Functional brain activity is highly associated with cortical myelination in neonates.

Functional organization of the human cerebral cortex is highly constrained by underlying brain structures, but how functional activity is associated with different brain structures during development is not clear, especially at the neonatal stage. Since long-range functional connectivity is far from mature in the dynamically developing neonatal brain, it is of great scientific significance to investigate the relationship between different structural and functional features at the local level. To this end, for the first time, correlation and regression analyses were performed to examine the relationship between cortical morphology, cortical myelination, age, and local brain functional activity, as well as functional connectivity strength using high-resolution structural and resting-state functional MRI data of 177 neonates (29-44 postmenopausal weeks, 98 male and 79 female) from both static and dynamic perspectives. We found that cortical myelination was most strongly associated with local brain functional activity across the cerebral cortex than other cortical structural features while controlling the age effect. These findings suggest the crucial role of cortical myelination in local brain functional development at birth, providing valuable insights into the fundamental biological basis of functional activity at this early developmental stage.

More light components and less light damage on rats' eyes: evidence for the photobiomodulation and spectral opponency.

The blue-light hazard (BLH) has raised concerns with the increasing applications of white light-emitting diodes (LEDs). Many researchers believed that the shorter wavelength or more light components generally resulted in more severe retinal damage. In this study, based on the conventional phosphor-coated white LED, we added azure (484 nm), cyan (511 nm), and red (664 nm) light to fabricate the low-hazard light source. The low-hazard light sources and conventional white LED illuminated 68 Sprague-Dawley (SD) rats for 7 days. Before and after light exposure, we measured the retinal function, thickness of retinal layers, and fundus photographs. The expression levels of autophagy-related proteins and the activities of oxidation-related biochemical indicators were also measured to investigate the mechanisms of damaging or protecting the retina. With the same correlated color temperature (CCT), the low-hazard light source results in significantly less damage on the retinal function and photoreceptors, even if it has two times illuminance and blue-light hazard-weighted irradiance ([Formula: see text]) than conventional white LED. The results illustrated that [Formula: see text] proposed by IEC 62471 could not exactly evaluate the light damage on rats' retinas. We also figured out that more light components could result in less light damage, which provided evidence for the photobiomodulation (PBM) and spectral opponency on light damage.

A Novel Way to Fill Green Gap of GaN-Based LEDs by Pinning Defects in Nanorod Array.

Nanorod array and planar green-emission InGaN/GaN multi-quantum well (MQW) LEDs were fabricated by lithography, nano-imprinting, and top-down etching technology. The defect-pinning effect of the nanostructure was found for the first time. The ratio of the bright regions to the global area in the panchromatic CL images of green MQW samples increased from 30% to about 90% after nano-fabrication. The overall luminous performance significantly improved. Throughout temperature-dependent photoluminescence (TDPL) and time-resolved PL (TRPL) measurements, the migration and recombination of carriers in the MQWs of green LEDs were analyzed. It was proved that nanostructures can effectively prevent carriers from being captured by surrounding nonradiative recombination centers. The overall PL integral intensity can be enhanced to above 18 times. A much lower carrier lifetime (decreasing from 91.4 to 40.2 ns) and a higher internal quantum efficiency (IQE) (increasing from 16.9% to 40.7%) were achieved. Some disputes on the defect influence were also discussed and clarified.

Functional individual variability development of the neonatal brain.

Individual variability in cognition and behavior results from the differences in brain structure and function that have already emerged before birth. However, little is known about individual variability in brain functional architecture at local level in neonates which is of great significance to explore owing to largely undeveloped long-range functional connectivity and segregated functions in early brain development. To address this, resting-state fMRI data of 163 neonates ranged from 32 to 45 postconceptional weeks (PCW) were used in this study, and various functional features including functional parcellation similarity, local brain activity and local functional connectivity were used to characterize individual functional variability. We observed significantly higher local functional individual variability in superior parietal, sensorimotor, and visual cortex, and lower variability in the frontal, insula and cingulate cortex relative to other regions within each hemisphere. The mean local functional individual variability significantly increased with age, and the age effect was found larger in brain regions such as the occipital, temporal, prefrontal and parietal cortex. Our findings promote the understanding of brain plasticity and regional differential maturation in the early stage.

