A broader conception of the user’s perceptual, cognitive, and motor capabilities considers tools as body extensions. By identifying specific tool-related motor-grounded mechanisms, the embodied approach assumes that this “extensional phenomenon” takes place not only at a behavioral level but also at a psychological level. At least four ways of conceiving embodiment in tool use have been offered in relation to the concepts of incorporation, perception, knowledge, and observation. Nevertheless, the validity of these conceptions has been rarely, if not never, assessed. In this article, we attempt to fill this gap by discussing each of these conceptions in turn, with the aim of determining whether it is justified to consider tools as detached objects of a special sort in embodied terms. We argue that tool incorporation is made possible by “distalization”, that is, an embodied mechanism specific to tool use. Nevertheless, there is neither empirical nor theoretical support for the hypothesis that specific tool-related embodied mechanisms are involved in perception, knowledge, and observation. In broad terms, there is a tendency in the literature to overinterpret tool use as an embodied phenomenon at a psychological level. Inevitably, this limitation leads us to under-intellectualize the underlying cognitive processes and, as a result, it prevents us from understanding the technical-reasoning skills that allow humans to transform dramatically the physical world.
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Here the term object does not refer only to an object with finite boundaries as a stick or a stone but can also include an object with no finite boundaries such as water or ground.
Gibson (1986) was in line with this, mentioning several times the case of “missiles” to illustrate his description of tools.
Patients with extinction can perceive a contralateral stimulus in isolation but can fail to perceive the same stimulus when presented together with an ipsilesional one. This phenomenon can arise cross-modally (e.g., visual-tactile extinction).
Distalization does not concern all the instances of tool use as defined by Shumaker et al. (2011), particularly in cases where the tool is thrown (i.e., throwing actions). We will not discuss further this aspect. Nevertheless, note that if distalization is considered as the core criterion of tool use, then throwing actions should be excluded from the category of tool-use actions (for a similar view, see Fragaszy and Mangalam 2018)..
This proposal also allows to draw a sharp distinction between “cloth-like objects” (e.g., gloves, shoes) and tools inasmuch as cloth-like objects do not need to be controlled differently to the body-only system contrary to tools.
In other words, distalization can be both innate and learnt.
The notion of physical understanding does not imply that an individual is able to reason about the physical world at an analogical level. As discussed in more details in Sect. 4.2., the ability to transfer what is understood technically from a situation to another situation is the key feature of technical reasoning (Osiurak et al. 2010).
It would be more correct to call these tool-centered affordances “xx-with-ability” rather than “xx-ability” (e.g., cut-with-ability instead of cut-ability), because they do not correspond to the actions that an individual can perform on but rather with the tool compared to user-centered affordances “xx-ability” (e.g., grasp-ability). This nomenclature was, for instance, used by Wagman and Carello (2001).
For this reason, Osiurak et al. (2017) recently proposed to limit the term affordances to the opportunities for action offered by the environment in terms of “motor actions”, and to use the term “mechanical action” when the opportunities for action concerns the interaction between two external objects. Note that one of these two external objects can be the body of the user (i.e., reflective actions, such as brushing teeth). In this case, the body is the “object” of the mechanical action.
This proposal is sometimes misinterpreted, as if it suggests that the acquisition of our knowledge about the physical world (i.e., mechanical knowledge) does not emerge from our interactions with it. As demonstrated by a significant body of evidence, most of mechanical knowledge is acquired through our interactions with the physical world (e.g., Baillargeon et al. 1992; for a review, see Lockman 2000). In a way, most—if not all—scholars agree with that. Nevertheless, this does not necessarily imply that the knowledge acquired is embodied and corresponds to a simulation of the sensorimotor experience linked to its acquisition.
The manipulation-knowledge hypothesis can be viewed as an embodied approach to tool use because it posits that knowledge about how to use tools is based on specific tool-related motor representations. In this way, the technical-reasoning hypothesis is a non-embodied approach because it denies the existence of such tool-related motor representations.
This cascade mechanism is obviously reiterative.
Even if semantic knowledge appears to be neither necessary nor sufficient to actually use tools, it might be indispensable to create abstract and generalizable concepts associated with tools and objects (e.g., Lambon Ralph et al. 2017; De Bellis et al. 2018; Wurm and Caramazza 2019; see also: Bar et al. 2006; Rogers and McClelland 2004). Hence, whereas mechanical knowledge is necessary to actually use tools, semantic knowledge might be considered as a complementary addendum in order to construct object-related representations. Such knowledge might be usable in everyday life by a reasoning-based agent (i.e., humans or future artificial intelligence), in the context of a cognitive-oriented functioning. Such an integrated perspective has been recently suggested by Federico and Brandimonte (2020) by introducing the concept of “action reappraisal”. Furthermore, semantic knowledge can play a specific role in some specific tool-use situations, such as when people are asked to use tools presented in isolation (i.e., single tool use). Indeed, in such situations, semantic knowledge might be useful to inform the individual about the conventional use of the tool presented, thereby allowing the individual to generate the mechanical action associated through technical reasoning (Osiurak 2014). This can explain why patients with a selective semantic deficit can show difficulties when asked to show how to use a familiar tool presented in isolation but not when presented with its corresponding object (Corbett et al. 2015; Baumard et al. 2016; see also Sirigu et al. 1991; Hodges et al. 2000; Osiurak et al. 2008; Lesourd et al. 2016).
