Velazquezpihl8474

We interpret the vibration-induced effects as consequences of using distorted copies of the central commands to the task-hand during force matching. In particular, using distorted copies of the RC for the antagonist muscle group could account for the differences between the task-hand and match-hand. We conclude that efferent signals may be distorted before their participation in the perceptual process. Such distortions emerge spontaneously and may be amplified by the response of sensory endings to muscle vibration combined over both agonist and antagonist muscle groups.Gold nanoparticles (GNP) have emerged as an alternative to biomaterials in biomedical applications. Research has clearly demonstrated the relative safety and low toxicity of these molecules. However, the possible neuroprotective effect of GNP on the central nervous system (CNS) and its relationship with neurological and psychiatric disorders remain unclear. Zebrafish is a reliable model to investigate the impact of ethanol (EtOH) consumption on the CNS, including reward signaling such as the cholinergic neurotransmission system. Here, we investigated whether cotreatment or pretreatment with GNP prevented EtOH-induced changes in acetylcholinesterase activity and oxidative stress in the brain of zebrafish. We exposed adult zebrafish to 2.5 mg·L-1 GNP 1 h prior to EtOH (1% v/v) treatment for 1 h, and cotreated adult zebrafish simultaneously with both substances for 1 h. Pretreatment with GNP did not prevent EtOH-induced increase in the acetylcholinesterase activity, whereas cotreatment with 2.5 mg·L-1 GNP and EtOH protected against this increase. The results also suggested similar protective effect on oxidative stress parameters in the zebrafish pretreated with GNP at 2.5 mg·L-1. GNP significantly decreased the levels of thiobarbituric acid reactive species and dihydrodichlorofluorescein levels when cotreated with EtOH. GNP also prevented EtOH-induced increase in superoxide dismutase and catalase activities, suggesting a modulatory role of GNP in enzymatic antioxidant defenses. Our results showed that GNP was able to modulate the disruption of cholinergic and oxidative homeostasis in the brain of zebrafish. These findings indicate for the first time that zebrafish is an interesting perspective to investigate nanoparticles against disorders related to alcohol abuse.Developmental cortical malformations (DCM) are one of the main causes of refractory epilepsy. Many are the mechanisms underlying the hyperexcitability in DCM, including the important contribution of N-methyl-D-aspartate receptors (NMDAR). NMDAR blockers are shown to abolish seizures and epileptiform activity. Memantine, a NMDAR antagonist used to treat Alzheimeŕs disease, has been recently investigated as a possible treatment for other neurological disorders. However, the effects on preventing or diminishing seizures are controversial. Here we aimed to evaluate the effects of memantine on pentylenetetrazole (PTZ)-induced seizures in the freeze-lesion (FL) model. Bilateral cortical microgyria were induced (FL) or not (Sham) in male Wistar neonate rats. At P30, subdural electrodes were implanted and 7 days later, video-EEG was recorded in animals receiving either memantine (FL-M or Sham-M) or saline (FL-S or Sham-S), followed by PTZ. Seizures were evaluated by video-EEG during one hour and scored according to Racine scale. The video-EEG analyses revealed that the number of seizures and the total duration of stage IV-V seizures developed during the 1 h-period increased after memantine application in all groups. The EEG power spectral density (PSD) analysis showed an increased PSD of pre-ictal delta in Sham-M animals and increased PSD of slow, middle and fast gamma oscillations after memantine injection that persists during the pre-ictal period in all groups. Our findings suggested that memantine was unable to control the PTZ-induced seizures and that the associated enhancement of PSD of gamma oscillations may contribute to the increased probability of seizure development in these animals.Brain-derived neurotrophic factor (BDNF) plays an important role in processes associated with neuroplasticity and neuroprotection. Evidence suggests that decreased BDNF levels in the central nervous system (CNS) represent a mechanism underlying the development of mood disorders. We hypothesize that both congenital and traumatic brain injury (mTBI)-induced blood-brain barrier (BBB) breakdown are responsible for brain BDNF depletion that contributes to the development of depressive-like symptoms. We employed a mouse model of innate differences in BBB integrity with high (HA) and low (LA) permeability. Depressive-like behaviours were determined under chronic mild stress (CMS) conditions or following mTBI using the tail suspension test (TST). Microvascular leakage of the BBB was evaluated using the Evans Blue Dye (EBD) extravasation method. BDNF concentrations in the brain and plasma were measured using the ELISA. Control HA mice with congenitally high BBB permeability showed exacerbated depressive-like behaviours compared with LA mice. In LA mice, with normal BBB function, mTBI, but not CMS, facilitated depressive-like behaviours, which correlated with enhanced BDNF efflux from the brain. In addition, mTBI triggered upregulation of the Bdnf gene in LA mice to compensate for BDNF loss. No alterations in BDNF levels were observed in mTBI and CMS-exposed HA mice. Moreover, CMS did not induce BBB damage or affect depressive-like behaviours in HA mice despite downregulating Bdnf gene expression. To conclude, BDNF efflux through the mTBI-disrupted BBB is strongly linked to the development of depressive-like behaviours, while the depressive phenotype in mice with congenital BBB dysfunction is independent of BDNF leakage.Mild cognitive impairment (MCI) detection using magnetic resonance image (MRI), plays a crucial role in the treatment of dementia disease at an early stage. Deep learning architecture produces impressive results in such research. Algorithms require a large number of annotated datasets for training the model. Akt inhibitor In this study, we overcome this issue by using layer-wise transfer learning as well as tissue segmentation of brain images to diagnose the early stage of Alzheimer's disease (AD). In layer-wise transfer learning, we used the VGG architecture family with pre-trained weights. The proposed model segregates between normal control (NC), the early mild cognitive impairment (EMCI), the late mild cognitive impairment (LMCI), and the AD. In this paper, 85 NC patients, 70 EMCI, 70 LMCI, and 75 AD patients access form the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Tissue segmentation was applied on each subject to extract the gray matter (GM) tissue. In order to check the validity, the proposed method is tested on preprocessing data and achieved the highest rates of the classification accuracy on AD vs NC is 98.