Optimum take-off angle in the long jump

In this study, we found that the optimum take-off angle for a long jumper may be predicted by combining the equation for the range of a projectile in free flight with the measured relations between take-off speed, take-off height and take-off angle for the athlete. The prediction method was evaluated using video measurements of three experienced male long jumpers who performed maximum-effort jumps over a wide range of take-off angles. To produce low take-off angles the athletes used a long and fast run-up, whereas higher take-off angles were produced using a progressively shorter and slower run-up. For all three athletes, the take-off speed decreased and the take-off height increased as the athlete jumped with a higher take-off angle. The calculated optimum take-off angles were in good agreement with the athletes' competition take-off angles

Reduction in Learning Rates Associated with Anterograde Interference Results from Interactions between Different Timescales in Motor Adaptation

Prior experiences can influence future actions. These experiences can not only drive adaptive changes in motor output, but they can also modulate the rate at which these adaptive changes occur. Here we studied anterograde interference in motor adaptation – the ability of a previously learned motor task (Task A) to reduce the rate of subsequently learning a different (and usually opposite) motor task (Task B). We examined the formation of the motor system's capacity for anterograde interference in the adaptive control of human reaching-arm movements by determining the amount of interference after varying durations of exposure to Task A (13, 41, 112, 230, and 369 trials). We found that the amount of anterograde interference observed in the learning of Task B increased with the duration of Task A. However, this increase did not continue indefinitely; instead, the interference reached asymptote after 15–40 trials of Task A. Interestingly, we found that a recently proposed multi-rate model of motor adaptation, composed of two distinct but interacting adaptive processes, predicts several key features of the interference patterns we observed. Specifically, this computational model (without any free parameters) predicts the initial growth and leveling off of anterograde interference that we describe, as well as the asymptotic amount of interference that we observe experimentally (R2 = 0.91). Understanding the mechanisms underlying anterograde interference in motor adaptation may enable the development of improved training and rehabilitation paradigms that mitigate unwanted interference.Engineering and Applied Science

Error Correction, Sensory Prediction, and Adaptation in Motor Control

Motor control is the study of how organisms make accurate goal-directed movements. There are two problems that the motor system must solve in order to achieve such control. The first problem is that sensory feedback is noisy and delayed, which can make movements inaccurate and unstable. The second problem is that the relationship between a motor command and the movement it produces is variable, as the body and the environment can both change. A solution is to build adaptive internal models of the body and the world. The predictions of these internal models, called forward models because they transform motor commands into sensory consequences, can be used to both produce a lifetime of calibrated movements, and to improve the ability of the sensory system to estimate the state of the body and the world around it. Forward models are only useful if they produce unbiased predictions. Evidence shows that forward models remain calibrated through motor adaptation: learning driven by sensory prediction errors.Engineering and Applied Science

Interacting Adaptive Processes with Different Timescales Underlie Short-Term Motor Learning

Multiple processes may contribute to motor skill acquisition, but it is thought that many of these processes require sleep or the passage of long periods of time ranging from several hours to many days or weeks. Here we demonstrate that within a timescale of minutes, two distinct fast-acting processes drive motor adaptation. One process responds weakly to error but retains information well, whereas the other responds strongly but has poor retention. This two-state learning system makes the surprising prediction of spontaneous recovery (or adaptation rebound) if error feedback is clamped at zero following an adaptation-extinction training episode. We used a novel paradigm to experimentally confirm this prediction in human motor learning of reaching, and we show that the interaction between the learning processes in this simple two-state system provides a unifying explanation for several different, apparently unrelated, phenomena in motor adaptation including savings, anterograde interference, spontaneous recovery, and rapid unlearning. Our results suggest that motor adaptation depends on at least two distinct neural systems that have different sensitivity to error and retain information at different rates

A Gain-Field Encoding of Limb Position and Velocity in the Internal Model of Arm Dynamics

Adaptability of reaching movements depends on a computation in the brain that transforms sensory cues, such as those that indicate the position and velocity of the arm, into motor commands. Theoretical consideration shows that the encoding properties of neural elements implementing this transformation dictate how errors should generalize from one limb position and velocity to another. To estimate how sensory cues are encoded by these neural elements, we designed experiments that quantified spatial generalization in environments where forces depended on both position and velocity of the limb. The patterns of error generalization suggest that the neural elements that compute the transformation encode limb position and velocity in intrinsic coordinates via a gain-field; i.e., the elements have directionally dependent tuning that is modulated monotonically with limb position. The gain-field encoding makes the counterintuitive prediction of hypergeneralization: there should be growing extrapolation beyond the trained workspace. Furthermore, nonmonotonic force patterns should be more difficult to learn than monotonic ones. We confirmed these predictions experimentally

