chapter 7 neuroarchaeology - emory...

Chapter 7Neuroarchaeology

Dietrich Stout and Erin Hecht

Abstract ‘‘Neuroarchaeology’’ in the broad sense refers to any application ofneuroscience theory and methods to archaeological questions. This includes theinterpretation of archaeological materials in terms of the cognitive operations andneural substrates they are thought to imply as well as the experimental study ofarchaeologically-visible behaviors using neuroscience methods. The particularstrengths and interests of archaeology have led neuroarchaeologists to focus onthree broad themes in neuroscience theory: grounded cognition, executive func-tion, and social cognition. Much of the published work in neuroarchaeology hasconsisted of attempts to apply neuroscience perspectives on these topics tointerpretations of the archaeological record. Experimental neuroarchaeology, astraightforward methodological extension of conventional experimental archae-ology, has been less common. This may change with the increasing availability ofneuroscience methods for investigating complex, real-world behaviors. The use ofneuroimaging methods to study experimental stone tool-making provides oneexample. Archaeology and neuroscience are united in the quest to understandhuman nature but remain deeply divided by disciplinary history, culture, methods,career paths, and institutional support. Whereas the utility of neuroscience meth-ods to archaeology is clear, there has been less interest among neuroscientists inthe potential contributions of archaeological strengths in the study of evolution andmaterial culture. The future of ‘‘neuroarchaeology’’ as just another niche focuswithin archaeology or as something more will ultimately depend on its relevanceto the questions and research agendas of neuroscientists.

Keywords Archaeology � Cognition � Neuroscience � Stone tools � Brainimaging

D. Stout (&) � E. HechtDepartment of Anthropology, Emory University, 1557 Dickey Drive,Atlanta, GA 30322, USAe-mail: [email protected]

E. Hechte-mail: [email protected]

� Springer International Publishing Switzerland 2015E. Bruner (ed.), Human Paleoneurology,Springer Series in Bio-/Neuroinformatics 3,DOI 10.1007/978-3-319-08500-5_7

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Introduction

The past 20 years have witnessed an explosive growth in the scale, diversity andpublic profile of neuroscience research, fueled in part by the development ofmethods like functional imaging and molecular genetics (Jones and Mendell1999). Neuroscientists have pushed the boundaries of their field in exciting newdirections and researchers in other disciplines have sought to tap into the novelinsights and opportunities of this booming enterprise. This has yielded a host ofhopeful interdisciplinary hybrids including neuroeconomics (Camerer et al. 2005),neurophilosophy (Churchland 1989), neuroergonomics (Parasuraman and Rizzo2006), neuroeducation (Battro et al. 2008), neuroanthropology (Domínguez Duqueet al. 2010), neuroachaeology (Malafouris 2009), and even neuroarthistory (Onians2007), to name just a few. As might be expected, the aims and accomplishments ofsuch 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 havesought to integrate theory and methods in a bilateral synergy. This has been moredifficult in some cases than others. Biological anthropology, 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 neurosciencewith the social sciences (Dias 2010; Roepstorff and Frith 2012) including culturalanthropology 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 ofthe neologism. It is thus useful to distinguish between Neuroarchaeology (narrowsense) and neuroarchaeology (general sense). As outlined by Malafouris (2009),Neuroarchaeology is an outgrowth of the cognitive-processual archaeology ofRenfrew (1994) and is explicitly grounded in Material Engagement Theory(Malafouris 2004; Renfrew 2004). Material Engagement Theory focuses on therole of objects in mediating human behavior, cognition, and sociality and is closelyaligned with approaches to cognition as extended (Clark and Chalmers 1998),grounded (Barsalou 2008), situated (Lave and Wenger 1991) and distributed(Hutchins 1995) developed in psychology, philosophy, anthropology, andelsewhere. 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 ofneuroscience theory and methods to archaeological questions. Examples includethe interpretation of archaeological materials in terms of the cognitive operationsand 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 hasmost commonly addressed the biocultural evolution of human cognitive capacities

146 D. Stout and E. Hecht

during the Paleolithic, in contrast to Neuroarchaeology which has often been moreinterested in the ‘‘post-evolutionary’’ effects of culture change on human cognitionin more recent (Holocene) contexts.

Although both Neuroarchaeologists and neuroarchaeologists have published inneuroscience journals and collaborated with neuroscientists, reciprocal interestfrom ‘‘mainstream’’ neuroscience has remained somewhat limited. For exampleRamachandran (2000) suggested that mirror neurons might explain the UpperPaleolithic ‘‘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 ofarchaeological evidence is made by Peeters et al. (2009), who refer to Oldowanand Acheulean tool industries in order to speculate about the timing of theemergence of a putative human cortical specialization for tool use. Perhaps themost systematic use of archaeological evidence has been in the development ofMichael Arbib’s (2011) Mirror System Hypothesis of language evolution. Therelatively limited interest in archaeology among neuroscientists is unsurprising andunlikely to change so long as the neuroarchaeology research agenda is set solely byarchaeologists in order to address archaeological questions. In a recent critique,Roepstorff and Frith (2012) similarly suggested that ‘‘neuroanthropology’’ is notactually a hybrid discipline but simply a new research focus within anthropology.The future of neuroarchaeology as just another niche focus within archaeology oras something more will ultimately depend on its relevance to the questions andresearch 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 mentalcapacities and patterns of thought from these reconstructed behaviors. Neurosci-entists work with extant organisms in order to study the genetics, structure, andfunction of nervous systems. Cognitive neuroscientists in particular study theneurobiological 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 existbetween the in vivo, organism-focused, experimental methods of the former andthe object-focused, reconstructive, historical methods of the latter. It is the hope ofneuroarchaeology that these differences are complementary and synergistic ratherthan disjunctive and insurmountable.