Technical-reasoning skills have also been shown to be a good predictor of cumulative performance in micro-society experiments in which participants have to perform a task (e.g., building a tower) as members of a chain (Osiurak et al. 2016; De Oliveira et al. 2019; Osiurak et al. 2020b, in press; see also Osiurak et al. submitted)..
According to the ecological/Gibsonian approach, animals can perceive directly the opportunities for action provided by the environment (i.e., affordances). As discussed above, this approach is viable only if affordances are considered as being restricted to the motor actions that are relative to the animal’s biomechanical/morphological properties (i.e., acting on). This approach can be articulated with the technical-reasoning hypothesis if we assume that technical reasoning is dedicated to form a representation of the tool-use action (i.e., acting with), which then guides the perception of the appropriate affordances (i.e., acting on; for discussion, see Osiurak et al. 2017). In this frame, we do not perceive affordances in order to determine how to use a tool with an object, but rather to realize the action intended by selecting and planning the appropriate motor actions. By contrast, it is difficult at a theoretical level to articulate the technical-reasoning hypothesis with the manipulation-knowledge hypothesis because both aim to explain how individuals determine how a tool has to be manipulated as a tool (i.e., either through technical reasoning or through the activation of manipulation knowledge). Interestingly, although both the ecological/Gibsonian approach and the manipulation-knowledge hypothesis can be labelled as embodied, they strongly diverge at a theoretical level (non-representational approach versus representational approach).
Anderson, S. J., Yamagishi, N., & Karavia, V. (2002). Attentional processes link perception and action. Proceedings of the Royal Society of London B, 269, 1225–1232.
Arbib, M. A., Bonaiuto, J. B., Jacobs, S., & Frey, S. H. (2009). Tool use and the distalization of the end-effector. Psychological Research, 73, 441–462.
Baber, C. (2003). Cognition and tool use: Forms of engagement in human and animal use of tools. London: Talyor & Francis.
Baber, C. (2006). Cognitive aspects of tool use. Applied Ergonomics, 37, 3–15.
Badets, A., Michelet, T., de Rugy, A., & Osiurak, F. (2017). Creating semantics in tool use. Cognitive Processing, 18, 129–134.
Badets, A., & Osiurak, F. (2015). A goal-based mechanism for delayed motor intention: Considerations from motor skills, tool use and action memory. Psychological Research, 79, 345–360.
Baillargeon, R., Needham, A., & DeVos, J. (1992). The development of young infants’ intuitions about support. Early Development and Parenting, 1, 69–78.
Bar, M., Kassam, K. S., Ghuman, A. S., Boshyan, J., Schmid, A. M., Dale, A. M., et al. (2006). Top-down facilitation of visual recognition. Proceedings of the National Academy of Science USA, 103, 449–454.
Barsalou, L. W. (2008). Grounded cognition. Annual Review of Psychology, 59, 617–645.
Barsalou, L. W. (2009). Simulation, situated conceptualization, and prediction. Philosophical Transactions of the Royal Society B, 364, 1281–1289.
Baumard, J., Lesourd, M., Jarry, C., Merck, C., Etcharry-Bouyx, F., Chauviré, V., et al. (2016). Tool use disorders in neurodegenerative diseases. Roles of semantic memory and technical reasoning. Cortex, 82, 119–132.
Beck, B. B. (1980). Animal tool use behavior: The use and manufacture of tools by animals. New York: Garland Press.
Bhalla, M., & Proffitt, D. R. (1999). Visual-motor recalibration in geographical slant perception. Journal of Experimental Psychology: Human Perception and Performance, 25, 1076–1096.
Bloesch, E. K., Davoli, C. C., Roth, N., Brockmole, J. R., & Abrams, R. A. (2012). Watch this! Observed tool use affects perceived distance. Psychonomic Bulletin & Review, 19, 177–183.
Bonnier, P. (1905). L’Aschématie. Revue Neurologique, 13, 606–609.
Borghi, A. M., & Riggio, L. (2009). Sentence comprehension and simulation of object temporary, canonical and stable affordances. Brain Research, 1253, 117–128.
Boyd, R., & Richerson, P. (1985). Culture and the evolutionary process. Chicago: University of Chicago Press.
Boyd, R., Richerson, P. J., & Henrich, J. (2011). The cultural niche: Why social learning is essential for human adaptation. Proceedings of the National Academy of Science USA, 108, 10918–10925.
