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What Neuropsychology Tells us About Human Tool Use? The Four Constraints Theory (4CT): Mechanics, Space, Time, and Effort

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Abstract

Our understanding of human tool use comes mainly from neuropsychology, particularly from patients with apraxia or action disorganization syndrome. However, there is no integrative, theoretical framework explaining what these neuropsychological syndromes tell us about the cognitive/neural bases of human tool use. The goal of the present article is to fill this gap, by providing a theoretical framework for the study of human tool use: The Four Constraints Theory (4CT). This theory rests on two basic assumptions. First, everyday tool use activities can be formalized as multiple problem situations consisted of four distinct constraints (mechanics, space, time, and effort). Second, each of these constraints can be solved by the means of a specific process (technical reasoning, semantic reasoning, working memory, and simulation-based decision-making, respectively). Besides presenting neuropsychological evidence for 4CT, this article shall address epistemological, theoretical and methodological issues I will attempt to resolve. This article will discuss how 4CT diverges from current cognitive models about several widespread hypotheses (e.g., notion of routine, direct and automatic activation of tool knowledge, simulation-based tool knowledge).

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Notes

  1. Some studies have assessed the apraxic patients’ ability to use several tools and objects together such as preparing instant coffee (multiple object task; e.g., De Renzi and Lucchelli 1988). These tasks are now considered as assessing the action disorganization syndrome because of the presence of several steps to achieve the goal (see below).

  2. The notion of “space constraint” stresses the problem that tools and objects are not always here now, that is, directly present to our senses (e.g., they are not visible because they are in another room). In this way, the emphasis is put on the problem of the absence. This differs dramatically from the perspective where the space is divided in function of the individual’s capacities (e.g., reaching space). In this way, it has been shown that tool use can extend our reaching space (e.g., Farnè and Làdavas 2000; Cardinalli et al. 2009; Iriki et al. 1996). Nevertheless, even if an object is out of reach, this object can still be present to the senses, if it is visible, for example.

  3. Several studies have revealed serious limitations on the ability of nonhuman animals to solve tool-use situations that are relatively simple for humans (e.g., Povinelli 2000; Santos et al. 2006; Visalberghi and Limongelli 1994). In line with this, it has been suggested that tool use in animals is not based on relational representations of the underlying generative mechanisms involved, but rather on “concrete” representations learned by trial-and-error (e.g., Penn et al. 2008). The notion of “basic processes” refers here to this kind of learning.

  4. Interestingly, nonhuman, animal users fail transfer tasks (Martin-Ordas et al. 2008; see Penn et al. 2008). These findings provide support for the idea that humans are able to reinterpret the physical world in terms of unobservable, hypothetical entities, such as causal forces (Penn et al. 2008; see below).

  5. The simulation-based knowledge is confronted with some limitations that will be discussed later.

  6. The term technique is used here as synonymous with “mechanical knowledge”.

  7. Semantic memory can be defined as “that system which processes, stores and retrieves information about the meaning of words, concepts and facts” (Warrington 1975). In other words, it allows us to think about things that are not here now (Tulving 1985).

  8. Of course, this is not to deny that it is different to know that knives can generally be found in kitchens or supermarkets and to remember that we possess the appropriate knife in our kitchen or the supermarket where we used to go. This issue is at the heart of important controversies concerning the distinction between semantic and episodic memory introduced by Tulving (1972). Unfortunately, this issue is beyond the scope of the present article, so I will only refer to semantic knowledge to describe the ability to think about things that are not here now. Of particular interest here is that semantic knowledge is fundamental to categorize the tools and objects in function of different activities, from very basic (body self-care, feeding, sleeping) to “non-basic” activities (relaxing, playing the guitar, working). And, it is this categorical organization, which allows us to know and even to remember how to get the appropriate tools and objects. In other words, semantic memory is viewed here as the means to organize the search in memory.

  9. This conception of working memory is quite consistent with current models (e.g., Baddeley 2003).

  10. Tools can also be used to enhance cognitive skills (Jonassen 1992; see also Vygotsky 1978). For instance, abacuses and pocket calculators improve calculation efficiency, and diaries and portable phones facilitate remembering the activities to perform. These tools might suggest that cognitive effort is also assessed when people are engaged in everyday activities. Unfortunately, this issue is beyond the scope of the present article.

  11. The simulation-based decision-making process has to be viewed as a dynamic process in that the effort associated with each option can be re-evaluated all along the activity. For instance, a user can choose to reach a ball that rolled under a sofa with the arm and then decide to get an umbrella to reach the ball with it.

  12. As stressed above, a potential mistake might be to believe that when patients show how to use a tool in a conventional way, they necessarily access information about the usual function.

  13. Recent evidence demonstrates that the perception of the length of rods via dynamic touch can be recalibrated after a training session with auditive feedback (Wagman and Abney 2012). Even if these results were not obtained in a tool-use situation they indicate that the perception of object properties is not specific to a particular perceptual modality but constrained by the object’s mechanical properties.

  14. These procedures have been reported to be impaired in brain-damaged patients, particularly those with damage to superior parietal lobes (Binkofski et al. 2001). The term of tactile agnosia/apraxia have been proposed, stressing the importance of both the sensory and motor components of the disorder. Note also that, besides these stereotypical exploratory procedures, people can perceive a certain number of properties of objects (e.g., mass, length), without the benefit of vision, simply by wielding the objects. This kind of touch is referred to as dynamic touch (Turvey 1996; Wagman and Abney 2012). Interestingly, it has been shown that people are able, via dynamic touch, to determine whether an object is more suited for a given tool-use action (e.g., hammering) than for another one (e.g., poking; Wagman and Carello 2001; see also Wagman and Carello 2003).

