Risk-Sensitive Optimal Feedback Control Accounts for Sensorimotor Behavior under Uncertainty

Many aspects of human motor behavior can be understood using optimality principles such as optimal feedback control. However, these proposed optimal control models are risk-neutral; that is, they are indifferent to the variability of the movement cost. Here, we propose the use of a risk-sensitive optimal controller that incorporates movement cost variance either as an added cost (risk-averse controller) or as an added value (risk-seeking controller) to model human motor behavior in the face of uncertainty. We use a sensorimotor task to test the hypothesis that subjects are risk-sensitive. Subjects controlled a virtual ball undergoing Brownian motion towards a target. Subjects were required to minimize an explicit cost, in points, that was a combination of the final positional error of the ball and the integrated control cost. By testing subjects on different levels of Brownian motion noise and relative weighting of the position and control cost, we could distinguish between risk-sensitive and risk-neutral control. We show that subjects change their movement strategy pessimistically in the face of increased uncertainty in accord with the predictions of a risk-averse optimal controller. Our results suggest that risk-sensitivity is a fundamental attribute that needs to be incorporated into optimal feedback control models

Implementation of population screening for colorectal cancer by repeated fecal occult blood test in the Netherlands

<p>Abstract</p> <p>Background</p> <p>Colorectal cancer (CRC) is the third most prevalent type of cancer in the world. Its prognosis is closely related to the disease stage at the time of diagnosis. Early detection of symptomless CRC or precursor lesions through population screening could reduce CRC mortality. However, screening programs are only effective if enough people are willing to participate. This study aims to asses the uptake of a second round of fecal occult blood test (FOBt) based screening and to explore factors that could potentially increase this uptake.</p> <p>Methods and design</p> <p>Two years after the first screening round, 10.000 average risk persons, aged 50 to 75, will again receive an invitation to participate in immunohistochemical FOBt (iFOBt) based screening. Eligible persons will be recruited through a city population database. Invitees will be randomized to receive either an iFOBt with a faeces collection paper or an iFOBt without a collection paper. The iFOBts will be analyzed in a specialized laboratory at the Academic Medical Centre. Positive iFOBts will be followed by a consultation at our outpatient clinic and, in the absence of contra-indications and after informed consent, by a colonoscopy. The primary outcome measure is the participation rate. Secondary outcome measures are the effect of the addition of a collection paper on the participation rate, reasons for participation and non-participation, measures of informed choice and psychological consequences of screening and measures of psychological and physical burden associated with the iFOBt and the colonoscopy. Another secondary outcome measure is the diagnostic yield of the program.</p> <p>Discussion</p> <p>In order to implement population screening for colorectal cancer in the Netherlands, information is needed on the uptake of repeated rounds of FOBt-based screening and on factors that could potentially increase this uptake in the future since effectiveness of such a program depends on the willingness of persons to participate. This study will provide information on the actual uptake and perception of a second round of iFOBt-based screening. The results of this study will contribute to the future implementation of a national colorectal screening program in the Netherlands.</p> <p>Trial registration</p> <p>Dutch Trial register: NTR1327</p

Neuromotor Noise, Error Tolerance and Velocity-Dependent Costs in Skilled Performance

In motor tasks with redundancy neuromotor noise can lead to variations in execution while achieving relative invariance in the result. The present study examined whether humans find solutions that are tolerant to intrinsic noise. Using a throwing task in a virtual set-up where an infinite set of angle and velocity combinations at ball release yield throwing accuracy, our computational approach permitted quantitative predictions about solution strategies that are tolerant to noise. Based on a mathematical model of the task expected results were computed and provided predictions about error-tolerant strategies (Hypothesis 1). As strategies can take on a large range of velocities, a second hypothesis was that subjects select strategies that minimize velocity at release to avoid costs associated with signal- or velocity-dependent noise or higher energy demands (Hypothesis 2). Two experiments with different target constellations tested these two hypotheses. Results of Experiment 1 showed that subjects chose solutions with high error-tolerance, although these solutions also had relatively low velocity. These two benefits seemed to outweigh that for many subjects these solutions were close to a high-penalty area, i.e. they were risky. Experiment 2 dissociated the two hypotheses. Results showed that individuals were consistent with Hypothesis 1 although their solutions were distributed over a range of velocities. Additional analyses revealed that a velocity-dependent increase in variability was absent, probably due to the presence of a solution manifold that channeled variability in a task-specific manner. Hence, the general acceptance of signal-dependent noise may need some qualification. These findings have significance for the fundamental understanding of how the central nervous system deals with its inherent neuromotor noise

