Neural decoding of reference frames during a tool sensing experiment

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The usage of a tool has been a phenomenon that has been occurring since the existence of humanity. When holding a stick the brain sees this stick as a bodily extension. Not only motor aspects but also sensory aspects play a role in how the brain embodies a tool. Tool-based reference frames tell us about the location in the brain where the information of this embodiment is processed. Machine learning methods can be used to predict these reference frames and are convenient when investigating the exact moment of when we start seeing evidence for these tool-based reference frames. During an EEG experiment the brain response of hitting an object with a tool and making a decision where this object was in space was measured. The data of the brain response was fed to a support vector machine that tried to classify the different hit locations. Significant results were found providing evidence for components such as N140 and P250. The research done in this tool sensing field could help adding information on how to restore perception on touch in proprioceptively deafferented patients. This design could then, in the long run, be implemented in prosthetics.
Faculteit der Sociale Wetenschappen