  15. Proponents of a strong, embodied cognition approach assume that, as people perceive visual tool or objects, simulations of potential actions can become automatically active in preparation for action (e.g., Barsalou 1999; Pezzulo et al. 2011). As discussed above, this proposal is debatable.

  16. All human societies develop technical equipment, which is modified and improved, a phenomenon called ratchet effect (Tomasello 1999; for further discussion on this aspect with regard to the principles of dialectic and stigmergy, see Osiurak et al. 2010).

References

  • Agre, P. E. (1988). The dynamic structure of everyday life (Tech. Rep. No. 1085). Massachusetts Institute of Technology: Artificial Intelligence Laboratory.

    Google Scholar 

  • Andersen, S. J., Yamagishi, N., & Karavia, V. (2002). Attentional processes link perception and action. Proceedings of the Royal Society of London B, 269, 1225–1232.

    Google Scholar 

  • Anderson, J. R., Bothwell, D., Byrne, M. D., Douglass, S., Lebiere, C., & Qin, Y. (2004). An integrated theory of mind. Psychological Review, 111, 1036–1060.

    PubMed  Google Scholar 

  • Baber, C. (2003). Cognition and tool use. London: Talyor & Francis.

    Google Scholar 

  • Baddeley, A. (2003). Working memory: Looking back and looking forward. Nature Reviews Neuroscience, 4, 829–839.

    CAS  PubMed  Google Scholar 

  • Barsalou, L. W. (1999). Perceptual symbol systems. Behavioral and Brain Sciences, 22, 577–660.

    CAS  PubMed  Google Scholar 

  • Barsalou, L. W. (2008). Grounded cognition. Annual Review of Psychology, 59, 617–645.

    PubMed  Google Scholar 

  • Bartolo, A., Daumüller, M., Della Sala, S., & Goldenberg, G. (2007). Relationship between object-related gestures and the fractionated object knowledge system. Behavioural Neurology, 18, 143–147.

    PubMed  Google Scholar 

  • Beck, B. B. (1980). Animal tool use behavior: The use and manufacture of tools by animals. New York: Garland STPM Press.

    Google Scholar 

  • Beck, S. R., Apperly, I. A., Chappel, J., Guthrie, C., & Cutting, N. (2011). Making tools isn’t child’s play. Cognition, 119, 301–306.

    PubMed  Google Scholar 

  • Bernstein, N. (1967). The coordination and regulation of movements. London: Pergamon.

    Google Scholar 

  • Besnard, J., Allain, P., Osiurak, F., Aubin, G., Etcharry-Bouyx, F., & Le Gall, D. (2009). Contrôle exécutif et comportement d’utilisation d’objets. Vers une dissociation. Revue de Neuropsychologie, 1, 120–132.

    Google Scholar 

  • Besnard, J., Allain, P., Aubin, G., Osiurak, F., Chauviré, V., Etcharry-Bouyx, F., et al. (2010). Utilization Behaviour: Clinical and theoretical approaches. Journal of the International Neuropsychological Society, 16, 1–10.

    Google Scholar 

  • Besnard, J., Allain, P., Aubin, G., Chauviré, V., Etcharry-Bouyx, F., & Le Gall, D. (2011). A contribution to the study of environmental dependency phenomena: The social hypothesis. Neuropsychologia, 49, 3278–3294.

    Google Scholar 

  • Bhalla, M., & Proffitt, D. R. (1999). Visual-motor recalibration in geographical slant perception. Journal of Experimental Psychology: Human Perception and Performance, 25, 1076–1096.

    CAS  PubMed  Google Scholar 

  • Binkofski, F., & Buxbaum, L. J. (2013). Two action systems in the human brain. Brain and Language, 127, 222–229.

    PubMed  Google Scholar 

  • Binkofski, F., Kunesch, E., Classen, J., Seitz, R. J., & Freund, H.-J. (2001). Tactile apraxia. Unimodal disorder of tactile object exploration associated with parietal lesions. Brain, 124, 132–144.

    CAS  Google Scholar 

  • Blakemore, S.-J., Wolpert, D. M., & Frith, C. D. (2002). Abnormalities in the awareness of action. Trends in Cognitive Sciences, 6, 237–242.

    PubMed  Google Scholar 

  • Boesch, C., & Boesch, H. (1981). Sex differences in the use of natural hammers by wild chimpanzees: A preliminary report. Journal of Human Evolution, 10, 585–593.

    Google Scholar 

  • Boesch, C., & Boesch, H. (1984). Possible causes of sex difference in the use of natural hammers by wild chimpanzees. Journal of Human Evolution, 13, 415–440.

    Google Scholar 

  • Boesch-Achermann, H., & Boesch, C. (1993). Tool use in wild chimpanzees: New light from dark forests. Current Directions in Psychological Science, 2, 18–21.

    Google Scholar 

  • Borghi, A. M., & Riggio, L. (2009). Sentence comprehension and simulation of object temporary, canonical and stable affordances. Brain Research, 1253, 117–128.

    CAS  PubMed  Google Scholar 

  • Botvinick, M. M., & Plaut, D. C. (2004). Doing without schema hierarchies: A recurrent connectionist approach to normal and impaired routine sequential action. Psychological Review, 111, 395–429.

    PubMed  Google Scholar 

  • Botvinick, M. M., & Rosen, Z. (2009). Anticipation of cognitive demand during decision-making. Psychological Research, 73, 835–842.

    PubMed Central  PubMed  Google Scholar 

  • Bozeat, S., Lambon Ralph, M. A., Patterson, K., & Hodges, J. R. (2002). When objects lose their meaning: What happens to their use? Cognitive, Affective and Behavioral Neurosciences, 2, 236–251.

    Google Scholar 

  • Brazzelli, M., Colombo, N., Della Sala, S., & Spinnler, H. (1994). Spared and impaired cognitive abilities after bilateral frontal damage. Cortex, 30, 27–51.