Bayesian Integration and Non-Linear Feedback Control in a Full-Body Motor Task

A large number of experiments have asked to what degree human reaching movements can be understood as being close to optimal in a statistical sense. However, little is known about whether these principles are relevant for other classes of movements. Here we analyzed movement in a task that is similar to surfing or snowboarding. Human subjects stand on a force plate that measures their center of pressure. This center of pressure affects the acceleration of a cursor that is displayed in a noisy fashion (as a cloud of dots) on a projection screen while the subject is incentivized to keep the cursor close to a fixed position. We find that salient aspects of observed behavior are well-described by optimal control models where a Bayesian estimation model (Kalman filter) is combined with an optimal controller (either a Linear-Quadratic-Regulator or Bang-bang controller). We find evidence that subjects integrate information over time taking into account uncertainty. However, behavior in this continuous steering task appears to be a highly non-linear function of the visual feedback. While the nervous system appears to implement Bayes-like mechanisms for a full-body, dynamic task, it may additionally take into account the specific costs and constraints of the task

The HSP90 Inhibitor NVP-AUY922 Radiosensitizes by Abrogation of Homologous Recombination Resulting in Mitotic Entry with Unresolved DNA Damage

Heat shock protein 90 (HSP90) is a molecular chaperone responsible for the conformational maintenance of a number of client proteins that play key roles in cell cycle arrest, DNA damage repair and apoptosis following radiation. HSP90 inhibitors exhibit antitumor activity by modulating the stabilisation and activation of HSP90 client proteins. We sought to evaluate NVP-AUY922, the most potent HSP90 inhibitor yet reported, in preclinical radiosensitization studies.NVP-AUY922 potently radiosensitized cells in vitro at low nanomolar concentrations with a concurrent depletion of radioresistance-linked client proteins. Radiosensitization by NVP-AUY922 was verified for the first time in vivo in a human head and neck squamous cell carcinoma xenograft model in athymic mice, as measured by delayed tumor growth and increased surrogate end-point survival (p = <0.0001). NVP-AUY922 was shown to ubiquitously inhibit resolution of dsDNA damage repair correlating to delayed Rad51 foci formation in all cell lines tested. Additionally, NVP-AUY922 induced a stalled mitotic phenotype, in a cell line-dependent manner, in HeLa and HN5 cell lines irrespective of radiation exposure. Cell cycle analysis indicated that NVP-AUY922 induced aberrant mitotic entry in all cell lines tested in the presence of radiation-induced DNA damage due to ubiquitous CHK1 depletion, but resultant downstream cell cycle effects were cell line dependent.These results identify NVP-AUY922 as the most potent HSP90-mediated radiosensitizer yet reported in vitro, and for the first time validate it in a clinically relevant in vivo model. Mechanistic analysis at clinically achievable concentrations demonstrated that radiosensitization is mediated by the combinatorial inhibition of cell growth and survival pathways, ubiquitous delay in Rad51-mediated homologous recombination and CHK1-mediated G(2)/M arrest, but that the contribution of cell cycle perturbation to radiosensitization may be cell line specific

Inferring Visuomotor Priors for Sensorimotor Learning

Sensorimotor learning has been shown to depend on both prior expectations and sensory evidence in a way that is consistent with Bayesian integration. Thus, prior beliefs play a key role during the learning process, especially when only ambiguous sensory information is available. Here we develop a novel technique to estimate the covariance structure of the prior over visuomotor transformations – the mapping between actual and visual location of the hand – during a learning task. Subjects performed reaching movements under multiple visuomotor transformations in which they received visual feedback of their hand position only at the end of the movement. After experiencing a particular transformation for one reach, subjects have insufficient information to determine the exact transformation, and so their second reach reflects a combination of their prior over visuomotor transformations and the sensory evidence from the first reach. We developed a Bayesian observer model in order to infer the covariance structure of the subjects' prior, which was found to give high probability to parameter settings consistent with visuomotor rotations. Therefore, although the set of visuomotor transformations experienced had little structure, the subjects had a strong tendency to interpret ambiguous sensory evidence as arising from rotation-like transformations. We then exposed the same subjects to a highly-structured set of visuomotor transformations, designed to be very different from the set of visuomotor rotations. During this exposure the prior was found to have changed significantly to have a covariance structure that no longer favored rotation-like transformations. In summary, we have developed a technique which can estimate the full covariance structure of a prior in a sensorimotor task and have shown that the prior over visuomotor transformations favor a rotation-like structure. Moreover, through experience of a novel task structure, participants can appropriately alter the covariance structure of their prior

Do Humans Optimally Exploit Redundancy to Control Step Variability in Walking?

