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Background: The use of near-infrared lasers for transcranial photobiomodulation (tPBM) offers a non-invasive method for influencing brain activity and is beneficial for various neurological conditions. However, comprehensive quantitative studies on its safety are lacking. Objective: This study aims to investigate the safety of 1064-nm laser-based tPBM across brain structure, brain function, neural damage, cognitive ability and tolerance. Methods: We employed a multimodal approach, using magnetic resonance imaging (MRI), electroencephalogram (EEG), biochemical analyses, and cognitive testing to quantitatively assess the potential adverse effects of tPBM on brain structure or function, neurons, glial cells, and executive function (EF). Additionally, a detailed questionnaire was used to evaluate subjective tolerance. Results: At the whole-brain structural level, no significant variations in gray matter, white matter, or cerebrospinal fluid volume or density were observed as a result of tPBM. There was no increase in neuron-specific enolase (NSE) or S100β levels suggesting no neuronal damage, but an unexpected significant reduction in NSE was detected which requires further study to assess its implications. EEG, analyzed through power spectra and expert evaluation, revealed no potential disease-inducing effects. A series of cognitive tests demonstrated no impairment in any of the EF components. Furthermore, the questionnaire data revealed minimal discomfort across fatigue, itching, pain, burning, warmth, dizziness, and drowsiness. Conclusions: Our data indicate that 1064 nm laser tPBM does not induce adverse effects on brain structure or function, nor does it impair cognitive abilities. tPBM is safe for specific parameters, highlighting its good tolerability.

Abstract Cerebral infra-slow oscillation (ISO) is a source of vasomotion in endogenic (E; 0.005–0.02 Hz), neurogenic (N; 0.02–0.04 Hz), and myogenic (M; 0.04–0.2 Hz) frequency bands. In this study, we quantified changes in prefrontal concentrations of oxygenated hemoglobin (Δ[HbO]) and redox-state cytochrome c oxidase (Δ[CCO]) as hemodynamic and metabolic activity metrics, and electroencephalogram (EEG) powers as electrophysiological activity, using concurrent measurements of 2-channel broadband near-infrared spectroscopy and EEG on the forehead of 22 healthy participants at rest. After preprocessing, the multi-modality signals were analyzed using generalized partial directed coherence to construct unilateral neurophysiological networks among the three neurophysiological metrics (with simplified symbols of HbO, CCO, and EEG) in each E/N/M frequency band. The links in these networks represent neurovascular, neurometabolic, and metabolicvascular coupling (NVC, NMC, and MVC). The results illustrate that the demand for oxygen by neuronal activity and metabolism (EEG and CCO) drives the hemodynamic supply (HbO) in all E/N/M bands in the resting prefrontal cortex. Furthermore, to investigate the effect of transcranial photobiomodulation (tPBM), we performed a sham-controlled study by delivering an 800-nm laser beam to the left and right prefrontal cortex of the same participants. After performing the same data processing and statistical analysis, we obtained novel and important findings: tPBM delivered on either side of the prefrontal cortex triggered the alteration or reversal of directed network couplings among the three neurophysiological entities (i.e., HbO, CCO, and EEG frequency-specific powers) in the physiological network in the E and N bands, demonstrating that during the post-tPBM period, both metabolism and hemodynamic supply drive electrophysiological activity in directed network coupling of the prefrontal cortex (PFC). Overall, this study revealed that tPBM facilitates significant modulation of the directionality of neurophysiological networks in electrophysiological, metabolic, and hemodynamic activities.