Brass, M., & Heyes, C. (2005). Imitation: Is cognitive neuroscience solving the correspondence problem? Trends in Cognitive Sciences, 9, 489–495.
Buxbaum, L. J. (2001). Ideomotor Apraxia: A call to action. Neurocase, 7, 445–448.
Buxbaum, L. J. (2017). Learning, remembering, and predicting how to use tools: Distributed neurocognitive mechanism. Comment on Osiurak and Badets (2016). Psychological Review, 124, 346–360.
Buxbaum, L. J., & Kalénine, S. (2010). Action knowledge, visuomotor activation, and embodiment in the two action systems. Annals of the New York Academy of Sciences, 1191, 201–218.
Buxbaum, L. J., Kyle, K. M., & Menon, R. (2005). On beyond mirror neurons: Internal representations subserving imitation and recognition skilled object-related actions in humans. Cognitive Brain Research, 25, 226–239.
Buxbaum, L. J., Schwartz, M. F., & Carew, T. G. (1997). The role of memory in object use. Cognitive Neuropsychology, 14, 219–254.
Caligiore, D., Borghi, A. M., Parisi, D., & Baldassarre, G. (2010). TRoPICALS: A computational embodied neuroscience model of compatibility effects. Psychological Review, 117, 1188–1228.
Cardinali, L., Frassinetti, F., Brozzolo, C., Urquizar, C., Roy, A. C., & Farnè, F. (2009). Tool-use induces morphological updating of the body schema. Current Biology, 19, 478–479.
Cho, D. T., & Proctor, R. W. (2010). The object-based Simon effect: Grasping affordance or relative location of the graspable part? Journal of Experimental Psychology: Human Perception and Performance, 36, 853–861.
Cho, D. T., & Proctor, R. W. (2011). Correspondence effects for objects with opposing left and right protrusions. Journal of Experimental Psychology: Human Perception and Performance, 37, 737–749.
Cho, D. T., & Proctor, R. W. (2013). Object-based correspondence effects for action-relevant and surface-property judgments with keypress responses: Evidence for a basis in spatial coding. Psychological Research, 77, 618–636.
Corbett, F., Jefferies, E., Burns, A., & Lambon Ralph, M. A. (2015). Deregulated semantic cognition contributes to object-use deficits in Alzheimer’s disease: A comparison with semantic aphasia and semantic dementia. Journal of Neuropsychology, 9, 219–241.
Danel, S., Osiurak, F., & von Bayern, A. M. P. (2017). From the age of 5 humans decide economically, whereas crows exhibit individual preferences. Scientific Reports, 7, 17043.
Daprati, E., & Sirigu, A. (2006). How we interact with objects: Learning from brain lesions. Trends in Cognitive Sciences, 10, 265–270.
Davoli, C. C., Brockmole, J. R., & Witt, J. K. (2012). Compressing perceived distance with remote tool-use: Real, imagined, and remembered. Journal of Experimental Psychology: Human Perception and Performance, 38, 80–89.
De Bellis, F., Magliacano, A., Sagliano, L., Conson, M., Grossi, D., & Trojano, L. (2018). Left inferior parietal and posterior temporal cortices mediate the effect of action observation on semantic processing of objects: Evidence from rTMS. Psychological Research, 84, 1006–1019.
De Grave, D. D. J., Brenner, E., & Smeets, J. B. J. (2011). Using a stick does not necessarily alter judged distances or reachability. PLoS ONE, 6, e16697.
De Oliveira, E., Reynaud, E., & Osiurak, F. (2019). Roles of technical reasoning, theory of mind, creativity, and fluid cognition in cumulative technological culture. Human Nature, 30, 326–340.
Decety, J., & Grezes, J. (1999). Neural mechanisms subserving the perception of human actions. Trends in Cognitive Sciences, 3, 172–178.
Decety, J., Jeannerod, M., & Prablanc, C. (1989). The timing of mentally represented actions. Behavioural Brain Research, 34, 35–42.
Decety, J., & Michel, F. (1989). Comparative analysis of actual and mental movement times in two graphic tasks. Brain and Cognition, 11, 87–97.
Decroix, J., & Kalénine, S. (2018). Timing of grip and goal activation during action perception: A priming study. Experimental Brain Research, 236, 2411–2426.
Decroix, J., & Kalénine, S. (2019). What first drives visual attention during the recognition of object-directed actions? The role of kinematics and goal information. Attention, Perception, & Psychophysics, 81, 2400–2409.
Drillis, R. J. (1963). Folk norms and biomechanics. Human Factors, 5, 427–441.
Durgin, F. H., Baird, J. A., Greenburg, M., Russell, R., Shaugnessy, K., & Waymouth, S. (2009). Who is being perceived? The experimental demands of wearing a backpack. Psychonomic Bulletin & Review, 16, 964–968.
Farnè, A., Iriki, A., & Làdavas, E. (2005). Shaping multisensory action-space with tools: Evidence from patients with cross-modal extinction. Neuropsychologia, 43, 238–248.
