A system for behavior prediction based on neural signals

Modeling the brain has been a major scientific endeavor in the last few decades. Models can be at different levels of abstraction like chemical, cellular, region etc. Limitations in physical experimental setup will create poor model, if a regular pattern classifier system is used. This paper proposes a pattern recognition system to classify/predict animal behavior based on hippocampal signals. This system, takes into account the practical constraints during acquisition of the neural signal. The system performance for action classification is tested using multiple databases and percentage misclassification as low as 3.25% was obtained.