Brain Connectivity Based Graph Convolutional Networks and Its Application to Infant Age Prediction.

Infancy is a critical period for the human brain development, and brain age is one of the indices for the brain development status associated with neuroimaging data. The difference between the predicted age based on neuroimaging and the chronological age can provide an important early indicator of deviation from the normal developmental trajectory. In this study, we utilize the Graph Convolutional Network (GCN) to predict the infant brain age based on resting-state fMRI data. The brain connectivity obtained from rs-fMRI can be represented as a graph with brain regions as nodes and functional connections as edges. However, since the brain connectivity is a fully connected graph with features on edges, current GCN cannot be directly used for it is a node-based method for sparse graphs. Hence, we propose an edge-based Graph Path Convolution (GPC) method, which aggregates the information from different paths and can be naturally applied on dense graphs. We refer the whole model as Brain Connectivity Graph Convolutional Networks (BC-GCN). Further, two upgraded network structures are proposed by including the residual and attention modules, referred as BC-GCN-Res and BC-GCN-SE to emphasize the information of the original data and enhance influential channels. Moreover, we design a two-stage coarse-to-fine framework, which determines the age group first and then predicts the age using group-specific BC-GCN-SE models. To avoid accumulated errors from the first stage, a cross-group training strategy is adopted for the second stage regression models. We conduct experiments on infant fMRI scans from 6 to 811 days of age. The coarse-to-fine framework shows significant improvements when being applied to several models (reducing error over 10 days). Comparing with state-of-the-art methods, our proposed model BC-GCN-SE with coarse-to-fine framework reduces the mean absolute error of the prediction from >70 days to 49.9 days. The code is now available at https://github.com/SCUT-Xinlab/BC-GCN.

Movie Events Detecting Reveals Inter-Subject Synchrony Difference of Functional Brain Activity in Autism Spectrum Disorder.

Recently, movie-watching fMRI has been recognized as a novel method to explore brain working patterns. Previous researchers correlated natural stimuli with brain responses to explore brain functional specialization by "reverse correlation" methods, which were based on within-group analysis. However, what external stimuli drove significantly different brain responses in two groups of different subjects were still unknown. To address this, sliding time windows technique combined with inter-Subject functional correlation (ISFC) was proposed to detect movie events with significant group differences between autism spectrum disorder (ASD) and typical development (TD) subjects. Then, using inter-Subject correlation (ISC) and ISFC analysis, we found that in three movie events involving character emotions, the ASD group showed significantly lower ISC in the middle temporal gyrus, temporal pole, cerebellum, caudate, precuneus, and showed decreased functional connectivity between large scale networks than that in TD. Under the movie event focusing on objects and scenes shot, the dorsal and ventral attentional networks of ASD had a strong synchronous response. Meanwhile, ASD also displayed increased functional connectivity between the frontoparietal network (FPN) and dorsal attention network (DAN), FPN, and sensorimotor network (SMN) than TD. ASD has its own unique synchronous response rather than being "unresponsive" in natural movie-watching. Our findings provide a new method and valuable insight for exploring the inconsistency of the brain "tick collectively" to same natural stimuli. This analytic approach has the potential to explore pathological mechanisms and promote training methods of ASD.

Common and Distinct Disruptions of Cortical Surface Morphology Between Autism Spectrum Disorder Children With and Without SHANK3 Deficiency.