Abstract Geographical and seasonal variations of gravity wave events in the upper mesosphere were investigated using the nightglow imaging data obtained by the Visible and near-Infrared Spectral Imager (VISI) on the Ionosphere, Mesosphere, upper Atmosphere and Plasmasphere (IMAP) onboard the International Space Station (ISS). The nadir-imaging data of the O2(0–0) atmospheric band (762 nm) with the typical emission peak around 95 km altitude was used to investigate small-scale waves (horizontal wavelengths less than ~ 200 km) on a global scale. To detect gravity wave events, the variance of high-pass filtered nightglow images within a local 100 km radius was evaluated, with a threshold set at three times the standard deviation from the average variance of the background level. A data screening algorithm that evaluates the variance of upwelling contamination light emission was also introduced to remove contaminated data. Applying the variance filter and data screening algorithm to a nearly 3-year data set, from November 2012 to August 2015, occurrence maps of wave events for four seasons were derived. The occurrence maps show a higher frequency of wave events in winter high latitudes (> 40° N/S), considerably attributed to gravity wave activity associated with the polar night jet. Hot spots were observed near orographic sources in winter high latitudes, including the eastern part of North America, Europe, and the southern Andes. In the summer hemisphere, hot spots were detected at mid-to-high latitudes such as North America, Europe, and the eastern side of the Eurasian continent, and at equatorial latitudes just above the intertropical convection zone (ITCZ). They are likely gravity waves from deep convection that arise from mid-latitude summertime thunderstorms and the ITCZ, respectively. During the equinox seasons, hot spots were detected near convective sources such as the Amazon Rainforest, Congo Rainforest, and the Indochina peninsula. Graphical Abstract

This work presents the mathematical definition and programming considerations of an efficient geometric algorithm used to add roofs to polyhedral 3D building models obtained from OpenStreetMap. The algorithm covers numerous roof shapes, including some well-defined shapes that lack an explicit reconstruction theory. These shapes include gabled, hipped, pyramidal, skillion, half-hipped, gambrel, and mansard. The input data for the developed code consist of latitude and longitude coordinates defining the target area. Geospatial data necessary for the algorithm are obtained through a request to the overpass-turbo service. The findings showcase outstanding performance for buildings with straightforward footprints, but they have limitations for the ones with intricate footprints. In future work, further refinement is necessary to solve the mentioned limitation.

This work presents a numerical mesh generation method for 3D urban scenes that could be easily converted into any 3D format, different from most implementations which are limited to specific environments in their applicability. The building models have shaped roofs and faces with static colors, combining the buildings with a ground grid. The building generation uses geographic positions and shape names, which can be extracted from OpenStreetMap. Additional steps, like a computer vision method, can be integrated into the generation optionally to improve the quality of the model, although this is highly time-consuming. Its function is to classify unknown roof shapes from satellite images with adequate resolution. The generation can also use custom geographic information. This aspect was tested using information created by procedural processes. The method was validated by results generated for many realistic scenarios with multiple building entities, comparing the results between using computer vision and not. The generated models were attempted to be rendered under Graphics Library Transmission Format and Unity Engine. In future work, a polygon-covering algorithm needs to be completed to process the building footprints more effectively, and a solution is required for the missing height values in OpenStreetMap.

IntroductionTranscranial photobiomodulation (tPBM) is a non-invasive neuromodulation technique that improves human cognition. The effects of tPBM of the right forehead on neurophysiological activity have been previously investigated using EEG in sensor space. However, the spatial resolution of these studies is limited. Magnetoencephalography (MEG) is known to facilitate a higher spatial resolution of brain source images. This study aimed to image post-tPBM effects in brain space based on both MEG and EEG measurements across the entire human brain.MethodsMEG and EEG scans were concurrently acquired for 6 min before and after 8-min of tPBM delivered using a 1,064-nm laser on the right forehead of 25 healthy participants. Group-level changes in both the MEG and EEG power spectral density with respect to the baseline (pre-tPBM) were quantified and averaged within each frequency band in the sensor space. Constrained modeling was used to generate MEG and EEG source images of post-tPBM, followed by cluster-based permutation analysis for family wise error correction (p < 0.05).ResultsThe 8-min tPBM enabled significant increases in alpha (8–12 Hz) and beta (13–30 Hz) powers across multiple cortical regions, as confirmed by MEG and EEG source images. Moreover, tPBM-enhanced oscillations in the beta band were located not only near the stimulation site but also in remote cerebral regions, including the frontal, parietal, and occipital regions, particularly on the ipsilateral side.DiscussionMEG and EEG results shown in this study demonstrated that tPBM modulates neurophysiological activity locally and in distant cortical areas. The EEG topographies reported in this study were consistent with previous observations. This study is the first to present MEG and EEG evidence of the electrophysiological effects of tPBM in the brain space, supporting the potential utility of tPBM in treating neurological diseases through the modulation of brain oscillations.

