Adaptive time-scale feature extraction in electroencephalographic responses to transcranial magnetic stimulation

Electroencephalographic responses evoked by transcranial magnetic stimulation (TMS) gain more and more interest for basic neurophysiological research and possibly diagnostic purposes. However, the separation of magnetically from non- magnetically induced brain activity still remains a challenge due to superimposed secondary effects, in particular auditory and somatosensory evoked potentials. In this study, we use optimized tight wavelet frames for the adaptive extraction of discriminant electroencephalographic time-scale features during TMS using figure-of-eight coil for focal stimulation and a combined auditory and somatosensory stimulation (ASS) paradigm. We restrict our focus to large-scale features which correspond to slow wave cortical potentials (SCPs). These potentials might reflect thalamocortical dynamics and are frequently used in biofeedback therapies. The proposed methods allows for a robust extraction of slow wave components and separated clearly the TMS from the ASS data. It is concluded that our study strongly supports recent suggestions that TMS modulates SCPs, reinforcing the theory that TMS leads to long term changes in the cortical excitability.