SH3 and Multiple Ankyrin Repeat Domains 3 (SHANK3)-caused autism spectrum disorder (ASD) may present a unique opportunity to clarify the heterogeneous neuropathological mechanisms of ASD. However, the specificity and commonality of disrupted large-scale brain organization in SHANK3-deficient children remain largely unknown. The present study combined genetic tests, neurobehavioral evaluations, and magnetic resonance imaging, aiming to explore the disruptions of both local and networked cortical structural organization in ASD children with and without SHANK3 deficiency. Multiple surface morphological parameters such as cortical thickness (CT) and sulcus depth were estimated, and the graph theory was adopted to characterize the topological properties of structural covariance networks (SCNs). Finally, a correlation analysis between the alterations in brain morphological features and the neurobehavioral evaluations was performed. Compared with typically developed children, increased CT and reduced nodal degree were found in both ASD children with and without SHANK3 defects mainly in the lateral temporal cortex, prefrontal cortex (PFC), temporo-parietal junction (TPJ), superior temporal gyrus (STG), and limbic/paralimbic regions. Besides commonality, our findings showed some distinct abnormalities in ASD children with SHANK3 defects compared to those without. Locally, more changes in the STG and orbitofrontal cortex were exhibited in ASD children with SHANK3 defects, while more changes in the TPJ and inferior parietal lobe (IPL) in those without SHANK3 defects were observed. For the SCNs, a trend toward regular network topology was observed in ASD children with SHANK3 defects, but not in those without. In addition, ASD children with SHANK3 defects showed more alterations of nodal degrees in the anterior and posterior cingulate cortices and right insular, while there were more disruptions in the sensorimotor areas and the left insular and dorsomedial PFC in ASD without SHANK3 defects. Our findings indicate dissociable disruptions of local and networked brain morphological features in ASD children with and without SHANK3 deficiency. Moreover, this monogenic study may provide a valuable path for parsing the heterogeneity of brain disturbances in ASD.

The effects of dynamic daylight-like light on the rhythm, cognition, and mood of irregular shift workers in closed environment.

Shift workers are mostly suffered from the disruption of circadian rhythm and health problems. In this study, we designed proper light environment to maintain stable circadian rhythm, cognitive performance, and mood status of shift workers. We used five-channel light-emitting diodes to build up the dynamic daylight-like light environment. The illuminance, correlated color temperature, and circadian action factor of light were tunable in the ranges of 226 to 678 lx, 2680 to 7314 K, and 0.32 to 0.96 throughout the day (5:30 to 19:40). During the nighttime, these parameters maintained about 200 lx, 2700 K, and 0.32, respectively. In this light environment, three subjects had engaged in shift work for 38 consecutive days. We measured plasma melatonin, activity counts, continuous performance tests, and visual analogue scale on mood to assess the rhythm, cognitive performance, and mood of subjects. After 38-day shift work, the subjects' peak melatonin concentration increased significantly. Their physiological and behavioral rhythms maintained stable. Their cognitive performance improved significantly after night work, compared with that before night work. Their mood status had no significant change during the 38-day shift work. These results indicated that the light environment was beneficial to maintain circadian rhythm, cognitive performance and mood status during long-term shift work in closed environment.

Investigation on many-body effects in micro-LEDs under ultra-high injection levels.

Micro-LEDs can work under an extremely high injection level and are widely used in high-brightness micro-displays and visible light communication. With the increase of carrier concentration, many-body effects gradually become important factors affecting devices' characteristics. Considering the effects of carrier scattering, bandgap renormalization, and Coulomb enhancement (CE), changes in the electroluminescence spectra of micro-LEDs are analyzed as the current density increases from 49.2 to 358.2 kA/cm2, the latter representing an ultra-high injection level. Affected by plasma screening, CE decreases below about 150 kA/cm2. After that, polarization screening dominates and effectively alleviates the spatial separation of electrons and holes, which results in CE increases to the maximum injection level of 358.2 kA/cm2. It is established that CE promotes radiative recombination processes. Different from the traditional phenomenon of "efficiency droop", the enhanced attraction between carriers leads to an abnormal increase of external quantum efficiency at high current density.

