Neural Decoding Part I

This chapter presents an open-ended approach toward solving the problem of neural decoding. Specifically, it addresses how to predict the upcoming direction of movement from a population of neuronal signals recorded from motor areas of a macaque monkey. Neural decoding is a mathematical mapping from the brain activity to the outside world. In the sensory domain, the outside world consists of the received visual, auditory, or other sensory information. In the motor domain, the outside world consists of the state of the skeletomuscular system. This is the inverse of neural encoding, which maps the outside world to brain activity. Neural decoding can also be thought of as pattern recognition. A set of neuronal spike times represents a pattern, and the goal of the decoder is to figure out which stimuli or movements are associated with which patterns. This is a common problem in science. Doctors perform pattern recognition when they produce a diagnosis from a collection of physical and physiological findings.