Farnè, A., & Làdavas, E. (2000). Dynamic size-change of hand peripersonal space following tool use. NeuroReport, 11, 1645–1659.
Federico, G., & Brandimonte, M. A. (2019). Tool and object affordances: An ecological eye-tracking study. Brain and Cognition, 135, 103582.
Federico, G., & Brandimonte, M. A. (2020). Looking to recognize: The pre-eminence of semantic over sensorimotor processing in human tool use. Scientific Reports, 10, 6157.
Firestone, C., & Scholl, B. J. (2016). Cognition does not affect perception: Evaluating the evidence for “top-down” effects. Behavioral and Brain Sciences, e229, 1–77.
Fragaszy, D. M., & Mangalam, M. (2018). Tooling. Advances in the Study of Behavior, 50, 177–241.
Frak, V. G., Paulingnan, Y., & Jeannerod, M. (2001). Orientation of the opposition axis in mentally simulated grasping. Experimental Brain Research, 136, 120–127.
Frey, S. H. (2007). What pus the how in where? Tool use and the divided visual stream hypothesis. Cortex, 43, 368–375.
Gibson, J. J. (1986). The ecological approach to visual perception. New York: Taylor & Francis (Original work published 1979).
Goldenberg, G. (2013). Apraxia: The cognitive side of motor control. Oxford: Oxford University Press.
Goldenberg, G., & Hagmann, S. (1998). Tool use and mechanical problem solving in apraxia. Neuropsychologia, 36, 581–589.
Goldenberg, G., & Spatt, J. (2009). The neural basis of tool use. Brain, 132, 1645–1655.
Hansell, M., & Ruxton, G. D. (2008). Setting tool use within the context of animal construction behaviour. Trends in Ecology & Evolution, 23, 73–78.
Head, H., & Holmes, G. (1911). Sensory disturbances from cerebral lesions. Brain, 34, 102–254.
Heilman, K. M., Maher, L. M., Greenwald, M. L., & Rothi, L. J. G. (1997). Conceptual apraxia from lateralized lesions. Neurology, 49, 457–464.
Heilman, K. M., Rothi, L. J., & Valenstein, E. (1982). Two forms of ideomotor apraxia. Neurology, 32, 342–346.
Hirose, N. (2002). An ecological approach to embodiment and cognition. Cognitive Systems Research, 3, 289–299.
Hodges, J. R., Bozeat, S., Lambon Ralph, M. A., Patterson, K., & Spatt, J. (2000). The role of knowledge in object use: Evidence from semantic dementia. Brain, 123, 1913–1925.
Horner, V., & Whiten, A. (2005). Causal knowledge and imitation/emulation switching in chimpanzees (Pan troglodytes) and children (Homo sapiens). Animal Cognition, 8, 164–181.
Horner, V., Whiten, A., Flynn, E., & de Waal, F. B. M. (2006). Faithful replication of foraging techniques along cultural transmission chains by chimpanzees and children. Proceedings of the National Academy of Sciences USA, 103, 13878–13883.
Humphreys, G. W. (2001). Objects, affordances, action. The Psychologist, 14, 408–412.
Hunt, G. R. (1996). Manufacture and use of hook tools by New Caledonian crows. Nature, 379, 249–251.
Hunt, G. R., & Gray, R. D. (2004). Direct observations of pandanus-tool manufacture and use by a New Caledonian crow (Corvus moneduloides). Animal Cognition, 7, 114–120.
Iriki, A., Tanaka, M., & Iwamura, Y. (1996). Coding of modified body schema during tool use by macaque postcentral neurones. NeuroReport, 7, 2325–2330.
Jarry, C., Osiurak, F., Delafuys, D., Chauviré, V., Etcharry-Bouyx, F., et al. (2013). Apraxia of tool use: More evidence for the technical reasoning hypothesis. Cortex, 49, 2322–2333.
Jeannerod, M. (2001). Neural simulation of action: A unifying mechanism for motor cognition. NeuroImage, 14, 103–109.
Johnson, S. H., Rotte, M., Grafton, S. T., Hinrichs, H., Gazzaniga, M. S., & Heinze, H. J. (2002). Selective activation of a parietofrontal circuit during implicitly imagined prehension. Neuroimage, 17, 1693–1704.
Johnson-Frey, S. H., & Grafton, S. T. (2003). From “acting on” to “acting with”: The functional anatomy of action representation. In C. Prablanc, D. Pélisson, & Y. Rossetti (Eds.), Progress in brain research (pp. 127–139). New York: Elsevier.
Johnson-Frey, S. H., Newman-Norlund, R., & Grafton, S. T. (2005). A distributed left hemisphere network active during planning of everyday tool use skills. Cerebral Cortex, 15, 681–695.
Kenward, B., Weir, A. A. S., Rutz, C., & Kacelnik, A. (2005). Behavioural ecology: Tool manufacture by naive juvenile crows. Nature, 433, 121.