Summary: Focusing attention in visual working memory (vWM) depends on the ability to filter distractors and expand the scope of targets. Although many properties of attention processes in vWM have been well documented, it remains unclear how the mechanisms of neurovascular coupling (NVC) function during attention processes in vWM. Here, we show simultaneous multimodal data that reveal the similar temporal and spatial features of attention processes during vWM. These similarities lead to common NVC outcomes across individuals. When filtering out distractors, the electroencephalography (EEG)-informed NVC displayed broader engagement across the frontoparietal network. A negative correlation may exist between behavioral metrics and EEG-informed NVC strength related to attention control. On a dynamic basis, NVC features exhibited higher discriminatory power in predicting behavior than other features alone. These results underscore how multimodal approaches can advance our understanding of the role of attention in vWM, and how NVC fluctuations are associated with actual behavior.

Abstract Enteral feeding is challenging in preterm infants because of gastrointestinal (GI) immaturity. Electrogastrography (EGG) is a non-invasive technology that measures gastric myoelectrical activity and can be utilized to measure changes that occur with maturation at different gestational ages (GA). Three gastric rhythms (GR) exist between 0.5–9 cycles per minute (cpm), namely, bradygastria (0.5 ≤ GR

IntroductionThe quantification of electroencephalography (EEG) microstates is an effective method for analyzing synchronous neural firing and assessing the temporal dynamics of the resting state of the human brain. Transcranial photobiomodulation (tPBM) is a safe and effective modality to improve human cognition. However, it is unclear how prefrontal tPBM neuromodulates EEG microstates both temporally and spectrally.Methods64-channel EEG was recorded from 45 healthy subjects in both 8-min active and sham tPBM sessions, using a 1064-nm laser applied to the right forehead of the subjects. After EEG data preprocessing, time-domain EEG microstate analysis was performed to obtain four microstate classes for both tPBM and sham sessions throughout the pre-, during-, and post-stimulation periods, followed by extraction of the respective microstate parameters. Moreover, frequency-domain analysis was performed by combining multivariate empirical mode decomposition with the Hilbert-Huang transform.ResultsStatistical analyses revealed that tPBM resulted in (1) a significant increase in the occurrence of microstates A and D and a significant decrease in the contribution of microstate C, (2) a substantial increase in the transition probabilities between microstates A and D, and (3) a substantial increase in the alpha power of microstate D.DiscussionThese findings confirm the neurophysiological effects of tPBM on EEG microstates of the resting brain, particularly in class D, which represents brain activation across the frontal and parietal regions. This study helps to better understand tPBM-induced dynamic alterations in EEG microstates that may be linked to the tPBM mechanism of action for the enhancement of human cognition.

In the realm of programming education, enhancing student commitment is pivotal for both academic success and practical application. Traditional methodologies often fall short in catering to the evolving needs of today’s learners. Addressing this gap, this paper introduces a web-based gamified tool designed to transform the pedagogical approach in programming courses. The study’s theoretical contribution lies in its exploration of gamification as a strategy to augment student commitment, bridging the divide between conventional teaching and contemporary learning needs. From a practical standpoint, empirical data encompassing performance metrics, dropout rates, and student feedback demonstrate the tool’s significant positive impact. Notably, students exhibited improved pass rates and reduced dropout tendencies, underscoring the tool’s practical efficacy. Furthermore, feedback highlighted the tool’s usability and the enhanced satisfaction derived from its engagement. Aligned with the existing literature, the findings advocate for the broader adoption of gamification in programming education. This research substantiates the potential of gamification as both a theoretical model and a practical strategy, enriching the discourse on modern programming education.

