PIPages
Labs

Karunesh Ganguly

University of California-San Francisco, CA·Neuroscience

Spinal cord injury, ALS (amyotrophic lateral sclerosis) and brainstem stroke can leave people unable to move their arms and hands. More than 200,000 patients live with tetraplegia, paralysis of all four limbs, or severe weakness that blocks everyday tasks like eating or grasping objects.

Fields

Neuroscience

Biomedical Engineering

Medicine & Clinical Research

Topics

brain-computer interface

neuroprosthetics

electrocorticography

Grants
1 known grant, through Jul 2029

What they work on

  1. Compare two neural decoding methods for their ability to give paralyzed patients stable, plug-and-play control of a robotic arm and hand with ECoG for at least 8 weeks without recalibration.
  2. Reduce decoding errors during long-term continuous use by tracking fluctuations in patients' neural states recorded with electrocorticography.
  3. Test an assistive system that pre-shapes the robotic hand during brain-controlled reaching, grasping and object manipulation to make real-world control more robust.

More about the research

Patients rank restoring arm and hand function as a top priority, yet no current therapy or device can restore reaching and grasping. Brain-computer interfaces (BCIs), which turn brain signals into commands for machines, offer a possible route.

Why it matters

People paralyzed by spinal cord injury, ALS or brainstem stroke currently have no way to regain reaching and grasping. Showing that an ECoG brain-computer interface can run a robotic arm and hand reliably for weeks without recalibration could move these devices toward clinical use. That could help such patients carry out daily tasks more independently.

Known grants

From NIH and NSF research grants. Labs often have other funding we can't see.

Long-term reliable neuroprosthetic control of a robotic arm and hand using electrocorticography.

NIH · Aug 2024 – Jul 2029

Closest labs

Lee Miller

Northwestern University, IL·Biomedical Engineering

Build decoders that predict intended muscle activity (EMG) from primary motor cortex spiking recorded in humans with high-level spinal cord injury, trained with EMG, hand posture and force data from able-bodied people doing the same actions.

Sergey Stavisky

University of California-Davis, CA·Neuroscience·Early-career

Record hundreds of individual neurons with implanted microelectrode arrays in the ventral precentral gyrus and superior temporal gyrus to learn which features of speech these neurons encode and when during speaking.

Jonathan Kao

University of California-Los Angeles, CA·Biomedical Engineering·Early-career

Train new recurrent neural network architectures on the decision-making and movement tasks animals perform, constrained by anatomy and neural recordings, then analyze them to propose mechanisms of cortical computation.

The school

University of California-San Francisco: 89 labs on PI Pages, $2.1B a year on research, 164 research doctorates a year.

More about University of California-San Francisco

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