The use of artificial neural networks in the motor program

Though it is commonly assumed that the brain creates "motor programs" which store the information essential to perform a motor skill, little direct evidence exists for such motor programs. Electromyography (EMG) provides a look into the motoneurons - level of a movement by measuring the electrical activity in relation to the muscle\´s involvement in the movement In this paper, artificial neural networks (ANNs) were applied to define the temporal patterns of EMG activity used by normal subjects in performing step-tracking tasks, and how such patterns change with practice. Our results demonstrate that ANNs could be trained to detect the input-output relationship between muscles\´ onset times and reaction times, and provided evidence to support the existence of a motor program.