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The maintenance of items in working memory relies on persistent neural activity in a widespread network of brain areas. To investigate the influence of load on working memory, we asked human subjects to maintain sets of letters in memory while we recorded single neurons and intracranial encephalography (EEG) in the medial temporal lobe and scalp EEG. Along the periods of a trial, hippocampal neural firing differentiated between success and error trials during stimulus encoding, predicted workload during memory maintenance, and predicted the subjects' behavior during retrieval. During maintenance, neuronal firing was synchronized with intracranial hippocampal EEG. On the network level, synchronization between hippocampal and scalp EEG in the theta-alpha frequency range showed workload dependent oscillatory coupling between hippocampus and cortex. Thus, we found that persistent neural activity in the hippocampus participated in working memory processing that is specific to memory maintenance, load sensitive and synchronized to the cortex.

Non-invasive EEG detection of very high frequency somatosensory evoked potentials featuring frequencies up to and above 1 kHz has been recently reported. Here, we establish the detectability of such components by combined low-noise EEG/MEG. We recorded SEP/SEF simultaneously using median nerve stimulation in five healthy human subjects inside an electromagnetically shielded room, combining a low-noise EEG custom-made amplifier (4.7 nV/√Hz) and a custom-made single-channel low-noise MEG (0.5 fT/√Hz @ 1 kHz). Both, low-noise EEG and MEG revealed three spectrally distinct and temporally overlapping evoked components: N20 (<100 Hz), sigma-burst (450-750 Hz), and kappa-burst (850-1200 Hz). The two recording modalities showed similar relative scaling of signal amplitude in all three frequencies domains (EEG [10 nV] ≅ MEG [1 fT]). Pronounced waveform (peak-by-peak) overlap of EEG and MEG signals is observed in the sigma band, whereas in the kappa band overlap was only partial. A decreasing signal-to-noise ratio (SNR; calculated for n = 12.000 averages) from sigma to kappa components characterizes both, electric and magnetic field recordings: Sigma-band SNR was 12.9  ±  5.5/19.8  ±  12.6 for EEG/MEG, and kappa-band SNR at 3.77  ±  0.8/4.5  ±  2.9. High-frequency performance of a tailor-made MEG matches closely with simultaneously recorded low-noise EEG for the non-invasive detection of somatosensory evoked activity at and above 1 kHz. Thus, future multi-channel dual-mode low-noise technology could offer complementary views for source reconstruction of the neural generators underlying such high-frequency responses, and render neural high-frequency processes related to multi-unit spike discharges accessible in non-invasive recordings.

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., (Copyright © 2012 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.)