Abstract Decision-making is one of the most critical activities of human beings. To better understand the underlying neurocognitive mechanism while making decisions under an economic context, we designed a decision-making paradigm based on the newsvendor problem (NP) with two scenarios: low-profit margins as the more challenging scenario and high-profit margins as the less difficult one. The EEG signals were acquired from healthy humans while subjects were performing the task. We adopted the Correlated Component Analysis (CorrCA) method to identify linear combinations of EEG channels that maximize the correlation across subjects ( $$n=23$$ n = 23 ) or trials ( $$n=40$$ n = 40 ). The inter-subject or inter-trial correlation values (ISC or ITC) of the first three components were estimated to investigate the modulation of the task difficulty on subjects’ EEG signals and respective correlations. We also calculated the alpha- and beta-band power of the projection components obtained by the CorrCA to assess the brain responses across multiple task periods. Finally, the CorrCA forward models, which represent the scalp projections of the brain activities by the maximally correlated components, were further translated into source distributions of underlying cortical activity using the exact Low Resolution Electromagnetic Tomography Algorithm (eLORETA). Our results revealed strong and significant correlations in EEG signals among multiple subjects and trials during the more difficult decision-making task than the easier one. We also observed that the NP decision-making and feedback tasks desynchronized the normalized alpha and beta powers of the CorrCA components, reflecting the engagement state of subjects. Source localization results furthermore suggested several sources of neural activities during the NP decision-making process, including the dorsolateral prefrontal cortex, anterior PFC, orbitofrontal cortex, posterior cingulate cortex, and somatosensory association cortex.

A recent study demonstrated that noninvasive measurements of cortical hemodynamics and metabolism in the resting human prefrontal cortex can facilitate quantitative metrics of unilateral mitochondrial–hemodynamic coupling and bilateral connectivity in infraslow oscillation frequencies in young adults. The infraslow oscillation includes three distinct vasomotions with endogenic (E), neurogenic (N), and myogenic (M) frequency bands. The goal of this study was to prove the hypothesis that there are significant differences between young and older adults in the unilateral coupling (uCOP) and bilateral connectivity (bCON) in the prefrontal cortex. Accordingly, we performed measurements from 24 older adults (67.2 ± 5.9 years of age) using the same two-channel broadband near-infrared spectroscopy (bbNIRS) setup and resting-state experimental protocol as those in the recent study. After quantification of uCOP and bCON in three E/N/M frequencies and statistical analysis, we demonstrated that older adults had significantly weaker bilateral hemodynamic connectivity but significantly stronger bilateral metabolic connectivity than young adults in the M band. Furthermore, older adults exhibited significantly stronger unilateral coupling on both prefrontal sides in all E/N/M bands, particularly with a very large effect size in the M band (>1.9). These age-related results clearly support our hypothesis and were well interpreted following neurophysiological principles. The key finding of this paper is that the neurophysiological metrics of uCOP and bCON are highly associated with age and may have the potential to become meaningful features for human brain health and be translatable for future clinical applications, such as the early detection of Alzheimer’s disease.

Transcranial photobiomodulation (tPBM) has been suggested as a non-invasive neuromodulation tool. The repetitive administration of light-emitting diode (LED)-based tPBM for several weeks significantly improves human cognition. To understand the electrophysiological effects of LED-tPBM on the human brain, we investigated alterations by repeated tPBM in vigilance performance and brain networks using electroencephalography (EEG) in healthy participants. Active and sham LED-based tPBM were administered to the right forehead of young participants twice a week for four weeks. The participants performed a psychomotor vigilance task (PVT) during each tPBM/sham experiment. A 64-electrode EEG system recorded electrophysiological signals from each participant during the first and last visits in a 4-week study. Topographical maps of the EEG power enhanced by tPBM were statistically compared for the repeated tPBM effect. A new data processing framework combining the group’s singular value decomposition (gSVD) with eLORETA was implemented to identify EEG brain networks. The reaction time of the PVT in the tPBM-treated group was significantly improved over four weeks compared to that in the sham group. We observed acute increases in EEG delta and alpha powers during a 10 min LED-tPBM while the participants performed the PVT task. We also found that the theta, beta, and gamma EEG powers significantly increased overall after four weeks of LED-tPBM. Combining gSVD with eLORETA enabled us to identify EEG brain networks and the corresponding network power changes by repeated 4-week tPBM. This study clearly demonstrated that a 4-week prefrontal LED-tPBM can neuromodulate several key EEG networks, implying a possible causal effect between modulated brain networks and improved psychomotor vigilance outcomes.