    CAS  PubMed  Google Scholar 

  • Bub, D. N., & Masson, M. E. J. (2010). Grasping beer mugs: On the dynamics of alignment effects induced by handled objects. Journal of Experimental Psychology: Human Perception and Performance, 36, 341–358.

    PubMed  Google Scholar 

  • Buxbaum, L. J. (2001). Ideomotor Apraxia: A call to action. Neurocase, 7, 445–448.

    CAS  PubMed  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • Buxbaum, L. J., Schwartz, M. F., & Carew, T. G. (1997). The role of memory in object use. Cognitive Neuropsychology, 14, 219–254.

    Google Scholar 

  • Buxbaum, L. J., Schwartz, M. F., & Montgomery, M. W. (1998). Ideational apraxia and naturalistic action. Cognitive Neuropsychology, 15, 617–643.

    CAS  PubMed  Google Scholar 

  • Buxbaum, L. J., Kyle, K. M., & Menon, R. (2005). On beyond mirror neurons: Internal representations subserving imitation and recognition of skilled object-related actions in humans. Cognitive Brain Research, 25, 226–239.

    PubMed  Google Scholar 

  • Cardinalli, L., Frassinetti, F., Brozzoli, C., Urquizar, C., Roy, A. C., & Farnè, A. (2009). Tool-use induces morphological updating of the body schema. Current Biology, 19, 478–479.

    Google Scholar 

  • Chappell, J., & Kacelnik, A. (2002). Tool selectivity in a non-primate species, the New Caledonian crow (Corvus moneduloides). Animal Cognition, 5, 71–78.

    PubMed  Google Scholar 

  • Chatterjee, A. (2010). Disemboying cognition. Language and Cognition, 2, 79–116.

    PubMed Central  PubMed  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • Clark, M. A., Merians, A. S., Kothari, A., Poizner, H., Macauley, B., Rothi, L. J. G., et al. (1994). Spatial planning deficits in limb apraxia. Brain, 117, 1093–1106.

    PubMed  Google Scholar 

  • Cooper, R. P. (2002). Order and disorder in everyday action: The roles of contention scheduling and supervisory attentional system. Neurocase, 8, 61–79.

    PubMed  Google Scholar 

  • Cooper, R. P., & Shallice, T. (2000). Contention scheduling and the control of routine activities. Cognitive Neuropsychology, 17, 297–338.

    CAS  PubMed  Google Scholar 

  • Cooper, R. P., & Shallice, T. (2006). Hierarchical schemas and goals in the control of sequential behavior. Psychological Review, 113, 887–916.

    PubMed  Google Scholar 

  • Cooper, R. P., Schwartz, M. F., Yule, P. G., & Shallice, T. (2005). The simulation of action disorganisation in complex activities of daily living. Cognitive Neuropsychology, 22, 959–1004.

    PubMed  Google Scholar 

  • Cubelli, R., Marchetti, C., Boscolo, G., & Della Sala, S. (2000). Cognition in action: Testing a model of limb apraxia. Brain and Cognition, 44, 144–165.

    CAS  PubMed  Google Scholar 

  • Daprati, E., & Sirigu, A. (2006). How we interact with objects: Learning from brain lesions. Trends in Cognitive Sciences, 10, 265–270.

    PubMed  Google Scholar 

  • De Renzi, E. (1989). Apraxia. In F. Boller & J. Grafman (Eds.), Handbook of neuropsychology (pp. 245–263). Amsterdam: Elsevier Science Publishers.

    Google Scholar 

  • De Renzi, E., & Lucchelli, F. (1988). Ideational apraxia. Brain, 111, 1173–1185.

    PubMed  Google Scholar 

  • De Renzi, E., Cavalleri, F., & Facchini, S. (1996). Imitation and utilisation behaviour. Journal of Neurology, Neurosurgery and Psychiatry, 61, 396–400.

    PubMed Central  PubMed  Google Scholar 

  • Decety, J., Jeannerod, M., & Prablanc, C. (1989). The timing of mentally represented actions. Behavioural Brain Research, 34, 35–42.

    CAS  PubMed  Google Scholar 

  • Duncan, J. (1986). Disorganisation of behaviour after frontal lobe damage. Cognitive Neuropsychology, 3, 271–290.

    Google Scholar 

  • Farnè, A., & Làdavas, E. (2000). Dynamic size-change of hand peripersonal space following tool use. NeuroReport, 11, 1645–1649.

    PubMed  Google Scholar 

  • Forde, E. M. E., & Humphreys, G. W. (2000). The role of semantic knowledge and working memory in everyday tasks. Brain and Cognition, 44, 214–252.

    CAS  PubMed  Google Scholar 

  • Frey, S. H. (2008). Tool use, communicative gesture and cerebral asymmetries in the modern human brain. Philosophical Transactions of the Royal Society of London B, 363, 1951–1957.

    Google Scholar 

  • Garcea, F. E., & Mahon, B. Z. (2012). What is a tool concept? Dissociating manipulation knowledge from function knowledge. Memory & Cognition, 40, 1303–1313.

    Google Scholar 

  • Gibson, J. J. (1979). The ecological approach to visual perception. Boston: Houghton-Mifflin Co.

    Google Scholar 

  • Gibson, K. R. (1993). Generative interplay between technical capacities, social relations, imitation and cognition. In K. R. Gibson & T. Ingold (Eds.), Tools, language and cognition in human evolution (pp. 251–269). New York: Cambridge University Press.

    Google Scholar 

  • Giovannetti, T., Britnell, P., Brennan, L., Siderowl, A., Grossman, M., Libon, D. J., et al. (2012). Everyday action impairment in Parkinson’s disease dementia. Journal of the International Neuropsychological Society, 18, 787–798.

