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Novel Tool Selection in Left Brain-Damaged Patients With Apraxia of Tool Use: A Study of Three Cases

Published online by Cambridge University Press:  26 December 2017

François Osiurak*
Affiliation:
Laboratoire d’Etude des Mécanismes Cognitifs (EA 3082), Université de Lyon, France Institut Universitaire de France, Paris, France
Marine Granjon
Affiliation:
Laboratoire d’Etude des Mécanismes Cognitifs (EA 3082), Université de Lyon, France
Isabelle Bonnevie
Affiliation:
Laboratoire d’Etude des Mécanismes Cognitifs (EA 3082), Université de Lyon, France
Joël Brogniart
Affiliation:
Laboratoire d’Etude des Mécanismes Cognitifs (EA 3082), Université de Lyon, France
Laura Mechtouff
Affiliation:
Unité de Neurologie Vasculaire, Hospices Civils de Lyon, Lyon, France
Amandine Benoit
Affiliation:
Unité de Neurologie Vasculaire, Hospices Civils de Lyon, Lyon, France
Norbert Nighoghossian
Affiliation:
Unité de Neurologie Vasculaire, Hospices Civils de Lyon, Lyon, France
Mathieu Lesourd
Affiliation:
Laboratoire d’Etude des Mécanismes Cognitifs (EA 3082), Université de Lyon, France
*
Correspondence and reprint requests to: François Osiurak, Laboratoire d’Etude des Mécanismes Cognitifs (EA 3082), Institut de Psychologie, 5, avenue Pierre Mendès-France, 69676 Bron Cedex, France. E-mail: [email protected]

Abstract

Objectives: Recent evidence indicates that some left brain-damaged (LBD) patients have difficulties to use familiar tools because of the inability to reason about physical object properties. A fundamental issue is to understand the residual capacity of those LBD patients in tool selection. Methods: Three LBD patients with tool use disorders, three right brain-damaged (RBD) patients, and six matched healthy controls performed a novel tool selection task, consisting in extracting a target out from a box by selecting the relevant tool among eight, four, or two tools. Three criteria were manipulated to make relevant and irrelevant tools (size, rigidity, shape). Results: LBD patients selected a greater number of irrelevant tools and had more difficulties to solve the task compared to RBD patients and controls. All participants committed more errors for selecting relevant tools based on rigidity and shape than size. In some LBD patients, the difficulties persisted even in the 2-Choice condition. Conclusions: Our findings confirm that tool use disorders result from impaired technical reasoning, leading patients to meet difficulties in selecting tools based on their physical properties. We also go further by showing that these difficulties can decrease as the choice is reduced, at least for some properties, opening new avenues for rehabilitation programs. (JINS, 2018, 24, 524–529)

Type
Brief Communication
Copyright
Copyright © The International Neuropsychological Society 2017 

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References

REFERENCES

Baumard, J., Osiurak, F., Lesourd, M., & Le Gall, D. (2014). Tool use disorders after left brain damage. Frontiers in Psychology, 5, 473.Google Scholar
Baumard, J., Lesourd, M., Jarry, C., Merck, C., Etcharry-Bouyx, F., Chauviré, V., & Le Gall, D. (2016). Tool use disorders in neurodegenerative diseases: Roles of semantic memory and technical reasoning. Cortex, 52, 119132.Google Scholar
Goldenberg, G. (2013). Apraxia: The cognitive side of motor control. Oxford: Oxford University Press.Google Scholar
Goldenberg, G., Daumüller, M., & Hagmann, S. (2001). Assessment of therapy of complex activities of daily living in apraxia. Neuropsychological Rehabilitation, 11, 147169.CrossRefGoogle Scholar
Goldenberg, G., & Hagmann, S. (1998a). Therapy of activities of daily living in patients with apraxia. Neuropsychological Rehabilitation, 8, 123141.Google Scholar
Goldenberg, G., & Hagmann, S. (1998b). Tool use and mechanical problem solving in apraxia. Neuropsychologia, 36, 581589.Google Scholar
Goldenberg, G., & Spatt, J. (2009). The neural basis of tool use. Brain, 132, 16451655.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, 625627.Google Scholar
Heilman, K.M., Maher, L.M., Greenwald, M.L., & Rothi, L.J.G. (1997). Conceptual apraxia from lateralized lesions. Neurology, 49, 457464.Google Scholar
Heilman, K.M., Rothi, L.J., & Valenstein, E. (1982). Two forms of ideomotor apraxia. Neurology, 32, 342346.Google Scholar
Heilman, K.M., & Watson, R.T. (2008). The disconnection apraxias. Cortex, 44, 975982.Google Scholar
Jarry, C., Osiurak, F., Delafuys, D., Chauviré, V., Etcharry-Bouyx, F., & Le Gall, D. (2013). Apraxia of tool use: More evidence for the technical reasoning hypothesis. Cortex, 49, 23222333.Google Scholar
Lesourd, M., Baumard, J., Jarry, C., Etcharry-Bouyx, F., Belliard, S., Moreaud, O., & Osiurak, F. (2016). Mechanical problem-solving strategies in Alzheimer’s disease and semantic dementia. Neuropsychology, 30, 612623.Google Scholar
Osiurak, F. (2014). What neuropsychology tells us about human tool use? The four constraints theory (4CT): Mechanics, space, time, and effort. Neuropsychology Review, 24, 88115.CrossRefGoogle ScholarPubMed
Osiurak, F., & Badets, A. (2016). Tool use and affordance: Manipulation-based versus reasoning-based approaches. Psychological Review, 123, 534568.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, 517540.Google Scholar
Osiurak, F., Jarry, C., Lesourd, M., Baumard, J., & Le Gall, D. (2013). Mechanical problem-solving in left brain-damaged patients and apraxia of tool use. Neuropsychologia, 51, 19641972.Google Scholar
Reynaud, E., Lesourd, M., Navarro, J., & Osiurak, F. (2016). On the neurocognitive origins of human tool use. A critical review of neuroimaging data. Neuroscience & BioBehavioral Reviews, 64, 421437.CrossRefGoogle ScholarPubMed
Rothi, L.J.G., Ochipa, C., & Heilman, K.M. (1991). A cognitive neuropsychological model of limb praxis. Cognitive Neuropsychology, 8, 443458.Google Scholar
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, 220250.Google Scholar