Kostov, K., & Janyan, A. (in press). Critical bottom-up attentional factors in the handle orientation effect: Asymmetric luminance transients and object-center eccentricity relative to fixation. Psychological Research.
Lambon Ralph, M. A., Jefferies, E., Patterson, K., & Rogers, T. T. (2017). The neural and computational bases of semantic cognition. Nature Reviews Neuroscience, 18, 42–55.
Lesourd, M., Baumard, J., Jarry, C., Etcharry-Bouyx, F., Belliard, S., Moreaud, O., et al. (2016). Mechanical problem-solving in Alzheimer’s disease and semantic dementia. Neuropsychology, 30, 612–623.
Lesourd, M., Naëgelé, B., Jaillard, A., Detante, O., & Osiurak, F. (2020). Using tools efficiently despite defective hand posture: A single-case study. Cortex, 129, 406–422.
Linkenauger, S. A., Witt, J. K., Stefanucci, J. K., Bakdash, J. Z., & Proffitt, D. R. (2009). The effects of handedness and reachability on perceived distance. Journal of Experimental Psychology: Human Perception and Performance, 35, 1649–1660.
Lockman, J. J. (2000). A perception-action perspective on tool use development. Child Development, 71, 137–144.
Malaivijitnond, S., Lekprayoon, C., Tandavanittj, N., Panha, S., Cheewatham, C., & Hamada, Y. (2007). Stone-tool usage by Thai long-tailed macaques (Macaca fascicularis). American Journal of Primatology, 69, 227–233.
Mangalam, M. (2016). What makes a tool. In T. K. Shackelford & V. A. Weekes-Shackelford (Eds.), Encyclopedia of evolutionary psychological science (pp. 1–5). Cham: Springer.
Mangalam, M., & Fragaszy, D. M. (2016). Transforming the body-only system into the body-plus-tool system. Animal Behaviour, 117, 115–122.
Maravita, A., Husain, M., Clarke, K., & Driver, J. (2001). Reaching with a tool extends visual–tactile interactions into far space: evidence from cross-modal extinction. Neuropsychologia, 39, 580–585.
Maravita, A., & Iriki, A. (2004). Tools for the body (schema). Trends in Cognitive Sciences, 8, 79–86.
Massen, C., & Prinz, W. (2007). Activation of actions rules in action observation. Journal of Experimental Psychology. Learning, Memory, and Cognition, 33, 1118–1130.
Massen, C., & Prinz, W. (2009). Movements, actions and tool-use actions: An ideomotor approach to imitation. Philosophical Transactions of the Royal Society of London B, 364, 2349–2358.
Merleau-Ponty, M. (1962). Phenomenology of perception. New York: Routledge (Original work published 1945)
Miller, L. E., Montroni, L., Koun, E., Salemme, R., Hayward, V., & Farnè, A. (2018). Sensing with tools extends somatosensory processing beyond the body. Nature, 561, 239–242.
Mizelle, J. C., & Wheaton, L. A. (2010). The neuroscience of storing and molding tool action concepts: How “plastic” is grounded cognition? Frontiers in Psychology, 1, 196.
Molto, L., Morgado, N., Guinet, E., Fazioli, L., Heurley, L. P., & Palluel-Germain, R. (2020). Motor simulation in tool-use effect on distance estimation. A replication of Witt and Proffitt (2008). Psychonomic Bulletin & Review, 27, 301–306.
Molto, L., Nalborczyk, L., Palluel-Germain, R., & Morgado, N. (in press). Action effects on visual perception of distances: A multilevel Bayesian meta-analysis. Psychological Science.
Morgado, N., Gentaz, E., Guinet, E., Osiurak, F., & Palluel-Germain, R. (2013). Within reach but no so reachable: Obstacles matter in visual perception of reaching distances. Psychonomic Bulletin & Review, 20, 462–467.
Nagell, K., Olguin, R. S., & Tomasello, M. (1993). Processes of social learning in the tool use of chimpanzees (Pan troglodytes) and human children (Homo sapiens). Journal of Comparative Psychology, 107, 174–186.
Naish, K. R., Reader, A. T., Houston-Price, C., Bremner, A. J., & Holmes, N. P. (2013). To eat or not to eat? Kinematics and muscle activity of reach-to-grasp movements are influenced by the action goal, but observers do not detect these differences. Experimental Brain Research, 225, 261–275.
Negri, G. A., Rumiati, R. I., Zadini, A., Ukmar, M., Mahon, B. Z., & Caramazza, A. (2007). What is the role of motor simulation in action and object recognition? Evidence from apraxia. Cognitive Neuropsychology, 24, 795–816.
Nicholson, T., Roser, M., & Bach, P. (2017). Understanding the goals of everyday instrumental actions is primarily linked to object, not motor-kinematic, information: Evidence from fMRI. PLoS ONE, 12, 1–21.
Norman, D. A. (1999). Affordance, conventions, and design. Interactions, 6, 38–43.
