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Interfacing With the Computational Brain

Lookup NU author(s): Professor Andrew Jackson


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Neuroscience is just beginning to understand the neural computations that underlie our remarkable capacity to learn new motor tasks. Studies of natural movements have emphasized the importance of concepts such as dimensionality reduction within hierarchical levels of redundancy, optimization of behavior in the presence of sensorimotor noise and internal models for predictive control. These concepts also provide a framework for understanding the improvements in performance seen in myoelectric-controlled interface and brain-machine interface paradigms. Recent experiments reveal how volitional activity in the motor system combines with sensory feedback to shape neural representations and drives adaptation of behavior. By elucidating these mechanisms, a new generation of intelligent interfaces can be designed to exploit neural plasticity and restore function after neurological injury.

Publication metadata

Author(s): Jackson A, Fetz EE

Publication type: Article

Publication status: Published

Journal: IEEE Transactions on Neural Systems and Rehabilitation Engineering

Year: 2011

Volume: 19

Issue: 5

Pages: 534-541

Print publication date: 09/06/2011

ISSN (print): 1534-4320

ISSN (electronic): 1558-0210

Publisher: IEEE


DOI: 10.1109/TNSRE.2011.2158586


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Funder referenceFunder name
Christopher and Dana Reeve Foundation
Life Sciences Discovery Fund
National Institutes of Health (NIH)
086561Wellcome Trust