Cortical activations in cognitive task performance at multiple frequency bands

Although cognitive functions are hypothesized to be mediated by synchronous neuronal interactions in multiple frequency bands among widely distributed cortical areas, we still lack a basic understanding of the distribution and task dependence of oscillatory activity across the cortical map. Here, we ask how the spectral and temporal properties of the local field potential (LFP) vary across the primate cerebral cortex, and how they are modulated during visual short-term memory. We measured the LFP from 55 cortical areas in two macaque monkeys while they performed a visual delayed match to sample task. Analysis of peak frequencies in the LFP power spectra reveals multiple discrete frequency bands between 3–80 Hz that differ between the two monkeys. The LFP power in each band, as well as the Sample Entropy, a measure of signal complexity, display distinct spatial gradients across the cortex, some of which correlate with reported spine counts in layer 3 pyramidal neurons. Cortical areas can be robustly decoded using a small number of spectral and temporal parameters, and significant task dependent increases and decreases in spectral power occur in all cortical areas. These findings reveal pronounced, widespread and spatially organized gradients in the spectral and temporal activity of cortical areas. Task-dependent changes in cortical activity are globally distributed, even for a simple cognitive task.

Altered Cerebellar Oscillations in Parkinson’s Disease Patients during Cognitive and Motor Tasks

A structure for an underwater sound absorber with subwavelength thickness and a quasi-perfect absorption property at multiple frequency bands is reported. This absorber consists of a viscoelastic coating layer embedded with periodically distributed plate scatterers (PSs). The embedded PSs cannot only slow sound waves in the coating, leading to a down-shifted resonance frequency where the absorption is maximized, but also introduce multiple local bending modes and local longitudinal modes in the coating. Via proper selection of the parameters of the PSs and the PS array, multiple local resonance modes of different types in a coating unit can be excited, resulting in quasi-perfect absorption of incident sound at multiple frequencies whose wavelengths are much longer than the thickness of the coating layer. For example, absorption (89%) of underwater sound at 462.9 Hz is achieved by such a layer with a thickness of 6 cm, which is 1.9% of the wavelength of the incident sound. Broadband quasi-perfect absorption can also be realized by coupling of those multiple local resonant modes. This quasi-perfect absorption property can also be observed for sound waves with different incident angles, because a large number of local intrinsic modes could still be excited.

Understanding user-induced effects on signal reception across multiple frequency bands is of great scientific and military importance to the wireless industry. Various onbody locations and directional heading of the user are believed to impact the performance of mobile devices, but there has been little work across multiple frequency bands to quantify these user-induced effects. In this work, we perform a measurement study to explore user effects on radio wave propagation with varying line-of-sight conditions and environments across multiple frequency bands, including white space (500 and 800 MHz), cellular (1800 MHz), and WiFi (2400 MHz) frequency bands. To do so, we first conduct a baseline experiment that characterizes the propagation channel in this environment. We show that the propagation differences for ground-to-ground communication (common in Ad Hoc and WiFi scenarios) and tower-to-ground communication (common in cellular scenarios) are frequency dependent. Then, we measure signal quality as a function of the on-body location of the receiver, directional heading of the user with respect to the transmitter, vegetation type, frequency band, and propagation distance. Our assessment reveals that the user directionality with respect to the transmitter can reduce received signal strength up to 20 dB and reduce throughput by 20.9% at most. We also find that the body can act like an antenna, increasing reception by 4.4 dB and throughput by 14.4% over a reference node at the same distance. Since our study spans many critical (UHF) frequency bands, we believe these results will have far-reaching impact on a broad range of network types.

In this paper, we investigate wireless-powered communication system (WPCS) with multiple frequency bands. When ambient RF signals can be used as an only energy source of wireless devices (WDs), a traditional signal-generator-based communication (SGC) might be demanding due to its high power consumption mainly because of RF-chain, so that backscatter communication (BC) has gained much attention recently. However, the bandwidth efficiency of BC is significantly limited, and thus BC is not always the best option for WPCSs. Thus, we analyze this trade-off by comparing their achievable capacity and show conditions in which the throughput of SGC is higher than BC when multiple frequency bands are available as an energy source and communication channel. Based on the analyses, we propose a hybrid approach with SGC and BC, which enables WDs to decide the best frequency band and communication method in a distributed manner.