    PubMed Central  PubMed  Google Scholar 

  • Goldenberg, G. (1995). Imitating gestures and manipulating a mannikin: The representation of the human body in ideomotor apraxia. Neuropsychologia, 33, 63–72.

    CAS  PubMed  Google Scholar 

  • Goldenberg, G. (1999). Matching and imitation of hand and finger postures in patients with damage in left or right hemisphere. Neuropsychologia, 37, 559–566.

    CAS  PubMed  Google Scholar 

  • Goldenberg, G. (2013a). Apraxia: The cognitive side of motor control. Oxford: Oxford University Press.

    Google Scholar 

  • Goldenberg, G. (2013b). Apraxia in left-handers. Brain, 136, 2592–2601.

    PubMed  Google Scholar 

  • Goldenberg, G., & Hagmann, S. (1998). Tool use and mechanical problem solving in apraxia. Neuropsychologia, 36, 581–589.

    CAS  PubMed  Google Scholar 

  • Goldenberg, G., & Spatt, J. (2009). The neural basis of tool use. Brain, 132, 1645–1655.

    CAS  PubMed  Google Scholar 

  • Goldenberg, G., Hartmann, K., & Schlott, I. (2003). Defective pantomime of object use in left brain damage: Apraxia or asymbolia? Neuropsychologia, 41, 1565–1573.

    PubMed  Google Scholar 

  • Goldenberg, G., Hentze, S., & Hermsdörfer, J. (2004). The effect of tactile feedback on pantomime of tool use in apraxia. Neurology, 63, 1863–1867.

    CAS  PubMed  Google Scholar 

  • Goldenberg, G., Hartmann-Schmid, K., Sürer, F., Daumüller, M., & Hermsdörfer, J. (2007). The impact of dysexecutive syndrome on use of tools and technical devices. Cortex, 43, 424–435.

    PubMed  Google Scholar 

  • Gredlein, J. M., & Bjorklund, D. F. (2005). Sex differences in young children’s use of tools in a problem-solving task. Human Nature, 16, 211–232.

    Google Scholar 

  • Greenwald, A. G. (1970). Sensory feedback mechanisms in performance control: With special reference to the ideomotor mechanism. Psychological Review, 77, 73–99.

    CAS  PubMed  Google Scholar 

  • Gruber, T., Clay, Z., & Zuberbühler, K. (2010). A comparison of bonobo and chimpanzee tool use: Evidence for a female bias in the Pan lineage. Animal Behaviour, 80, 1023–1033.

    Google Scholar 

  • Hartmann, K., Goldenberg, G., Daumüller, M., & Hermsdörfer, J. (2005). It takes the whole brain to make a cup of coffee: The neuropsychology of naturalistic actions involving technical devices. Neuropsychologia, 43, 625–627.

    PubMed  Google Scholar 

  • Heilman, K. M., Rothi, L. J., & Valenstein, E. (1982). Two forms of ideomotor apraxia. Neurology, 32, 342–346.

    CAS  PubMed  Google Scholar 

  • Heilman, K. M., Rothi, L. J. G., Mack, L., Feinberg, T., & Watson, R. T. (1986). Apraxia after superior parietal lesions. Cortex, 32, 141–150.

    Google Scholar 

  • Hermsdörfer, J., Hentze, S., & Goldenberg, G. (2006). Spatial and kinematic features of apraxic movement depend on the mode of execution. Neuropsychologia, 44, 1642–1652.

    PubMed  Google Scholar 

  • Hodges, J. R., Spatt, J., & Patterson, K. (1999). “What” and “how”: Evidence for the dissociation of object knowledge and mechanical problem-solving skills in the human brain. Proceeding of the National Academy of Sciences of the United States of America, 96, 9444–9448.

    CAS  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • Hommel, B., Müsseler, J., Aschersleben, G., & Prinz, W. (2001). The theory of event coding (TEC): A framework for perception and action planning. Behavioral and Brain Sciences, 24, 849–937.

    CAS  PubMed  Google Scholar 

  • Humphreys, G. W., & Forde, E. M. E. (1998). Disordered action schema and action disorganisation syndrome. Cognitive Neuropsychology, 15, 771–811.

    Google Scholar 

  • Iriki, A., Tanaka, M., & Iwamura, Y. (1996). Coding of modified body schema during tool use by macaque postcentral neurones. NeuroReport, 7, 2325–2330.

    CAS  PubMed  Google Scholar 

  • Jacobs, D. H., Adair, J. C., Williamson, D. J. G., Na, D. L., Gold, M., Foundas, A. L., et al. (1999). Apraxia and motor-skill acquisition in Alzheimer disease are dissociable. Neuropsychologia, 37, 875–880.

    CAS  PubMed  Google Scholar 

  • James, W. (2007). The principles of psychology. New York: Cosimo Classics (Original work published 1890)

  • Janczyk, M., Pfister, R., & Kunde, W. (2012). On the persistence of tool- based compatibility effects. Zeitschrift für Psychologie, 220, 16–22.

    Google Scholar 

  • Jarry, C., Osiurak, F., Delafuys, D., Chauviré, V., Etcharry-Bouyx, F., & Le Gall, D. (2013). Apraxia of tool use: More évidence for the technical reasoning hypothesis. Cortex, 49, 2322–2333.

    PubMed  Google Scholar 

  • Jax, S. A., & Buxbaum, L. J. (2010). Response interference between functional and structural actions linked to the same familiar object. Cognition, 115, 350–355.

    PubMed Central  PubMed  Google Scholar 

  • Jeannerod, M. (2001). Neural simulation of action: a unifying mechanism for motor cognition. NeuroImage, 14, 103–109.

    Google Scholar 

  • Johnson, S. L. (1981). Effect of training device on retention and transfer of a procedural task. Human Factors, 23, 257–272.