Though never without controversy, archaeology does have well developedtheory 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 methodsinclude experimental replication (Coles 1979; Saraydar 2008) and ethnographicanalogy (David and Kramer 2001). Theory and methods for moving from inferred

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behaviors to ancient cognition are much less developed, and cognitive archaeol-ogists have a long history of borrowing from psychology and cognitive science inan attempt to fill this gap (e.g. Wynn 1979). In many ways, neuroarchaeology issimply the latest incarnation of this tradition. Its particular appeal is the possibilityof linking ancient cognition to evolving neurobiological substrates. It is thus fairlyclear what neuroscience has to offer archaeology, but what does archaeology haveto offer neuroscience? The key strengths of archaeology are its evolutionary timedepth and its focus on material culture.

Evolutionary theory is fundamental to all biological sciences, and the value ofan evolutionary perspective has already motivated productive integration betweenbiological anthropology and neuroscience. Comparative functional and anatomicalstudies (in which living species are compared in order to infer ancestral conditionsand identify neurocognitive specializations) are conducted by researchers withcross-cutting neuroscience and anthropology training and affiliations and arepublished and cited across core neuroscience and anthropology journals.Archaeology offers another source of evolutionary data that has yet to be exploitedin this interdisciplinary fashion. Although the comparative method is extremelyuseful, it does have a weakness in its inability to resolve the sequence, context, andtiming of evolutionary events since the last common ancestor of the species beingcompared. Comparative studies can thus identify human neural specializations forlanguage, tool use and social cognition that are absent in chimpanzees (Rilling andStout In press) but not when or under what conditions during the past 7–10 millionyears of hominin evolution these specializations emerged. As Wynn (2002) haspointed out, archaeology can help fill these gaps by documenting the chronology,geography, and context for the emergence of new behaviors in the 2.5 millionyears since the first appearance of a human material culture record (Semaw 2000).

The other major strength of archaeology is precisely its focus on this materialrecord. Archaeologists obviously have little choice but to focus on artifacts, butthey have made a virtue of this necessity by thinking deeply on the role ofmateriality in human culture and cognition. Like the air we breathe, humanmaterial 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 ignoredwhat might be most distinctive and significant about our species …what makeshumans unique is that we take part in diverse interactions with innumerable kindsof artifacts in the course of daily activities’’. Particularly relevant to neuroscienceare the ways in which interactions with artifacts extend [or even constitute(Malafouris 2004)] human cognition and sociality. Material culture is a durablemedium 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 tostudying social signaling via facial expressions and eye gaze but have completelyignored clothing and personal adornment. Even neuroscientists explicitly inter-ested in tool-use have often considered it sufficient to study pantomimed gestureswithout any actual object and have devoted almost no attention to the purposefulmodification of artifacts that is the practical goal of most human tool use.


Archaeology has developed theory and methods for dealing with the central role ofobjects in human life that may be useful to neuroscientists, particularly as theycontinue to push the boundaries of their field to address more and more complexdomains 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 neuroscienceperspectives 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 tounderstand human psychology purely in terms of observable behaviors, wassupplanted by Cognitivism, which reasserted the reality and importance of internalmental states and processes in explaining overt behavior. This was the ‘‘CognitiveRevolution’’ that led to the establishment of the cognitive sciences, includingcognitive neuroscience (Miller 2003). Perhaps reflecting these reactionary origins,the orthodox view in the cognitive sciences has been that cognition consists of themanipulation of abstract, ‘‘amodal’’, symbols that are distinct from the ‘‘modal’’systems of perception (e.g. vision, hearing), action (e.g. motor control) andinteroception (e.g. body states, emotions) more directly associated with producingbehavior (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 themore 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 Smith1994) as well as bodily states (Lakoff and Johnson 1980). Grounded Cognitionquestions the central importance of abstract symbol manipulation in human cog-nition and replaces it with an emphasis on ‘‘grounded’’ simulation in the brain’smodal systems of perception, action and interoception. For example, semanticknowledge 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 substantialevidence that the actions of others (including speech) are understood throughinternal 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 classicalCognitivist view of mental processes as abstract symbol manipulation has


encouraged neuroarchaeologists and others to seriously consider: (1) extending theconcept 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 areconsonant with archaeological insights into the importance of artifacts in shapinghuman experience. Artifacts are not just something people think about, they aresomething people think with. Malafouris (2004, 2008) in particular has drawn onAndy Clark’s (e.g. Clark 2008; Clark and Chalmers 1998) concept of an ExtendedMind to argue that artifacts help to actively constitute cognitive systems, ratherthan simply influencing internal cognition. For example, a Mycenaean Linear Btablet may be thought of as enabling a redistribution of memory functions outsidethe brain and indeed as partially instantiating a new ‘‘extended’’ cognitive systemthat includes reading as one of its behaviors. The incorporation of bodily orna-ments, from Paleolithic shell beads to Mycenaean gold rings, into the body imagemight 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 social science (e.g. Gell 1998; Hutchins1995) and philosophy (e.g. Merleau-Ponty 1962) this theory of human ‘‘MaterialEngagement’’ also draws support from neuroscientific evidence that externalobjects can indeed come to be represented in the brain as literal extensions of thebody. Head and Holmes (1911) are commonly credited with originating the con-cept of a ‘‘body schema’’ localized in the parietal lobe, including the speculationthat 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 Iriki2004) used single neuron recording to show that bimodal (visual/somatosensory)neurons in the parietal cortex actually changed their response patterns whenmacaques learn to use a rake. For example, ‘‘distal type’’ neurons with somato-sensory and visual receptive fields centered on the hand extended their receptivefield 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-dependentassimilation of the tool into the body schema’’. Although single neuron recordingis an invasive procedure that cannot ethically be applied to human subjects,behavioral and neuropsychological evidence strongly supports the existence ofsimilar neural mechanisms in humans. For example, brain-damaged patients suf-fering from selective spatial awareness difficulties in near (personal) space makeerrors on a line bisection task when using a stick to point (i.e. an extension of thebody) but perform normally using a laser pointer (Berti and Frassinetti 2000).


