Superposition model for steady state visually evoked potentials

Steady State Visually Evoked Potentials (SSVEP) are signals produced in the occipital part of the brain when someone gaze a light flickering at a fixed frequency. These signals have been used for Brain Machine Interfacing (BMI), where one or more stimuli are presented and the system has to detect what is the stimulus the user is attending to. It has been proposed that the SSVEP signal is produced by superposition of Visually Evoked Potentials (VEP) but there is not a model that shows that. We propose a model for a SSVEP signal that is a superposition of the response to the rising and falling edges of the stimuli and that can be calculated for different frequencies. This model is based in the phase between the stimulus and the SSVEP signal considering that the phase is stable over the time. We fit the model for 4 volunteers that gazed stimuli in the frequencies of 9hz, 11hz, 13hz and 15hz, and duty-cycles of 20%, 35%, 50%, 65% and 80%. We found the parameters of the model for every volunteer using the data of Oz electrode and a genetic algorithm. The proposed model is useful for find the best duty-cycle of the stimulus and it can be useful for select a code in the stimuli different for a square signal, the model only consider one frequency at the same time, but the results showed that it could be possible to find a more generic model.