Notes

Sulfonylurea use is connected with greater infarct dimension inside individuals using diabetes as well as ST-elevation myocardial infarction.
The present review focuses on i) research updates on traditional uses, ii) phytopharmacology and clinical studies on Berberis species, and iii) active metabolites in the prevention and treatment of diabetes and other metabolic diseases with a detailed mechanism of action. Furthermore, the review critically analyzes current research gaps in the therapeutic use of Berberis species and berberine and provides future recommendations. Copyright © 2020 Belwal, Bisht, Devkota, Ullah, Khan, Pandey, Bhatt and Echeverría.[This corrects the article DOI 10.3389/fnagi.2019.00343.]. Copyright © 2020 Smolek, Cubinkova, Brezovakova, Valachova, Szalay, Zilka and Jadhav.The study investigated the consequences of age-related decline in inhibition processes on intentional switching between bimanual coordination patterns. Fifteen young (24±2.8 years) and 20 older adults (69±5.3 years) performed Stroop tasks and bimanual coordination tasks. Stroop tasks included neutral, congruent, and incongruent conditions. Response time and error rate were measured. Bimanual coordination tasks consisted of performing in-phase (IP) and anti-phase (AP) patterns. Participants were requested to switch as quickly as possible from one pattern to the other, resulting in two different switching directions (AP to IP; IP to AP). Mean and standard deviation (SD) of the continuous relative phase (CRP) were calculated pre- and post-switching for each participant. Total switching time (TST) was measured. selleck products The switching phase was also decomposed into reaction time (RT) and reversal time (REvT). Pearson correlation analyses were performed to test for correlations between (i) SD of CRP and response time in Strat inhibition processes are involved in switching between bimanual coordination patterns, at least to trigger the early phase of switching. They also support the hypothesis that inhibition processes are more involved in maintaining the AP pattern and switching to the IP pattern. Finally, age-related changes in switching times seem to be prominently mediated by alterations of inhibition processes. Copyright © 2020 Temprado, Torre, Langeard, Julien-Vintrou, Devillers-Réolon, Sleimen-Malkoun and Berton.An intrinsic problem when using hemodynamic responses for the brain-machine interface is the slow nature of the physiological process. In this paper, a novel method that estimates the oxyhemoglobin changes caused by neuronal activations is proposed and validated. In monitoring the time responses of blood-oxygen-level-dependent signals with functional near-infrared spectroscopy (fNIRS), the early trajectories of both oxy- and deoxy-hemoglobins in their phase space are scrutinized. Furthermore, to reduce the detection time, a prediction method based upon a kernel-based recursive least squares (KRLS) algorithm is implemented. In validating the proposed approach, the fNIRS signals of finger tapping tasks measured from the left motor cortex are examined. The results show that the KRLS algorithm using the Gaussian kernel yields the best fitting for both ΔHbO (i.e., 87.5%) and ΔHbR (i.e., 85.2%) at q = 15 steps ahead (i.e., 1.63 s ahead at a sampling frequency of 9.19 Hz). This concludes that a neuronal activation can be concluded in about 0.1 s with fNIRS using prediction, which enables an almost real-time practice if combined with EEG. link2 Copyright © 2020 Zafar and Hong.Repetitive and intensive physiotherapy is indispensable to patients with ankle disabilities. Increasingly robot-assisted technology has been employed in the treatment to reduce the burden of the therapists and the related costs of the patients. This paper proposes a configuration of a wearable parallel mechanism to supplement the equipment selection for ankle rehabilitation. The kinematic analysis, i.e., the inverse position solution and Jacobian matrices, is elaborated. Several performance indices, including the reachable workspace index, motion isotropy index, force transfer index, and maximum torque index, are developed based on the derived kinematic solution. Moreover, according to the proposed kinematic configuration and wearable design concept, the mechanical structure that contains a basic machine-drive system and a multi-model position/force data collection system is designed in detail. Finally, the results of the performance evaluation indicate that the wearable parallel robot possesses sufficient motion isotropy, high force transfer performance, and large maximum torque performance within a large workspace that can cover all possible range of motion of human ankle complex, and is suitable for ankle rehabilitation. Copyright © 2020 Zuo, Li, Dong, Zhou, Fan and Kong.In this study, we developed a novel robotic system with a muscle-to-muscle interface to enhance rehabilitation of post-stroke patients. The developed robotic rehabilitation system was designed to provide patients with stage appropriate physical rehabilitation exercise and muscular stimulation. Unlike the position-based control of conventional bimanual robotic therapies, the developed system stimulates the activities of the target muscles, as well as the joint movements of the paretic limb. The robot-assisted motion and the electrical stimulation on the muscles of the paretic side are controlled by on-line comparison of the motion and the muscle activities between the paretic and unaffected sides. With the developed system, the rehabilitation exercise can be customized and modulated depending on the patient's stage of motor recovery after stroke. The system can be operated in three different modes allowing both passive and active exercises. The effectiveness of the developed system was verified with healthy human subjects, where the subjects were paired to serve as the unaffected side and the paretic side of a hemiplegic patient. Copyright © 2020 Bong, Jung, Park, Kim and Park.Natural brains perform miraculously well in learning new tasks from a small number of samples, whereas sample efficient learning is still a major open problem in the field of machine learning. Here, we raise the