Iriki’s group has also used tracer techniques to examine anatomical changes inconnectivity associated with tool training in macaques (Hihara et al. 2006). Theyreported the development of new projections from high order visual areas near thetemporo-parietal junction to the intraparietal sulcus (see Fig. 7.1), where bimodalneurons are found, and speculate that this physical change in connectivity enablesthe body schema flexibility of tool-trained macaques. Tracer techniques requirekilling the subject, and so cannot be applied in humans, however the non-invasivetechnique of Diffusion Tensor Imaging (DTI, see Sect. Neuroarchaeology Meth-ods) has now provided extensive evidence of experience-dependent changes inhuman 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 documentedexperience-dependant changes in grey matter density, and there is now widespreadacceptance that even adult brains are highly plastic in response to environment andexperience.

For Malafouris (2010) this plasticity is yet another reason to consider the brainitself as a cultural artifact, and to focus on the broader organism-environmentsystem as the proper unit of analysis. Archaeology has much to offer neurosciencein this regard, both in taking material culture seriously and in appreciating the fullscope of human cultural and technological variation through time and space.Renfrew (2008) has argued that even in the absence of significant biologicalevolution, the past 60,000 years have witnessed a fundamental, culturally-drivenreorganization of the human brain and cognition. Within neuroscience (thoughperhaps not in the mainstream), Iriki (Iriki and Sakura 2008) has made a somewhatsimilar proposal that the origins of human tool use, with its intimate relation tobody schema representation and sense of self, set up a unique feedback interactionbetween organism and environment leading to the emergence of consciousness,Theory of Mind, and eventually ‘‘scientific and technical civilization’’. These ideasabout the evolution of organism-environment systems may be further related to theconcept of Niche Construction in evolutionary biology (Odling-Smee et al. 2003),which recognizes that organisms alter environments in a multitude of ways thatinfluence the selective pressures acting on their own offspring. For example, ter-mites not only build mounds but are exquisitely adapted to live in them. Overevolutionary and historical time, humans have constructed a complex diversity ofcognitive, cultural and technological niches. Neuroarchaeologists would argue thatit is no more possible to understand human cognition without reference to this factthan 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 ofhuman uniqueness and cognitive evolution often focus on ‘‘higher order’’ capac-ities for abstract thought, problem solving and symbol use. Grounded Cognition


Fig. 7.1 Functional neuroanatomy. a Cortical regions discussed in the text. Prefrontal regionsadapted 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 Oldowanand Acheulean toolmaking; red circles indicate regions activated by Acheulean toolmaking only.Both technologies activate bilateral inferior and superior parietal cortex and intraparietal sulcus, aswell as left ventral premotor cortex. Acheulean tool-making specifically activates the righthemisphere homologue of Broca’s area in the inferior frontal gyrus, right ventral premotor cortexand dorsal premotor cortex bilaterally. Abbreviations: FPC frontopolar cortex; mPFC medialprefrontal cortex; mid-DLPFC mid-dorsolateral prefrontal cortex; PMd dorsal premotor cortex;pre-PMd/caudal PFC pre-dorsal premotor/caudal prefrontal cortex; dIPS/SPL dorsal intraparietalsulcus/superior parietal lobule; aIPS anterior intraparietal sulcus; IPL inferior parietal lobule; TPJtemporo-parietal junction; PMv ventral premotor cortex; IFG inferior frontal gyrus


suggests that such higher order capacities are firmly based in the brain’s modalsystems for perception and action. This in turn suggests that much of the story ofhuman cognitive evolution may actually concern changing capacities for concretesensation and action in the world, as opposed to abstract internal representation.This perspective has been most fully developed in the work of Blandine Bril andcolleagues on the kinematic organization of stone knapping behaviors.

Bril’s work on stone knapping is empirical and experimental (see below), but inthis section we will focus on the broader theoretical framework (e.g. Bril and Roux2005a), which has its foundations in Ecological Psychology (Gibson 1986; Reed1996) and the Dynamical Systems approach to cognition and action (Bernstein1996; Thelen and Smith 1994). Broadly speaking, Ecological Psychology contendsthat behavior and cognition can only be properly understood as properties ofintegrated organism-environment systems. For Gibson (1986) this includes theconcept of ‘‘direct perception’’, which rejects the conventional view that percep-tion occurs through the production of internal representations based on limitedsensory input (e.g. patterns of light falling on the retina). Gibson instead charac-terizes perception as an active process of engagement with the environment, sothat 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 includesespecially his concept of ‘‘affordance’’. An affordance is a possibility for actionthat 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—thesame 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 inobject perception by recognizing that perception occurs for action (Fagg and Arbib1998; Grèzes and Decety 2002) and cannot be easily separated from it. Even theperception of space can be altered by motor planning and activity—for exampledistances appear greater if there is more resistance to movement (Kirsch et al.2012). Such findings have led to a questioning of conventional distinctionsbetween sensory and motor systems in the brain, and to the concept of ‘‘activeperception’’ (Pulvermüller and Fadiga 2010). As Gibson (1986, p. 223) put it: ‘‘Wemust perceive in order to move, but we must move in order to perceive’’.

Bruner (2010) considered the relevance of such sensorimotor integration, andparticularly visuospatial integration in frontoparietal neural networks, to classi-cally ‘‘cognitive’’ functions such as working memory and general intelligence. Heargues that multisensory integration in upper parietal areas supports the formationof goal-oriented spatial frames for action guiding the allocation of attention andgeneration of intentions. This interpretation is particularly interesting in light ofpaleoneurological evidence presented by Bruner that modern human brains aredistinguished from other hominin taxa by a differential enlargement of the upperparietal region.

The Dynamical Systems approach is closely related to Ecological Psychologyand similarly opposed to mainstream, representational accounts of cognition.


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 dynamicallystable 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 (McClellandet al. 2010). As the name implies, the Dynamical Systems approach focuses onpatterns 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 isrecognized 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 thelevel of individual muscles this number is closer to 1,000 (Bril and Roux 2005a). Acentral 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 ahammer. 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 thisperspective, control emerges from the discovery of effective movement synergiesthat coordinate action with respect to a goal (or ‘‘attractor’’) without limiting thedegrees of freedom that allow for adaptive flexibility and dynamic stability. Insofaras the discovery of effective synergies changes an organism’s possibilities foraction in its environment, it may be considered as a form of experience-dependentaffordance perception.

