Gillporter6088

Difficulty sleeping in a novel environment is a common phenomenon that is often described as the first night effect (FNE). Previous works have found FNE on sleep architecture and sleep power spectra parameters, especially during non-rapid eye movement (NREM) sleep. However, the impact of FNE on sleep parameters, including local differences in electroencephalographic (EEG) activity across nights, has not been systematically assessed. Here, we performed high-density EEG sleep recordings on 27 healthy individuals on two nights and examined differences in sleep architecture, NREM (stages 2 and 3) EEG power spectra, and NREM power topography across nights. We found higher wakefulness after sleep onset (WASO), reduced sleep efficiency, and less deep NREM sleep (stage 3), along with increased high-frequency NREM EEG power during the first night of sleep, corresponding to small to medium effect sizes (Cohen's d ≤ 0.5). PF-04965842 order Furthermore, study individuals showed significantly lower slow-wave activity in right frontal/prefrontal regions as well as higher sigma and beta activities in medial and left frontal/prefrontal areas, yielding medium to large effect sizes (Cohen's d ≥ 0.5). Altogether, these findings suggest the FNE is characterized by less efficient, more fragmented, shallower sleep that tends to affect especially certain brain regions. The magnitude and specificity of these effects should be considered when designing sleep studies aiming to compare across night effects.Mild traumatic brain injury (mTBI) without skull fracturing is the most common occurrence of all TBIs and is considered as a serious public health concern. Animal models of mTBI are essential to investigation of TBI and its effects. In the current study, we developed and characterized a reproducible mouse model of mild TBI, meanwhile, the effects of this mTBI model, as well as repetitive mTBIs (rmTBIs), on the endothelial function of mouse aortas were also studied. In variety of closed-head models of mTBI, impact velocity, weight, and dwell time are the main parameters that affect the severities of injury. Here, we used a device, converting parameters of velocity, tip weight, and dwell time into impact force, to develop a mouse model of close-head mTBI. Mice were subjected to a mild TBI induced by the impact forces of 500, 600, 700 and 800 kdyn, respectively. Later, brain injuries were assessed histologically and molecularly. Systemic and brain inflammation were measured by plasma cytokine assay and glial fibrillary acidic protein (GFAP) staining. The composite neurobehavioral test revealed significant acute functional deficits in mice after mTBI, corresponding to the degree of injury. Mice brain undergoing mTBI had significant elevated GFAP staining. Plasma cytokines interleukin-1β (IL-1β) and superoxide dismutase (SOD) were significantly increased within 2 h after mTBI. Taken together, these data suggest that the mTBI mouse model introduce within our study exhibits good repeatability and comparable pathological characters. Moreover, we used this mTBI mouse model to determine the effect of single or rmTBIs on systemic vasoconstriction and relaxation. The isometric-tension results indicate that rmTBIs induce a pronounced and long-lasting endothelial dysfunction in mouse aorta.Hyperammonaemic encephalopathy in adults is a rare condition in the absence of liver disease and is associated with a high mortality and risk of permanent neurological deficits. Seldomly, the condition is caused by an inborn error of metabolism in the urea cycle, triggered by an exogenic factor such as gastrointestinal haemorrhage, gastric bypass surgery, starvation, seizures, vigorous exercise, burn injuries, or drugs hampering the elimination of ammonia. Here, we present a fatal case of an unrecognized genetic ornithine transcarbamylase deficiency (OTCD) presenting with a subacute progressive encephalopathy. We review the current literature and discuss the differential diagnosis and treatment options. As swift diagnosis and initiation of treatment is vital, awareness of hyperammonaemic encephalopathy and its possible causes can help improve the prognosis of this condition.Developmental prosopagnosia (DP)-or 'face blindness'-refers to life-long problems with facial recognition in the absence of brain injury. We know that neurodevelopmental disorders tend to co-occur, and this study aims to explore if individuals with self-reported DP also report indications of other neurodevelopmental disorders, deficits, or conditions (developmental comorbidity). In total, 115 individuals with self-reported DP participated in this online cross-sectional survey. Face recognition impairment was measured with a validated self-report instrument. Indications of difficulties with navigation, math, reading, or spelling were measured with a tailored questionnaire using items from published sources. Additional diagnoses were measured with direct questions. We also included open-ended questions about cognitive strengths and difficulties. Results Overall, 57% reported at minimum one developmental comorbidity of interest, with most reflecting specific cognitive impairment (e.g., in memory or object recognition) rather than diagnostic categories (e.g., ADHD, dyslexia). Interestingly, many participants reported cognitive skills or strengths within the same domains that others reported impairment, indicating a diverse pattern of cognitive strengths and difficulties in this sample. The frequency and diversity of self-reported developmental comorbidity suggests that face recognition could be important to consider in future investigations of neurodevelopmental