Steady state evoked potentials (SSEPs) using multiple frequency inputs are a well-known method to study the underlying dynamics in the visual, auditory and somatosensory system. Multi-frequency SSEPs provide insight into system dynamics such as delay, non-linearities, and frequency response function. Despite extensive research, little is known about the nociceptive system and its dynamics. Previous research showed the possibility to evoke single frequency nociceptive SSEPs using block wave stimulation. In the present study, we explored the feasibility of evoking multi-frequency nociceptive SSEPs using a multisine frequency modulated pulse train. The novel electrical stimulation technique using a frequency pulse train composed of 3, 7 and 13 Hz can stimulate multiple frequencies simultaneously. For the first time, we were able to induce multi-frequency SSEPs indicated by a contralateral maximal signal to noise ratio EEG response for 3 and 7 Hz. The power in 3 and 7 Hz showed significantly higher power compared to all other frequencies up until 40 Hz. The novel stimulation technique offers a unique opportunity to measure multi-frequency SSEPs related to nociceptive processing, allowing better localization of nociceptive signal processing and possible insight into the dynamics of the nociceptive regulation system.

Stroke is a cerebrovascular disorder with 15 million cases every year worldwide. The most common symptom is motor deficits. In order to overcome such symptoms, the motor brain either repairs the damaged tissue or reorganises to compensate for the injured brain region. To stimulate this reorganisation transcranial Direct Current Stimulation (tDCS) is considered to be a promising thera- peutic intervention. Simulations of electric field distributions generated by tDCS currently entail individualised volume conduction models to improve tDCS. A volume conduction model includes geometry and conductivity properties of tissue types in healthy subjects. When applying existing models to chronic stroke subjects, electric field distribution patterns differ substantially compared to healthy subject distribution patterns. In current models, the lesion is not identified and acknowledged as a distinctive tissue type, as it is yet unclear what the lesion influence is. However, the lesion is a potential source of variability in desired electric field distribution which could result in different motor recovery. A volume conduction model is designed by combining the software SimNIBS, which can segment the head of healthy subjects and LINDA, able to distinguish lesion tissue of chronic stroke subjects. The location and the conductivity value of the lesion seem to influence the electric field distribution of tDCS where this individualised model is preferred. Including the lesion is an important advance towards the use of volume conduction models for chronic stroke subjects to prospectively find optimal electrode configurations, keep the safety margins and to prospectively analyse the results of tDCS.