Osiurak, F. (2014). What neuropsychology tells us about human tool use? The four constraints theory (4CT): Mechanics, space, time, and effort. Neuropsychology Review, 24, 88–115.
Osiurak, F. (2017). Cognitive paleoanthropology and technology: Toward a parsimonious theory (PATH). Review of General Psychology, 21, 292–307.
Osiurak, F. (2020). The tool instinct. New York: Wiley.
Osiurak, F., Aubin, G., Allain, P., Jarry, C., Richard, I., & Le Gall, D. (2008). Object utilization versus object usage: A single-case study. Neurocase, 14, 169–183.
Osiurak, F., & Badets, A. (2014). Pliers, not fingers: Tool-action effect in a motor intention paradigm. Cognition, 130, 66–73.
Osiurak, F., & Badets, A. (2016). Tool use and affordance: Manipulation-based versus reasoning-based approaches. Psychological Review, 123, 534–568.
Osiurak, F., & Badets, A. (2017). Use of tools and misuse of embodied cognition. Psychological Review, 124, 361–368.
Osiurak, F., Badets, A., Rossetti, Y., Lesourd, M., Navarro, J., & Reynaud, E. (2020a). Disembodying (tool use) action understanding. Neuroscience and Biobehavioral Reviews, 114, 229–231.
Osiurak, F., Cretel, C., Duhau-Marmon, N., Fournier, I., Marignier, L., De Oliveira, E., Navarro, J., & Reynaud, E. (in press). The pedagogue, the engineer, and the friend: From whom do we learn? Human Nature.
Osiurak, F., & Danel, S. (2018). Dexterity and tool use: Beyond the embodied theory. Animal Behaviour, 139, e1–e4.
Osiurak, F., De Oliveira, E., Navarro, J., Lesourd, M., Claidière, N., & Reynaud, E. (2016). Physical intelligence does matter to cumulative technological culture. Journal of Experimental Psychology: General, 145, 941–948.
Osiurak, F., De Oliveira, E., Navarro, J., & Reynaud, E. (2020b). The castaway island: Distinct roles of theory of mind and technical reasoning in cumulative technological culture. Journal of Experimental Psychology: General, 149, 58–66.
Osiurak, F., & Heinke, D. (2018). Looking for intoolligence: A unified framework for the cognitive study of human tool use and technology. American Psychologist, 73, 169–185.
Osiurak, F., Jarry, C., Allain, P., Aubin, G., Etcharry-Bouyx, F., Richard, I., et al. (2009). Unusual use of objects after unilateral brain damage: The technical reasoning model. Cortex, 45, 769–783.
Osiurak, F., Jarry, C., & Le Gall, D. (2010). Grasping the affordances, understanding the reasoning: Toward a dialectical theory of human tool use. Psychological Review, 117, 517–540.
Osiurak, F., Lasserre, S., Arbanti, J., Brogniart, J., Bluet, A., Navarro, J., & Reynaud, E. (submitted). Technical reasoning is necessary not to reinvent the wheel.
Osiurak, F., Lesourd, M., Delporte, L., & Rossetti, Y. (2018). Tool use and generalized motor programs: We all are natural born poly-dexters. Scientific Reports, 8, 10429.
Osiurak, F., Lesourd, M., Navarro, J., & Reynaud, E. (2020c). Technition: When tools come out of the closet. Perspectives on Psychological Science, 15, 880–897.
Osiurak, F., Morgado, N., & Palluel-Germain, R. (2012). Tool use and perceived distance: When unreachable becomes sponatenously reachable. Experimental Brain Research, 218, 331–339.
Osiurak, F., Morgado, N., Vallet, G. T., Drot, M., & Palluel-Germain, R. (2014). Getting a tool gives wings: Underestimation of effort for tool use. Psychological Research, 78, 1–9.
Osiurak, F., & Reynaud, E. (2020). The elephant in the china shop: When technical reasoning meets cumulative technological culture. Behavioral and Brain Sciences, 43, e156.
Osiurak, F., & Rossetti, Y. (2017). Definition: Limb apraxia. Cortex, 93, 228.
Osiurak, F., Rossetti, Y., & Badets, A. (2017). What is an affordance? 40 years later. Neuroscience and Biobehavioral Reviews, 77, 403–417.
Parsons, L. M. (1987). Imagined spatial transformation of one’s body. Journal of Experimental Psychology: General, 116, 172–191.
Peck, A. J., Jeffers, R. G., Carello, C., & Turvey, M. T. (1996). Haptically perceiving the length of one rod by means of another. Ecological Psychology, 8, 237–258.
Pellicano, A., & Binkofski, F. (in press). The prominent role of perceptual salience in object discrimination: Over discrimination of graspable side does not activate grasping affordances. Psychological Research.
Pellicano, A., Iani, C., Borghi, A. M., Rubichi, S., & Nicoletti, R. (2010). Simon-like and functional affordance effects with tools: The effects of object perceptual discrimination and object action state. Quarterly Journal of Experimental Psychology, 63, 2190–2201.