These theoretical considerations, informed by experimental kinematic results,have led Bril and colleagues to suggest that early (i.e. Oldowan) stages of hominintechnological evolution were enabled by changing perceptual-motor, rather thancognitive, capacities (Bril and Roux 2005b) and furthermore that the difficulty ofdiscovering the appropriate movement synergies (i.e. the cryptic nature of taskaffordances) implies that ‘‘the recurrence of a learning situation which allows thetransmission of the skill, possibly by providing the opportunities for first-handexperience, is likely to have been a prerequisite to the emergence of controlledflaking 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 similarconclusions 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 comesfrom histological studies of occipital visual cortex in humans versus other primates(Preuss et al. 1999) and fMRI experiments showing human parietal cortexresponses 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


and others on the social and environmental facilitation or ‘‘scaffolding’’ of affor-dance perception/skill acquisition is supported a wide array of research onapprenticeship learning and related topics across disciplines ranging from devel-opmental and comparative psychology to anthropology and education (Fragaszy2011; Ingold 2001; Lave and Wenger 1991; Rogoff 1990; Tomasello 1999;Vygotsky 1978; Zukow-Goldring and Arbib 2007). The key to understanding theperception-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 rejectsthe conventional mind-body dualism which would see cognitive ‘‘competence’’ asseparable 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 anorganism, and other biological processes (e.g., genetic activity, neural activity) arecomponents, that stabilizes the transmission of the detection of the constraints andopportunities for action in the environment across generations’’.

Executive Function

Interest in the Grounded Cognition perspectives discussed above should not be seenas precluding research focused more directly on the ‘‘higher order’’ capacities forplanning, problem solving, and conceptualization that have traditionally been seenas defining uniquely human cognition. The goal of emergentist perspectives is notimpose 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 andWynn 2001) and are classically associated with prefrontal cortex. Such functionshave been of great interest to researchers across cognitive psychology (the study ofmental processes, especially using psychometric experiments and formal model-ing), cognitive neuropsychology (the study of brain function, especially throughwork with brain-damaged patients), and cognitive neuroscience (discussed above).This diverse history is reflected in an equally diverse range of partially overlappingterminology and theoretical frameworks that can be quite confusing.

In cognitive archaeology, Frederick Coolidge and Thomas Wynn (e.g. Coolidgeand Wynn 2005, 2009; Wynn and Coolidge 2004) have applied the multi-com-ponent Working Memory model of Baddeley (e.g. 2003) which derives fromcognitive psychology. As discussed by Coolidge et al. (this volume) this modelincludes 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’’. Workingmemory capacity, including especially amodal attention regulation, has been linkedto ‘‘fluid intelligence’’ (i.e. novel problem solving ability) (e.g. Engle et al. 1999).


Coolidge and Wynn (2005) hypothesized that a recent (60,000–130,000 years ago)genetic mutation affecting the central executive of working memory might beresponsible for the emergence of fully modern behavior and cognition in thearchaeological 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 modularityversus ‘‘cognitive fluidity’’ derived from developmental psychology (e.g. Karmil-off-Smith 1992). Mithen proposed that evolution of a novel capacity for fluidintegration across multiple ‘‘specialized intelligences’’ explained the emergence ofmodern behavior. Stout (2010, 2011); Stout et al. (2008) focused on earlier (LowerPaleolithic) time periods using cognitive neuroscience models of hierarchicalinformation processing in prefrontal cortex (e.g. Badre and D’Esposito 2009;Koechlin and Jubault 2006) to suggest a gradual evolution of executive function aswell as possible links with the emergence of language (Stout and Chaminade 2012).

Insofar as there is a core concept running across these various theories andapplications, it is that executive functions have to do with the selection andorganization 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 theparsing/production of hierarchical structure (e.g. nesting of behavioral sub-goals).The frontal lobes appear critical to these capacities, although it is increasinglyrecognized that control processes are distributed across functional circuits inte-grating frontal and parietal brain regions (Dosenbach et al. 2008). Questions abouthow to sub-divide or ‘‘fractionate’’ executive function into psychologically realcomponents, and whether these components are functionally localized to differentportions of frontal cortex remain controversial and at the forefront of research.

A prevailing view in cognitive neuroscience is that frontal cortex function isorganized along a posterior to anterior gradient of increasing abstraction (seeFig. 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. spatialand object domains)

2. Relational integration: proceeds from 1st order relations (properties such ascolor), 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 asA is to B), and so on.

3. Temporal abstraction: maintenance of general action goals (e.g. make asandwich) over extended periods of time in contrast to concrete goals (e.g. slicebread) 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


‘‘open package’’. Conversely, the abstract goal ‘‘prepare lunch’’ on a particularday might not involve any knives or sandwiches at all.

Brain imaging experiments designed using these various definitions haveconsistently documented increasingly anterior frontal involvement as abstractionincreases, suggesting that this is indeed a fundamental organizing principle offrontal cortex. However defined, capacities for abstract cognition supported byanterior frontal cortex are clearly important for the planning and execution ofcomplex adaptive behavior, which is commonly impaired in patients with frontaldamage (Stuss and Alexander 2007). Research in comparative neuroanatomy hasidentified evolutionary changes in the organization and interconnectivity of humananterior frontal cortex that may support uniquely human capacities for abstractcognitive control (Teffer and Semendeferi 2012; Reyes and Sherwood, thisvolume).

