in neuroarchaeology specifically. Stone knapping is the ear- liest known uniquely human behavior (Roux and Bril 2005), dating back at least 2.5 million years (Semaw 2000). Although it may appear esoteric in the modern world, stone tool-making has been practiced in one form or another by virtually every human until quite recently. In fact, stone tool-making is a proto- typical human skill integrating demands for planning, problem solving and per- ceptual-motor coordination within a pragmatic, collaborative context. Together with its likely evolutionary importance, this makes stone tool-making an inter- esting object of study for cognitive neuroscience as well as archaeology. The Early Stone Age (ESA) alone encompasses roughly 90 % (2.6–0.25 Ma) of human and charts a technological progression from simple Oldowan stone chips to large, skilfully shaped Acheulean cutting tools (Stout 2011). During this period hominin brain size nearly tripled, from the high end of the chimpanzee range to the low end of the modern human range. It is reasonable to conjecture that many distinctive aspects of modern human brain structure and function evolved during this period of massive brain expansion. Oldowan flaking, known from approximately 2.6–1.6 million years ago, is a simple process of striking sharp cutting flakes from a stone core using direct percussion. However, even this simple technology requires substantial visuomotor coordination, including visual evaluation of core morphology (e.g. edge angles, location of convexities and concavities) in order to select appropriate targets for percussion, as well as active proprioceptive sensation and precise bimanual coordination to guide forceful blows to small targets on the core. After approximately 1.7 million years ago, flake-based Oldowan technology began to be replaced by ‘‘Acheulean’’ technology, involving the intentional shaping of cores into large cutting tools known as ‘‘picks’’, ‘‘handaxes’’ and ‘‘cleavers’’. Such shaping requires greater perceptual-motor skill to precisely control stone fracture patterns and more complex action plans that relate individual flake removals to each other in pursuit of a distal goal. By 500, 000 years ago, some ‘‘Late Acheulean’’ tools exhibit a high level of refinement that additionally involves the careful preparation of edges and surfaces, known as ‘‘platform preparation’’, before flake removals. Platform preparation is often done on the face opposite a planned flake removal: the core is flipped over (‘‘inverted’’) and a new hammerstone and/or hammerstone grip is selected and used to abrade/micro-flake the edge through light, tangential blows. This preparatory operation introduces a new subroutine to toolmaking action plans, increasing their hierarchical depth. In a series of experimental neuroarchaeology studies, we have attempted to shed light on neurocognitive foundations and evolutionary implications of ESA tool- making. Using FDG-PET, fMRI, and kinematic recording methods we have studies the neural correlates (Stout and Chaminade 2007; Stout et al. 2008), manipulative complexity (Faisal et al. 2010), and hierarchical organization (Stout 2011) 164 D. Stout and E. Hecht of Oldowan and Acheulean tool-making methods, as well as the brain mechanisms involved in the observational understanding of these methods (Stout et al. 2011). The locations of knapping-related brain activations observed in these studies are illustrated in Fig. 7.1b. In an early study (Stout and Chaminade 2007), we employed FDG-PET to image brain activity during the making of Oldowan tools by naïve subjects before and after practice. Tool-making was contrasted with a control task consisting of simple, bimanual percussion of two stones (without any attempt to produce flakes) in order to identify any unique demands of actual knapping. We found that Oldowan tool-making by modern subjects was supported by a mosaic of primitive and derived parietofrontal perceptual-motor systems. These included anterior intraparietal sulcus (IPS) and ventral premotor cortex (PMv) areas homologous to those which support manual prehension (Rizzolatti et al. 1998) and simple tool use (Obayashi et al. 2001) in monkeys, as well as more dorsal portions of IPS with functional specializations for representation of the central visual field and per- ception of three-dimensional form from motion that appear to be derived in humans (Orban et al. 2006). Practice effects were observed in higher order visual association areas related to visual search and object recognition as well as in PMv, a region involved in grasping and grip selection. These neurophysiological prac- tice effects were paralleled by changes in the artifacts produced which reflected enhanced perception of core affordances, including the exploitation of acute edge angles. No activation was observed in prefrontal executive cortices associated with strategic action planning or in more posterior portions of inferior parietal cortex thought to play a role in the representation of everyday tool use skills (e.g. Johnson-Frey et al. 2005). We concluded, in agreement with Bril and Roux (2005b), that uniquely human capacities for sensorimotor adaptation and affor- dance perception, rather than abstract