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Short-term motor adaptation to novel movement dynamics has been shown to involve at least two concurrent learning processes: a slow process that responds weakly to error but retains information well and a fast process that responds strongly to error but has poor retention. This modeling framework can explain several properties of motion-dependent motor adaptation (e.g., 24 h retention). An important assumption of this computational framework is that learning is only based on the experienced movement error, and the effect of noise (either internally generated or externally applied) is not considered. We examined the respective error sensitivity by quantifying adaptation in three subject groups distinguished by the noise added to the motion-dependent perturbation. We assessed the feedforward adaptive changes in motor output and examined the adaptation rate, retention, and decay of learning. Applying a two-state modeling framework showed that the applied noise during training mainly affected the fast learning process, with the slow process largely unaffected; participants in the higher noise groups demonstrated a reduced force profile following training, but the decay rate across groups was similar, suggesting that the slow process was unimpaired across conditions. Collectively, our results provide evidence that noise significantly decreases motor adaptation, but this reduction may be due to its influence over specific learning mechanisms. Importantly, this may have implications for how the motor system compensates for random fluctuations, especially when affected by brain disorders that result in movement tremor (e.g., essential tremor). 

Interval timing is a fundamental component of action and is susceptible to motor-related temporal distortions. Previous studies have shown that concurrent movement biases temporal estimates, but have primarily considered self-modulated movement only. However, real-world encounters often include situations in which movement is restricted or perturbed by environmental factors. In the following experiments, we introduced viscous movement environments to externally modulate movement and investigated the resulting effects on temporal perception. In two separate tasks, participants timed auditory intervals while moving a robotic arm that randomly applied four levels of viscosity. Results demonstrated that higher viscosity led to shorter perceived durations. Using a drift-diffusion model and a Bayesian observer model, we confirmed these biasing effects arose from perceptual mechanisms, instead of biases in decision making. These findings suggest that environmental perturbations are an important factor in movement-related temporal distortions, and enhance the current understanding of the interactions of motor activity and cognitive processes. 

Abstract With the increasing use of Li batteries for storage, their safety issues and energy densities are attracting considerable attention. Recently, replacing liquid organic electrolytes with solid‐state electrolytes (SSE) has been hailed as the key to developing safe and high‐energy‐density Li batteries. In particular, Li_1+xAl_xTi_2−x(PO4)₃(LATP) has been identified as a very attractive SSE for Li batteries due to its excellent electrochemical stability, low production costs, and good chemical compatibility. However, interfacial reactions with electrodes and poor thermal stability at high temperatures severely restrict the practical use of LATP in solid‐state batteries (SSB). Herein, a systematic review of recent advances in LATP for SSBs is provided. This review starts with a brief introduction to the development history of LATP and then summarizes its structure, ion transport mechanism, and synthesis methods. Challenges (e.g., intrinsic brittleness, interfacial resistance, and compatibility) and corresponding solutions (ionic substitution, additives, protective layers, composite electrolytes, etc.) that are critical for practical applications are then discussed. Last, an outlook on the future research direction of LATP‐based SSB is provided.