Medlinchen8979

Also, ratios of glutamate/glutamine and glutamate/aspartate were assessed as markers of synaptic function and activated glucose metabolism, respectively. Pairwise comparison of metabolite profiles at baseline and 193 ± 4 min after ketamine challenge yielded no differences. Minimal detectable concentration differences estimated with post hoc power analysis (power = 80%, alpha = 0.05) were below 0.5 μmol/g, namely 0.39 μmol/g (∼4%) for glutamate, 0.28 μmol/g (∼10%) for Gln, ∼14% for glutamate/glutamine and ∼8% for glutamate/aspartate. Despite the high sensitivity to detect between-session differences in glutamate and glutamine concentrations, our study did not detect delayed glutamatergic responses to subanesthetic ketamine doses in PCC.A major characteristic of spiking neural networks (SNNs) over conventional artificial neural networks (ANNs) is their ability to spike, enabling them to use spike timing for coding and efficient computing. In this paper, we assess if neuromorphic datasets recorded from static images are able to evaluate the ability of SNNs to use spike timings in their calculations. We have analyzed N-MNIST, N-Caltech101 and DvsGesture along these lines, but focus our study on N-MNIST. First we evaluate if additional information is encoded in the time domain in a neuromorphic dataset. We show that an ANN trained with backpropagation on frame-based versions of N-MNIST and N-Caltech101 images achieve 99.23 and 78.01% accuracy. These are comparable to the state of the art-showing that an algorithm that purely works on spatial data can classify these datasets. Second we compare N-MNIST and DvsGesture on two STDP algorithms, RD-STDP, that can classify only spatial data, and STDP-tempotron that classifies spatiotemporal data. We demonstrate that RD-STDP performs very well on N-MNIST, while STDP-tempotron performs better on DvsGesture. Since DvsGesture has a temporal dimension, it requires STDP-tempotron, while N-MNIST can be adequately classified by an algorithm that works on spatial data alone. This shows that precise spike timings are not important in N-MNIST. N-MNIST does not, therefore, highlight the ability of SNNs to classify temporal data. The conclusions of this paper open the question-what dataset can evaluate SNN ability to classify temporal data?Resting state functional MRI (rs-fMRI) is a widespread and powerful tool for investigating functional connectivity (FC) and brain disorders. However, FC analysis can be seriously affected by random and structured noise from non-neural sources, such as physiology. Thus, it is essential to first reduce thermal noise and then correctly identify and remove non-neural artifacts from rs-fMRI signals through optimized data processing methods. However, existing tools that correct for these effects have been developed for human brain and are not readily transposable to rat data. Therefore, the aim of the present study was to establish a data processing pipeline that can robustly remove random and structured noise from rat rs-fMRI data. It includes a novel denoising approach based on the Marchenko-Pastur Principal Component Analysis (MP-PCA) method, FMRIB's ICA-based Xnoiseifier (FIX) for automatic artifact classification and cleaning, and global signal regression (GSR). Our results show that (I) MP-PCA denoising substantially improves the temporal signal-to-noise ratio, (II) the pre-trained FIX classifier achieves a high accuracy in artifact classification, and (III) both independent component analysis (ICA) cleaning and GSR are essential steps in correcting for possible artifacts and minimizing the within-group variability in control animals while maintaining typical connectivity patterns. Reduced within-group variability also facilitates the exploration of potential between-group FC changes, as illustrated here in a rat model of sporadic Alzheimer's disease.Homeostatic sleep pressure can cause cognitive impairment, in which executive function is the most affected. Previous studies have mainly focused on high homeostatic sleep pressure (long-term sleep deprivation); thus, there is still little related neuro-psycho-physiological evidence based on low homeostatic sleep pressure (12 h of continuous wakefulness) that affects executive function. This study aimed to investigate the impact of lower homeostatic sleep pressure on executive function. Our study included 14 healthy young male participants tested using the Go/NoGo task in normal resting wakefulness (1000 am) and after low homeostatic sleep pressure (1000 pm). Behavioral data (response time and accuracy) were collected, and electroencephalogram (EEG) data were recorded simultaneously, using repeated measures analysis of variance for data analysis. Compared with resting wakefulness, the participants' response time to the Go stimulus was shortened after low homeostatic sleep pressure, and the correct response rate was reduced. Furthermore, the peak amplitude of Go-P2 decreased significantly, and the peak latency did not change significantly. For NoGo stimulation, the peak amplitude of NoGo-P2 decreased significantly (p less then 0.05), and the peak latency was significantly extended (p less then 0.05). Thus, the P2 wave is likely related to the attention and visual processing and reflects the early judgment of the perceptual process. Therefore, the peak amplitude of Go-P2 and NoGo-P2 decreased, whereas the peak latency of NoGo-P2 increased, indicating that executive function is impaired after low homeostatic sleep pressure. This study has shown that the P2 wave is a sensitive indicator that reflects the effects of low homeostatic sleep pressure on executive function, and that it is also an important window to observe the effect of homeostatic sleep pressure and circadian rhythm on cognitive function.Diffusion tensor tractography (DTT) is derived from diffusion tensor imaging. It has allowed visualization and estimation of neural tract injury, which may be associated with the pathogenesis of neuropathic pain (NP). The aim of the present study was to review DTT studies that demonstrated the relationship between neural injuries and NP and to describe the potential use of DTT in the evaluation of neural injuries that are involved in the pathophysiological process of NP. A PubMed search was conducted for articles published until July 3, 2020, which used DTT to investigate the association between neural injuries and NP. The key search phrase for identifying potentially relevant articles was (diffusion tensor tractography AND pain). The following inclusion criteria were applied for article selection (1) studies involving patients with NP and (2) studies in which DTT was applied for the evaluation of NP. Review articles were excluded. Altogether, 108 potentially relevant articles were identified. After reading the titles and abstracts and assessment of eligibility based on the full-text articles, 46 publications were finally included in our review. The results of the included studies suggested that DTT may be beneficial in identifying the pathophysiological mechanism of NP of various origins including central pain caused by brain injuries, trigeminal neuralgia, sciatica, and some types of headache. Further studies are needed to validate the efficacy of DTT in investigating the pathophysiology of other types of NP.Brief fragments of sleep shorter than 15 s are defined as microsleep episodes (MSEs), often subjectively perceived as sleepiness. Their main characteristic is a slowing in frequency in the electroencephalogram (EEG), similar to stage N1 sleep according to standard criteria. selleck chemicals llc The maintenance of wakefulness test (MWT) is often used in a clinical setting to assess vigilance. Scoring of the MWT in most sleep-wake centers is limited to classical definition of sleep (30 s epochs), and MSEs are mostly not considered in the absence of established scoring criteria defining MSEs but also because of the laborious work. We aimed for automatic detection of MSEs with machine learning, i.e., with deep learning based on raw EEG and EOG data as input. We analyzed MWT data of 76 patients. Experts visually scored wakefulness, and according to recently developed scoring criteria MSEs, microsleep episode candidates (MSEc), and episodes of drowsiness (ED). We implemented segmentation algorithms based on convolutional neural networkt of human experts. The code of the algorithms (https//github.com/alexander-malafeev/microsleep-detection) and data (https//zenodo.org/record/3251716) are available.