The Effect of Blue-enriched White Light on Cognitive Performances and Sleepiness of Simulated Shift Workers: A Randomized Controlled Trial.

BACKGROUND: Shift work is associated with reduced performance and efficiency, the current study aimed at investigating whether blue-enriched white light could improve workers' performance. METHODS: The study, which adopted a randomized controlled trial, was conducted among 48 simulated shift workers. The participants performed sustained attention task, working memory task, and sleepiness task during night shift work. The data was analyzed using two-way repeated measure ANOVA. RESULTS: The results indicated that, compared to conventional light, participants' correct responses of the sustained attention significantly increased when they were exposed to blue-enriched white light, correspondingly, the commission errors and omission errors declined. Furthermore, the blue-enriched white light had a significant effect on the decrease of sleepiness. However, the working memory was not significantly affected. CONCLUSION: Exposing to blue-enriched white light can improve sustained attention and reduce sleepiness.

Exploring functional brain activity in neonates: A resting-state fMRI study.

The human brain is born with a certain maturity, but quantitatively measuring the maturation and development of functional brain activity in neonates remains a topic of vigorous scientific research, especially the dynamic characteristics. To address this, T1w, T2w, and resting-state functional magnetic resonance imaging (rs-fMRI) data from 40 full-term healthy neonates and 38 adults were adopted in this study. Group differences of local brain activity and functional connectivity between neonates and adults from both static and dynamic perspectives were explored. We found that the neonatal brain is largely immature in general. Sensorimotor areas were the most active, well-connected, and temporally dynamic. Compared with adults, visual and primary auditory areas in neonates showed higher or similar local activity but lower static and dynamic connections with other brain regions. Our findings provide new references and valuable insights for time-varying and local brain functional activity in neonates.

Study on Electron-Induced Surface Plasmon Coupling with Quantum Well Using a Perturbation Method.

Ag nanoparticles (NPs) are filled in a photonic crystal (PhC) hole array on green light emitting diodes (LEDs). The localized surface plasmon (LSP)-quantum well (QW) coupling effect is studied by measuring the cathodoluminescence (CL) spectra impinging at the specific spots on the Ag NPs. Twenty-six percent and fifty-two percent enhancements of the CL intensities are obtained at the center and edge of the Ag NP, respectively, compared to the result that the electron-beam (e-beam) excites the QW directly. To illustrate the coupling process of the three-body system of e-beam-LSP-QW, a perturbation theory combining a three-dimensional (3D) finite difference time domain (FDTD) simulation is put forward. The effects of the polarization orientation of the dipole and the field symmetry of the LSP on the LSP-QW coupling are also discussed.

Investigation on entraining and enhancing human circadian rhythm in closed environments using daylight-like LED mixed lighting.

Humans can undergo circadian disruption and misalignment when living in closed environments without sufficient daylight. Therefore, it is of great significance to investigate the effects of artificial light on the circadian rhythm. In this work, the red, green, blue, warm white, and cool white (RGBWW) five-channel light-emitting diodes (LEDs) were fabricated as the only light sources in the closed environment. The LED mixed lighting showed a high color rendering index (CRI) all the time. During the day, the light simulated the daylight and increased the tunability of the circadian action factor (CAF) and correlated color temperature (CCT). At night, it maintained low CAF and CCT. Three subjects did irregular shift work in the closed environment for 38 days. Their plasma melatonin and daily activity were measured to assess the circadian rhythm. After 38 days, the subjects' peak melatonin times did not shift significantly (p = 0.676), while their peak melatonin concentrations increased apparently (p = 0.005). The start times of the least active 5-h period (L5) in one day fluctuated in a small range. The standard deviation (SD) was <15.11 min in most times. These results demonstrated that the subjects' rhythms maintained stable and were enhanced. The periods of circular cross-correlation between activity and CAF oscillated around 24 h (SD = 15.4 min), indicating the entrainment of light on the stable 24-h rhythm. It was concluded that the daylight-like LED lighting effectively entrained and enhanced the circadian rhythm in the closed environment.

