Deep brain stimulation: BCI at large, where are we going to?

Area of Science:

• Biomedical Engineering
• Neuroscience
• Neurosurgery

Background:

• Deep brain stimulators (DBS) require innovative technological advancements for therapeutic applications.
• Robotized exoskeletons necessitate brain-computer interfaces (BCIs) capable of controlling numerous degrees of freedom (DoF).
• Functional neurosurgery encompasses various devices including stimulators, infusion devices, and neuroprostheses.

Purpose of the Study:

• To report the development of nanomicrotechnology prototypes for 3D DBS and motor neuroprostheses.
• To design and test novel BCI components for enhanced functional neurosurgery.
• To develop and validate an electroencephalogram (EEG) recognition algorithm for BCI applications.

Main Methods:

• Designed and implanted a programmable multiplexer for DBS in Parkinsonian patients.
• Developing a telepowered, wireless cortical BCI implant with a 64-electrode array for ECoG data acquisition.
• Utilized a wavelet-based Iterative N-way Partial Least Square (INPLS) algorithm for online detection of brain signatures in animal models.

Main Results:

• A 3D multiplexer enabled tailored electrical field application for STN stimulation.
• Cortical BCI implant components are undergoing reliability and toxicology testing for human implantation.
• The INPLS algorithm achieved approximately 80% accuracy in detecting cortical signatures associated with lever presses in rats.

Conclusions:

• Developed multielectrode wireless implants to enable ECoG-driven effectors.
• These technologies advance new generations of cortical and deep brain stimulators.
• BCIs are integral to DBS, driving innovation in functional neurosurgery and neuroprosthetics.