    Google Scholar 

  • Johnson-Frey, S. H. (2007). What puts the how in where? Tool use and the divided visual streams hypothesis. Cortex, 43, 368–375.

    Google Scholar 

  • Jonassen, D. H. (1992). What are cognitive tools? In P. A. M. Kommers, D. H. Jonassen, J. T. Mayes, & A. Ferreira (Eds.), Cognitive Tools for Learning (NATO ASI Series, pp. 1–6).

    Google Scholar 

  • Klatzky, R. L., & Lederman, S. J. (2002). Touch. In A. F. Healy & R. W. Proctor (Eds.), Experimental Psychology (pp. 147–176). New York: Wiley.

    Google Scholar 

  • Kool, W., McGuire, J. T., Rosen, Z. B., & Botvinick, M. M. (2010). Decision making and the avoidance of cognitive demand. Journal of Experimental Psychology: General, 139, 665–682.

    Google Scholar 

  • Kunde, W., Müsseler, J., & Heuer, H. (2007). Spatial compatibility effects with tool use. Human Factors, 49, 661–670.

    PubMed  Google Scholar 

  • Latash, M. L., Scholz, J. P., & Schöner, G. (2007). Toward a new theory of motor synergies. Motor Control, 11, 267–308.

    Google Scholar 

  • Lauro-Grotto, R., Piccini, C., & Shallice, T. (1997). Modality-specific operations in semantic dementia. Cortex, 33, 593–622.

    CAS  PubMed  Google Scholar 

  • Leakey, R. (1980). The making of Mankind. London: Book Club Associates.

    Google Scholar 

  • Lederman, S. J., & Klatzky, R. L. (1987). Hand movements: A window into haptic object recognition. Cognitive Psychology, 19, 342–368.

    CAS  PubMed  Google Scholar 

  • Leroi-Gourhan, A. (1971). L’Homme et la matière. Paris: Albin Michel.

    Google Scholar 

  • Lesourd, M., Le Gall, D., Baumard, J., Croisile, B., Jarry, C., & Osiurak, F. (2013). Apraxia and Alzheimer’s disease: Review and perspectives. Neuropsychology Review, 23, 234–256.

    PubMed  Google Scholar 

  • Lhermitte, F. (1983). Utilisation behaviour and its relation to lesions of the frontal lobes. Brain, 106, 237–255.

    PubMed  Google Scholar 

  • Lhermitte, F., Pillon, B., & Serdaru, M. (1986). Human autonomy and the frontal lobes. Part I: Imitation and utilization behavior: A neuropsychological study of 75 patients. Annals of Neurology, 19, 326–334.

    CAS  PubMed  Google Scholar 

  • Limongelli, L., Boysen, S. T., & Visalberghi, E. (1995). Comprehension of cause-effect relations in a tool-using task by chimpanzees (Pan troglodytes). Journal of Comparative Psychology, 109, 18–26.

    CAS  PubMed  Google Scholar 

  • Lonsdorf, E. V. (2005). Sex differences in the development of termite-fishing skills in the wild chimpanzees, Pan troglodytes schweinfurthii, of Gombe National Park, Tanzania. Animal Behaviour, 70, 673–683.

    Google Scholar 

  • Macuga, K. L., Papailiou, A. P., & Frey, S. H. (2012). Motor imagery of tool use: Relationship to actual use and adherence to Fitts’ law across tasks. Experimental Brain Research, 218, 169–174.

    PubMed Central  PubMed  Google Scholar 

  • Mahon, B. Z., & Caramazza, A. (2008). A critical look at the embodied cognition hypothesis and a new proposal for grounding conceptual content. Journal of Physiology, 102, 59–70.

    PubMed  Google Scholar 

  • Mahon, B. Z., & Caramazza, A. (2009). Concepts and categories: A cognitive neuropsychological perspective. Annual Review of Psychology, 60, 27–51.

    PubMed Central  PubMed  Google Scholar 

  • Maravita, A., & Iriki, A. (2004). Tools for the body (schema). Trends in Cognitive Sciences, 8, 79–86.

    PubMed  Google Scholar 

  • Martin-Ordas, G., Call, J., & Colmenares, F. (2008). Tubes, tables and traps: Great apes solve two functionally equivalent trap tasks but show no evidence of transfer across tasks. Animal Cognition, 11, 423–430.

    PubMed Central  PubMed  Google Scholar 

  • Massen, C. (2013). Cognitive representations of tool-use interactions. New Ideas in Psychology, 31, 239–246.

    Google Scholar 

  • Massen, C., & Prinz, W. (2007). Programming tool-use actions. Journal of Experimental Psychology: Human Perception and Performance, 33, 692–704.

    PubMed  Google Scholar 

  • Massen, C., & Prinz, W. (2009). Movements, actions and tool-use actions: An ideomotor approach to imitation. Philosophical Transactions of the Royal Society B, 364, 2349–2358.

    Google Scholar 

  • McGrew, W. C. (1992). Chimpanzee material culture: Implications for human evolution. Cambridge: Cambridge University Press.

    Google Scholar 

  • Milner, A. D., & Goodale, M. A. (2006). The visual brain in action. Oxford: Oxford University Press.

    Google Scholar 

  • Morady, K., & Humphreys, G. (2011). Multiple tasks demands in action disorganization syndrome. Neurocase, 17, 461–472.

    PubMed  Google Scholar 

  • 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.

    Google Scholar 

  • Mounoud, P. (1996). A recursive transformation of central cognitive mechanisms: The shift from partial to whole representation. In A. J. Sameroff & M. M. Haith (Eds.), The five to seven year shift: the age of reason and responsibility (pp. 85–110). Chicago: Chicago University Press.