Functional Parcellation of Individual Cerebral Cortex Based on Functional MRI.

The human brain atlas assists us to enhance our scientific understanding of brain structure and function. The typical anatomical atlases are mainly based on brain morphometry which cannot ensure the consistency of structure and function, and are also hard to cover individual functional differences especially in cerebral cortex. Thus, in recent years, functional atlases for individuals have captured great attention, since they are essential not only for identifying the unique functional organization of individual brains, but also to explore individual variations in behaviors. In this study, a novel approach was proposed to accurately parcellate the whole cerebral cortex at the individual level using resting-state functional magnetic resonance image (rs-fMRI). To examine the functional homogeneity in parcellation, a new evaluation criterion, similarity of cluster (SC) coefficient, was proposed. The parcellation results demonstrated the high consistency between two resting-state sessions (Dice >0.72). The most consistent parcellation appeared in the frontal cortex and the least consistent parcellation appeared in the occipital cortex. The functional homogeneity of subregions was high in frontal cortex and insula whereas low in precentral gyrus. According to SC value, the optimal clustering number was about 1600 per hemisphere. Identification accuracy was 100% between two rs-fMRI sessions, and it was also above 0.97 for rest-task and task-task sessions.

CO2 emissions patterns of 26 cities in the Yangtze River Delta in 2015: Evidence and implications.

As a country with the highest CO2 emissions and at the turning point of socio-economic transition, China's effort to reduce CO2 emissions will be crucial for climate change mitigation. Yet, due to geospatial variations of CO2 emissions in different cities, it is important to develop city-specific policies and tools to help control and reduce CO2 emissions. The key question is how to identify and quantify these variations so as to provide reference for the formulation of the corresponding mitigation policies. This paper attempts to answer this question through a case study of 26 cities in the Yangtze River Delta. The CO2 emissions pattern of each city is measured by two statistics: Gini coefficient to describe its quantitative pattern and Global Moran's I index to capture its spatial pattern. It is found that Gini coefficients in all these cities are all greater than 0.94, implying a highly polarized pattern in terms of quantity; and the maximum value for Global Moran's I index is 0.071 with a standard deviation of 0.021, indicating a weak spatial clustering trend but strong difference among these cities. So, it would be more efficient for these cities at current stage to reduce CO2 emissions by focusing on the large emission sources at certain small localities, particularly the very built-up areas rather than covering all the emission sources on every plot of the urban prefectures. And by a combination of these two metrics, the 26 cities are regrouped into nine types with most of them are subject to type HL and ML. These reclassification results then can serve as reference for customizing mitigation policies accordingly and positioning these policies in a more accurate way in each city.

Meta-Network Analysis of Structural Correlation Networks Provides Insights Into Brain Network Development.

Analysis of developmental brain networks is fundamentally important for basic developmental neuroscience. In this paper, we focus on the temporally-covarying connection patterns, called meta-networks, and develop a new mathematical model for meta-network decomposition. With the proposed model, we decompose the developmental structural correlation networks of cortical thickness into five meta-networks. Each meta-network exhibits a distinctive spatial connection pattern, and its covarying trajectory highlights the temporal contribution of the meta-network along development. Systematic analysis of the meta-networks and covarying trajectories provides insights into three important aspects of brain network development.

Different memory patterns of digits: a functional MRI study.

