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

Abstract

Brain-computer interfaces (BCI) translate brain signals into artificial output to restore or replace natural central nervous system (CNS) functions. Multiple processes, including sensorimotor integration, decision-making, motor planning, execution, and updating, are involved in any movement. For example, a BCI may be better able to restore naturalistic motor behaviors if it uses signals from multiple brain areas and decodes natural behaviors' cognitive and motor aspects. This review provides an overview of the preliminary information necessary to plan a BCI project focusing on intracortical implants in primates. Since the brain structure and areas of non-human primates (NHP) are similar to humans, exploring the result of NHP studies will eventually benefit human BCI studies. The different types of BCI systems based on the target cortical area, types of signals, and decoding methods will be discussed. In addition, various successful state-of-the-art cases will be reviewed in more detail, focusing on the general algorithm followed in the real-time system. Finally, an outlook for improving the current BCI research studies will be debated.

Keywords: BCI; Brain-computer interfaces; Decision-Making; Decoding Methods; Intention Estimation; Motor Cortex; Prefrontal Cortex.

Fig. 1

The sensory and motor areas involved in movement. (A) The primary visual cortex (V1) and the primary somatosensory cortex (S1) send sensory information to the posterior parietal cortex (PPC). This information is processed and sent to the prefrontal cortex (PFC) and the pre-motor cortex (PMC). PMC then sends the processed information to the primary motor cortex (M1). Reproduced from work by Casey Henley, licensed under a Creative Commons Attribution Non-Commercial Share-Alike (CC BY-NC-SA) 4.0 International License. (B) The movements are planned in the PFC, organized in PMC, and executed in M1 through the spinal cord