Neural representations arise from high-dimensional population activity,but current neuromodulation methods lack the precision to write information into the central nervous system at this complexity.In this perspective...Neural representations arise from high-dimensional population activity,but current neuromodulation methods lack the precision to write information into the central nervous system at this complexity.In this perspective,we propose high-dimensional stimulation as an approach to better approximate natural neural codes for brain-machine interfaces.Key advancements in resolution,coverage,and safety are essential,with flexible microelectrode arrays offering a promising path toward precise synthetic neural codes.展开更多
基金funded by R01EY036094(L.L)R01NS102917(C.X)+1 种基金U01NS115588(C.X)U01NS131086(C.X&L.L.)。
文摘Neural representations arise from high-dimensional population activity,but current neuromodulation methods lack the precision to write information into the central nervous system at this complexity.In this perspective,we propose high-dimensional stimulation as an approach to better approximate natural neural codes for brain-machine interfaces.Key advancements in resolution,coverage,and safety are essential,with flexible microelectrode arrays offering a promising path toward precise synthetic neural codes.
