Targeted memory reactivation of face-name learning depends on ample and undisturbed slow-wave sleep

Face memory, including the ability to recall a person’s name, is of major importance in social contexts. Like many other memory functions, it may rely on sleep. We investigated whether targeted memory reactivation during sleep could improve associative and perceptual aspects of face memory. Participants studied 80 face-name pairs, and then a subset of spoken names with associated background music was presented unobtrusively during a daytime nap. This manipulation preferentially improved name recall and face recognition for those reactivated face-name pairs, as modulated by two factors related to sleep quality; memory benefits were positively correlated with the duration of stage N3 sleep (slow-wave sleep) and negatively correlated with measures of sleep disruption. We conclude that (a) reactivation of specific face-name memories during sleep can strengthen these associations and the constituent memories, and that (b) the effectiveness of this reactivation depends on uninterrupted N3 sleep.

Spatiotemporal Patterns of Adaptation-Induced Slow Oscillations in a Whole-Brain Model of Slow-Wave Sleep

During slow-wave sleep, the brain is in a self-organized regime in which slow oscillations (SOs) between up- and down-states travel across the cortex. While an isolated piece of cortex can produce SOs, the brain-wide propagation of these oscillations are thought to be mediated by the long-range axonal connections. We address the mechanism of how SOs emerge and recruit large parts of the brain using a whole-brain model constructed from empirical connectivity data in which SOs are induced independently in each brain area by a local adaptation mechanism. Using an evolutionary optimization approach, good fits to human resting-state fMRI data and sleep EEG data are found at values of the adaptation strength close to a bifurcation where the model produces a balance between local and global SOs with realistic spatiotemporal statistics. Local oscillations are more frequent, last shorter, and have a lower amplitude. Global oscillations spread as waves of silence across the undirected brain graph, traveling from anterior to posterior regions. These traveling waves are caused by heterogeneities in the brain network in which the connection strengths between brain areas determine which areas transition to a down-state first, and thus initiate traveling waves across the cortex. Our results demonstrate the utility of whole-brain models for explaining the origin of large-scale cortical oscillations and how they are shaped by the connectome.

Meander-DGS Effect on Electromagnetic Bandgap Structure for Power/Ground Noise Suppression in High-Speed Integrated Circuit Packages and PCBs

In this paper, we present the impact of a meander-shaped defected ground structure (MDGS) on the slow-wave characteristics of a lowest-order passband and a low cutoff frequency of the first stopband of an electromagnetic bandgap (EBG) structure for power/ground noise suppression in high-speed integrated circuit packages and printed circuit boards (PCBs). A semi-analytical method is presented to rigorously analyze the MDGS effect. In the analytical method, a closed-form expression for a low cutoff frequency of the MDGS-EBG structure is extracted with an effective characteristic impedance and a slow-wave factor. The proposed analytical method enables the fast analysis of the MDGS-EBG structure so that it can be easily optimized. The analysis of the MDGS effect revealed that the low cutoff frequency increases up to approximately 19% while comparing weakly and strongly coupled MDGSs. It showed that the miniaturization of the MDGS-EBG structure can be achieved. It was experimentally verified that the low cutoff frequency is reduced from 2.54 GHz to 2.00 GHz by decreasing the MDGS coupling coefficient, which is associated with the miniaturization of the MDGS-EBG structure in high-speed packages and PCBs.

Sleep slow-wave oscillations trigger seizures in a genetic epilepsy model of Dravet syndrome

Sleep is the brain state when cortical activity decreases and memory consolidates. However, in human epileptic patients, including genetic epileptic seizures such as Dravet syndrome, sleep is the preferential period when epileptic spike-wave discharges (SWDs) appear, with more severe epileptic symptoms in female patients than male patients, which influencing patient sleep quality and memory. Currently, seizure onset mechanisms during sleep period still remain unknown. Our previous work has shown that the sleep-like state-dependent synaptic potentiation mechanism can trigger epileptic SWDs (Zhang et al., 2021). In this study, using one heterozygous (het) knock-in (KI) transgenic mice (GABAA receptor γ2 subunit Gabrg2Q390X mutation) and an optogenetic method, we hypothesized that slow-wave oscillations (SWOs) themselves in vivo could trigger epileptic seizures. We found that epileptic SWDs in het Gabrg2+/Q390X KI mice exhibited preferential incidence during NREM sleep period, accompanied by motor immobility/ facial myoclonus/vibrissal twitching, with more frequent incidence in female het KI mice than male het KI mice. Optogenetic induced SWOs in vivo significantly increased epileptic seizure incidence in het Gabrg2+/Q390X KI mice with increased duration of NREM sleep or quiet-wakeful states. Furthermore, suppression of SWO-related homeostatic synaptic potentiation by 4-(diethylamino)-benzaldehyde (DEAB) injection (i.p.) greatly decreased seizure incidence in het KI mice, suggesting that SWOs did trigger seizure activity in het KI mice. In addition, EEG delta-frequency (0.1-4 Hz) power spectral density during NREM sleep was significantly larger in female het Gabrg2+/Q390X KI mice than male het Gabrg2+/Q390X KI mice, which likely contributes to the gender difference in seizure incidence during NREM sleep/quiet-wake as that in human patients.