comorbidity patterns.Adding relaxation techniques during nap or auditory stimulation of EEG slow oscillation (SO) during nighttime sleep may limit cognitive impairments in sleep-deprived subjects, potentially through alleviating stress-releasing effects. We compared daytime sleepiness, cognitive performances, and salivary stress biomarker responses in 11 volunteers (aged 18-36) who underwent 5 days of sleep restriction (SR, 3 h per night, with 30 min of daily nap) under three successive conditions control (SR-CT), relaxation techniques added to daily nap (SR-RT), and auditory stimulation of sleep slow oscillations (SO) during nighttime sleep (SR-NS). Test evaluation was performed at baseline (BASE), the fifth day of chronic SR (SR5), and the third and fifth days after sleep recovery (REC3, REC5, respectively). At SR5, less degradation was observed for percentage of commission errors in the executive Go-noGo inhibition task in SR-RT condition compared to SR-CT, and for sleepiness score in SR-NS condition compared both to SR-CT and SR-RT. Beneficial effects of SR-RT and SR-NS were additionally observed on these two parameters and on salivary α-amylase (sAA) at REC3 and REC5. Adding relaxation techniques to naps may help performance in inhibition response, and adding nocturnal auditory stimulation of SO sleep may benefit daytime sleepiness during sleep restriction with persistent effects during recovery. The two strategies activated the autonomic nervous system, as shown by the sAA response.Brain neural activity decoding is an important branch of neuroscience research and a key technology for the brain-computer interface (BCI). Researchers initially developed simple linear models and machine learning algorithms to classify and recognize brain activities. With the great success of deep learning on image recognition and generation, deep neural networks (DNN) have been engaged in reconstructing visual stimuli from human brain activity via functional magnetic resonance imaging (fMRI). In this paper, we reviewed the brain activity decoding models based on machine learning and deep learning algorithms. Specifically, we focused on current brain activity decoding models with high attention variational auto-encoder (VAE), generative confrontation network (GAN), and the graph convolutional network (GCN). Furthermore, brain neural-activity-decoding-enabled fMRI-based BCI applications in mental and psychological disease treatment are presented to illustrate the positive correlation between brain decoding and BCI. Finally, existing challenges and future research directions are addressed.Parkinson's disease (PD) is a neurodegenerative disorder characterized by cardinal motor symptoms and other non-motor symptoms. Studies have investigated various brain areas in PD by detecting white matter alterations using diffusion magnetic resonance imaging processing techniques, which can produce diffusion metrics such as fractional anisotropy and quantitative anisotropy. In this study, we compared the quantitative anisotropy of whole brain regions throughout the subcortical and cortical areas between newly diagnosed PD patients and healthy controls. Additionally, we evaluated the correlations between the quantitative anisotropy of each region and respective neuropsychological test scores to identify the areas most affected by each neuropsychological dysfunction in PD. We found significant quantitative anisotropy differences in several subcortical structures such as the basal ganglia, limbic system, and brain stem as well as in cortical structures such as the temporal lobe, occipital lobe, and insular lobe. Additionally, we found that quantitative anisotropy of some subcortical structures such as the basal ganglia, cerebellum, and brain stem showed the highest correlations with motor dysfunction, whereas cortical structures such as the temporal lobe and occipital lobe showed the highest correlations with olfactory dysfunction in PD. Our study also showed evidence regarding potential neural compensation by revealing higher diffusion metric values in early-stage PD than in healthy controls. We anticipate that our results will improve our understanding of PD's pathophysiology.We previously suggested that stochastic processes are fundamental in the development of sporadic adult onset neurodegenerative disorders. In this study, we develop a theoretical framework to explain stochastic processes at the protein, DNA and RNA levels. We propose that probability determines random sequencing changes, some of which favor neurodegeneration in particular anatomical spaces, and that more than one protein may be affected simultaneously. The stochastic protein changes happen in three-dimensional space and can be considered to be vectors in a space-time continuum, their trajectories and kinetics modified by physiological variables in the manifold of intra- and extra-cellular space. The molecular velocity of these degenerative proteins must obey the second law of thermodynamics, in which entropy is the driver of the inexorable progression of neurodegeneration in the context of the N-body problem of interacting proteins, time-space manifold of protein-protein interactions in phase space, and compounded by the intrinsic disorder of protein-protein networks. This model helps to elucidate the existence of multiple misfolded proteinopathies in adult sporadic neurodegenerative disorders.Disruptive behavior disorders (DBD) refer to a group of conditions that typically share difficulties in modulating aggressive conducts, self-control, and impulses, with resulting behaviors that constitute a threat to others' safety and to social norms [...].