Theoretical Perspective on an Ideomotor Brain-Computer Interface: Toward a Naturalistic and Non-invasive Brain-Computer Interface Paradigm Based on Action-Effect Representation

Recent years have been marked by the fulgurant expansion of non-invasive Brain-Computer Interface (BCI) devices and applications in various contexts (medical, industrial etc.). This technology allows agents “to directly act with thoughts,” bypassing the peripheral motor system. Interestingly, it is...

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Vydáno v:Frontiers in human neuroscience Ročník 15; s. 732764
Hlavní autoři: Le Bars, Solène, Chokron, Sylvie, Balp, Rodrigo, Douibi, Khalida, Waszak, Florian
Médium: Journal Article
Jazyk:angličtina
Vydáno: Lausanne Frontiers Research Foundation 28.10.2021
Frontiers
Frontiers Media S.A
Témata:
action-effect prediction
Artificial intelligence
Brain
Cognitive science
Computer applications
Human influences
Human Neuroscience
human voluntary action
ideomotor
Implants
intention decoding
Interfaces
Medical imaging
non-invasive brain-computer interface
Paradigms
ISSN:1662-5161, 1662-5161
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Abstract Recent years have been marked by the fulgurant expansion of non-invasive Brain-Computer Interface (BCI) devices and applications in various contexts (medical, industrial etc.). This technology allows agents “to directly act with thoughts,” bypassing the peripheral motor system. Interestingly, it is worth noting that typical non-invasive BCI paradigms remain distant from neuroscientific models of human voluntary action. Notably, bidirectional links between action and perception are constantly ignored in BCI experiments. In the current perspective article, we proposed an innovative BCI paradigm that is directly inspired by the ideomotor principle, which postulates that voluntary actions are driven by the anticipated representation of forthcoming perceptual effects. We believe that (1) adapting BCI paradigms could allow simple action-effect bindings and consequently action-effect predictions and (2) using neural underpinnings of those action-effect predictions as features of interest in AI methods, could lead to more accurate and naturalistic BCI-mediated actions.
AbstractList Recent years have been marked by the fulgurant expansion of non-invasive Brain-Computer Interface (BCI) devices and applications in various contexts (medical, industrial etc.). This technology allows agents “to directly act with thoughts”, bypassing the peripheral motor system. Interestingly, it is worth noting that typical non-invasive BCI paradigms remain distant from neuroscientific models of human voluntary action. Notably, bidirectional links between action and perception are constantly ignored in BCI experiments. In the current perspective article, we proposed an innovative BCI paradigm that is directly inspired by the ideomotor principle, which postulates that voluntary actions are driven by the anticipated representation of forthcoming perceptual effects. We believe that (1) adapting BCI paradigms could allow simple action-effect bindings and consequently action-effect predictions and (2) using neural underpinnings of those action-effect predictions as features of interest in AI methods, could lead to more accurate and naturalistic BCI-mediated actions.
Recent years have been marked by the fulgurant expansion of non-invasive Brain-Computer Interface (BCI) devices and applications in various contexts (medical, industrial etc.). This technology allows agents "to directly act with thoughts," bypassing the peripheral motor system. Interestingly, it is worth noting that typical non-invasive BCI paradigms remain distant from neuroscientific models of human voluntary action. Notably, bidirectional links between action and perception are constantly ignored in BCI experiments. In the current perspective article, we proposed an innovative BCI paradigm that is directly inspired by the ideomotor principle, which postulates that voluntary actions are driven by the anticipated representation of forthcoming perceptual effects. We believe that (1) adapting BCI paradigms could allow simple action-effect bindings and consequently action-effect predictions and (2) using neural underpinnings of those action-effect predictions as features of interest in AI methods, could lead to more accurate and naturalistic BCI-mediated actions.Recent years have been marked by the fulgurant expansion of non-invasive Brain-Computer Interface (BCI) devices and applications in various contexts (medical, industrial etc.). This technology allows agents "to directly act with thoughts," bypassing the peripheral motor system. Interestingly, it is worth noting that typical non-invasive BCI paradigms remain distant from neuroscientific models of human voluntary action. Notably, bidirectional links between action and perception are constantly ignored in BCI experiments. In the current perspective article, we proposed an innovative BCI paradigm that is directly inspired by the ideomotor principle, which postulates that voluntary actions are driven by the anticipated representation of forthcoming perceptual effects. We believe that (1) adapting BCI paradigms could allow simple action-effect bindings and consequently action-effect predictions and (2) using neural underpinnings of those action-effect predictions as features of interest in AI methods, could lead to more accurate and naturalistic BCI-mediated actions.
Author Le Bars, Solène
Balp, Rodrigo
Waszak, Florian
Douibi, Khalida
Chokron, Sylvie
AuthorAffiliation 2 Université de Paris, INCC UMR 8002, CNRS , Paris , France
1 Altran Lab, Capgemini Engineering , Paris , France
3 Fondation Ophtalmologique Adolphe de Rothschild , Paris , France
AuthorAffiliation_xml – name: 2 Université de Paris, INCC UMR 8002, CNRS , Paris , France
– name: 3 Fondation Ophtalmologique Adolphe de Rothschild , Paris , France
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Copyright © 2021 Le Bars, Chokron, Balp, Douibi and Waszak. 2021 Le Bars, Chokron, Balp, Douibi and Waszak
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Snippet Recent years have been marked by the fulgurant expansion of non-invasive Brain-Computer Interface (BCI) devices and applications in various contexts (medical,...
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SubjectTerms action-effect prediction
Artificial intelligence
Brain
Cognitive science
Computer applications
Human influences
Human Neuroscience
human voluntary action
ideomotor
Implants
intention decoding
Interfaces
Medical imaging
non-invasive brain-computer interface
Paradigms
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Title Theoretical Perspective on an Ideomotor Brain-Computer Interface: Toward a Naturalistic and Non-invasive Brain-Computer Interface Paradigm Based on Action-Effect Representation
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