Neuralink Brain-Computer Interface for Quadriplegia

(CAN-PRIME Trial)

Overseen By Neuralink Clinical Team

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Neuralink Corp

Disqualifiers: Seizures, Diabetes, Obesity, Smoking, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: 1

6 Participants Needed

Trial Summary

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications. It's best to discuss this with the study team or your doctor.

What data supports the effectiveness of the Neuralink Brain-Computer Interface treatment for quadriplegia?

Research shows that brain-computer interfaces can restore movement in paralyzed limbs by linking brain activity to muscle stimulation. In studies with animals and humans, these systems have successfully restored hand and leg movements, suggesting potential benefits for people with quadriplegia. ^{1 2 3 4 5}

How is the Neuralink Brain-Computer Interface treatment different from other treatments for quadriplegia?

The Neuralink Brain-Computer Interface treatment is unique because it involves an implantable device that directly interfaces with the brain to read motor intent and control devices, offering a novel way to restore function for quadriplegic patients. Unlike other treatments that may rely on external devices or muscle signals, this approach uses a brain implant and a surgical robot to provide a more direct and potentially more effective method of control. ^{6 7 8 9 10}

What is the purpose of this trial?

The CAN-PRIME Study is to test the safety and functionality of Neuralink's N1 Implant and R1 Robot in people who have difficulty moving their arms and legs (tetraparesis or tetraplegia). The N1 Implant is a small, wireless device placed in the skull. It connects to tiny threads inserted into the brain by the R1 Robot, which is a machine designed to carefully place these threads. This study will help researchers learn how well the implant and robot work and if they are safe for use.

Eligibility Criteria

This trial is for individuals with severe movement disabilities due to conditions like Motor Neuron Disease, Spinal Cord Injury, or ALS. Participants should have limited arm and leg mobility (tetraparesis or tetraplegia). Specific eligibility details are not provided but typically include age, health status, and the severity of paralysis.

Inclusion Criteria

Presence of a stable caregiver

Life expectancy ≥ 12 months

I have had severe quadriplegia for at least a year without improvement.

Exclusion Criteria

I have a history of diabetes that is hard to control.

Any condition which, in the opinion of the Investigator, would compromise your ability to safely participate in the study or undergo the implantation procedure

My BMI is over 40.

Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Implantation

Participants undergo the implantation of the N1 device using the R1 Robot

1 week

1 visit (in-person)

Post-Implantation Monitoring

Participants are monitored for safety and functionality of the N1 Implant and R1 Robot

8 weeks

Weekly visits (in-person)

Follow-up

Participants are monitored for safety and effectiveness after the initial monitoring period

4 weeks

Treatment Details

Interventions

• N1 Implant
• R1 Robot

Trial Overview The CAN-PRIME Study tests Neuralink's N1 Implant and R1 Robot. The implant goes into the skull and connects to brain threads placed by the robot. It aims to see if people can control external devices using their thoughts.

Participant Groups

Group I: CAN-PRIME: Precise Robotically Implanted Brain-Computer Interface Experimental Treatment 2 Interventions

Open label

N1 Implant is already approved in United States, Canada for the following indications:

Approved in United States as Neuralink N1 Implant for:

• Quadriplegia due to cervical spinal cord injury or amyotrophic lateral sclerosis (ALS)

Approved in Canada as Neuralink N1 Implant for:

• Tetraparesis or tetraplegia due to cervical spinal cord injury or amyotrophic lateral sclerosis (ALS)

Who Is Running the Clinical Trial?

Neuralink Corp

Lead Sponsor

Trials

3

Recruited

10+

University Health Network, Toronto

Collaborator

Trials

1,555

Recruited

526,000+

Findings from Research

A portable, fully implanted brain-computer interface successfully restored hand grasp control in a 21-year-old male with complete cervical quadriplegia, achieving a mean decoding accuracy of 89.0% during a 29-week laboratory study.

The system demonstrated high accuracy (91.3% in open-loop and 88.3% in closed-loop trials) for controlling hand movements at home, indicating its potential for practical use in improving functional independence for individuals with spinal cord injuries.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Implantable brain-computer interface for neuroprosthetic-enabled volitional hand grasp restoration in spinal cord injury. Cajigas, I., Davis, KC., Meschede-Krasa, B., et al.[2023]

A brain-spine interface was successfully developed in non-human primates, allowing for the restoration of weight-bearing locomotion in a paralyzed leg just six days after a spinal cord injury, demonstrating significant potential for rehabilitation.

The system utilized epidural electrical stimulation linked to real-time neural activity from the motor cortex, indicating a promising method for bypassing spinal cord lesions and restoring movement control, with components already approved for human research.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A brain-spine interface alleviating gait deficits after spinal cord injury in primates. Capogrosso, M., Milekovic, T., Borton, D., et al.[2022]

The novel tilt brain-machine interface (BMI) task developed for female rats allows for natural engagement of the lower body, enabling researchers to study spinal cord injury (SCI) models without requiring the animals to learn new skills or rely on external rewards.