conceptualization and planning, were central factors in the initial stages of human technological evolution. One shortcoming of this initial study was that subjects only practiced tool- making for a very limited time (4 h) and did not achieve skills comparable to even the earliest toolmakers. This lack of subject expertise also prevented any study of more advanced, Acheulean, knapping methods. To address these shortcomings, we undertook a further FDG-PET study including expert subjects and a comparison of Oldowan and Late Acheulean technologies (Stout et al. 2008). In the Oldowan condition, we found that expert tool-makers were able to remove more and larger flakes from cores, and thus to generate heavily worked artifacts similar to those found at actual Oldowan sites. Larger, longer flakes travel further across core surfaces and leave relatively flat scars and acute angles on the core rather than the obtuse, rounded core angles typical of novice performance. Consistent success in large flake detachment thus tends to produce advantageous morphology for further flake removals without the need for explicit and detailed planning by the tool- maker. Consistent with these differences in performance we observed greater activation in the supramarginal gyrus of the inferior parietal lobe in experts during Oldowan knapping. This region is involved in body schema representation (see above), and its increased activity likely reflects enhanced expert sensorimotor 7 Neuroarchaeology 165 representations of the tool+body system allowing for more efficient knapping gestures. In comparison to Oldowan knapping, Late Acheulean tool-making producing additional activity in the right hemisphere, including the supramarginal gyrus of the inferior parietal lobule, the right PMv, and the right hemisphere homolog of anterior Broca’s area (Brodmann area 45, IFG pars triangularis), a region that is bilaterally involved in higher-order hierarchical cognition (see above) and which has been specifically implicated in the executive function of response inhibition (Aron et al. 2004) as well as the processing of linguistic context and prosody (intonational contours) (Bookheimer 2002). Observation of increased IFG acti- vation in Late Acheulean tool-making supports long-standing archaeological intuitions regarding the cognitive sophistication of Acheulean technology (Gowlett 1986; Oakley 1954; Wynn 1979), and specifically reflects the complex hierarchical organization (Holloway 1969) of Acheulean action sequences. Evidence of overlap between Acheulean tool-making and aspects of language processing in IFG also provides general support and specific archaeological grounding for hypotheses linking manual praxis to language evolution. Evidence of strong right hemisphere involvement in Acheulean tool-making is an unexpected result given that both language and tool-use are widely considered to be left lateralized. Indeed, this apparent co-lateralization has been a major impetus stimulating interest in possible relations between tool use, handedness, and the evolution of left hemisphere language circuits (e.g. Corballis 2003). However, recent years have seen an increasing awareness of the important and distinctive contributions of the right hemisphere. In the case of linguistic pro- cessing, there is evidence of right hemisphere dominance for affective prosody and context-dependent meaning (i.e. discourse level processing) (Menenti et al. 2009; Ross and Monnot 2008), while in the case of tool use, the right hemisphere appears to play a key role in coordinating protracted, multi-step, manual action sequences (Frey and Gerry 2006; Hartmann et al. 2005). In both cases, right hemisphere contributions pertain to the larger scale spatio-temporal and/or conceptual inte- gration of behaviour, which may help to explain why these contributions have been less apparent in neuroscientific and neuropsychological investigations focusing on smaller scale (e.g. phonological, lexico-semantic, syntactic) language processing or on the simple use of everyday tools (e.g. pantomiming the use of a hammer or comb). The identification of right hemisphere involvement in stone tool-making is a good example of the way in which experimental neuroarchae- ology, and particularly its focus on complex, real-world behavior, can help address issues of interest to mainstream cognitive neuroscience. The potential theoretical importance of right hemisphere involvement in stone tool-making led us to conduct a further experiment using a data glove to record left hand postures during experimental knapping (Faisal et al. 2010). What our pre- vious experiment did not make clear was whether increased right hemisphere activation reflected increased demands for grasp control in the contralateral hand, distinctive right hemisphere contributions to the cognitive control of complex action sequences, or both. During stone knapping, the non-dominant hand plays a 166 D. Stout and E. Hecht critical role supporting and orienting the stone core from which flakes are detached by relatively invariant ballistic strikes from a hammerstone held in the dominant hand. We wanted to further investigate the role of the non-dominant hand in Oldowan and Acheulean technologies