Title

Exploiting Multiple Sensory Modalities in Brain-Machine Interfaces

Document Type

Article

Language

eng

Publication Date

11-2009

Publisher

Elsevier

Source Publication

Neural Networks

Source ISSN

0893-6080

Abstract

Recent improvements in cortically-controlled brain-machine interfaces (BMIs) have raised hopes that such technologies may improve the quality of life of severely motor-disabled patients. However, current generation BMIs do not perform up to their potential due to the neglect of the full range of sensory feedback in their strategies for training and control. Here we confirm that neurons in the primary motor cortex (MI) encode sensory information and demonstrate a significant heterogeneity in their responses with respect to the type of sensory modality available to the subject about a reaching task. We further show using mutual information and directional tuning analyses that the presence of multi-sensory feedback (i.e. vision and proprioception) during replay of movements evokes neural responses in MI that are almost indistinguishable from those responses measured during overt movement. Finally, we suggest how these playback-evoked responses may be used to improve BMI performance.

Comments

Neural Networks, Vol. 22, No. 9 (November 2009): 1224-1234. DOI.

Aaron Suminski was affiliated with University of Chicago at the time of publication.

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