Transcranial photobiomodulation (tPBM) has been considered a safe and effective brain stimulation modality being able to enhance cerebral oxygenation and neurocognitive function. To better understand the underlying neurophysiological effects of tPBM in the human brain, we utilized a 111-channel functional near infrared spectroscopy (fNIRS) system to map cerebral hemodynamic responses over the whole head to 8-min tPBM with 1,064-nm laser given on the forehead of 19 healthy participants. Instead of analyzing broad-frequency hemodynamic signals (0–0.2 Hz), we investigated frequency-specific effects of tPBM on three infra-slow oscillation (ISO) components consisting of endogenic, neurogenic, and myogenic vasomotions. Significant changes induced by tPBM in spectral power of oxygenated hemoglobin concentration (Δ[HbO]), functional connectivity (FC), and global network metrics at each of the three ISO frequency bands were identified and mapped topographically for frequency-specific comparisons. Our novel findings revealed that tPBM significantly increased endogenic Δ[HbO] powers over the right frontopolar area near the stimulation site. Also, we demonstrated that tPBM enabled significant enhancements of endogenic and myogenic FC across cortical regions as well as of several global network metrics. These findings were consistent with recent reports and met the expectation that myogenic oscillation is highly associated with endothelial activity, which is stimulated by tPBM-evoked nitric oxide (NO) release.

Transcranial Photobiomodulation (tPBM) has demonstrated its ability to alter electrophysiological activity in the human brain. However, it is unclear how tPBM modulates brain electroencephalogram (EEG) networks and is related to human cognition. In this study, we recorded 64-channel EEG from 44 healthy humans before, during, and after 8-min, right-forehead, 1,064-nm tPBM or sham stimulation with an irradiance of 257 mW/cm2. In data processing, a novel methodology by combining group singular value decomposition (gSVD) with the exact low-resolution brain electromagnetic tomography (eLORETA) was implemented and performed on the 64-channel noise-free EEG time series. The gSVD+eLORETA algorithm produced 11 gSVD-derived principal components (PCs) projected in the 2D sensor and 3D source domain/space. These 11 PCs took more than 70% weight of the entire EEG signals and were justified as 11 EEG brain networks. Finally, baseline-normalized power changes of each EEG brain network in each EEG frequency band (delta, theta, alpha, beta and gamma) were quantified during the first 4-min, second 4-min, and post tPBM/sham periods, followed by comparisons of frequency-specific power changes between tPBM and sham conditions. Our results showed that tPBM-induced increases in alpha powers occurred at default mode network, executive control network, frontal parietal network and lateral visual network. Moreover, the ability to decompose EEG signals into individual, independent brain networks facilitated to better visualize significant decreases in gamma power by tPBM. Many similarities were found between the cortical locations of SVD-revealed EEG networks and fMRI-identified resting-state networks. This consistency may shed light on mechanistic associations between tPBM-modulated brain networks and improved cognition outcomes.

Goal: It is challenging to clinically discern the severity of neonatal hypoxic ischemic encephalopathy (HIE) within hours after birth in time for therapeutic decision-making for hypothermia. The goal of this study was to determine the shortest duration of the EEG based PAC index to provide real-time guidance for clinical decision-making for neonates with HIE. Methods: Neonates were recruited from a single-center Level III NICU between 2017 and 2019. A time-dependent, PAC-frequency-averaged index, tPACm, was calculated to characterize intrinsic coupling between the amplitudes of 12–30 Hz and the phases of 1–2 Hz oscillation from 6-h EEG data at electrode P3 during the first day of life, using different sizes of moving windows including 10 s, 20 s, 1 min, 2 min, 5 min, 10 min, 20 min, 30 min, 60 min, and 120 min. Time-dependent receiver operating characteristic (ROC) curves were generated to examine the performance of the accurate window tPACm as a neurophysiologic biomarker. Results: A total of 33 neonates (mild-HIE, n = 15 and moderate/severe HIE, n = 18) were enrolled. Mixed effects models demonstrated that tPACm between the two groups was significantly different with window time segments of 3–120 min. By observing the estimates of group differences in tPACm across different window sizes, we found 20 min was the shortest window size to optimally distinguish the two groups (p < 0.001). Time-varying ROC showed significant average area-under-the-curve of 0.82. Conclusions: We demonstrated the feasibility of using tPACm with a 20 min EEG time window to differentiate the severity of HIE and facilitate earlier diagnosis and treatment initiation.