ObjectiveThis study aimed to elucidate the distributions of abnormal activities, as well as the functional connectivity and topological properties of brain networks, in patients diagnosed with anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis.MethodFrom February 2016 to February 2025, acute-phase magnetoencephalography (MEG) data were successfully acquired from 16 patients diagnosed with anti-NMDAR encephalitis at the Affiliated Brain Hospital of Nanjing Medical University. MEG was employed to evaluate the power spectral density (PSD) across multiple frequency bands. Further analysis concentrated on functional connectivity and the topological characteristics of brain networks in order to identify distinctive neurophysiological features associated with the condition.ResultsDuring the acute phase, the PSD in the delta band (1–3 Hz) showed greater power in posterior regions and lower power in anterior regions, with the highest energy concentrated bilaterally in the occipitoparietal and temporal areas. In the theta band (5–7 Hz), the PSD was predominantly localized to the bilateral occipitoparietal regions. The beta1 band (13–20 Hz) was primarily distributed in the right temporo-occipitoparietal regions, while the beta2 band (20–30 Hz) was predominantly distributed in the left temporal, occipitoparietal, and certain frontal regions. Functional connectivity analysis revealed enhanced connections between the left caudal anterior cingulate (CAC_L) and the left superior parietal lobe in the delta and theta bands. Increased connectivity was also observed between the left frontal pole and Precuneus_L, CAC_L, and the left superior temporal gyrus (STG_L)in the theta and beta2 bands. Furthermore, enhanced connectivity between STG_L and Pericalcarine_R was observed in the theta, beta2, and gamma bands. Patients with anti-NMDAR encephalitis demonstrated significantly reduced global efficiency and notable increases in average path length, local efficiency, and clustering coefficient in multiple bands, suggesting local clustering of brain networks during the acute phase.ConclusionAlterations in PSD distribution and brain networks across different frequency bands may provide valuable insights into the electrophysiological changes observed in the brains of anti-NMDAR encephalitis patients. Furthermore, these findings may offer valuable mechanistic insights that could contribute to the development of future diagnostic strategies.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00415-025-13302-x.

Recent findings in monkeys suggest that intrinsic periodic spiking activity in selective cortical areas occurs at timescales that follow a sensory or lower order-to-higher order processing hierarchy (Murray JD, Bernacchia A, Freedman DJ, Romo R, Wallis JD, Cai X, Padoa-Schioppa C, Pasternak T, Seo H, Lee D, Wang XJ. Nat Neurosci 17: 1661-1663, 2014). It has not yet been fully explored if a similar timescale hierarchy is present in humans. Additionally, these measures in the monkey studies have not addressed findings that rhythmic activity within a brain area can occur at multiple frequencies. In this study we investigate in humans if regions may be biased toward particular frequencies of intrinsic activity and if a full cortical mapping still reveals an organization that follows this hierarchy. We examined the spectral power in multiple frequency bands (0.5-150 Hz) from task-independent data using magnetoencephalography (MEG). We compared standardized power across bands to find regional frequency biases. Our results demonstrate a mix of lower and higher frequency biases across sensory and higher order regions. Thus they suggest a more complex cortical organization that does not simply follow this hierarchy. Additionally, some regions do not display a bias for a single band, and a data-driven clustering analysis reveals a regional organization with high standardized power in multiple bands. Specifically, theta and beta are both high in dorsal frontal cortex, whereas delta and gamma are high in ventral frontal cortex and temporal cortex. Occipital and parietal regions are biased more narrowly toward alpha power, and ventral temporal lobe displays specific biases toward gamma. Thus intrinsic rhythmic neural activity displays a regional organization but one that is not necessarily hierarchical.NEW & NOTEWORTHY The organization of rhythmic neural activity is not well understood. Whereas it has been postulated that rhythms are organized in a hierarchical manner across brain regions, our novel analysis allows comparison of full cortical maps across different frequency bands, which demonstrate that the rhythmic organization is more complex. Additionally, data-driven methods show that rhythms of multiple frequencies or timescales occur within a particular region and that this nonhierarchical organization is widespread.

