Noninvasive Detection of Motor-Evoked Potentials in Response to Brain Stimulation Below the Noise Floor—How Weak Can a Stimulus Be and Still Stimulate

Motor-evoked potentials (MEP) are one of the most important responses to brain stimulation, such as supra-threshold transcranial magnetic stimulation (TMS) and electrical stimulation. The understanding of the neurophysiology and the determination of the lowest stimulation strength that evokes responses requires the detection of even smallest responses, e.g., from single motor units, but available detection and quantization methods are rather simple and suffer from a large noise floor. The paper introduces a more sophisticated matched-filter detection method that increases the detection sensitivity and shows that activation occurs well below the conventional detection level. In consequence, also conventional threshold definitions, e.g., as 50 μV median response amplitude, turn out to be substantially higher than the point at which first detectable responses occur. The presented method uses a matched-filter approach for improved sensitivity and generates the filter through iterative learning from the presented data. In contrast to conventional peak-to-peak measures, the presented method has a higher signal-to-noise ratio (≥14 dB). For responses that are reliably detected by conventional detection, the new approach is fully compatible and provides the same results but extends the dynamic range below the conventional noise floor. The underlying method is applicable to a wide range of well-timed biosignals and evoked potentials, such as in electroencephalography.