P 222. Studying the dynamics of the TMS-EEG signal

Abstract

Introduction Combined transcranial magnetic stimulation (TMS) and electroencephalography (EEG) has proven to be a useful tool when probing the effective connectivity. However, the TMS-evoked responses seem to vary significantly from trial to another. This is partially due to the constantly changing underlying brain state, which is likely to affect the evoked response. Thus, it is important to understand the relationship between the current brain state dynamics and the evoked TMS-EEG responses. This work concentrates on the non-linear dynamic behaviour of EEG signal before and after TMS stimuli. Objectives Our objective is to study the effects of TMS on the dynamics of the brain state as well as the effects of the current brain state dynamics on the TMS-evoked responses. Materials and methods In the analysis, 16 different TMS-EEG data sets, where the stimuli had been delivered on the left primary motor cortex with 100% motor threshold intensity. The Nexstim eXimia magnetic stimulator and TMS-compatible EEG system were used to collect the data. It is known that the trajectory of a system in the state space can reveal some vital properties of the underlying dynamics. In this work, we studied the projection of the state-space trajectory onto the EEG signal space using 16 EEG channels confining the stimulation area. The data analysis consisted of computation of three commonly known non-linear measures for trial-level data: quantitative recurrence analysis, Lyapunov stability, and correlation dimension. In short, the recurrence analysis measures the distances between the state vectors defining the state of the system as a function of time. Lyapunov stability is used to describe the chaotic properties of the system, whereas correlation dimension measures the complexity of the underlying system. In the figure one can see a schematic picture of the hypothesis behind the present work. The post-synaptic currents (A) define accurately the electric state of the brain. The brain state advances spontaneously in the state space (red line). However, TMS might shift the system rapidly to a certain subset and also affect the later motion of the trajectory (green line). We can observe the projection of the trajectory on the EEG signal space (dotted lines) spanned by channels ch i and ch j . Results The mean distance between the state vectors right before and right after the stimulus was greater than the mean distance separating state vectors during spontaneous activity. Furthermore, the results indicated that the state vector was moving faster during approximately 300-ms long period after the stimulus than during spontaneous activity. The results also showed some evidence that the correlation dimension might decrease as an effect of TMS. With the present data available the Lyapunov-stability analysis did not show clear results. Conclusion The results indicate that the “artificial” activity created by TMS is propagating faster in the system than the spontaneous activity. This might be due to higher local free energy close to the stimulation site, which the system tries to minimize as fast as possible. Furthermore, it seems that TMS actually does shift the brain state to a slightly different subset in the brain state space.