Effects of Human Cerebellar Thalamus Disruption on Adaptive Control of Reaching

Lesion or degeneration of the cerebellum can profoundly impair adaptive control of reaching in humans. Computational models have proposed that internal models that help control movements form in the cerebellum and influence planned motor output through the cerebello-thalamo-cortical pathway. However, lesion studies of the cerebellar thalamus have not consistently found impairment in reaching or adaptation of reaching. To elucidate the role of the cerebellar thalamus in humans, we studied a group of essential tremor (ET) patients with deep brain stimulation (DBS) electrodes placed in the cerebellar thalamus. The stimulation can be turned on or off remotely and is thought to reduce tremor by blocking the spread of the pathological output from the cerebellum. We studied the effect of thalamic DBS on the ability to adapt arm movements to novel force fields. Although thalamic DBS resulted in a dramatic and significant reduction of tremor in ET, it also impaired motor adaptation: the larger the stimulation voltage, the greater the reduction in rates of adaptation. We next examined ET patients that had undergone unilateral thalamotomy in the cerebellar thalamus and found that adaptation with the contralateral arm was impaired compared with the ipsilateral arm. Therefore, although both lesion and electrical stimulation of the cerebellar thalamus are highly effective in reducing tremor, they significantly impair the ability of the brain to form internal models of action. Adaptive control of reaching appears to depend on the integrity of the cerebello-thalamo-cortical pathway.Engineering and Applied Science

Bayesian and "Anti-Bayesian" Biases in Sensory Integration for Action and Perception in the Size-Weight Illusion

Which is heavier: a pound of lead or a pound of feathers? This classic trick question belies a simple but surprising truth: when lifted, the pound of lead feels heavier—a phenomenon known as the size–weight illusion. To estimate the weight of an object, our CNS combines two imperfect sources of information: a prior expectation, based on the object's appearance, and direct sensory information from lifting it. Bayes' theorem (or Bayes' law) defines the statistically optimal way to combine multiple information sources for maximally accurate estimation. Here we asked whether the mechanisms for combining these information sources produce statistically optimal weight estimates for both perceptions and actions. We first studied the ability of subjects to hold one hand steady when the other removed an object from it, under conditions in which sensory information about the object's weight sometimes conflicted with prior expectations based on its size. Since the ability to steady the supporting hand depends on the generation of a motor command that accounts for lift timing and object weight, hand motion can be used to gauge biases in weight estimation by the motor system. We found that these motor system weight estimates reflected the integration of prior expectations with real-time proprioceptive information in a Bayesian, statistically optimal fashion that discounted unexpected sensory information. This produces a motor size–weight illusion that consistently biases weight estimates toward prior expectations. In contrast, when subjects compared the weights of two objects, their perceptions defied Bayes' law, exaggerating the value of unexpected sensory information. This produces a perceptual size–weight illusion that biases weight perceptions away from prior expectations. We term this effect “anti-Bayesian” because the bias is opposite that seen in Bayesian integration. Our findings suggest that two fundamentally different strategies for the integration of prior expectations with sensory information coexist in the nervous system for weight estimation.Engineering and Applied Science

The antidepressant effect and safety of non-intranasal esketamine:A systematic review

BACKGROUND: The introduction of esketamine into the field of psychiatry comes on the heels of excitement from studies on racemic ketamine. While the intranasal route has been the most studied to date, other modes of administration of esketamine may also be of interest in the management of depression. AIMS: To systematically review the literature on non-intranasal esketamine for depression in terms of its antidepressant effect and safety. METHODS: We searched PubMed, Embase, the Cochrane Library, and Google Scholar from inception up to February 2021. Search terms included a combination of Medical Subject Headings and text words indicative of esketamine and depression. We selected both controlled and uncontrolled studies examining non-intranasal esketamine for the treatment of depression. RESULTS: We identified four randomized controlled trials (RCTs) on intravenous esketamine and 15 open-label studies on intravenous (n = 80), subcutaneous (n = 73), and oral (n = 5) esketamine. We found intravenous, subcutaneous, and possibly oral administration of esketamine to be effective in reducing depressive symptoms in most patients with major depressive disorder, bipolar depression, and (severe) treatment-resistant depression. Clinical response to repeated administration of esketamine persisted over the course of treatment. Esketamine was well tolerated by most patients, but open-label data indicate marked psychotomimetic symptoms in exceptional cases. The overall quality of the controlled studies was considered high, the overall quality of the uncontrolled studies low to moderate. CONCLUSIONS: Intravenous, subcutaneous, and possibly oral esketamine may offer an effective and safe addition to the depression treatment armamentarium. However, as most included studies lacked a control group and had small sample sizes, the quality of our results is limited. Different types and formulations of ketamine remain to be compared directly

Modeling broadband X-ray absorption of massive star winds

We present a method for computing the net transmission of X-rays emitted by shock-heated plasma distributed throughout a partially optically thick stellar wind from a massive star. We find the transmission by an exact integration of the formal solution, assuming that the emitting plasma and absorbing plasma are mixed at a constant mass ratio above some minimum radius, below which there is assumed to be no emission. This model is more realistic than either the slab absorption associated with a corona at the base of the wind or the exospheric approximation that assumes that all observed X-rays are emitted without attenuation from above the radius of optical depth unity. Our model is implemented in XSPEC as a pre-calculated table that can be coupled to a user-defined table of the wavelength dependent wind opacity. We provide a default wind opacity model that is more representative of real wind opacities than the commonly used neutral interstellar medium (ISM) tabulation. Preliminary modeling of \textit{Chandra} grating data indicates that the X-ray hardness trend of OB stars with spectral subtype can largely be understood as a wind absorption effect.Comment: 9 pages, 9 figures. Includes minor corrections made in proof