    Google Scholar 

  • Negri, G. A., Lunardelli, A., Reverberi, C., Gigli, G. L., & Rumiati, R. I. (2007a). Degraded semantic knowledge and accurate object use. Cortex, 43, 376–388.

    PubMed  Google Scholar 

  • Negri, G. A. L., Rumiati, R. I., Zadini, A., Ukmar, M., Mahon, B. Z., & Caramazza, A. (2007b). What is the role of motor stimulation in action and object recognition? Evidence from apraxia. Cognitive Neuropsychology, 24, 795–816.

    PubMed  Google Scholar 

  • Nonaka, T. (2013). Motor variability but functional specificity: The case of a C4 tetraplegic mouth calligrapher. Ecological Psychology, 25, 131–154.

    Google Scholar 

  • Norman, D. A. (1981). Categorization of action slips. Psychological Review, 88, 1–14.

    Google Scholar 

  • Norman, D. A., & Shallice, T. (1986). Attention to action: Willed and automatic control of behavior. In R. Davidson, G. Schwartz, & D. Shapiro (Eds.), Consciousness and self-regulation: Advances in research and theory (pp. 1–18). New York: Plenum Press.

    Google Scholar 

  • Osiurak, F. (2013). Apraxia of tool use is not a matter of affordances. Frontiers in Human Neuroscience, 7, 890.

    PubMed Central  PubMed  Google Scholar 

  • Osiurak, F., & Badets, A. (2014). Pliers, not fingers. Tool-action effect in a motor intention paradigm. Cognition, 130, 66–73.

    Google Scholar 

  • Osiurak, F., Aubin, G., Allain, P., Jarry, C., Richard, I., & Le Gall, D. (2008a). Object usage and object utilization. A single-case study. Neurocase, 14, 169–183.

    Google Scholar 

  • Osiurak, F., Aubin, G., Allain, P., Jarry, C., Etcharry-Bouyx, F., Richard, I., et al. (2008b). Different constraints on grip selection in brain-damaged patients. Object use versus object transport. Neuropsychologia, 46, 2431–2434.

    Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • Osiurak, F., Jarry, C., & Le Gall, D. (2011). Re-examining the gesture engram hypothesis. New perspectives on apraxia of tool use. Neuropsychologia, 49, 299–312.

    Google Scholar 

  • Osiurak, F., Jarry, C., Baltenneck, N., Boudin, B., & Le Gall, D. (2012a). Make a gesture and I will tell you what you are miming. Pantomime recognition in healthy subjects. Cortex, 48, 584–592.

    Google Scholar 

  • Osiurak, F., Morgado, N., & Palluel-Germain, R. (2012b). Tool use and perceived distance. When unreachable becomes sponatenously reachable. Experimental Brain Research, 218, 331–339.

    PubMed  Google Scholar 

  • Osiurak, F., Jarry, C., Lesourd, M., Baumard, J., & Le Gall, D. (2013a). Mechanical problem-solving in left brain-damaged patients. Neuropsychologia, 51, 1964–1972.

    PubMed  Google Scholar 

  • Osiurak, F., Roche, K., Ramone, J., & Chainay, H. (2013b). Handing a tool to someone can take more time than using it. Cognition, 128, 76–81.

    PubMed  Google Scholar 

  • Osiurak, F., Wagner, C., Djerbi, S., & Navarro, J. (2013c). Why do we use automatic tools? The priority of control over effort. Experimental Psychology, 60, 453–468.

    PubMed  Google Scholar 

  • Osiurak, F., Morgado, N., Vallet, G., Drot, M., & Palluel-Germain, R. (2014). Getting a tool gives wings: Underestimation of effort for tool use. Psychological Research, 78, 1–9.

    PubMed  Google Scholar 

  • Pascual-Leone, A., Grafman, J., Clark, K., Stewart, M., Massaquoi, S., Lou, J.-S., et al. (1993). Procedural learning in Parkinson’s disease and cerebellar degeneration. Annuals of Neurology, 34, 594–602.

    CAS  Google Scholar 

  • Penfield, W., & Evans, J. (1935). The frontal lobe in man: A clinical study of maximum removals. Brain, 58, 115–133.

    Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • Pezzulo, G., Barsalou, L. W., Cangelosi, A., Fischer, M. H., McRae, K., & Spivey, M. J. (2011). The mechanics of embodiment: A dialog on embodiment and computational modeling. Frontiers in Psychology, 2, 5.

    PubMed Central  PubMed  Google Scholar 

  • Pezzulo, G., Barsalou, L. W., Cangelosi, A., Fischer, M. H., McRae, K., & Spivey, M. J. (2013). Computational grounded cognition: A new alliance between grounded cognition and computational modeling. Frontiers in Psychology, 3, 612.

    PubMed Central  PubMed  Google Scholar 

  • Phillips, J. C., & Ward, R. (2002). S-R correspondence effects of irrelevant visual affordance: time course and specificity of response activation. Visual Cognition, 9, 540–558.

    Google Scholar 

  • Povinelli, D. J. (2000). Folk physics for apes. New York: Oxford University Press.

    Google Scholar 

  • Prinz, W. (1997). Perception and action planning. European Journal of Cognitive Psychology, 9, 129–154.

    Google Scholar 

  • Proffitt, D. R. (2006). Embodied perception and the economy of action. Perspectives in Psychological Science, 1, 110–122.

    Google Scholar 

  • Proffitt, D. R., Stefanucci, J., Banton, T., & Epstein, W. (2003). The role of effort in distance perception. Psychological Science, 14, 409–428.

    Google Scholar 

  • Reason, J. T. (1979). Actions not as planned: The price of automatization. In G. Underwood & R. Stevens (Eds.), Aspects of consciousness (pp. 67–89). London: London Academic Press.