Introduction: Transcranial photobiomodulation (tPBM) is a non-invasive neuromodulation technique that improves human cognition. The effects of tPBM of the right forehead on neurophysiological activity have been previously investigated using EEG in sensor space. However, the spatial resolution of these studies is limited. Magnetoencephalography (MEG) is known to facilitate a higher spatial resolution of brain source images. This study aimed to image post-tPBM effects in brain space based on both MEG and EEG measurements across the entire human brain. Methods: MEG and EEG scans were concurrently acquired for 6 min before and after 8-min of tPBM delivered using a 1,064-nm laser on the right forehead of 25 healthy participants. Group-level changes in both the MEG and EEG power spectral density with respect to the baseline (pre-tPBM) were quantified and averaged within each frequency band in the sensor space. Constrained modeling was used to generate MEG and EEG source images of post-tPBM, followed by cluster-based permutation analysis for family wise error correction (p < 0.05). Results: The 8-min tPBM enabled significant increases in alpha (8-12 Hz) and beta (13-30 Hz) powers across multiple cortical regions, as confirmed by MEG and EEG source images. Moreover, tPBM-enhanced oscillations in the beta band were located not only near the stimulation site but also in remote cerebral regions, including the frontal, parietal, and occipital regions, particularly on the ipsilateral side. Discussion: MEG and EEG results shown in this study demonstrated that tPBM modulates neurophysiological activity locally and in distant cortical areas. The EEG topographies reported in this study were consistent with previous observations. This study is the first to present MEG and EEG evidence of the electrophysiological effects of tPBM in the brain space, supporting the potential utility of tPBM in treating neurological diseases through the modulation of brain oscillations. [ABSTRACT FROM AUTHOR]

Multi-group of strong atmospheric waves (wave packet #1-#5) over China associated with the 2022 Hunga Tonga--Hunga Ha'apai (HTHH) volcano eruptions were observed in the mesopause region using a ground-based airglow network. The phase speed wave packet #1 and wave packet #2 is approximately 312 m/s and 238 m/s respectively, which is consistent with Lamb wave L0 mode and L1 mode from theoretical prediction. The wave fronts of Lamb wave L0 and L1 below the lower thermosphere are vertical, while the wave fronts of L0 mode tilt forward above exhibiting internal wave characteristics, which show good agreement with the theoretical results. Two types of tsunamis were simulated, one type of tsunami is induced by the atmospheric pressure wave (TIAPW) and the other type tsunami is directly induced by the Tonga volcano eruption (TITVE). From backward ray tracing analysis, the TIAPW and TITVE were likely the sources of the acoustic-gravity waves (AGWs) accompanying wave packet #2 and wave packet #4-5, respectively. The scale of tsunamis near the coast is very consistent with the atmospheric AGWs observed by the airglow network. The AGWs triggered by TITVE propagate nearly 3000 km inland with the support of duct and persist for about 4.5 hr and almost covers the Chinese Mainland. The atmospheric pressure wave can directly affect the upper atmosphere, and can also be coupled with the upper atmosphere through the indirect way of generating tsunami and subsequently tsunami generating AGWs, which will provide a new understanding of the coupling between ocean and atmosphere. [ABSTRACT FROM AUTHOR]

This work uses 17 years of upper mesospheric carbon monoxide (CO) and temperature observations by the Microwave Limb Sounder (MLS) on-board the Aura satellite to present and explain the seasonal and interannual variability of the migrating diurnal tide (DW1) component of upper mesospheric CO. This work then compares these observations to simulations by the Specified Dynamics - Whole Atmosphere Community Climate Model with Ionosphere/Thermosphere eXtension (SD-WACCM-X). Results show that, for all seasons, MLS CO DW1 peaks above 85 km and has a latitude structure resembling the (1,1) mode in temperature. On the other hand, SD-WACCM-X DW1 also peaks above 85 km and has a latitude structure resembling the (1,1) mode but it simulates 2 local maximum of the (1,1) mode between 85 km and 92 km. Despite the differences in altitude structure, a tendency analysis and the adiabatic displacement method revealed that, on seasonal and interannual timescales, observed and modelled CO's (1,1) component can be reproduced solely using vertical advection. It was also found that both observed and modelled CO's (1,1) component contains interannual oscillations with periodicities close to that of the Quasi-biennial Oscillation and the El Nino Southern Oscillation. From these results, this work concludes that on seasonal and interannual timescales, the observed and modelled (1,1) mode affects the global structure of upper mesospheric CO primarily through vertical advection. [ABSTRACT FROM AUTHOR]