Évaluation cognitive de la disposition Mindfulness : approche expérimentale classique et perspectives d’une approche intégrative

Deep reinforcement learning has achieved significant success in solving sequential decision-making tasks. Excellent models usually require the input of valid state signals during training, which is challenging to encode temporal state features for the deep reinforcement learning model. To address this issue, recent methods attempt to encode multi-step sequential state signals so as to obtain more comprehensive observational information. However, these methods usually have a lower performance on complex continuous control tasks because mapping the state sequence into a low-dimensional embedding causes blurring of the immediate state features. In this paper, we propose a multiple frequency bands temporal state representation learning framework. The temporal state signals are decomposed into discrete state signals of various frequency bands by Discrete Fourier Transform (DFT). Then, feature signals filtered out different high-frequency bands are generated. Meanwhile, the mask generator evaluates the weights of signals of various frequency bands and encodes high-quality representations for agent training. Our intuition is that temporal state representations considering multiple frequency bands have high fidelity and stability. We conduct experiments tasks and verify that our method has obvious advantages over the baseline in complex continuous control tasks such as Walker and Crawler.

A large number of traffic accidents due to driver drowsiness have been under more attention of many countries. The organization of the functional brain network is associated with drowsiness, but little is known about the brain network topology that is modulated by drowsiness. To clarify this problem, in this study, we introduce a novel approach to detect driver drowsiness. Electroencephalogram (EEG) signals have been measured during a simulated driving task, in which participants are recruited to undergo both alert and drowsy states. The filtered EEG signals are then decomposed into multiple frequency bands by wavelet packet transform. Functional connectivity between all pairs of channels for multiple frequency bands is assessed using the phase lag index (PLI). Based on this, PLI-weighted networks are subsequently calculated, from which minimum spanning trees are constructed-a graph method that corrects for comparison bias. Statistical analyses are performed on graph-derived metrics as well as on the PLI connectivity values. The major finding is that significant differences in the delta frequency band for three graph metrics and in the theta frequency band for five graph metrics suggesting network integration and communication between network nodes are increased from alertness to drowsiness. Together, our findings also suggest a more line-like configuration in alert states and a more star-like topology in drowsy states. Collectively, our findings point to a more proficient configuration in drowsy state for lower frequency bands. Graph metrics relate to the intrinsic organization of functional brain networks, and these graph metrics may provide additional insights on driver drowsiness detection for reducing and preventing traffic accidents and further understanding the neural mechanisms of driver drowsiness.

Impact of age and obstacle negotiation on timing measures of gait initiation

Difficulty performing concurrent tasks while walking, or dual-task walking, may have negative consequences for safe and independent functional mobility among older adults. Older adults with amnestic mild cognitive impairment (aMCI) may demonstrate slower gait and worse cognitive task speed or accuracy during dual-task conditions. However, prior research has not consistently quantified cognitive performance during dual-task walking, and it is unclear whether changes in dual-task performance are consistent across different task combinations. The purpose of this study was to compare cognitive and gait performance during dual-task conditions in older adults with aMCI and those with normal cognition (NC). An observational cross-sectional study was conducted with 40 community-dwelling older adults, aged 70-95years with aMCI (n=18) and NC (n=22). Gait (self-paced, fast-paced) and cognitive task performance (serial 3, serial 7 subtraction) were quantified during single-task and dual-task conditions. Linear mixed-effects models with a random effect for participants were used to quantify differences between groups (aMCI vs NC) and task conditions (single-task vs dual-task). Further analysis was performed to quantify cognitive performance and gait changes during more challenging dual-task combinations. Across task combinations, gait performance declined for both groups during dual-task conditions. Gait speed was slower during dual-task conditions than single-task conditions in both the NC and aMCI groups for all task combinations. Older adults with aMCI performed worse on cognitive tasks than those with NC during both single-task and dual-task conditions. Correct response rate was slower for people with aMCI than NC during both single-task and dual-task conditions. Dual-task activities, combining gait and cognitive processes, are associated with fall risk and are therefore commonly evaluated in physical therapy care for older adults. Both aMCI and NC groups walked slower during dual-task conditions, but the aMCI group experienced changes with a lower cognitive load. This highlights the importance of quantifying both cognitive and gait performance during dual-task assessments. Changes in cognitive task and gait performance were consistent across different dual-task combinations, which could inform dual-task interventions.