The inferior frontal gyrus (IFG) in particular has been linked with humancapacities for language, tool use, and social learning, making it of special interestto neuroarchaeologists. IFG includes Broca’s area and has long been associatedwith speech production and syntactic processing (Broca 2006 [1861]; Hagoort2005). More recently, IFG has been shown to participate in a range of non-linguistic behaviors from object manipulation to sequence prediction, visualsearch, arithmetic and music (Fadiga et al. 2009; Fink et al. 2006; Schubotz andvon Cramon 2003). It has been proposed that this superficial behavioral diversitystems from an underlying computational role of IFG in the processing of hierar-chically structured information (i.e. policy abstraction) (Koechlin and Jubault2006), leading to speculation that this function may have evolved first in thecontext of manual praxis before being co-opted to support other behaviors such aslanguage (Pulvermüller and Fadiga 2010). Neuroarchaeological studies of stonetool-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) isa 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 socialcognition enabled the high-fidelity cultural learning which subsequently did ‘‘theactual work in creating many, if not all, of the most distinctive and importantcognitive products and processes of the species Homo sapiens’’. (Tomasello 1999,p. 11). Importantly, this cultural mechanism of cognitive change implies apotentially faster (‘‘historical’’) rate of change compared to biological evolution. Itis thus appealing to conjecture that a single change in social cognition mightexplain the apparent increase in rates of cultural change that some archaeologistssee as marking the initial emergence of ‘‘modern human behavior’’ in the African


Middle Stone Age. As mentioned in the introduction, for example, V.S. Rama-chandran has suggested that developments in the mirror neuron system of actionunderstanding 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 andparietal cortex of macaque monkeys (Rizzolatti and Craighero 2004). These areneurons that respond both to observed actions and the self-performance of asimilar action. Neurons with similar properties are thought to exist in humans(Kilner et al. 2009) and to provide a mechanism of action understanding throughinternal simulation or ‘‘motor resonance’’. It has further been proposed that thisbasic mechanism of action understanding is the foundation for more sophisticatedforms 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 inhuman Broca’s area and its macaque homolog has also suggested potential links tolanguage evolution (Rizzolatti and Arbib 1998). Michael Arbib’s Mirror SystemHypothesis proposes that a primitive anthropoid action understanding systemunderwent successive evolutionary modifications to support imitation, pantomime,manual ‘‘protosign’’ and ultimately vocal language, thus providing a neuralunderpinning for earlier ‘‘gestural hypotheses’’ (Hewes 1973) of language origins.It is important to note that macaque monkeys have mirror neurons but do notimitate, so any account of human imitation and cumulative culture invoking themirror neurons must include evolutionary changes to this system. For example,human mirror neurons respond to pantomimed grasping movements lacking anobject, whereas monkey mirror neurons do not (Gallese et al. 2004). Thesefunctional differences may be related to the pattern of increasing white matterconnectivity 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 aset of beliefs about how minds work (Gopnik and Wellman 1992). The debatebetween ‘‘Simulation Theory’’ and ‘‘Theory Theory’’ is complex and unresolved,but for current purposes does draw attention to brain regions outside the mirrorsystem that are widely thought to be involved in the representation and attributionof mental states: the temporo-parietal junction (TPJ) and the medial prefrontalcortex (Fig. 7.1). As reviewed by Frith and Frith (2006), TPJ appears to beinvolved in visual perspective taking while medial prefrontal cortex is specificallyinvolved in ‘‘mentalizing’’—thinking about the mental states of oneself and ofothers.

Henshilwood and colleagues (2011) have suggested that evolutionary changesin TPJ may explain the emergence of major innovations in the South Africanarchaeological record after 77,000 years ago. Specifically, they argue (p. 378) thatinnovations such as personal ornamentation, finely-made stone points, and


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 ofthe temporoparietal areas implicated in higher theory of mind and attentionalflexibility’’.

Neuroarchaeology Methods

One of the core challenges for neuroarchaeology is to reconcile the historicallysituated and interpretive approach of archaeology with the experimental ethos ofneuroscience. 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 topursue tightly controlled laboratory paradigms that can provide rigorous tests ofwell-defined hypotheses. In discussing the interface between neuroscience andanthropology, 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 andsubsequent data analysis, the anthropological intervention seems rarely very usefulin its own right… When one, as an anthropologist, tries, out of the best ofintentions, to go down the experimental route, one runs the risk of experiencing adouble failure. On the one hand, one may be selling out on what anthropology isgood at but, on the other hand, one is not gaining the rigor and/or style which isrequired 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 neuroarchaeologistare to apply neuroscience findings to the interpretation of archaeological materials,as reviewed in the previous section, and perhaps to try to exert some influence overthe broader theoretical framing of neuroscience research (cf. Malafouris 2009).However, archaeology does differ from (sociocultural) anthropology in having awell-established experimental component. Experimental archaeology seeks torecreate past processes (Fig. 7.2) in order to test hypotheses about the relationshipbetween material remains and the processes (natural and human) that producethem. For example, researchers might test the influence of furnace temperature onthe chemical composition of slag left behind by ore smelting or the effect of angleand force of percussion on flake detachment during stone tool production.Experimental archaeological concern with the detailed study and description ofbehavioral 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 studycomplex real-world behaviors rigorously, in detail, and on multiple levels (e.g.functional anatomy, cognitive processes, action organization, kinematics,neurophysiology).


The work of Blandine Bril, discussed above, provides one good example. Bril,trained as a movement scientist, has working with colleagues in archaeology andprimatology to elucidate the foundations of stone knapping skill. This had includedstudies of traditional stone bead knappers in India (Bril et al. 2000, 2005),experimental subjects re-creating early (Oldowan) tools (Bril et al. 2010; Nonakaet 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 AmericanJournal of Physical Anthropology and the Journal of Human Evolution. Bril hasused a variety of motion recording methods, including accelerometers directlyattached to hammers, multi-camera video for 3D motion reconstruction, and theFlock of Birds magnetic marker system, to measure inter-individual (e.g. skillrelated) variation in percussive gestures and outcomes. In one interdisciplinary

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


study (Nonaka et al. 2010), Bril’s group combined movement science with lithicanalysis methods from archaeology to compare knapping intentions, outcomes andassociated kinematic variation across subjects with different levels of experience.Such work is obviously of interest to archaeologists, but also helps to revealinteractions between experience, perception, action and cognition that are ofinterest to neuroscientists.

