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Theoretical Perspective on an Ideomotor Brain-Computer Interface: Toward a Naturalistic and Non-invasive
Solène Le Bars1,2, Sylvie Chokron2,3, Rodrigo Balp1
1Altran Lab, Capgemini Engineering, Paris, France.
Frontiers in Human Neuroscience
|November 15, 2021
Summary
This study introduces a novel brain-computer interface (BCI) paradigm inspired by the ideomotor principle. By integrating action-effect predictions, this approach aims for more naturalistic BCI-mediated actions.
Area of Science:
- Neuroscience
- Human-Computer Interaction
- Artificial Intelligence
Background:
- Non-invasive Brain-Computer Interface (BCI) technology is rapidly expanding across medical and industrial fields.
- Current BCI paradigms often overlook the neuroscientific principles of voluntary action, particularly the bidirectional link between action and perception.
Purpose of the Study:
- To propose an innovative BCI paradigm based on the ideomotor principle.
- To enhance BCI accuracy and naturalism by incorporating action-effect prediction mechanisms.
Main Methods:
- The proposed paradigm is inspired by the ideomotor principle, where voluntary actions are driven by anticipated perceptual effects.
- It suggests adapting BCI paradigms to establish action-effect bindings and predictions.
- Utilizing neural underpinnings of these predictions as features for AI methods.
Main Results:
- The adaptation of BCI paradigms can facilitate simple action-effect bindings and subsequent predictions.
- Integrating neural data related to action-effect predictions can improve AI models for BCI control.
Conclusions:
- The ideomotor-inspired BCI paradigm offers a more neuroscientifically grounded approach to BCI design.
- This innovative approach has the potential to lead to more accurate and naturalistic BCI-mediated actions by leveraging predictive neural mechanisms.