Fisetin, a natural potent flavonoid, has various beneficial, pharmacological activities. In this study, we investigated expression changes of the fisetin regulating genes in lipopolysaccharide (LPS)-treated RAW264.7 cells and explored the role of fisetin in inflammation and autophagy.

Microarray analysis identified 1,071 genes that were regulated by fisetin in LPS-treated RAW264.7 cells, and these genes were mainly related to the process of immune system response. Quantitative real-time polymerase chain reaction and Bio-Plex analysis indicated that fisetin decreased the expression and secretion of several inflammatory cytokines in cells administered with LPS. Western blot analysis and immunofluorescence assay showed that fisetin decreased microtubule-associated protein 1 light-chain 3B (LC3B) and lysosome-associated membrane protein 1 (LAMP1) expression in LPS-treated cells, while the autophagy inhibitor chloroquine (CQ) could partially reverse this effect. In addition, fisetin reduced the elevated expression of p-PI3K, p-AKT and p-mTOR induced by LPS in a concentration-dependent manner.

Fisetin diminished the expression and secretion of inflammatory cytokines and facilitated autophagosome-lysosome fusion and degradation in LPS-treated RAW264.7 cells via inhibition of the PI3K/AKT/mTOR signaling pathway. Overall, the results of this study provide new clues for the anti-inflammatory mechanism of fisetin and explain the crosstalk between autophagy and inflammation to some extent.

Fisetin diminished the expression and secretion of inflammatory cytokines and facilitated autophagosome-lysosome fusion and degradation in LPS-treated RAW264.7 cells via inhibition of the PI3K/AKT/mTOR signaling pathway. Overall, the results of this study provide new clues for the anti-inflammatory mechanism of fisetin and explain the crosstalk between autophagy and inflammation to some extent.

Celiac disease is a chronic autoimmune disease triggered by gluten exposure in genetically predisposed individuals. A life-long intake of a gluten-free (GF) diet is required for its management. Wheat, rye and barley are eliminated in a GF diet and the nutritional adequacy of the diet has been questioned. In Norway, cereals and bread constitute a key role of the diet and are the main source of fiber intake. Gluten restrictions may therefore offer important implications for nutrient adequacy especially linked to fiber intake in people with celiac disease.

The aim of the study was to investigate the nutritional quality and price of GF products and compare with gluten-containing counterparts available at instead of in the Norwegian market.

The macronutrient content of 423 unique GF products were compared with 337 equivalents with gluten. All products were selected from grocery stores and web-based shops, with the aim of including as many GF products as possible. Listed macronutrients content and price in 11 different food categories were compared to gluten-containing counterparts with Wilcoxon signed rank test.