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The Intentional Attunement Hypothesis The Mirror Neuron System and Its Role in Interpersonal Relations

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Biomimetic Neural Learning for Intelligent Robots

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3575))

Abstract

Neuroscientific research has unveiled neural mechanisms mediating between the personal experiential knowledge we hold of our lived body, and the implicit certainties we simultaneously hold about others. Such personal, body-related experiential knowledge enables our intentional attunement with others, which in turn constitutes a shared manifold of intersubjectivity. This we-centric space allows us to personally characterize and provide experiential understanding to the actions performed by others, and the emotions and sensations they experience. A direct form of “experiential understanding” is achieved by modeling the behavior of other individuals as intentional experience on the basis of the equivalence between what the others do and feel and what we do and feel. This parsimonious modeling mechanism is embodied simulation. The mirror neuron system is likely a neural correlate of this mechanism. This account shades some light on too often sidelined aspects of social cognition. More generally, it emphasizes the role played in cognition by neural sensory-motor integration.

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Author information

Authors and Affiliations

  1. Dept.of Neuroscience, University of Parma, via Volturno, 39, I-43100, Parma, ITALY

    Vittorio Gallese

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  1. Vittorio Gallese
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Editors and Affiliations

  1. University of Sunderland, SR6 0DD, Sunderland, United Kingdom

    Stefan Wermter

  2. Institute of Neural Information Processing, University of Ulm, D-89069, Ulm, Germany

    GĂĽnther Palm

  3. Hybrid Intelligent Systems, SCAT, University of Sunderland, UK

    Mark Elshaw

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Gallese, V. (2005). The Intentional Attunement Hypothesis The Mirror Neuron System and Its Role in Interpersonal Relations. In: Wermter, S., Palm, G., Elshaw, M. (eds) Biomimetic Neural Learning for Intelligent Robots. Lecture Notes in Computer Science(), vol 3575. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11521082_2

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  • DOI: https://doi.org/10.1007/11521082_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-27440-7

  • Online ISBN: 978-3-540-31896-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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