Pellicano, A., Lugli, L., Binkofski, F., Rubichi, S., Iani, C., & Nicoletti, R. (2019). The unimanual handle-to-hand correspondence effect: Evidence for a location coding account. Psychological Research, 83, 1383–1399.
Penn, D. C., Holyoak, K. J., & Povinelli, D. J. (2008). Darwin’s mistake: Explaining the discontinuity between human and nonhuman minds. Behavioral and Brain Sciences, 31, 109–130.
Philbeck, J. W., & Witt, J. K. (2015). Action-specific influences on perception and postperceptual processes: Present controversies and future directions. Psychological Bulletin, 141, 1120–1144.
Pinker, S. (2010). The cognitive niche: Coevolution of intelligence, sociality, and language. Proceedings of the National Academy of Science, 107, 8993–8999.
Poizner, H., Clark, M., Merians, A. S., Macauley, B., Rothi, L. J. G., & Heilman, K. M. (1995). Joint coordination deficits in limb apraxia. Brain, 118, 227–242.
Proffitt, D. R. (2006). Embodied perception and the economy of action. Perspectives in Psychological Science, 1, 110–122.
Proffitt, D. R., Stefanucci, J., Banton, T., & Epstein, W. (2003). The role of effort in distance perception. Psychological Science, 14, 409–428.
Reynaud, E., Lesourd, M., Navarro, J., & Osiurak, F. (2016). On the neurocognitive origins of human tool use: A critical review of neuroimaging data. Neuroscience and Biobehavioral Reviews, 64, 421–437.
Reynaud, E., Navarro, J., Lesourd, M., & Osiurak, F. (2019). To watch is to work: A critical review of neuroimaging data on Tool-use Observation Network (ToON). Neuropsychology Review, 29, 484–497.
Rizzolatti, G., & Matelli, M. (2003). Two different streams form the dorsal visual system: Anatomy and functions. Experimental Brain Research, 153, 146–157.
Robertson, I. (2020). A little too technical: The threat of intellectualising technical reasoning. Behavioral and Brain Sciences, 43, e156.
Rogers, T. T., & McClelland, J. L. (2004). Semantic cognition: A parallel distributed processing approach. Cambridge: MIT press.
Rothi, L. J. G., Ochipa, C., & Heilman, K. M. (1991). A cognitive neuropsychological model of limb praxis. Cognitive Neuropsychology, 8, 443–458.
Rumiati, R. I., & Humphreys, G. W. (1998). Recognition by action: Dissociating visual and semantic routes to action in normal observers. Journal of Experimental Psychology: Human Perception and Performance, 24, 631–647.
Rutz, C., & Hunt, G. R. (2020). New Caledonian crows afford invaluable comparative insights into human cumulative technological culture. Behavioral and Brain Sciences, 43, e156.
Schnall, S., Zadra, J. R., & Proffitt, D. R. (2010). Direct evidence for the economy of action: Glucose and the perception of geographical slant. Perception, 39, 464–482.
Shipton, C., & Nielsen, M. (2015). Before cumulative culture: The evolutionary origins of overimitation and shared intentionality. Human Nature, 26, 33145.
Shumaker, R. W., Walkup, K. R., & Beck, B. B. (2011). Animal tool behavior. Baltimore: John Hopkins University Press.
Sirigu, A., Duhamel, J. R., Cohen, L., Pillon, B., Dubois, B., & Agid, Y. (1996). The mental representation of hand movements after parietal cortex damage. Science, 273, 1564–1568.
Sirigu, A., Duhamel, J. R., & Poncet, M. (1991). The role of sensorimotor experience in object recognition. Brain, 114, 2555–2573.
Stoffregen, T. A., Yang, C. M., Giveans, M. R., Flanagan, M., & Bardy, B. G. (2009). Movement in the perception of an affordance for wheelchair locomotion. Ecological Psychology, 21, 1–36.
Stout, D., & Hecht, E. E. (2017). Evolutionary neuroscience of cumulative culture. Proceedings of the National Academy of Sciences, 114, 7861–7868.
Symes, E., Ellis, R., & Tucker, M. (2007). Visual object affordances: Object orientation. Acta Psychologica, 124, 238–255.
Taylor, A. H., & Jelbert, S. (2020). The crow in the room: New Caledonian crows offer insight into the necessary and sufficient conditions for cumulative cultural evolution. Behavioral and Brain Sciences, 43, e156.
Tennie, C., Call, J., & Tomasello, M. (2010). Evidence for emulation in chimpanzees in social settings using the floating peanut task. PLoS ONE, 5, e10544.
Thill, S., Caligiore, D., Borghi, A. M., Ziemke, T., & Baldassarre, G. (2013). Theories and computational models of affordance and mirror system: An integrative review. Neuroscience and Biobehavioral Reviews, 37, 491–521.
