Towards non-invasive multi-unit spike recordings: mapping 1kHz EEG signals over human somatosensory cortex.

OBJECTIVE

Scalp-derived human somatosensory evoked potentials (SEPs) contain high-frequency oscillations (600 Hz; 'sigma-burst') reflecting concomitant bursts of spike responses in primary somatosensory cortex that repeat regularly at 600 Hz. Notably, recent human intracranial SEP have revealed also 1 kHz responses ('kappa-burst'), possibly reflecting non-rhythmic spiking summed over multiple cells (MUA: multi-unit activity). However, the non-invasive detection of EEG signals at 1 kHz typical for spikes has always been limited by noise contributions from both, amplifier and body/electrode interface. Accordingly, we developed a low-noise recording set-up optimised to map non-invasively 1 kHz SEP components.

METHODS

SEP were recorded upon 4 Hz left median nerve stimulation in 6 healthy human subjects. Scalp potentials were acquired inside an electrically and magnetically shielded room using low-noise custom-made amplifiers. Furthermore, in order to reduce thermal Johnson noise contributions from the sensor/skin interface, electrode impedances were adjusted to ≤ 1 kΩ. Responses averaged after repeated presentation of the stimulus (n=4000 trials) were evaluated by spatio-temporal pattern analyses in complementary spectral bands.

RESULTS

Three distinct spectral components were identified: N20 (<100 Hz), sigma-burst (450-750 Hz), and kappa-burst (850-1200 Hz). The two high-frequency bursts (sigma, kappa) exhibited distinct and partially independent spatiotemporal evolutions, indicating subcortical as well as several cortical generators.

CONCLUSIONS

Using a dedicated low-noise set-up, human SEP 'kappa-bursts' at 1 kHz can be non-invasively detected and their scalp distribution be mapped. Their topographies indicate a set of subcortical/cortical generators, at least partially distinct from the topography of the 600 Hz sigma-bursts described previously.

SIGNIFICANCE

The non-invasive detection and surface mapping of 1 kHz EEG signals presented here provides an essential step towards non-invasive monitoring of multi-unit spike activity.