Neuro-electrical activity-based brain-computer interface for interacting with the deep human brain

The Brain-Machine Interface (BMI, also known as the Brain-Computer Interface) provides a new dimension for humans to interact with machines and the environment. Brain-machine interfaces help restore or improve human physical or mental functions. Scientists are investigating different technologies that interact with the brain on different levels, as shown in the diagram below.

The cerebral cortex has long been the subject of brain-machine interface research. By recording neural activity in multiple cortical regions to understand human intent, researchers are enabling paralyzed patients to control robotic arms and prosthetics, helping people with disabilities to communicate effectively. to

Using traditional brain-computer interfaces, sensory and motor signals such as visual responses, hand movements, and speech can be decoded in a constrained laboratory environment. Applying these techniques to everyday life remains challenging.

Deep brain regions are heavily involved in basic life functions. To better understand how the brain works, we need to investigate the deep functions of the brain. Subcortical brain regions are prime targets for invasive neuromodulation and clinical neurotherapy. Structural and functional abnormalities in the human deep brain have been observed in various neurological and psychiatric disorders, including Parkinson’s disease, Alzheimer’s disease, depression, obsessive-compulsive disorder, and others. area. This is a new research area with great potential for clinical applications.

The diagram above shows the main methods of recording and stimulation from the surface to the depth of the brain. In addition to recording and decoding, deep brain machine interfaces can also modulate pathological states of the brain by applying therapeutic stimuli. Advanced DBMI technology is designed to record and decode deep neural activity with high spatiotemporal resolution and efficiently configure stimulation parameters to precisely modulate brain states. Developing a DBMI with long-term efficacy remains challenging due to the limited understanding of mechanisms such as CNS plasticity and adaptation.

Since the nervous system primarily communicates information via electrical signals, brain-computer interfaces via electrical signals are of the greatest research interest in this area. This article reviews current neuro-electrical activity-based brain-computer interface technologies available to humans and their applications in sensing and modulating brain activity. The authors present his two widely used deep brain interface systems, deep brain stimulation (DBS) and stereotaxic electroencephalography (sEEG), with particular attention to the latest technological advances and clinical applications. . The potential of DBMI to be used as a powerful brain research platform and its therapeutic utility is addressed. The paper also describes a closed-loop control framework for DBMI systems and the development of closed-loop deep brain interface techniques for clinical applications.

The corresponding author of the review is Professor Luming Li of Tsinghua University, the first author is Associate Professor Yanan Sui, and the co-authors are Dr. Huiling Yu, Dr. Chen Zhang, Dr. Yue Chen, and associate researcher Changqing Jiang. .