Acoustic Slow-Wave Effect Metamaterial Muffler for Noise Control of HVDC Converter Station

Aiming at the noise control of the HVDC converter station, a one-dimensional two-port metamaterial muffler based on the acoustic slow-wave effect is designed and manufactured. The metamaterial muffler achieves a broadband quasi-perfect absorption of noise from 600 to 900 Hz while ensuring a certain ventilation capacity. In addition, the internal equivalent sound velocity curve and the sound pressure and velocity field of the muffler are used to reveal the mechanism of its broadband quasi-perfect sound absorption. The performance of the muffler was verified by theoretical, numerical, and experimental models. The work in this paper is of guiding significance for solving the noise problem in HVDC converter stations.

Pathological slow-wave activity and impaired working memory binding in post-traumatic amnesia

The mechanism by which information is bound together in working memory is a central question for cognitive neuroscience. This binding is transiently disrupted during periods of post-traumatic amnesia following significant head injuries. The reason for this impairment is unclear but may be due to electrophysiological changes produced by head impacts. These are common and include pathological low frequency activity, which is associated with poorer neurological outcomes and may disrupt cortical communication. Here, we investigate associative memory binding during post-traumatic amnesia and test the hypothesis that misbinding is caused by a disruption in cortical communication produced by the pathological slowing of brain activity. Thirty acute moderate-severe traumatic brain injury patients (mean time since injury = 10 days) and 26 healthy controls were tested with a precision working memory paradigm that required the association of object and location information. A novel entropy ratio measure was calculated from behavioural performance. This provided a continuous measure of the degree of misbinding and the influence of distracting information. Resting state EEG was used to assess the electrophysiological effects of traumatic brain injury. Patients in post-traumatic amnesia showed abnormalities in working memory function and made significantly more misbinding errors than patients who were not in post-traumatic amnesia and controls. Patients showed a higher entropy ratio in the distribution of spatial responses, indicating that working memory recall was abnormally biased by the locations of non-target items suggesting a specific impairment of object and location binding. Slow wave activity was increased following traumatic brain injury. Increases in the delta-alpha ratio indicative of an increase in low frequency power specifically correlated with binding impairment in working memory. In contrast, although connectivity was increased in the theta band and decreased in the alpha band after traumatic brain injury, this did not correlate with working memory impairment. Working memory and electrophysiological abnormalities both normalised at six-month follow-up, in keeping with a transient increase in slow-wave activity causing post-traumatic amnesia that impaired working memory function. These results show that patients in post-traumatic amnesia show high rates of working memory misbinding that are associated with a pathological shift towards lower frequency oscillations.

Reconfigurations in brain networks upon awakening from slow wave sleep: Interventions and implications in neural communication

Sleep inertia is the brief period of impaired alertness and performance experienced immediately after waking. While the neurobehavioral symptoms of sleep inertia are well-described, less is known about the neural mechanisms underlying this phenomenon. A better understanding of the neural processes during sleep inertia may offer insight into the cognitive impairments observed and the awakening process generally. We observed brain activity following abrupt awakening from slow wave sleep during the biological night. Using electroencephalography (EEG) and a network science approach, we evaluated power, clustering coefficient, and path length across frequency bands under both a control condition and a blue-enriched light intervention condition in a within-subject design. We found that under control conditions, the awakening brain is typified by an immediate reduction in global theta, alpha, and beta power. Simultaneously, we observed a decrease in the clustering coefficient and an increase in path length within the delta band. Exposure to blue-enriched light immediately after awakening ameliorated these changes, but only for clustering. Our results suggest that long-range network communication within the brain is crucial to the waking process and that the brain may prioritize these long-range connections during this transitional state. Our study highlights a novel neurophysiological signature of the awakening brain and provides a potential mechanistic explanation for the effect of light in improving performance after waking.