Abstract
The recording of motor-evoked potentials (MEPs) elicited by single pulses of transcranial magnetic stimulation (TMS) over the primary motor cortex (M1) is a widely used non-invasive technique to assess motor cortex excitability in humans. Recently, it was shown that the electroencephalogram (EEG) can be used to measure TMS-evoked brain potentials (TEPs). Following M1 stimulation, TEPs consist of early latency responses maximal over the stimulation site, followed by later responses hypothesized to originate from frontal and temporo-parietal regions. Here, we characterized the relationship between TEPs and MEPs using machinelearning techniques, with the aim of exploring the functional significance of these brain responses and their relation to M1 excitability. Furthermore, considering that M1 excitability may be expected to vary spontaneously according to intrinsic fluctuations in neuronal excitation, we also examined whether the EEG signal measured before the onset of the TMS pulse is predictive of the elicited MEPs
Gan Huang
My research interests include Neural Modulation, Brain Computer Interface and Neural Prosthetics.