Experimental neuroarchaeologists are interested in the relationship betweenhuman brains, behavior and evolution. Whereas archaeologists bring to the tablean evolutionary time depth and a relatively sophisticated body of theory andmethod for dealing with the material outcomes of behavior, neuroscientists havedeveloped a powerful array of techniques for relating behavior to the brain. Theseinclude techniques for studying brain anatomy as well as physiology (used to inferfunction). These techniques may be used in comparative studies of human andnon-human primates, or in human experimental subjects replicating archaeologi-cally attested prehistoric behaviors.

A review of neuroscience methods for studying brain structure and function ispresented in the Appendix 1 of this book. Each of these different techniques isapplicable for addressing different aspects of a given topic, so different techniquescan often be used productively in combination. For example, of the structuraltechniques discussed here, the ones most commonly used to investigate neuroar-chaeological questions about brain anatomy are structural MRI and DTI. Thesetwo techniques work well as complementary approaches, since structural MRI canbe used to compare anatomical differences in gray matter (e.g., using voxel-basedmorphometry or measurements of sulcal variability), and DTI can identify dif-ferences in white matter (e.g., using tractography or measurements of fractionalanisotropy). Of the functional techniques discussed here, the ones that have beenused most extensively to investigate neural correlates of archaeologically-relevantbehaviors in modern humans are fMRI and FDG-PET. These two techniques alsofit together well as complementary approaches. FDG-PET can be used in natu-ralistic behavioral situations, which allows reliable localization of the generalbrain regions associated with the actual behavior under study [e.g., actual, activeflint-knapping (Stout and Chaminade 2007; Stout et al. 2008)]. However, thespatial and temporal resolution of this technique is rather poor. Follow-up fMRIexperiments can provide greater spatial and temporal detail about activationsassociated with a version of the behavior modified for the scanner [e.g., watchingvideos of flint-knapping and pressing a button to indicate cognitive judgmentsabout 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 apesand has been used to study chimpanzee brain activations during archaeologically-relevant behaviors like communication and executed/observed grasping (Rillinget 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 canthen be compared to other functional imaging studies in macaques and humans inorder to trace the evolution of functional adaptations in the primate lineage and toidentify functional responses that are unique to humans.


Some of the techniques discussed here, like histology and intracranial neuralrecordings, are considered ‘‘gold standards’’ for assessing brain anatomy andfunction but cannot be used in living humans or great apes. This limits or precludestheir direct use in most neurarchaeology experiments, but they can still beimportant sources of information for designing or interpreting experiments inhumans and great apes. For example, comparative MRI and DTI studies oftendraw on histological analyses of cytoarchitecture and connectivity, which providecellular-level information about interspecies differences. Similarly, functionalneuroimaging studies in humans and chimpanzees are often designed to investigateneural systems that were originally identified using cellular recordings in maca-ques. For example, macaque mirror neurons were discovered in this manner, andwere found not to respond to manual actions that do not involve objects [e.g.,mimed grasping movements (Rizzolatti et al. 1996)]. Functional imaging studies inchimpanzees and humans, though, do show activation in homologous regionsduring the observation of mimed grasping movements, suggesting an actualfunctional difference in this system that may be relevant to the evolution of manualactions (Hecht et al. 2013).

A few cutting-edge techniques were not discussed here because they are still inthe nascent stages of development, but may ultimately be useful for addressingneuroarchaeological questions. Near-infrared spectroscopy (NIRS) is a functionalneuroimaging method that uses changes in the absorbance of near-infrared light bybrain tissue just under the skull to measure to changes in the oxygenation ofhemoglobin as a proxy for neural activity (Ferrari and Quaresima 2012). It hasspatial resolution as high as fMRI and temporal resolution as high as EEG, can beused 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 recenttechnique called CLARITY exposes post-mortem brain tissue to a series of agentsthat render most of the tissue transparent, allowing 3D imaging of cells or axonsthat are labeled with different agents (Chung et al. 2013). So far, this technique hasbeen used on whole mouse brains and slices of human brain. Its extension tocomparative human/chimpanzee neuroanatomy could provide a new sourceinformation 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 stainingmethod at the end of the nineteenth century which enabled visualization of singleneurons by pioneers like Ramon y Cajal, to the invention of MR imaging at the endof the twentieth century which enabled the study of real-time function in livinghuman brains. The techniques described in this chapter have all been broadly usedin 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 orimprovements to these techniques, or the invention of novel techniques, or all havethe potential to drive significant future discoveries.


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 least2.5 million years (Semaw 2000). Although it may appear esoteric in the modernworld, stone tool-making has been practiced in one form or another by virtuallyevery human society 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. Togetherwith 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) ofhuman prehistory and charts a technological progression from simple Oldowanstone chips to large, skilfully shaped Acheulean cutting tools (Stout 2011). Duringthis period hominin brain size nearly tripled, from the high end of the chimpanzeerange to the low end of the modern human range. It is reasonable to conjecture thatmany distinctive aspects of modern human brain structure and function evolvedduring this period of massive brain expansion.

Oldowan flaking, known from approximately 2.6–1.6 million years ago, is asimple process of striking sharp cutting flakes from a stone core using directpercussion. However, even this simple technology requires substantial visuomotorcoordination, including visual evaluation of core morphology (e.g. edge angles,location of convexities and concavities) in order to select appropriate targets forpercussion, as well as active proprioceptive sensation and precise bimanualcoordination to guide forceful blows to small targets on the core.

After approximately 1.7 million years ago, flake-based Oldowan technologybegan to be replaced by ‘‘Acheulean’’ technology, involving the intentionalshaping of cores into large cutting tools known as ‘‘picks’’, ‘‘handaxes’’ and‘‘cleavers’’. Such shaping requires greater perceptual-motor skill to preciselycontrol stone fracture patterns and more complex action plans that relate individualflake 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 additionallyinvolves the careful preparation of edges and surfaces, known as ‘‘platformpreparation’’, before flake removals. Platform preparation is often done on the faceopposite a planned flake removal: the core is flipped over (‘‘inverted’’) and a newhammerstone and/or hammerstone grip is selected and used to abrade/micro-flakethe edge through light, tangential blows. This preparatory operation introduces anew subroutine to toolmaking action plans, increasing their hierarchical depth.

