Zacholucas8268

Here, we provide a synopsis of bidirectional AMPAR dysregulation in animal models of brain disorders and review the preclinical evidence on the therapeutic targeting of AMPARs.Background and Objective Electroencephalography (EEG) can be used to control machines with human intention, especially for paralyzed people in rehabilitation exercises or daily activities. Some effort was put into this but still not enough for online use. To improve the practicality, this study aims to propose an efficient control method based on P300, a special EEG component. Moreover, we have developed an upper-limb assist robot system with the method for verification and hope to really help paralyzed people. Methods We chose P300, which is highly available and easily accepted to obtain the user's intention. Preprocessing and spatial enhancement were firstly implemented on raw EEG data. Then, three approaches- linear discriminant analysis, support vector machine, and multilayer perceptron -were compared in detail to accomplish an efficient P300 detector, whose output was employed as a command to control the assist robot. Results The method we proposed achieved an accuracy of 94.43% in the offline test with the data from eight participants. It showed sufficient reliability and robustness with an accuracy of 80.83% and an information transfer rate of 15.42 in the online test. Furthermore, the extended test showed remarkable generalizability of this method that can be used in more complex application scenarios. Conclusion From the results, we can see that the proposed method has great potential for helping paralyzed people easily control an assist robot to do numbers of things.Determination of muscle forces during motion can help to understand motor control, assess pathological movement, diagnose neuromuscular disorders, or estimate joint loads. Difficulty of in vivo measurement made computational analysis become a common alternative in which, as several muscles serve each degree of freedom, the muscle redundancy problem must be solved. Unlike static optimization (SO), synergy optimization (SynO) couples muscle activations across all time frames, thereby altering estimated muscle co-contraction. This study explores whether the use of a muscle synergy structure within an SO framework improves prediction of muscle activations during walking. A motion/force/electromyography (EMG) gait analysis was performed on five healthy subjects. A musculoskeletal model of the right leg actuated by 43 Hill-type muscles was scaled to each subject and used to calculate joint moments, muscle-tendon kinematics, and moment arms. Muscle activations were then estimated using SynO with two to six synergies and traditional SO, and these estimates were compared with EMG measurements. Synergy optimization neither improved SO prediction of experimental activation patterns nor provided SO exact matching of joint moments. Finally, synergy analysis was performed on SO estimated activations, being found that the reconstructed activations produced poor matching of experimental activations and joint moments. As conclusion, it can be said that, although SynO did not improve prediction of muscle activations during gait, its reduced dimensional control space could be beneficial for applications such as functional electrical stimulation or motion control and prediction.Electrical excitation of neural tissue has wide applications, but how electrical stimulation interacts with neural tissue remains to be elucidated. Here, we propose a new theory, named the Circuit-Probability theory, to reveal how this physical interaction happen. The relation between the electrical stimulation input and the neural response can be theoretically calculated. We show that many empirical models, including strength-duration relationship and linear-non-linear-Poisson model, can be theoretically explained, derived, and amended using our theory. Furthermore, this theory can explain the complex non-linear and resonant phenomena and fit in vivo experiment data. In this letter, we validated an entirely new framework to study electrical stimulation on neural tissue, which is to simulate voltage waveforms using a parallel RLC circuit first, and then calculate the excitation probability stochastically.Memory deficits are a common and frequently-cited consequence of moderate-severe traumatic brain injury (TBI). However, we know less about how TBI influences relational memory, which allows the binding of the arbitrary elements of experience and the flexible use and recombination of relational representations in novel situations. Relational memory is of special interest for individuals with TBI, given the vulnerability of the hippocampus to injury mechanisms, as well as a growing body of literature establishing the role of relational memory in flexible and goal-directed behavior. In this study, participants with and without a history of moderate-severe TBI completed a continuous relational memory task for face-scene pairings. Participants with TBI exhibited a disruption in relational memory not only when tested after a delay, but also when tested with no experimenter-imposed delay after stimulus presentation. Further, canonical assessments of working and episodic memory did not correspond with performance on the face-scene task, suggesting that this task may tap into relational memory differently and with greater sensitivity than standardized memory assessments. These results highlight the need for rigorous assessment of relational memory in TBI, which is likely to detect deficits that have specific consequences for community reintegration and long-term functional outcomes.The magnocellular system has been implicated in the rapid processing of facial emotions, such as fear. Of the various anatomical possibilities, the retino-colliculo-pulvinar route to the amygdala is currently