Neurovascular coupling in eye-open-eye-close task and resting state: Spectral correspondence between concurrent EEG and fMRI.

Neurovascular coupling serves as an essential neurophysiological mechanism in functional neuroimaging, which is generally presumed to be robust and invariant across different physiological states, encompassing both task engagement and resting state. Nevertheless, emerging evidence suggests that neurovascular coupling may exhibit state dependency, even in normal human participants. To investigate this premise, we analyzed the cross-frequency spectral correspondence between concurrently recorded electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data, utilizing them as proxies for neurovascular coupling during the two conditions: an eye-open-eye-close (EOEC) task and a resting state. We hypothesized that given the state dependency of neurovascular coupling, EEG-fMRI spectral correspondences would change between the two conditions in the visual system. During the EOEC task, we observed a negative phase-amplitude-coupling (PAC) between EEG alpha-band and fMRI visual activity. Conversely, in the resting state, a pronounced amplitude-amplitude-coupling (AAC) emerged between EEG and fMRI signals, as evidenced by the spectral correspondence between the EEG gamma-band of the midline occipital channel (Oz) and the high-frequency fMRI signals (0.15-0.25 Hz) in the visual network. This study reveals distinct scenarios of EEG-fMRI spectral correspondence in healthy participants, corroborating the state-dependent nature of neurovascular coupling.

Synthesis of Optically Active Organofluorides by Ring Opening of Oxazolidinone-Fused Aziridines.

A general method for synthesizing optically active, primary, secondary, and tertiary organofluorides was developed. This chiral pool synthesis utilized the skeleton of arabinose to generate diastereomerically pure 2-oxazolidinone-fused aziridines, which underwent ring opening with a fluoride anion. The adducts, polyoxygenated organofluorides, were useful precursors to various fluorinated compounds, such as fluorinated amino acids.

Jellyfish Search-Optimized Deep Learning for Compressive Strength Prediction in Images of Ready-Mixed Concrete.

Most building structures that are built today are built from concrete, owing to its various favorable properties. Compressive strength is one of the mechanical properties of concrete that is directly related to the safety of the structures. Therefore, predicting the compressive strength can facilitate the early planning of material quality management. A series of deep learning (DL) models that suit computer vision tasks, namely the convolutional neural networks (CNNs), are used to predict the compressive strength of ready-mixed concrete. To demonstrate the efficacy of computer vision-based prediction, its effectiveness using imaging numerical data was compared with that of the deep neural networks (DNNs) technique that uses conventional numerical data. Various DL prediction models were compared and the best ones were identified with the relevant concrete datasets. The best DL models were then optimized by fine-tuning their hyperparameters using a newly developed bio-inspired metaheuristic algorithm, called jellyfish search optimizer, to enhance the accuracy and reliability. Analytical experiments indicate that the computer vision-based CNNs outperform the numerical data-based DNNs in all evaluation metrics except the training time. Thus, the bio-inspired optimization of computer vision-based convolutional neural networks is potentially a promising approach to predict the compressive strength of ready-mixed concrete.

Think Hard or Think Smart: Network Reconfigurations After Divergent Thinking Associate With Creativity Performance.

Evidence suggests divergent thinking is the cognitive basis of creative thoughts. Neuroimaging literature using resting-state functional connectivity (RSFC) has revealed network reorganizations during divergent thinking. Recent studies have revealed the changes of network organizations when performing creativity tasks, but such brain reconfigurations may be prolonged after task and be modulated by the trait of creativity. To investigate the dynamic reconfiguration, 40 young participants were recruited to perform consecutive Alternative Uses Tasks (AUTs) for divergent thinking and two resting-state scans (before and after AUT) were used for mapping the brain reorganizations after AUT. We split participants into high- and low-creative groups based on creative achievement questionnaire (CAQ) and targeted on reconfigurations of the two brain networks: (1) default-mode network (DMN) and (2) the network seeded at the left inferior frontal gyrus (IFG) because the between-group difference of AUT-induced brain activation located at the left IFG. The changes of post-AUT RSFCs (DMN and IFGN) indicated the prolonged effect of divergent thinking. More specifically, the alterations of RSFCIFG-AG and RSFCIFG-IPL (AG: angular gyrus, IPG: inferior parietal lobule) in the high-creative group had positive relationship with their AUT performances (originality and fluency), but not found in the low-creative group. Furthermore, the RSFC changes of DMN did not present significant relationships with AUT performances. The findings not only confirmed the possibility of brain dynamic reconfiguration following divergent thinking, but also suggested the distinct IFGN reconfiguration between individuals with different creativity levels.

Synthesis of Methyl l-Kijanosides by Regio- and Stereoselective Ring Opening of 2-Oxazolidinone-Fused Aziridines.

Kijanose is one of the most highly functionalized deoxysugars found in nature and a challenging synthetic target. We found that the ring opening of trisubstituted, 2-oxazolidinone-fused aziridines is regio- and stereoselective, and the azide adduct has the same stereochemistry as that of kijanose after converting the azido to a nitro group. Therefore, both α- and ß-methyl l-kijanosides were prepared from ethyl l-lactate in 14% total yield.