Thompson, E. L., Bird, G., & Catmur, C. (2019). Conceptualizing and testing action understanding. Neuroscience and Biobehavioral Reviews, 105, 106–114.
Tomasello, M., Carpenter, M., Call, J., Behne, T., & Moll, H. (2005). Understanding and sharing intentions: The origins of cultural cognition. Behavioral and Brain Sciences, 28, 675–735.
Tomasello, M., Davis-Dasilva, M., Camak, L., & Bard, K. (1987). Observational learning of tool-use by young chimpanzees. Human Evolution, 2, 175–183.
Tomasello, M., Kruger, A. C., & Ratner, H. H. (1993). Cultural learning. Behavioral and Brain Sciences, 16, 495–552.
Tucker, M., & Ellis, R. (1998). On the relations between seen objects and components of potential actions. Journal of Experimental Psychology: Human Perception and Performance, 24, 830–846.
Vaesen, K. (2012). The cognitive bases of human tool use. Behavioral and Brain Sciences, 35, 203–218.
van Elk, M. (2014). The left inferior parietal lobe represents stored hand-postures for object use and action prediction. Frontiers in Psychology, 5, 333.
van Elk, M., van Schie, H. T., & Bekkering, H. (2008). Conceptual knowledge for understanding other’s actions is organized primarily around action goals. Experimental Brain Research, 189, 99–107.
van Elk, M., van Schie, H., & Bekkering, H. (2014). Action semantics: A unifying conceptual framework for the selective use of multimodal and modality-specific object knowledge. Physics of Life Reviews, 11, 220–250.
van Owerwalle, F., & Baetens, K. (2009). Understanding others’ actions and goals by mirror and mentalizing systems: A meta-analysis. NeuroImage, 48, 564–584.
Vingerhoets, G., Vandamme, K., & Vercammen, A. (2009). Conceptual and physical object qualities contribute differently to motor affordances. Brain and Cognition, 69, 481–489.
Virgo, J., Pillon, J., Navarro, J., Reynaud, E., & Osiurak, F. (2017). Are you sure you’re faster when using a cognitive tool? American Journal of Psychology, 130, 493–503.
Wagman, J. B., & Carello, C. (2001). Affordances and inertial constraints on tool use. Ecological Psychology, 13, 173–195.
Wagman, J. B., & Carello, C. (2003). Haptically creating affordances: The user-tool interface. Journal of Experimental Psychology: Applied, 9, 175–186.
Watson, C. E., & Buxbaum, L. J. (2014). Uncovering the architecture of action semantics. Journal of Experimental Psychology: Human Perception and Performance, 40, 1832–1848.
Whiten, A., Goodall, J., McGrew, W. C., Nishida, T., Reynolds, V., Sugiyama, Y., et al. (1999). Cultures in chimpanzees. Nature, 399, 682–685.
Whiten, A., Horner, V., & de Waal, F. B. M. (2005). Conformity to cultural norms of tool use in chimpanzees. Nature, 437, 737–740.
Whiten, A., Horner, V., & Marshall-Pescini, S. R. J. (2003). Cultural panthropology. Evolutionary Anthropolology, 12, 92–105.
Witt, J. K. (2011a). Action’s effect on perception. Current Directions in Psychological Science, 20, 201–206.
Witt, J. K. (2011b). Tool use influences perceived shape and perceived parallelism, which serves as indirect measures of perceived distance. Journal of Experimental Psychology: Human Perception and Performance, 37, 1148–1156.
Witt, J. K., & Proffitt, D. R. (2008). Action-specific influences on distance perception: A role for motor simulation. Journal of Experimental Psychology: Human Perception and Performance, 34, 1479–1492.
Witt, J. K., Proffitt, D. R., & Epstein, W. (2005). Tool use affects perceived distance, but only when you intend to use it. Journal of Experimental Psychology: Human Perception and Performance, 31, 880–888.
Wohlschläger, A., Gattis, M., & Bekkering, H. (2003). Action generation and action perception in imitation: An instance of the ideomotor principle. Philosophical Transactions of the Royal Society B, 358, 501–515.
Wolpert, L. (2003). Causal belief and the origins of technology. Philosophical Transactions of the Royal Society of London, 361A, 1709–1719.
Wurm, M. F., & Caramazza, A. (2019). Distinct roles of temporal and frontoparietal cortex in representing actions across vision and language. Nature Communications, 10, 289.
This work was performed within the framework of the LABEX CORTEX (ANR-11-LABX-0042) of Université de Lyon, within the program “Investissements d’Avenir” (ANR-11- IDEX-0007) operated by the French National Research Agency (ANR).
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Osiurak, F., Federico, G. Four ways of (mis-)conceiving embodiment in tool use. Synthese (2020). https://doi.org/10.1007/s11229-020-02960-1
- Tool use
- Technical reasoning
- Tool incorporation
- Manipulation knowledge
- Perception and action
- Action observation