Antioxidant and neuroprotective effects of synthesized sintenin derivatives

Three series of sintenin derivatives (compounds 1-14) were designed and prepared and their antioxidative and neuroprotective effects were evaluated. The in vitro models of scavenging 1,1-diphenyl-2-picrylhydrazyl (DPPH) radicals, chelating ferrous ions, inhibiting the rat brain homogenates lipid peroxidation, and protecting neurons damaged by hydrogen peroxide were employed for bioassays. It was found that sintenin derivatives 4 and 13 showed remarkable antioxidative and neuroprotective activities.

Functional connectivity of major depression disorder using ongoing EEG during music perception

Abstract Objective The functional connectivity (FC) of major depression disorder (MDD) has not been well studied under naturalistic and continuous stimuli conditions. In this study, we investigated the frequency-specific FC of MDD patients exposed to conditions of music perception using ongoing electroencephalogram (EEG). Methods First, we applied the phase lag index (PLI) method to calculate the connectivity matrices and graph theory-based methods to measure the topology of brain networks across different frequency bands. Then, classification methods were adopted to identify the most discriminate frequency band for the diagnosis of MDD. Results During music perception, MDD patients exhibit…

Increasing Stability of EEG Components Extraction Using Sparsity Regularized Tensor Decomposition

Tensor decomposition has been widely employed for EEG signal processing in recent years. Constrained and regularized tensor decomposition often attains more meaningful and interpretable results. In this study, we applied sparse nonnegative CANDECOMP/PARAFAC tensor decomposition to ongoing EEG data under naturalistic music stimulus. Interesting temporal, spectral and spatial components highly related with music features were extracted. We explored the ongoing EEG decomposition results and properties in a wide range of sparsity levels, and proposed a paradigm to select reasonable sparsity regularization parameters. The stability of interesting components extraction from fourteen subjects’ dat…

Shared and Unshared Feature Extraction in Major Depression During Music Listening Using Constrained Tensor Factorization

Ongoing electroencephalography (EEG) signals are recorded as a mixture of stimulus-elicited EEG, spontaneous EEG and noises, which poses a huge challenge to current data analyzing techniques, especially when different groups of participants are expected to have common or highly correlated brain activities and some individual dynamics. In this study, we proposed a data-driven shared and unshared feature extraction framework based on nonnegative and coupled tensor factorization, which aims to conduct group-level analysis for the EEG signals from major depression disorder (MDD) patients and healthy controls (HC) when freely listening to music. Constrained tensor factorization not only preserve…

Combined Behavioral and Mismatch Negativity Evidence for the Effects of Long-Lasting High-Definition tDCS in Disorders of Consciousness: A Pilot Study

Objective: To evaluate the effects of long-term High-definition transcranial direct current stimulation (HD-tDCS) over precuneus on the level of consciousness (LOC) and the relationship between Mismatch negativity (MMN) and the LOC over the therapy period in patients with Disorders of consciousness (DOCs). Methods: We employed a with-in group repeated measures design with an anode HD-tDCS protocol (2 mA, 20 min, the precuneus) on 11 (2 vegetative state and nine minimally conscious state) patients with DOCs. MMN and Coma Recovery Scale-Revised (CRS-R) scores were measured at four time points: before the treatment of HD-tDCS (T0), after a single session of HD-tDCS (T1), after the treatment of…

An Automatic Sleep Scoring Toolbox : Multi-modality of Polysomnography Signals’ Processing

Sleep scoring is a fundamental but time-consuming process in any sleep laboratory. To speed up the process of sleep scoring without compromising accuracy, this paper develops an automatic sleep scoring toolbox with the capability of multi-signal processing. It allows the user to choose signal types and the number of target classes. Then, an automatic process containing signal pre-processing, feature extraction, classifier training (or prediction) and result correction will be performed. Finally, the application interface displays predicted sleep structure, related sleep parameters and the sleep quality index for reference. To improve the identification accuracy of minority stages, a layer-w…

Spatial Properties of Mismatch Negativity in Patients with Disorders of Consciousness

In recent decades, event-related potentials have been used for the clinical electrophysiological assessment of patients with disorders of consciousness (DOCs). In this paper, an oddball paradigm with two types of frequencydeviant stimulus (standard stimuli were pure tones of 1000 Hz; small deviant stimuli were pure tones of 1050 Hz; large deviant stimuli were pure tones of 1200 Hz) was applied to elicit mismatch negativity (MMN) in 30 patients with DOCs diagnosed using the JFK Coma Recovery ScaleRevised (CRS-R). The results showed that the peak amplitudes of MMN elicited by both large and small deviant stimuli were significantly different from baseline. In terms of the spatial properties of…

Altered EEG Oscillatory Brain Networks During Music-Listening in Major Depression

To examine the electrophysiological underpinnings of the functional networks involved in music listening, previous approaches based on spatial independent component analysis (ICA) have recently been used to ongoing electroencephalography (EEG) and magnetoencephalography (MEG). However, those studies focused on healthy subjects, and failed to examine the group-level comparisons during music listening. Here, we combined group-level spatial Fourier ICA with acoustic feature extraction, to enable group comparisons in frequency-specific brain networks of musical feature processing. It was then applied to healthy subjects and subjects with major depressive disorder (MDD). The music-induced oscil…

Xenon Recovery by DD3R Zeolite Membranes: Application in Anaesthetics.

Xe is only produced by cryogenic distillation of air, and its availability is limited by the extremely low abundance. Therefore, Xe recovery after usage is the only way to guarantee sufficient supply and broad application. Herein we demonstrate DD3R zeolite as a benchmark membrane material for CO2 /Xe separation. The CO2 permeance after an optimized membrane synthesis is one order magnitude higher than for conventional membranes and is less susceptible to water vapour. The overall membrane performance is dominated by diffusivity selectivity of CO2 over Xe in DD3R zeolite membranes, whereby rigidity of the zeolite structure plays a key role. For relevant anaesthetic composition ( 320 h). Thi…

Response to Discussion on Y. Zhu, X. Wang, K. Mathiak, P. Toiviainen, T. Ristaniemi, J. Xu, Y. Chang and F. Cong, Altered EEG Oscillatory Brain Networks During Music-Listening in Major Depression, International Journal of Neural Systems, Vol. 31, No. 3 (2021) 2150001 (14 pages).