    Google Scholar 

  • Rieger, M. (2004). Automatic keypress activation in skilled typing. Journal of Experimental Psychology: Human Perception and Performance, 30, 555–565.

    PubMed  Google Scholar 

  • Rieger, M., & Massen, C. (2014). Tool characteristics in imagery of tool actions. Psychological Research, 78, 10–17.

    PubMed  Google Scholar 

  • Rizzolatti, G., & Craighero, L. (2004). The mirror neuron system. Annual Review of Neuroscience, 27, 169–192.

    CAS  PubMed  Google Scholar 

  • Rosenbaum, D. A. (2008). Reaching while walking: Reaching distance costs more than walking distance. Psychonomic Bulletin & review, 15, 1100–1104.

    Google Scholar 

  • Rosenbaum, D. A., Marchak, F., Barnes, H. J., Vaughan, J., Slotta, J., & Jorgensen, M. (1990). Constraints for action selection: Overhand versus underhand grips. In M. Jeannerod (Ed.), Attention and performance XIII (pp. 321–342). Hillsdale: Erlbaum.

    Google Scholar 

  • Rosenbaum, D. A., Vaughan, J., Barnes, H. J., & Jorgensen, M. J. (1992). Time course of movement planning: Selection of handgrips for object manipulation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 18, 1058–1073.

    CAS  PubMed  Google Scholar 

  • Rosenbaum, D. A., Meulenbroek, R. J., Vaughan, J., & Jansen, C. (2001). Posture-based motion planning: Applications to grasping. Psychological Review, 108, 709–734.

    CAS  PubMed  Google Scholar 

  • Rothi, L. J. G., Ochipa, C., & Heilman, K. M. (1991). A cognitive neuropsychological model of limb praxis. Cognitive Neuropsychology, 8, 443–458.

    Google Scholar 

  • Roy, E. A., & Square, P. A. (1985). Common considerations in the study of limb, verbal and oral apraxia. In E. A. Roy (Ed.), Neuropsychological studies of apraxia and related disorders (pp. 111–161). Amsterdam: Elsevier.

    Google Scholar 

  • Rumelhart, D. E., Smolensky, P., McClelland, J. L., & Hinton, G. E. (1986). Schemata and sequential thought processes in PDP models. In J. L. McClelland & D. E. Rumelhart (Eds.), Parallel distributed processing: Explorations in the microstructure of cognition (pp. 7–57). Cambridge: MIT Press.

    Google Scholar 

  • Santos, L. R., Pearson, H. M., Spaepen, G. M., Tsao, F., & Hauser, M. (2006). Probing the limits of tool competence: Experiments with two non-tool-using species (Cercopithecus aethiops and Saguinus oedipus). Animal Cognition, 9, 94–109.

    PubMed  Google Scholar 

  • Schwartz, M. F. (1995). Re-examining the role of executive functions in routine action production. Annals of the New York Academy of Science, 769, 321–335.

    CAS  Google Scholar 

  • Schwartz, M. F., Reed, E. S., Montgomery, M. W., Palmer, C., & Mayer, N. H. (1991). The quantitative description of action disorganisation after brain damage: A case study. Cognitive Neuropsychology, 8, 381–414.

    Google Scholar 

  • Schwartz, M. F., Montgomery, M. W., Buxbaum, L. J., Lee, S. S., Carew, T. G., Coslett, H. B., et al. (1998). Naturalistic action impairment in closed head injury. Neuropsychology, 12, 13–28.

    CAS  PubMed  Google Scholar 

  • Schwartz, M. F., Segal, M., Veramonti, T., Ferraro, M., & Buxbaum, L. J. (2002). The naturalistic action test: A standardized assessment for everyday action impairment. Neuropsychological Rehabilitation, 12, 311–339.

    Google Scholar 

  • Shallice, T., & Burgess, P. W. (1991). Deficits in strategy application following frontal lobe damage in man. Brain, 114, 727–741.

    PubMed  Google Scholar 

  • Shallice, T., Burgess, P. W., Schon, F., & Baxter, D. M. (1989). The origins of utilisation behaviour. Brain, 112, 1587–1598.

    PubMed  Google Scholar 

  • Shaw, R. (2003). The agent-environment interface: Simon’s indirect or Gibson’s direct coupling. Ecological Psychology, 15, 37–106.

    Google Scholar 

  • Shaw, R., Turvey, M. T., & Mace, W. (1982). Ecological psychology: The consequence of a commitment to realism. In W. Weimer & D. Palermo (Eds.), Cognition and the symbolic process (pp. 159–226). Hillsdale: Lawrence Erlbaum Associates.

    Google Scholar 

  • Silveri, M. C., & Ciccarelli, N. (2009). Semantic memory in object use. Neuropsychologia, 47, 2634–2641.

    PubMed  Google Scholar 

  • Singh, D. (1970). Preference for bar pressing to obtain reward over freeloading in rats and children. Journal of Comparative and Physiological Psychology, 73, 320–327.

    Google Scholar 

  • Sirigu, A., Duhamel, J.-R., & Poncet, M. (1991). The role of sensorimotor experience in object recognition. Brain, 114, 2555–2573.

    PubMed  Google Scholar 

  • Solomon, R. L. (1948). The influence of work on behavior. Psychological Bulletin, 45, 1–40.

    CAS  PubMed  Google Scholar 

  • Solway, A., & Botvinick, M. M. (2012). Goal-directed decision making as probabilistic inference: A computational framework and potential neural correlates. Psychological Review, 119, 120–154.

    PubMed Central  PubMed  Google Scholar 

  • Spatt, J., Bak, T., Bozeat, S., Patterson, K., & Hodges, J. R. (2002). Apraxia, mechanical problem solving and semantic knowledge: Contributions to object usage in corticobasal degeneration. Journal of Neurology, 249, 601–608.