in order to clarify its relationship with the observed contralateral brain activation. We found that, whereas hand postures involved in Oldowan and Acheulean knapping were both more complex than a control task (box stacking) there was no observable difference between the two technologies. This led us to conclude that the very different material outcomes of Oldowan and Acheulean knapping reflect differences at a higher level of behavioral organization—in particular distinctive right hemisphere contributions to the regulation of hierarchically complex (policy abstraction), temporally extended (temporal abstraction) action sequences. Dif- ferences in brain activation between Oldowan and Acheulean knapping are thus consistent with an evolutionary scenario in which manual and perceptual-motor adaptations were critical to the earliest stages of human technological evolution, but later developments were more dependent on enhanced executive function (see above). Another key topic of interest in the neuroarchaeology of stone tool-making is the role of different social cognitive (see above) mechanisms is the cultural transmis- sion of Paleolithic technologies. To address this, we conducted an fMRI study (Stout et al. 2011) of subjects at different skill levels observing 20 s video clips of an expert demonstrator producing Oldowan or Acheulean tools. Once again we employed a control condition that consisted of the demonstrator engaged in simple bimanual percussion without flake production. This research was designed to play to the strengths of the fMRI method which, in contrast to FDG-PET, does not allow imaging of natural behavior outside the scanner but does benefit from greater spatial and temporal resolution, greater statistical power (due to stimulus/task repetition), and easier subject recruitment (due to absence of injections and radiation exposure). We were particularly interested in testing the relative contribution of ‘‘bottom-up’’ motor resonance vs. ‘‘top-down’’ intention reading (i.e. Simulation Theory vs. Theory Theory) in the observational understanding of Paleolithic technology across variation in subject expertise (Naïve, Trained [16 h], and Expert) and technological complexity (Oldowan vs. Acheulean). To identify brain systems involved in the observation of Paleolithic tool- making, we examined contrasts of tool-making observation with the control condition. Results were remarkably similar to those obtained from previous FDG- PET studies of tool-making execution, including greater activation of right IFG pars triangularis, despite the different experimental tasks and imaging modalities used. This indicates that neural systems involved in the observational under- standing of Paleolithic toolmaking are very similar to those involved in execution, as predicted by simulation accounts of action understanding. To investigate the effects of expertise on tool-making observation, we examined the unique responses of each subject group (Naïve, Trained and Expert) to dif- ferent tool-making stimuli (Oldowan vs. Acheulean). This provided evidence for the functional ‘‘reorganization’’ (Kelly and Garavan 2005) of activation between 7 Neuroarchaeology 167 groups, reflecting expertise-dependent shifts in cognitive strategy. Naïve subjects show activation in core motor resonance structures together with the ventral prefrontal cortex, as expected for a low-level strategy of novel action under- standing through kinematic simulation. Trained subjects show strong, statistically indistinguishable responses to both Oldowan and Acheulean stimuli, perhaps reflecting the particular social context and motivational set associated with training. Finally, Expert subjects display activation in the medial prefrontal cortex, a classic mentalizing region (se above), suggesting a relatively high level, infer- ential strategy of intention reading. In this context, shared pragmatic skills may provide the foundation for sharing of higher level intentions, in keeping with the motor resonance accounts for the development of Theory of Mind (Gallese et al. 2009). More broadly, the apparent shift in observation strategy from Naive kinematic simulation to Expert mentalizing is consistent with a ‘‘mixed’’ model of action understanding (Grafton 2009) involving contextually variable interactions between bottom-up resonance and top-down interpretation. These findings are consistent with a model of knapping skill acquisition in which observation and imitation alternates with individual practice and behavioral exploration in an iterative fashion. For example, Blandine Bril’s (see above) work has clearly documented that the ‘‘elementary’’ percussive gesture of stone knap- ping requires a highly coordinated and precise strike. However, the important parameters (e.g. kinetic energy) are not perceptually available to naïve observers, nor captured in existing internal models for more generic percussive acts. Thus, the observer must begin by (incorrectly) imitating the observed gesture, checking the outcome against the predicted (desired) outcome and then embarking on a lengthy process of goal-oriented behavioral exploration [i.e. deliberate practice (Ericsson et al. 1993; Rossano 2003)] in order to (re)discover the