In a series of experimental neuroarchaeology studies, we have attempted to shedlight on neurocognitive foundations and evolutionary implications of ESA tool-making. Using FDG-PET, fMRI, and kinematic recording methods we have studiesthe neural correlates (Stout and Chaminade 2007; Stout et al. 2008), manipulativecomplexity (Faisal et al. 2010), and hierarchical organization (Stout 2011)


of Oldowan and Acheulean tool-making methods, as well as the brain mechanismsinvolved in the observational understanding of these methods (Stout et al. 2011).The locations of knapping-related brain activations observed in these studies areillustrated in Fig. 7.1b.

In an early study (Stout and Chaminade 2007), we employed FDG-PET toimage brain activity during the making of Oldowan tools by naïve subjects beforeand after practice. Tool-making was contrasted with a control task consisting ofsimple, bimanual percussion of two stones (without any attempt to produce flakes)in order to identify any unique demands of actual knapping. We found thatOldowan tool-making by modern subjects was supported by a mosaic of primitiveand derived parietofrontal perceptual-motor systems. These included anteriorintraparietal sulcus (IPS) and ventral premotor cortex (PMv) areas homologous tothose 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 withfunctional specializations for representation of the central visual field and per-ception of three-dimensional form from motion that appear to be derived inhumans (Orban et al. 2006). Practice effects were observed in higher order visualassociation 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 reflectedenhanced perception of core affordances, including the exploitation of acute edgeangles. No activation was observed in prefrontal executive cortices associated withstrategic action planning or in more posterior portions of inferior parietal cortexthought 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 centralfactors 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 eventhe earliest toolmakers. This lack of subject expertise also prevented any study ofmore advanced, Acheulean, knapping methods. To address these shortcomings, weundertook a further FDG-PET study including expert subjects and a comparison ofOldowan and Late Acheulean technologies (Stout et al. 2008). In the Oldowancondition, we found that expert tool-makers were able to remove more and largerflakes from cores, and thus to generate heavily worked artifacts similar to thosefound at actual Oldowan sites. Larger, longer flakes travel further across coresurfaces and leave relatively flat scars and acute angles on the core rather than theobtuse, rounded core angles typical of novice performance. Consistent success inlarge flake detachment thus tends to produce advantageous morphology for furtherflake removals without the need for explicit and detailed planning by the tool-maker. Consistent with these differences in performance we observed greateractivation in the supramarginal gyrus of the inferior parietal lobe in experts duringOldowan knapping. This region is involved in body schema representation (seeabove), and its increased activity likely reflects enhanced expert sensorimotor


representations of the tool+body system allowing for more efficient knappinggestures.

In comparison to Oldowan knapping, Late Acheulean tool-making producingadditional activity in the right hemisphere, including the supramarginal gyrus ofthe inferior parietal lobule, the right PMv, and the right hemisphere homolog ofanterior Broca’s area (Brodmann area 45, IFG pars triangularis), a region that isbilaterally involved in higher-order hierarchical cognition (see above) and whichhas 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 archaeologicalintuitions regarding the cognitive sophistication of Acheulean technology (Gowlett1986; Oakley 1954; Wynn 1979), and specifically reflects the complex hierarchicalorganization (Holloway 1969) of Acheulean action sequences. Evidence of overlapbetween Acheulean tool-making and aspects of language processing in IFG alsoprovides general support and specific archaeological grounding for hypotheseslinking manual praxis to language evolution.

Evidence of strong right hemisphere involvement in Acheulean tool-making isan unexpected result given that both language and tool-use are widely consideredto be left lateralized. Indeed, this apparent co-lateralization has been a majorimpetus 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 anddistinctive contributions of the right hemisphere. In the case of linguistic pro-cessing, there is evidence of right hemisphere dominance for affective prosody andcontext-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 appearsto play a key role in coordinating protracted, multi-step, manual action sequences(Frey and Gerry 2006; Hartmann et al. 2005). In both cases, right hemispherecontributions pertain to the larger scale spatio-temporal and/or conceptual inte-gration of behaviour, which may help to explain why these contributions havebeen less apparent in neuroscientific and neuropsychological investigationsfocusing on smaller scale (e.g. phonological, lexico-semantic, syntactic) languageprocessing or on the simple use of everyday tools (e.g. pantomiming the use of ahammer or comb). The identification of right hemisphere involvement in stonetool-making is a good example of the way in which experimental neuroarchae-ology, and particularly its focus on complex, real-world behavior, can help addressissues of interest to mainstream cognitive neuroscience.

The potential theoretical importance of right hemisphere involvement in stonetool-making led us to conduct a further experiment using a data glove to record lefthand postures during experimental knapping (Faisal et al. 2010). What our pre-vious experiment did not make clear was whether increased right hemisphereactivation reflected increased demands for grasp control in the contralateral hand,distinctive right hemisphere contributions to the cognitive control of complexaction sequences, or both. During stone knapping, the non-dominant hand plays a


critical role supporting and orienting the stone core from which flakes are detachedby relatively invariant ballistic strikes from a hammerstone held in the dominanthand. We wanted to further investigate the role of the non-dominant hand inOldowan and Acheulean technologies in order to clarify its relationship with theobserved contralateral brain activation.

We found that, whereas hand postures involved in Oldowan and Acheuleanknapping were both more complex than a control task (box stacking) there was noobservable difference between the two technologies. This led us to conclude thatthe very different material outcomes of Oldowan and Acheulean knapping reflectdifferences at a higher level of behavioral organization—in particular distinctiveright hemisphere contributions to the regulation of hierarchically complex (policyabstraction), temporally extended (temporal abstraction) action sequences. Dif-ferences in brain activation between Oldowan and Acheulean knapping are thusconsistent with an evolutionary scenario in which manual and perceptual-motoradaptations were critical to the earliest stages of human technological evolution,but later developments were more dependent on enhanced executive function (seeabove).