    PubMed  Google Scholar 

  • Symes, E., Ellis, R., & Tucker, M. (2005). Dissociating object-based and space-based affordances. Visual Cognition, 12, 1337–1361.

    Google Scholar 

  • Tarte, R. D. (1981). Contrafreeloading in humans. Psychological Reports, 49, 859–866.

    Google Scholar 

  • 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 & BioBehavioral Reviews, 37, 491–521.

    Google Scholar 

  • Tipper, S. P., Paul, M. A., & Hayes, A. E. (2006). Vision-for-action: the effects of object property discrimination and action state on affordance compatibility effects. Psychonomic Bulletin & Review, 13, 493–498.

    Google Scholar 

  • Tolman, E. C. (1949). The nature and functioning of wants. Psychological Review, 56, 357–369.

    CAS  PubMed  Google Scholar 

  • Tomasello, M. (1999). The human adaptation for culture. Annual Review of Anthropology, 28, 509–529.

    Google Scholar 

  • 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.

    CAS  PubMed  Google Scholar 

  • Tulving, E. (1972). Episodic and semantic memory. In E. Tulving & W. Donaldson (Eds.), Organization of memory (pp. 381–403). New York: New York Academic Press.

    Google Scholar 

  • Tulving, E. (1985). Memory and consciousness. Canadian Psychology, 25, 1–12.

    Google Scholar 

  • Turvey, M. T. (1996). Dynamic Touch. American Psychologist, 51, 1134–1152.

    CAS  PubMed  Google Scholar 

  • Vaesen, K. (2012). The cognitive bases of human tool use. Behavioral and Brain Sciences, 35, 203–218.

    PubMed  Google Scholar 

  • Valyear, K. F., Chapman, C. S., Gallivan, J. P., Mark, R. S., & Culham, J. C. (2011). To use or to move: Goal-set modulates priming when grasping real tools. Experimental Brain Research, 212, 125–142.

    PubMed  Google Scholar 

  • van der Steen, M. C., & Bongers, R. M. (2011). Joint angle variability and co-variation in a reaching with a rod task. Experimental Brain Research, 208, 411–422.

    PubMed  Google Scholar 

  • van Schaik, C. P., Deaner, R. O., & Merrill, M. Y. (1999). The conditions for tool use in primates: Implications for the evolution of material culture. Journal of Human Evolution, 36, 19–41.

    Google Scholar 

  • Vingerhoets, G., Vandamme, K., & Vercammen, A. (2009). Conceptual and physical object qualities contribute differently to motor affordances. Brain and Cognition, 69, 481–489.

    CAS  PubMed  Google Scholar 

  • Vingerhoets, G., Acke, F., Alderweireldt, A. S., Nys, J., Vandemaele, P., & Achten, E. (2012). Cerebral lateralization of praxis in right- and left-handedness: Same pattern, different strength. Human Brain Mapping, 33, 763–777.

    PubMed  Google Scholar 

  • Vingerhoets, G., Alderweireldt, A. S., Vandemaele, P., Cai, Q., van der Haegen, L., Brysbaert, M., et al. (2013). Praxis and language are linked: Evidence from co-lateralization in individuals with atypical language dominance. Cortex, 49, 172–183.

    PubMed  Google Scholar 

  • Visalberghi, E., & Limongelli, L. (1994). Lack of comprehension of cause-effect relations in tool-using capuchin monkeys (Cebus apella). Journal of Comparative Psychology, 108, 15–22.

    CAS  PubMed  Google Scholar 

  • Visalberghi, E., & Trinca, L. (1989). Tool use in capuchin monkeys: Distinguishing between performing and understanding. Primates, 30, 511–521.

    Google Scholar 

  • Vygotsky, L. (1978). Mind in society: The development of higher psychological processes. Boston: Harvard University Press.

    Google Scholar 

  • Wagman, J. B., & Abney, D. H. (2012). Transfer of recalibration from audition to touch: Modality independence as a special case of anatomical independence. Journal of Experimental Psychology: Human Perception and Performance, 38, 589–602.

    PubMed  Google Scholar 

  • Wagman, J. B., & Carello, C. (2001). Affordances and inertial constraints on tool use. Ecological Psychology, 13, 173–195.

    Google Scholar 

  • Wagman, J. B., & Carello, C. (2003). Haptically creating affordances: The user-tool interface. Journal of Experimental Psychology: Applied, 3, 175–186.

    Google Scholar 

  • Warrington, E. K. (1975). The selective impairment of semantic memory. Quarterly Journal of Experimental Psychology, 27, 635–657.

    CAS  PubMed  Google Scholar 

  • Waters, R. H. (1937). The principle of least effort in learning. Journal of General Psychology, 16, 3–20.

    Google Scholar 

  • Witt, J. K. (2011a). Action’s effect on perception. Current Directions in Psychological Science, 20, 201–206.

    Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • 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.

    PubMed Central  PubMed  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • Wolpert, D. M., Ghahramani, Z., & Jordan, M. I. (1995). An internal model for sensorimotor integration. Science, 269, 1880–1882.

    CAS  PubMed  Google Scholar 

  • Zadikoff, C., & Lang, A. E. (2005). Apraxia in movement disorders. Brain, 128, 1480–1497.

    PubMed  Google Scholar 

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Acknowledgments

This work was supported by grants from ANR (Agence Nationale pour la Recherche; Project Démences et Utilisation d’Outils/Dementia and Tool Use, N°ANR 2011 MALZ 006 03), and 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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    François Osiurak

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Osiurak, F. What Neuropsychology Tells us About Human Tool Use? The Four Constraints Theory (4CT): Mechanics, Space, Time, and Effort. Neuropsychol Rev 24, 88–115 (2014). https://doi.org/10.1007/s11065-014-9260-y

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