Neural system characterizes information in external stimulations by spatiotemporal encoding. In order to reveal the underlying mechanisms about the conduction and function of acupuncture signal, experiments are designed that is different types of manual acupuncture (MA) manipulations are taken at 'Zusanli' points of experiment rats, and the induced electrical signals in spinal dorsal root ganglion are detected and recorded. First, the firings of neuronal clusters are distinguished by extracting features of each spike shapes. Then types of acupuncture manipulations taken on the rats are inferred with a high probability by Bayesian decoding algorithm based on each single trial. Data in the first 200. ms from acupuncture onset are recognized to play a crucial role in increasing the decoding performance in all sessions. These results are proved to be significant by statistical analysis. These studies have offered new insights into neural processing underlying acupuncture and may help to construct the interface between neural systems and machines and improve the clinical study.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Cognitive Neuroscience
- Artificial Intelligence