This task effectively engages both hemispheres of the cortex and allows for adjustable difficulty, making it a promising tool for investigating how brain plasticity interacts with BMI training in the context of SCI.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A rodent brain-machine interface paradigm to study the impact of paraplegia on BMI performance. Bridges, NR., Meyers, M., Garcia, J., et al.[2020]

Neural interface systems (NISs) are promising devices that allow individuals with paralysis to control assistive technologies using brain signals, showing potential for reanimating muscles based on direct commands from the brain.

Initial pilot trials using an intracortical microelectrode sensor have demonstrated that even years after injury, neurons in the motor cortex can still be engaged to operate devices, indicating the lasting potential of brain signals for functional recovery.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Assistive technology and robotic control using motor cortex ensemble-based neural interface systems in humans with tetraplegia. Donoghue, JP., Nurmikko, A., Black, M., et al.[2018]

Motor neuroprosthetic devices, also known as brain-computer interfaces, can decode brain signals related to motor intent, allowing individuals with severe motor impairments to control devices and improve their interaction with the environment.

As the field of neuroprosthetics advances, understanding the principles of operation and surgical considerations for implantation will be crucial for neurosurgeons to effectively help patients with conditions like spinal cord injury and stroke.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

The emerging world of motor neuroprosthetics: a neurosurgical perspective. Leuthardt, EC., Schalk, G., Moran, D., et al.[2007]

A case study involving a participant with spastic quadriplegic cerebral palsy demonstrated that training with a commercial EEG-based brain-computer interface (BCI) over four weeks led to improved control of distinct EEG patterns, allowing the participant to type a sentence six weeks post-training.

The study emphasized that factors like motivation, fatigue, and concentration significantly affect BCI performance, highlighting the need for engaging and customized training environments to enhance the effectiveness of assistive technologies for individuals with severe disabilities.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Training to use a commercial brain-computer interface as access technology: a case study. Taherian, S., Selitskiy, D., Pau, J., et al.[2017]

A wearable neural interface using high-density surface electromyography (HDEMG) was developed to detect signals from spared motor units in the forearms of individuals with tetraplegia, allowing for the identification of myoelectric activity even without visible finger movement.

This technology demonstrated the ability to decode motor intent from over 30 active motor neurons, providing a promising method for controlling assistive devices and studying spinal network recovery after injury.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A wearable neural interface for detecting and decoding attempted hand movements in a person with tetraplegia. Ting, J., Farina, D., Weber, DJ., et al.[2020]

Recent advancements in brain-machine interfaces (BMIs) show promise for improving control over prosthetic devices using neural activity, which could significantly benefit individuals with neurological disorders.

Despite the progress, current neural interfaces still struggle to achieve effective control of prosthetic limbs, indicating that further research is needed to develop clinically viable solutions.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Advances in neuroprosthetic learning and control. Carmena, JM.[2021]

Brain-computer interfaces (BCIs) have significant potential for neuroprosthetic applications, particularly in controlling devices for hand grasp, multijoint movements, and lower extremities.

The review identifies current limitations in BCIs and emphasizes the need for further research to improve the integration of BCIs with functional electrical stimulation (FES) systems for better performance in neuroprosthetics.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Brain-Computer Interface-FES Integration: Towards a Hands-free Neuroprosthesis Command System. Boord, P., Barriskill, A., Craig, A., et al.[2022]

Brain-computer interfaces (BCI) are promising devices that can help quadriplegic patients regain control by interpreting brain signals to operate physical and virtual prosthetics.

The future of BCI technology aims to include sensory feedback, which will enhance the user experience and effectiveness for patients with neurological injuries.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Brain-Computer Interfaces in Quadriplegic Patients. Lee, MB., Kramer, DR., Peng, T., et al.[2019]

References

1. England pubmed.ncbi.nlm.nih.gov

Implantable brain-computer interface for neuroprosthetic-enabled volitional hand grasp restoration in spinal cord injury. [2023]

2. England pubmed.ncbi.nlm.nih.gov

A brain-spine interface alleviating gait deficits after spinal cord injury in primates. [2022]

3. Netherlands pubmed.ncbi.nlm.nih.gov

A rodent brain-machine interface paradigm to study the impact of paraplegia on BMI performance. [2020]

4. England pubmed.ncbi.nlm.nih.gov

Assistive technology and robotic control using motor cortex ensemble-based neural interface systems in humans with tetraplegia. [2018]

5. United States pubmed.ncbi.nlm.nih.gov

The emerging world of motor neuroprosthetics: a neurosurgical perspective. [2007]

6. England pubmed.ncbi.nlm.nih.gov

Training to use a commercial brain-computer interface as access technology: a case study. [2017]

7. United States pubmed.ncbi.nlm.nih.gov

A wearable neural interface for detecting and decoding attempted hand movements in a person with tetraplegia. [2020]

8. United States pubmed.ncbi.nlm.nih.gov

Advances in neuroprosthetic learning and control. [2021]

9. United States pubmed.ncbi.nlm.nih.gov

Brain-Computer Interface-FES Integration: Towards a Hands-free Neuroprosthesis Command System. [2022]

10. United States pubmed.ncbi.nlm.nih.gov

Brain-Computer Interfaces in Quadriplegic Patients. [2019]