question, how the neural coding scheme affects sample efficiency, and make first progress on this question by proposing and analyzing a learning algorithm that uses a simple reinforce-type plasticity mechanism and does not require any gradients to learn low dimensional mappings. It harnesses three bio-plausible mechanisms, namely, population codes with bell shaped tuning curves, continous attractor mechanisms and probabilistic synapses, to achieve sample efficient learning. We show both theoretically and by simulations that population codes with broadly tuned neurons lead to high sample efficiency, whereas codes with sharply tuned neurons account for high final precision. Moreover, a dynamic adaptation of the tuning width during learning gives rise to both, high sample efficiency and high final precision. We prove a sample efficiency guarantee for our algorithm that lies within a logarithmic factor from the information theoretical optimum. Our simulations show that for low dimensional mappings, our learning algorithm achieves comparable sample efficiency to multi-layer perceptrons trained by gradient descent, although it does not use any gradients. Furthermore, it achieves competitive sample efficiency in low dimensional reinforcement learning tasks. From a machine learning perspective, these findings may inspire novel approaches to improve sample efficiency. From a neuroscience perspective, these findings suggest sample efficiency as a yet unstudied functional role of adaptive tuning curve width. link3 Copyright © 2020 Meier, Dang-Nhu and Steger.Neurons in many brain regions exhibit spontaneous, intrinsic rhythmic firing activity. This rhythmic firing activity may determine the way in which these neurons respond to extrinsic synaptic inputs. We hypothesized that neurons should be most responsive to inputs at the frequency of the intrinsic oscillation frequency. We addressed this question in the ventral tegmental area (VTA), a dopaminergic nucleus in the midbrain. VTA neurons have a unique propensity to exhibit spontaneous intrinsic rhythmic activity in the 1-5 Hz frequency range, which persists in the in-vitro brain slice, and form a network of weakly coupled oscillators. Here, we combine in-vitro simultaneous recording of action potentials from a 60 channel multi-electrode-array with cell-type-specific optogenetic stimulation of the VTA dopamine neurons. We investigated how VTA neurons respond to wide-band stochastic (Poisson input) as well as regular laser pulses. Strong synchrony was induced between the laser input and the spike timing of the neurons, both for regular pulse trains and Poisson pulse trains. For rhythmically pulsed input, the neurons demonstrated resonant behavior with the strongest phase locking at their intrinsic oscillation frequency, but also at half and double the intrinsic oscillation frequency. Stochastic Poisson pulse stimulation provided a more effective stimulation of the entire population, yet we observed resonance at lower frequencies (approximately half the oscillation frequency) than the neurons' intrinsic oscillation frequency. The non-linear filter characteristics of dopamine neurons could allow the VTA to predict precisely timed future rewards based on past sensory inputs, a crucial component of reward prediction error signaling. In addition, these filter characteristics could contribute to a pacemaker role for the VTA in synchronizing activity with other regions like the prefrontal cortex and the hippocampus. Copyright © 2020 van der Velden, Vinck and Wadman.Purpose Gliomas are the most common primary brain malignancies, with varying degrees of aggressiveness and prognosis. Understanding of tumor biology and intra-tumor heterogeneity is necessary for planning personalized therapy and predicting response to therapy. Accurate tumoral and intra-tumoral segmentation on MRI is the first step toward understanding the tumor biology through computational methods. The purpose of this study was to design a segmentation algorithm and evaluate its performance on pre-treatment brain MRIs obtained from patients with gliomas. Materials and Methods In this study, we have designed a novel 3D U-Net architecture that segments various radiologically identifiable sub-regions like edema, enhancing tumor, and necrosis. Weighted patch extraction scheme from the tumor border regions is proposed to address the problem of class imbalance between tumor and non-tumorous patches. The architecture consists of a contracting path to capture context and the symmetric expanding path that enables pore and enhancing tumor, respectively. Conclusion The results of this study show the potential of patch-based 3D U-Net for the accurate intra-tumor segmentation. From experiments, it is observed that the weighted patch-based segmentation approach gives comparable performance with the pixel-based approach when there is a thin boundary between tumor subparts. Copyright © 2020 Baid, Talbar, Rane, Gupta, Thakur, Moiyadi, Sable, Akolkar and Mahajan.Many people with cognitive disabilities avoid outside activities, apparently for fear of getting lost. However, little is known about the nature of the difficulties encountered and the ways in which these individuals deal with them. None of the few studies on wayfinding by people with cognitive disabilities have explored the various specific difficulties they meet in everyday life. Using both a qualitative and quantitative methodology, this study aimed at profiling the types of difficulties encountered in urban mobility and the associated problem-solving strategies. In order to provide more direct evidence from the field, we conducted semi-structured interviews using the critical incident technique (Flanagan, 1954). Among the 66 participants interviewed, 44 had cognitive disabilities and 22 were matched controls. The analysis of the transcripts showed in particular an overall reduced autonomy in problem-solving strategies for people with a cognitive disability. The multiple correspondence analysis highlighted three main types of complex situations, covering a comprehensive range of complex situations that are met in everyday life by these individuals.
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