It is widely accepted that humans and animals minimize energetic cost while walking. While such principles predict average behavior, they do not explain the variability observed in walking. For robust performance, walking movements must adapt at each step, not just on average. Here, we propose an analytical framework that reconciles issues of optimality, redundancy, and stochasticity. For human treadmill walking, we defined a goal function to formulate a precise mathematical definition of one possible control strategy: maintain constant speed at each stride. We recorded stride times and stride lengths from healthy subjects walking at five speeds. The specified goal function yielded a decomposition of stride-to-stride variations into new gait variables explicitly related to achieving the hypothesized strategy. Subjects exhibited greatly decreased variability for goal-relevant gait fluctuations directly related to achieving this strategy, but far greater variability for goal-irrelevant fluctuations. More importantly, humans immediately corrected goal-relevant deviations at each successive stride, while allowing goal-irrelevant deviations to persist across multiple strides. To demonstrate that this was not the only strategy people could have used to successfully accomplish the task, we created three surrogate data sets. Each tested a specific alternative hypothesis that subjects used a different strategy that made no reference to the hypothesized goal function. Humans did not adopt any of these viable alternative strategies. Finally, we developed a sequence of stochastic control models of stride-to-stride variability for walking, based on the Minimum Intervention Principle. We demonstrate that healthy humans are not precisely “optimal,” but instead consistently slightly over-correct small deviations in walking speed at each stride. Our results reveal a new governing principle for regulating stride-to-stride fluctuations in human walking that acts independently of, but in parallel with, minimizing energetic cost. Thus, humans exploit task redundancies to achieve robust control while minimizing effort and allowing potentially beneficial motor variability

A Single-Rate Context-Dependent Learning Process Underlies Rapid Adaptation to Familiar Object Dynamics

Motor learning has been extensively studied using dynamic (force-field) perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar object dynamics, however, the representations can be engaged based on visual context, and are updated by a single-rate process

Genome-Wide Identification of Alternatively Spliced mRNA Targets of Specific RNA-Binding Proteins

BACKGROUND: Alternative splicing plays an important role in generating molecular and functional diversity in multi-cellular organisms. RNA binding proteins play crucial roles in modulating splice site choice. The majority of known binding sites for regulatory proteins are short, degenerate consensus sequences that occur frequently throughout the genome. This poses an important challenge to distinguish between functionally relevant sequences and a vast array of those occurring by chance. METHODOLOGY/PRINCIPAL FINDINGS: Here we have used a computational approach that combines a series of biological constraints to identify uridine-rich sequence motifs that are present within relevant biological contexts and thus are potential targets of the Drosophila master sex-switch protein Sex-lethal (SXL). This strategy led to the identification of one novel target. Moreover, our systematic analysis provides a starting point for the molecular and functional characterization of an additional target, which is dependent on SXL activity, either directly or indirectly, for regulation in a germline-specific manner. CONCLUSIONS/SIGNIFICANCE: This approach has successfully identified previously known, new, and potential SXL targets. Our analysis suggests that only a subset of potential SXL sites are regulated by SXL. Finally, this approach should be directly relevant to the large majority of splicing regulatory proteins for which bonafide targets are unknown

Principles of sensorimotor learning.

The exploits of Martina Navratilova and Roger Federer represent the pinnacle of motor learning. However, when considering the range and complexity of the processes that are involved in motor learning, even the mere mortals among us exhibit abilities that are impressive. We exercise these abilities when taking up new activities - whether it is snowboarding or ballroom dancing - but also engage in substantial motor learning on a daily basis as we adapt to changes in our environment, manipulate new objects and refine existing skills. Here we review recent research in human motor learning with an emphasis on the computational mechanisms that are involved