Due to the rapid development of wireless communication systems, good numbers of services and devices use different frequency bands and protocols. To concurrently cover all these services, the antenna in communication devices should operate over multiple frequency bands. The use of wide and multi-band antennas not only reduces the number of antennas necessary to cover multiple frequency bands but also lessens the system complexity, size, and costs. To operate over eight frequency bands to cover sixteen well-established narrow service bands, a planar monopole antenna is proposed for portable communication devices. The proposed antenna is comprised of an inverted F-shaped monopole patch with a rotated L-shaped strip and an F-shaped ground strip with a rotated L-shaped branch. The studied antenna can excite at multiple resonant modes which helps it to achieve eight measured operating bands of 789–921 MHz, 1367–1651 MHz, 1995–2360 MHz, 2968–3374 MHz, 3546–3707, 4091–4405 MHz, 4519–5062 MHz and 5355–6000 MHz. The achieved measured operating bands can cover sixteen popular narrow service bands for 4G/3G/2G, MWT, WiFi, WiMAX, WLAN, and sub-6 GHz 5G wireless communication system. The studied antenna achieved good gain, efficiency and exhibits stable radiation characteristics. Moreover, the antenna does not use any lumped element and left ample space for other circuitries which makes it easier to use in portable devices such as tablets, laptops, etc. with low manufacturing cost.

In this paper, we introduce an effective technique for designing diffusion electromagnetic (EM) surfaces with polarization and angle-insensitive characteristics over multiple wide bands. The proposed EM surface consists of a random pixelated metal structure in the middle of double substrate layers and a metallic ground at the bottom. Phase cancellation for radar cross section (RCS) reduction is achieved by different propagation paths generated by the pixelated metallic layer. The theoretical prediction of the reduction frequency band and reduction value is derived by transmission line theory, which serves as guidance to design the EM surface for the required operating band. Using this technique, an EM surface is designed for 10 dB RCS reduction over multiple frequency bands, and the first two reduction bands are 5.98–16.23 GHz and 26.69–37.1 GHz with fractional bandwidths of 92.3% and 32.6%, respectively. The non-reduction frequency band between the first two reduction bands is almost at the K-band (18–27 GHz), which is unusable for long-range transmission because of its high atmospheric loss. Moreover, the bandwidth of RCS reduction bands is stable for oblique incident angles up to 40° for both TE and TM polarizations. Based on theoretical study and simulation results, a prototype of this EM surface is fabricated and experimentally characterized. The theoretical analysis, simulation and experiment results are in good agreement. The proposed method comprehensively solves the problems of narrow bandwidth, time-consuming optimization of the unit cell, high bistatic RCS value, and sensitivity to polarization and incident angles found in recent RCS reduction research.

Resting state low-frequency brain activity may aid in our understanding of the mechanisms of aging-related cognitive decline. Our purpose was to explore the characteristics of the amplitude of low-frequency fluctuations (ALFF) in different frequency bands of fMRI to better understand cognitive aging. Thirty-seven cognitively normal older individuals underwent a battery of neuropsychological tests and MRI scans at baseline and four years later. ALFF from five different frequency bands (typical band, slow-5, slow-4, slow-3, and slow-2) were calculated and analyzed. A two-way ANOVA was used to explore the interaction effects in voxel-wise whole brain ALFF of the time and frequency bands. Paired-sample t-test was used to explore within-group changes over four years. Partial correlation analysis was performed to assess associations between the altered ALFF and cognitive function. Significant interaction effects of time × frequency were distributed over inferior frontal gyrus, superior frontal gyrus, right rolandic operculum, left thalamus, and right putamen. Significant ALFF reductions in all five frequency bands were mainly found in the right hemisphere and the posterior cerebellum; whereas localization of the significantly increased ALFF were mainly found in the cerebellum at typical band, slow-5 and slow-4 bands, and left hemisphere and the cerebellum at slow-3, slow-2 bands. In addition, ALFF changes showed frequency-specific correlations with changes in cognition. These results suggest that changes of local brain activity in cognitively normal aging should be investigated in multiple frequency bands. The association between ALFF changes and cognitive function can potentially aid better understanding of the mechanisms underlying normal cognitive aging.