Intracortical brain-computer interfaces in primates: a review and outlook

Area of Science:

• Neuroscience
• Biomedical Engineering
• Rehabilitation Technology

Background:

• Brain-computer interfaces (BCI) translate neural signals into commands to restore or replace functions of the central nervous system (CNS).
• Movement involves complex processes like sensorimotor integration, decision-making, and motor planning.
• Utilizing signals from multiple brain areas and decoding cognitive/motor aspects can enhance naturalistic motor behavior restoration.

Purpose of the Study:

• To provide preliminary information for planning intracortical brain-computer interface (BCI) projects in primates.
• To review different BCI system types based on target cortical areas, signal types, and decoding methods.
• To discuss successful state-of-the-art BCI cases and algorithms for real-time systems.

Main Methods:

• Literature review of existing BCI research, focusing on intracortical implants in primates.
• Analysis of non-human primate (NHP) studies due to their brain structure similarities to humans.
• Detailed examination of BCI system architectures, signal processing, and decoding algorithms.

Main Results:

• NHP studies offer valuable insights for developing human BCI applications.
• Various BCI systems differ in target areas, signal acquisition (e.g., electrocorticography, intracortical arrays), and decoding strategies.
• Successful real-time BCI systems often employ sophisticated algorithms for decoding neural activity.

Conclusions:

• Planning BCI projects requires understanding neural signal processing and primate neuroanatomy.
• Advancements in BCI technology, particularly through NHP research, hold significant promise for restoring human CNS functions.
• Future research should focus on improving current BCI algorithms and system integration for enhanced performance.