New Framework to Move Bi-Directional Brain-Computer Interfaces Out of the Laboratory

Outcome/Accomplishment

Brain-computer interfaces are poised to advance from the traditional goal of controlling prosthetic devices to combining neural decoding and encoding within a single neuroprosthetic device under a framework developed by researchers at the Center for Neurotechnology (CNT), an NSF-funded Engineering Research Center (ERC) at the University of Washington.

Impact/Benefits

This new way of thinking about the development of bi-directional brain-computer interfaces (BBCIs) opens the door to moving neural devices for engineering neural plasticity out of the laboratory and into real-world settings. BBCIs can be used for closed-loop control of prosthetic devices, reanimation of paralyzed limbs, restoration of sensorimotor and cognitive function, neuro-rehabilitation, enhancement of memory, and brain augmentation.

Explanation/Background

After a promising start in the 1960s, the field of brain-computer interfaces (BCIs) entered a lull of several decades. Spurred in the 1990s by the advent of multi-electrode recordings as well as fast and cheap computers, the field saw a resurgence of BCI study. Now researchers have begun to explore bi-directional BCIs which integrate decoding and encoding in a single system.

CNT Co-Director Rajesh Rao described the innovative conceptual framework for developing BBCIs in a 2019 paper. His framework uses a "co-processor" neural network and an "emulator" neural network to allow a BBCI to transform complex brain activity to appropriate stimulation patterns for re-animating paralyzed limbs and engineering neuroplasticity for rehabilitation.

Image

Location

Seattle, Washington

e-mail

website

Start Year

Biotechnology and Healthcare

Biotechnology and Health Care Icon
Biotechnology and Health Care Icon

Biotechnology and Healthcare

Lead Institution

University of Washington

Core Partners

MIT, San Diego University
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Outcome/Accomplishment

Brain-computer interfaces are poised to advance from the traditional goal of controlling prosthetic devices to combining neural decoding and encoding within a single neuroprosthetic device under a framework developed by researchers at the Center for Neurotechnology (CNT), an NSF-funded Engineering Research Center (ERC) at the University of Washington.

Location

Seattle, Washington

e-mail

website

Start Year

Biotechnology and Healthcare

Biotechnology and Health Care Icon
Biotechnology and Health Care Icon

Biotechnology and Healthcare

Lead Institution

University of Washington

Core Partners

MIT, San Diego University

Impact/benefits

This new way of thinking about the development of bi-directional brain-computer interfaces (BBCIs) opens the door to moving neural devices for engineering neural plasticity out of the laboratory and into real-world settings. BBCIs can be used for closed-loop control of prosthetic devices, reanimation of paralyzed limbs, restoration of sensorimotor and cognitive function, neuro-rehabilitation, enhancement of memory, and brain augmentation.

Explanation/Background

After a promising start in the 1960s, the field of brain-computer interfaces (BCIs) entered a lull of several decades. Spurred in the 1990s by the advent of multi-electrode recordings as well as fast and cheap computers, the field saw a resurgence of BCI study. Now researchers have begun to explore bi-directional BCIs which integrate decoding and encoding in a single system.

CNT Co-Director Rajesh Rao described the innovative conceptual framework for developing BBCIs in a 2019 paper. His framework uses a "co-processor" neural network and an "emulator" neural network to allow a BBCI to transform complex brain activity to appropriate stimulation patterns for re-animating paralyzed limbs and engineering neuroplasticity for rehabilitation.