An Eigenmode Study of Nanoantennas from Terahertz to Optical Frequencies

In this work, we present a rigorous full-wave eigenanalysis for the study of nanoantennas operating at both terahertz (THz) (0.1–10 THz), and infrared/optical (10–750 THz) frequency spectrums. The key idea behind this effort is to reveal the physical characteristics of nanoantennas such that we can transfer and apply the state-of-the-art antenna design methodologies from microwaves to terahertz and optics. Extensive attention is given to penetration depth in metals to reveal whether the surface currents are sufficient for the correct characterization of nanoantennas, or the involvement of volume currents is needed. As we show with our analysis, the penetration depth constantly reduces until the region of 200 THz; beyond this point, it shoots up, requiring volume currents for the exact characterization of the corresponding radiating structures. The cases of a terahertz rectangular patch antenna and a plasmonic nanoantenna are modeled, showing in each case the need of surface and volume currents, respectively, for the antenna’s efficient characterization.

Measuring MEG closer to the brain: Performance of on-scalp sensor arrays

Optically-pumped magnetometers (OPMs) have recently reached sensitivity levels required for magnetoencephalogra-phy (MEG). OPMs do not need cryogenics and can thus be placed within millimetres from the scalp into an array that adapts to the invidual head size and shape, thereby reducing the distance from cortical sources to the sensors. Here, we quantified the improvement in recording MEG with hypothetical on-scalp OPM arrays compared to a 306-channel state-of-the-art SQUID array (102 magnetometers and 204 planar gradiometers).We simulated OPM arrays that measured either normal (nOPM; 102 sensors), tangential (tOPM; 204 sensors), or all components (aOPM; 306 sensors) of the magnetic field. We built forward models based on magnetic resonance images of 10 adult heads; we employed a three-compartment boundary element model and distributed current dipoles evenly across the cortical mantle.Compared to the SQUID magnetometers, nOPM and tOPM yielded 7.5 and 5.3 times higher signal power, while the correlations between the field patterns of source dipoles were reduced by factors of 2.8 and 3.6, respectively. Values of the field-pattern correlations were similar across nOPM, tOPM and SQUID gradiometers. Volume currents reduced the signals of primary currents on average by 10%, 72% and 15% in nOPM, tOPM and SQUID magnetometers, respectively. The information capacities of the OPM arrays were clearly higher than that of the SQUID array. The dipole-localization accuracies of the arrays were similar while the minimum-norm-based point-spread functions were on average 2.4 and 2.5 times more spread for the SQUID array compared to nOPM and tOPM arrays, respectively.

Millivolt-Scale DC Shifts in the Human Scalp EEG: Evidence for a Nonneuronal Generator

Slow shifts in the human scalp-recorded EEG, including those related to changes in brain CO2 levels, have been generally assumed to result from changes in the level of tonic excitation of apical dendrites of cortical pyramidal neurons. We readdressed this issue using DC-EEG shifts elicited in healthy adult subjects by hypo- or hypercapnia. A 3-min period of hyperventilation resulted in a prompt negative shift with a rate of up to 10 μV/s at the vertex (Cz) and an extremely steep dependence (up to 100 μV/mmHg) on the end-tidal Pco2. This shift had a maximum of up to −2 mV at Cz versus the temporal derivations (T3/T4). Hyperventilation-like breathing of 5% CO2-95% O2, which does not lead to a significant hypocapnia, resulted in a near-complete block of the negative DC shift at Cz. Hypoventilation, or breathing 5% CO2 in air at normal respiratory rate, induced a positive shift. The high amplitude of the voltage gradients on the scalp induced by hyperventilation is not consistent with a neuronal origin. Instead, the present data suggest that they are generated by extracortical volume currents driven by a Pco2-dependent potential difference across epithelia separating the cerebrospinal fluid and blood. Since changes in respiratory patterns and, hence, in the level of brain Pco2, are likely to occur under a number of experimental conditions in which slow EEG responses have been reported (e.g., attention shifts, preparatory states, epileptic seizures, and hypoxic episodes), the present results call for a thorough reexamination of the mechanisms underlying scalp-recorded DC-EEG responses.