favored. However, it is not clear whether and when amygdala arousal activates the primary visual cortex (V1). Non-linear visual evoked potentials provide a well-accepted technique for examining temporal processing in the magnocellular and parvocellular pathways in the visual cortex. Here, we investigated the relationship between facial emotion processing and the separable magnocellular (K2.1) and parvocellular (K2.2) components of the second-order non-linear multifocal visual evoked potential responses recorded from the occipital scalp (OZ). Stimuli comprised pseudorandom brightening/darkening of fearful, happy, neutral faces (or no face) with surround patches decorrelated from the central face-bearing patch. For the central patch, the spatial contrast of the faces was 30% while the modulation of the per-pixel brightening/darkening was uniformly 10% or 70%. From 14 neurotypical young adults, we found a significant interaction between emotion and contrast in the magnocellularly driven K2.1 peak amplitudes, with greater K2.1 amplitudes for fearful (vs. happy) faces at 70% temporal contrast condition. Taken together, our findings suggest that facial emotional information is present in early V1 processing as conveyed by the M pathway, and more activated for fearful as opposed to happy and neutral faces. An explanation is offered in terms of the contest between feedback and response gain modulation models.Individuals with autism show difficulties in using sentence context to identify the correct meaning of ambiguous words, such as homonyms. In this study, the brain basis of sentence context effects on word understanding during reading was examined in autism spectrum disorder (ASD) and typical development (TD) using magnetoencephalography. The correlates of a history of developmental language delay in ASD were also investigated. Event related field responses at early (150 ms after the onset of a final word) and N400 latencies are reported for three different types of sentence final words dominant homonyms, subordinate homonyms, and unambiguous words. Clear evidence for semantic access was found at both early and conventional N400 latencies in both TD participants and individuals with ASD with no history of language delay. By contrast, modulation of evoked activity related to semantic access was weak and not significant at early latencies in individuals with ASD with a history of language delay. The reduced sensitivity to semantic context in individuals with ASD and language delay was accompanied by strong right hemisphere lateralization at early and N400 latencies; such strong activity was not observed in TD individuals and individuals with ASD without a history of language delay at either latency. These results provide new evidence and support for differential neural mechanisms underlying semantic processing in ASD, and indicate that delayed language acquisition in ASD is associated with different lateralization and processing of language.Tactile stimulation is less frequently used than visual for brain-computer interface (BCI) control, partly because of limitations in speed and accuracy. Non-visual BCI paradigms, however, may be required for patients who struggle with vision dependent BCIs because of a loss of gaze control. With the present study, we attempted to replicate earlier results by Herweg et al. (2016), with several minor adjustments and a focus on training effects and usability. We invited 16 healthy participants and trained them with a 4-class tactile P300-based BCI in five sessions. Their main task was to navigate a virtual wheelchair through a 3D apartment using the BCI. We found significant training effects on information transfer rate (ITR), which increased from a mean of 3.10-9.50 bits/min. Further, both online and offline accuracies significantly increased with training from 65% to 86% and 70% to 95%, respectively. We found only a descriptive increase of P300 amplitudes at Fz and Cz with training. GPCR inhibitor Furthermore, we report subjective data from questionnaires, which indicated a relatively high workload and moderate to high satisfaction. Although our participants have not achieved the same high performance as in the Herweg et al. (2016) study, we provide evidence for training effects on performance with a tactile BCI and confirm the feasibility of the paradigm.Decision-making requires the accumulation of sensory evidence. However, in everyday life, sensory information is often ambiguous and contains decision-irrelevant features. This means that the brain must disambiguate sensory input and extract decision-relevant features. Sensory information processing and decision-making represent two subsequent stages of the perceptual decision-making process. While sensory processing relies on occipito-parietal neuronal activity during the earlier time window, decision-making lasts for a prolonged time, involving parietal and frontal areas. Although perceptual decision-making is being actively studied, its neuronal mechanisms under ambiguous sensory evidence lack detailed consideration. Here, we analyzed the brain activity of subjects accomplishing a perceptual decision-making task involving the classification of ambiguous stimuli. We demonstrated that ambiguity induced high frontal θ-band power for 0.15 s post-stimulus onset, indicating increased reliance on top-down processes, such as expectations and memory. Ambiguous processing also caused high occipito-parietal β-band power for 0.2 s and high fronto-parietal β-power for 0.35-0.42 s post-stimulus onset. We supposed that the former component reflected the disambiguation process while the latter reflected the decision-making phase. Our findings complemented existing knowledge about ambiguous perception by providing additional information regarding the temporal discrepancy between the different cognitive processes during perceptual decision-making.