BACKGROUND: Psychological investigations and functional imaging technology have been used to describe neural correlations of different types of memory with various stimuli. Memory with limited storage capacity and a short retention time can be classified as short-term memory (STM) while long-term memory (LTM) can be life-long without defined capacity. METHODS: To identify brain activation pattern associated with different modes of memory for numerical figures, we detected brain activities from twenty-two healthy subjects when performing three types of memory tasks for numbers, namely STM, LTM and working memory (WM), by using functional magnetic resonance imaging (fMRI) technique. RESULTS: The result revealed variable patterns of activation in different brain regions responding to different types of memory tasks. The activation regions with primary processing and transient maintenance of STM for numerical figures are located in the visual cortex and mainly encoded by visual representations, while LTM was encoded by semantics and mainly recruiting left frontal cortex. We also found that subcortical structures, such as the caudate nucleus and the marginal division of the striatum, plays important roles in working memory. CONCLUSIONS: Activation of different brain regions in these three kinds of memories, indicating that different kinds of memories rely on different neural correlates and mental processes.

Effects of interfaces and current spreading on the thermal transport of micro-LEDs for kA-per-square-cm current injection levels.

The three-dimensional thermal characteristics of micro-light-emitting diodes (µLEDs) on GaN and sapphire substrates were studied with forward-voltage methods, thermal transient measurements, and infrared thermal imaging. The µLEDs on the GaN substrate showed an approximately 10 °C lower junction temperature and smaller amplitude of the K factors than those on the sapphire substrate under the current injection level of 4 kA cm-2. The thermal transient measurement showed that the spreading thermal resistances of the mesa, the GaN epilayer, and the interface of the GaN/substrate were reduced significantly for µLEDs on the GaN substrate because of the high-quality GaN crystal and the homogeneous interfaces. The infrared thermal images showed lower total average junction temperatures and more uniform temperature distributions for the µLEDs on the GaN substrate, which were also simulated with APSYS software. The thermal transport mechanisms are discussed for the lateral and vertical directions in the µLEDs.

Spatiotemporal Analysis of Developing Brain Networks.

Recent advances in MRI have made it easier to collect data for studying human structural and functional connectivity networks. Computational methods can reveal complex spatiotemporal dynamics of the human developing brain. In this paper, we propose a Developmental Meta-network Decomposition (DMD) method to decompose a series of developmental networks into a set of Developmental Meta-networks (DMs), which reveal the underlying changes in connectivity over development. DMD circumvents the limitations of traditional static network decomposition methods by providing a novel exploratory approach to capture the spatiotemporal dynamics of developmental networks. We apply this method to structural correlation networks of cortical thickness across subjects at 3-20 years of age, and identify four DMs that smoothly evolve over three stages, i.e., 3-6, 7-12, and 13-20 years of age. We analyze and highlight the characteristic connections of each DM in relation to brain development.

Different Developmental Pattern of Brain Activities in ADHD: A Study of Resting-State fMRI.

There are distinct symptoms for attention deficit hyperactivity disorder (ADHD) at different ages. To explore the developmental mechanism of ADHD from childhood to adolescence, patients from different age groups with ADHD drawn from a large dataset should be investigated. In this study, we hypothesized that there are significant differences in the developmental patterns of local and global brain activities between ADHD and typically developing (TD) individuals. Three voxel-based measurements and the functional connectivity (FC) of the brain networks were extracted from resting-state functional magnetic resonance imaging (fMRI) of both ADHD and TD participants 7-16 years of age. The topological properties of brain networks in both groups were also analyzed, including hubs, hemispheric symmetry, together with local and global efficiency. The results showed, from the local perspective, that the ADHD group had abnormal amplitude of low-frequency fluctuation, fractional amplitude of low-frequency fluctuation, and regional homogeneity in the medial orbital frontal cortex, anterior cingulate cortex, postcentral gyrus, thalamus, precuneus, and cerebellum compared with the TD group. From the global perspective, the aberrant FC between multiple networks, such as the default mode network (DMN), the attention network, and the executive control network, might directly contribute to symptom differences in childhood and adolescence in ADHD patients. Finally, from the developmental perspective, there was delayed maturation of brain networks in the ADHD group, especially in the DMN. Overall, we presented the differences in brain networks between the ADHD and TD group from multiple perspectives and demonstrated the developmental abnormality of brain networks in ADHD patients, contributing to the study of the etiology of ADHD.