Clinical trial NCT02224469: First Study With a Brain Implant to Help Locked-in Patients Communicate at Home
Official title: Utrecht Neural Prosthesis (UNP): A Pilot Study on Controllability of Brain Signals and Application in locked-in Patients
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Locked-In Syndrome
Keywords: Brain-Computer Interface
Motor Cortex
Dorsolateral Prefrontal Cortex
Quality of Life
Lead sponsor: UMC Utrecht
Sponsor class: OTHER
First posted: 2014-08-25
Enrollment: 3
Sex: ALL
Minimum age (years): 18
Maximum age (years): 75
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: NA
Intervention model: SINGLE_GROUP
Primary purpose: SUPPORTIVE_CARE

Brief summary: In this study a new means of communication for people with locked-in syndrome will be tested. The investigators will record brain signals directly from the surface of the brain by means of a completely implantable system. These brain signals are fed wirelessly into an assistive technology device and will control this device for communication and environmental control at the users home.

Detailed description: In this pilot study we will provide locked-in people with a new means of communication which has not been possible up to now. For the first time, we will test whether we can record and decode neural signals obtained directly from the brain, for control over a computer. The target population is people with locked-in syndrome. For these patients there is no technique available to allow them to communicate unaided. We have developed a brain-computer interface (BCI) system that can read activity directly from the brain, and can convert the activity to a digital switch. The system, called the Utrecht Neural Prosthesis (UNP), consists of an implantable amplifier for electrical brain signals, a set of electrodes positioned on the surface of the brain and a wireless receiver, placed outside of the body. A dedicated computer will convert the signals to electrical pulses for standard Assistive Technology devices. The UNP can in principle enable the patient to engage in any activity that is offered by commercial Assistive Technology companies that can be performed with switch signals, for instance operating home apparatus or writing text. Most importantly, we aim to achieve unsupervised function of the BCI, meaning that the patient will be able to use it at home without the aid of researchers or other experts (but with minimal caregiver assistance).

Eligibility criteria: Inclusion Criteria:

* Age 18 - 75
* Locked-in status (i.e. severely paralyzed with communication problems)

  * in case of trauma or stroke: at least 1 year after the event
  * in case of a neuromuscular disease: slow progression allowed
* Rudimentary form of communication possible (e.g. through assistive technology, eye blinks or eye movements, severely impaired speech)
* Mentally and physically capable of giving informed consent
* Lives in or close to the Netherlands
* MR compatible

  * able to lie flat in the scanner
  * no metal objects in or attached to the body
  * no claustrophobia
* Visus (largely) intact
* Cognition intact (IQ\>80)
* Compatible with implantation procedure

  * good respiratory function or stable respiratory situation using ventilation assistance

Exclusion Criteria:

* Strong and frequent spasms
* Vital indication for blood thinners
* Current brain tumor or history of tumor resection
* Quick medical or neurological deterioration
* Patients who are considered legally incapable (and who therefore will not be able to give informed consent)
* Current or recent psychiatric disorder
* Catabolic state
* Allergy to the materials of the implant

Primary outcomes:
measure: Unsupervised BCI performance
timeFrame: up to 1 year
Secondary outcomes:
measure: Patient Satisfaction
timeFrame: up to 1 year
Other outcomes:
measure: supervised BCI performance
timeFrame: up to 28 weeks
Locations:
city: Utrecht
country: Netherlands
facility: University Medical Center
Study officials:
affiliation: UMC Utrecht
name: Nick F Ramsey, PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Vansteensel MJ, Hermes D, Aarnoutse EJ, Bleichner MG, Schalk G, van Rijen PC, Leijten FS, Ramsey NF. Brain-computer interfacing based on cognitive control. Ann Neurol. 2010 Jun;67(6):809-16. doi: 10.1002/ana.21985.
citation: Torres Valderrama A, Paclik P, Vansteensel MJ, Aarnoutse EJ, Ramsey NF. Error probability of intracranial brain computer interfaces under non-task elicited brain states. Clin Neurophysiol. 2012 Dec;123(12):2392-401. doi: 10.1016/j.clinph.2012.05.006. Epub 2012 Jun 12.
citation: Vansteensel MJ, Pels EGM, Bleichner MG, Branco MP, Denison T, Freudenburg ZV, Gosselaar P, Leinders S, Ottens TH, Van Den Boom MA, Van Rijen PC, Aarnoutse EJ, Ramsey NF. Fully Implanted Brain-Computer Interface in a Locked-In Patient with ALS. N Engl J Med. 2016 Nov 24;375(21):2060-2066. doi: 10.1056/NEJMoa1608085. Epub 2016 Nov 12.
citation: Freudenburg ZV, Branco MP, Leinders S, van der Vijgh BH, Pels EGM, Denison T, van den Berg LH, Miller KJ, Aarnoutse EJ, Ramsey NF, Vansteensel MJ. Sensorimotor ECoG Signal Features for BCI Control: A Comparison Between People With Locked-In Syndrome and Able-Bodied Controls. Front Neurosci. 2019 Oct 16;13:1058. doi: 10.3389/fnins.2019.01058. eCollection 2019.
citation: Pels EGM, Aarnoutse EJ, Leinders S, Freudenburg ZV, Branco MP, van der Vijgh BH, Snijders TJ, Denison T, Vansteensel MJ, Ramsey NF. Stability of a chronic implanted brain-computer interface in late-stage amyotrophic lateral sclerosis. Clin Neurophysiol. 2019 Oct;130(10):1798-1803. doi: 10.1016/j.clinph.2019.07.020. Epub 2019 Jul 27.
citation: Pels EGM, Aarnoutse EJ, Ramsey NF, Vansteensel MJ. Estimated Prevalence of the Target Population for Brain-Computer Interface Neurotechnology in the Netherlands. Neurorehabil Neural Repair. 2017 Jul;31(7):677-685. doi: 10.1177/1545968317714577. Epub 2017 Jun 22.
citation: Leinders S, Vansteensel MJ, Branco MP, Freudenburg ZV, Pels EGM, Van der Vijgh B, Van Zandvoort MJE, Ramsey NF, Aarnoutse EJ. Dorsolateral prefrontal cortex-based control with an implanted brain-computer interface. Sci Rep. 2020 Sep 22;10(1):15448. doi: 10.1038/s41598-020-71774-5.
citation: Leinders S, Vansteensel MJ, Piantoni G, Branco MP, Freudenburg ZV, Gebbink TA, Pels EGM, Raemaekers MAH, Schippers A, Aarnoutse EJ, Ramsey NF. Using fMRI to localize target regions for implanted brain-computer interfaces in locked-in syndrome. Clin Neurophysiol. 2023 Nov;155:1-15. doi: 10.1016/j.clinph.2023.08.003. Epub 2023 Aug 18.