relevant task constraints and develop corresponding internal models. Because there are a huge number of variables to be explored, this skill acquisition process may be quite lengthy. This process may be accelerated by continued observation of expert performance, which provides a sensory model to be matched, or through intentional teaching by a mentor, which might involve ostensive cues and/or modified performance (demonstration) to highlight relevant variables, structured coaching (Vygotsky 1978), or explicit semantic information about the task. In this context, social motivation for practice (implicating additional social cognitive and affective mechanisms) may also be critical for technological reproduction (Lave and Wenger 1991; Roux 1990; Stout 2002, 2010). We have argued (Stout and Chaminade 2012) that this account of socially facilitated knapping skill acquisi- tion, together with evidence of medial prefrontal ‘‘mentalizing’’ in expert knappers during technical action observation, provides support of a ‘‘technological peda- gogy’’ hypothesis, which proposes that intentional pedagogical demonstration could have provided an adequate scaffold for the evolution of intentional vocal communication. 168 D. Stout and E. Hecht

The Prospects of Neuroarchaeology

The construction of the word ‘‘neuroarchaeology’’ implies a primary role for archaeology, i.e. archaeology informed by neuroscience. On the other hand, the perceived need to coin a new term to describe this research focus suggests broader aspirations to create a truly new, hybrid discipline. This is unlikely to happen at the pragmatic level of institutions and training programs, and self-identified neu- roarchaeologists will likely continue to be found in anthropology and archaeology departments, rather than in psychology, cognitive science, or neuroscience. However, neuroarchaeologists may still hope to promote interdisciplinarity and to work with researchers outside archaeology on truly hybrid research agendas. At times, terms other than neuroarchaeology [e.g. ‘‘evolutionary neuroscience’’ (Stout and Chaminade 2007)] may be more appropriate to describe these activities. Archaeology and neuroscience are united in the quest to understand human nature but deeply divided by disciplinary history, culture, methods, career paths, and institutional support. Collaborative work between researchers with different specializations has been (e.g. Bril et al. 2012; Stout and Chaminade 2012; Wynn and Coolidge 2010) and will likely continue to be the most productive way to advance a hybrid research agenda. The promise of the hybrid agenda is to combine archaeological evidence, theory, and methods for addressing the evolutionary history, spatiotemporal diversity, and concretely situated nature of real-world human behavior with the sophisticated cognitive models and rigorous experi- mental methods of neuroscience. For archaeology and neuroscience to ‘‘meet in the middle’’, it will be necessary for neuroscientists to find ways to accommodate more naturalistic behavior into their research paradigms and for archaeologists to pursue more exacting experimental description and analysis of their behaviors of interest. Fortunately progress has already been made in both directions. Tech- niques such as intersubject correlation (Hasson et al. 2004) and event related (Bartels and Zeki 2004) analyses of fMRI data, as well as ‘‘out of the scanner’’ methods like eye-tracking, EEG, FDG-PET, and NIRS, are enhancing the ability of cognitive neuroscience to address natural behavior. At the same time archae- ologists are adopting methods for more detailed descriptions of behaviors like stone knapping (Faisal et al. 2010; Nonaka et al. 2010) and hafting (Wadley 2010) that will make these behaviors more amenable to neuroscientific investigation. Neuroarchaeology thus stands poised to pursue an increasingly empirical and hypothesis-driven approach to the study of human cognitive evolution.

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Authors Biography

Dietrich Stout is an Assistant Professor of Anthropology at Emory University. He received his Ph.D. in in 2003 from Indiana University, Bloomington, where he studied with Nicholas Toth and Kathy Schick. He served as a Visiting Assistant Professor in Anthropology at George Washington University for 1 year and as a Lecturer (equivalent U.S. Asst. Prof.) in Paleolithic Archaeology at the University College London Institute of Archaeology for 4 years before relocating to Emory in 2009. His research focus on Paleolithic stone tool-making integrates methods ranging from lithic analysis to experimental archaeology, ethn- oarchaeology, and brain imaging.

Erin Hecht received a B.S. in Cognitive Science from the Uni- versity of California, San Diego in 2006 and a Ph.D. in Neuro- science from Emory University in 2013. In 2013, she performed postdoctoral research in the Department of Anthropology at Emory University with Dietrich Stout. As of 2014, she is a postdoctoral researcher in the Department of Psychology at Georgia State Uni- versity. She studies the evolution of social cognition. Her research has involved comparative structural and functional neuroimaging studies in humans and nonhuman primates.