Neural Decoding and Applications in Bioelectronic Medicine

Abstract

Neural decoding is a field involving the use of signal processing and machine learning methods to decode brain activity for various applications including assistive technology for people living with paralysis and diagnosing brain-related diseases such as Parkinson’s, Alzheimer’s, schizophrenia and obsessive compulsive disorder. The use of neural decoding, however, could be extended to applications in bioelectronic medicine, a field focused on the treatment and diagnosis of organ and other diseases through neurostimulation and neurosensing in the central and peripheral nervous system. Specifically, there is increasing evidence that neurostimulation can upregulate or downregulate the immune system, and, just as the nervous system innervates our organs and helps regulate their function, it also can modulate the immune system response and even affect acute inflammation response. Previous research in bioelectronic medicine has been focused primarily on open-loop neurostimulation without sensing methods or algorithms to automatically control the spatial and temporal characteristics of the stimulation. Research involving neural decoding methods has been conducted for other neurostimulation applications including the treatment of epilepsy and Parkinson’s disease. Introducing sensing and neural decoding methods into the bioelectronic medicine field could improve the diagnosis and treatment of a wide variety of diseases by closing the loop, which would allow automatic and adaptive neurostimulation that could increase its overall efficacy. There will be important related research questions and challenges to address as we attempt to place a control system on top of an already existing control system—a vast, complex and dynamic one—the human nervous system.