Another key topic of interest in the neuroarchaeology of stone tool-making is therole 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 ofan expert demonstrator producing Oldowan or Acheulean tools. Once again weemployed a control condition that consisted of the demonstrator engaged in simplebimanual percussion without flake production. This research was designed to playto the strengths of the fMRI method which, in contrast to FDG-PET, does not allowimaging of natural behavior outside the scanner but does benefit from greater spatialand 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 technologyacross variation in subject expertise (Naïve, Trained [16 h], and Expert) andtechnological 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 controlcondition. Results were remarkably similar to those obtained from previous FDG-PET studies of tool-making execution, including greater activation of right IFGpars triangularis, despite the different experimental tasks and imaging modalitiesused. 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 examinedthe unique responses of each subject group (Naïve, Trained and Expert) to dif-ferent tool-making stimuli (Oldowan vs. Acheulean). This provided evidence forthe functional ‘‘reorganization’’ (Kelly and Garavan 2005) of activation between


groups, reflecting expertise-dependent shifts in cognitive strategy. Naïve subjectsshow activation in core motor resonance structures together with the ventralprefrontal cortex, as expected for a low-level strategy of novel action under-standing through kinematic simulation. Trained subjects show strong, statisticallyindistinguishable responses to both Oldowan and Acheulean stimuli, perhapsreflecting the particular social context and motivational set associated withtraining. 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 mayprovide the foundation for sharing of higher level intentions, in keeping with themotor resonance accounts for the development of Theory of Mind (Gallese et al.2009). More broadly, the apparent shift in observation strategy from Naivekinematic simulation to Expert mentalizing is consistent with a ‘‘mixed’’ model ofaction understanding (Grafton 2009) involving contextually variable interactionsbetween bottom-up resonance and top-down interpretation.

These findings are consistent with a model of knapping skill acquisition inwhich observation and imitation alternates with individual practice and behavioralexploration in an iterative fashion. For example, Blandine Bril’s (see above) workhas clearly documented that the ‘‘elementary’’ percussive gesture of stone knap-ping requires a highly coordinated and precise strike. However, the importantparameters (e.g. kinetic energy) are not perceptually available to naïve observers,nor captured in existing internal models for more generic percussive acts. Thus, theobserver must begin by (incorrectly) imitating the observed gesture, checking theoutcome against the predicted (desired) outcome and then embarking on a lengthyprocess of goal-oriented behavioral exploration [i.e. deliberate practice (Ericssonet al. 1993; Rossano 2003)] in order to (re)discover the relevant task constraintsand develop corresponding internal models. Because there are a huge number ofvariables to be explored, this skill acquisition process may be quite lengthy. Thisprocess may be accelerated by continued observation of expert performance,which provides a sensory model to be matched, or through intentional teaching bya mentor, which might involve ostensive cues and/or modified performance(demonstration) to highlight relevant variables, structured coaching (Vygotsky1978), or explicit semantic information about the task. In this context, socialmotivation for practice (implicating additional social cognitive and affectivemechanisms) may also be critical for technological reproduction (Lave andWenger 1991; Roux 1990; Stout 2002, 2010). We have argued (Stout andChaminade 2012) that this account of socially facilitated knapping skill acquisi-tion, together with evidence of medial prefrontal ‘‘mentalizing’’ in expert knappersduring technical action observation, provides support of a ‘‘technological peda-gogy’’ hypothesis, which proposes that intentional pedagogical demonstrationcould have provided an adequate scaffold for the evolution of intentional vocalcommunication.


The Prospects of Neuroarchaeology

The construction of the word ‘‘neuroarchaeology’’ implies a primary role forarchaeology, i.e. archaeology informed by neuroscience. On the other hand, theperceived need to coin a new term to describe this research focus suggests broaderaspirations to create a truly new, hybrid discipline. This is unlikely to happen at thepragmatic level of institutions and training programs, and self-identified neu-roarchaeologists will likely continue to be found in anthropology and archaeologydepartments, rather than in psychology, cognitive science, or neuroscience.However, neuroarchaeologists may still hope to promote interdisciplinarity and towork with researchers outside archaeology on truly hybrid research agendas. Attimes, terms other than neuroarchaeology [e.g. ‘‘evolutionary neuroscience’’ (Stoutand Chaminade 2007)] may be more appropriate to describe these activities.

Archaeology and neuroscience are united in the quest to understand humannature but deeply divided by disciplinary history, culture, methods, career paths,and institutional support. Collaborative work between researchers with differentspecializations has been (e.g. Bril et al. 2012; Stout and Chaminade 2012; Wynnand Coolidge 2010) and will likely continue to be the most productive way toadvance a hybrid research agenda. The promise of the hybrid agenda is to combinearchaeological evidence, theory, and methods for addressing the evolutionaryhistory, spatiotemporal diversity, and concretely situated nature of real-worldhuman behavior with the sophisticated cognitive models and rigorous experi-mental methods of neuroscience. For archaeology and neuroscience to ‘‘meet inthe middle’’, it will be necessary for neuroscientists to find ways to accommodatemore naturalistic behavior into their research paradigms and for archaeologists topursue more exacting experimental description and analysis of their behaviors ofinterest. 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 abilityof cognitive neuroscience to address natural behavior. At the same time archae-ologists are adopting methods for more detailed descriptions of behaviors likestone 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 andhypothesis-driven approach to the study of human cognitive evolution.

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Authors Biography

Dietrich Stout is an Assistant Professor of Anthropology at EmoryUniversity. He received his Ph.D. in Paleoanthropology in 2003from Indiana University, Bloomington, where he studied withNicholas Toth and Kathy Schick. He served as a Visiting AssistantProfessor in Anthropology at George Washington University for1 year and as a Lecturer (equivalent U.S. Asst. Prof.) in PaleolithicArchaeology at the University College London Institute ofArchaeology for 4 years before relocating to Emory in 2009. Hisresearch focus on Paleolithic stone tool-making integrates methodsranging 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 performedpostdoctoral research in the Department of Anthropology at EmoryUniversity with Dietrich Stout. As of 2014, she is a postdoctoralresearcher in the Department of Psychology at Georgia State Uni-versity. She studies the evolution of social cognition. Her researchhas involved comparative structural and functional neuroimagingstudies in humans and nonhuman primates.


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