Narrow Results

In this work we use Generalized Linear Models (GLMs) in order to identify a complex neurophysiological system, called muscle spindle that involves stationary point processes. Three parameters are of interest because they describe the intrinsic properties of the system: the threshold, the recovery and the summation function. These parameters are included in the GLMs and their estimates are obtained by using the maximum likelihood approach. Two cases are examined. In the first case, there is no input present and it is shown that the system fires spontaneously. In the second case, the system is affected by the presence of a gamma motoneurone. It is shown that there is no spontaneous activity and the behavior of the system is excitatory. These results are in accordance with previous work. In the present work a new parameter, the carry over effect function is included in the model. The performance of the new model is compared with the previous results and it is shown that the addition of the carry over effect function in the model improves the results significantly.