Current Status and Development on the Brain–Computer Interface

Dear Colleagues,

Brain–computer interfaces (BCIs) are neurotechnologies that enable direct communication between the brain and external devices, circumventing traditional neuromuscular pathways. By measuring brain activity, usually through electroencephalography (EEG), and converting it into digital commands, BCIs can control various devices such as computers, prosthetic limbs, and even household appliances. The potential applications of BCIs are vast and promising, especially in the medical field. They offer the promise of restoring movement and communication abilities to individuals with severe disabilities, such as those suffering from spinal cord injuries, amyotrophic lateral sclerosis (ALS), or stroke. Beyond medical applications, BCIs are being explored in the realms of sport, gaming, virtual reality, and even in enhancing cognitive functions such as attention.

The technology behind BCIs involves a complex interplay of neuroscience, cognitive science, engineering, and computer science. Despite the significant advancements made in recent years, several challenges persist. One of the primary hurdles is achieving high signal accuracy and reliability, as brain signals can be noisy and difficult to interpret. BCIs also require sophisticated algorithms to decode the neural signals accurately and translate them into executable commands. User adaptability is another critical issue, as the system must be intuitive and responsive to individual users' unique neural patterns. Developing new user training protocols for brain–computer interfaces is crucial to enhancing their effectiveness and accessibility for a broader range of individuals. Furthermore, there are ethical considerations, particularly concerning privacy and the potential for misuse of neural data. As research and development continue to advance, the future of BCIs holds great promise, potentially revolutionizing how we interact with technology and improving the quality of life for many individuals.

Dr. Camille Jeunet
Dr. Hakim Si-Mohammed
Dr. Lea Pillette
Guest Editors

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• brain–computer interface
• neurofeedback
• signal processing
• user training
• neuroergonomics