An Integrated Decision Making Approach for Adaptive Shared Control of Mobility Assistance Robots

© 2016, Springer Science+Business Media Dordrecht. Mobility assistance robots provide support to elderly or patients during walking. The design of a safe and intuitive assistance behavior is one of the major challenges in this context. We present an integrated approach for the context-specific, on-line adaptation of the assistance level of a rollator-type mobility assistance robot by gain-scheduling of low-level robot control parameters. A human-inspired decision-making model, the drift-diffusion Model, is introduced as the key principle to gain-schedule parameters and with this to adapt the provided robot assistance in order to achieve a human-like assistive behavior. The mobility assistance robot is designed to provide (a) cognitive assistance to help the user following a desired path towards a predefined destination as well as (b) sensorial assistance to avoid collisions with obstacles while allowing for an intentional approach of them. Further, the robot observes the user long-term performance and fatigue to adapt the overall level of (c) physical assistance provided. For each type of assistance a decision-making problem is formulated that affects different low-level control parameters. The effectiveness of the proposed approach is demonstrated in technical validation experiments. Moreover, the proposed approach is evaluated in a user study with 35 elderly persons. Obtained results indicate that the proposed gain-scheduling technique incorporating ideas of human decision-making models shows a general high potential for the application in adaptive shared control of mobility assistance robots

An astrocyte-dependent mechanism for neuronal rhythmogenesis

Communication between neurons rests on their capacity to change their firing pattern to encode different messages. For several vital functions, such as respiration and mastication, neurons need to generate a rhythmic firing pattern. Here we show in the rat trigeminal sensori-motor circuit for mastication that this ability depends on regulation of the extracellular Ca2+ concentration ([Ca2+]e) by astrocytes. In this circuit, astrocytes respond to sensory stimuli that induce neuronal rhythmic activity, and their blockade with a Ca2+ chelator prevents neurons from generating a rhythmic bursting pattern. This ability is restored by adding S100b, an astrocytic Ca2+-binding protein, to the extracellular space, while application of an anti-S100b antibody prevents generation of rhythmic activity. These results indicate that astrocytes regulate a fundamental neuronal property: the capacity to change firing pattern. These findings may have broad implications for many other neural networks whose functions depend on the generation of rhythmic activity

Is media multitasking good for cybersecurity? Exploring the relationship between media multitasking and everyday cognitive failures on self-reported risky cybersecurity behaviors

The current study focused on how engaging in media multitasking (MMT) and the experience of everyday cognitive failures impact on the individual's engagement in risky cybersecurity behaviors (RCsB). In total, 144 participants (32 males, 112 females) completed an online survey. The age range for participants was 18 to 43 years (M = 20.63, SD = 4.04). Participants completed three scales which included an inventory of weekly MMT, a measure of everyday cognitive failures, and RCsB. There was a significant difference between heavy media multitaskers (HMM), average media multitaskers (AMM), and light media multitaskers (LMM) in terms of RCsB, with HMM demonstrating more frequent risky behaviors than LMM or AMM. The HMM group also reported more cognitive failures in everyday life than the LMM group. A regression analysis showed that everyday cognitive failures and MMT acted as significant predictors for RCsB. These results expand our current understanding of the relationship between human factors and cybersecurity behaviors, which are useful to inform the design of training and intervention packages to mitigate RCsB

Modeling the Violation of Reward Maximization and Invariance in Reinforcement Schedules

It is often assumed that animals and people adjust their behavior to maximize reward acquisition. In visually cued reinforcement schedules, monkeys make errors in trials that are not immediately rewarded, despite having to repeat error trials. Here we show that error rates are typically smaller in trials equally distant from reward but belonging to longer schedules (referred to as “schedule length effect”). This violates the principles of reward maximization and invariance and cannot be predicted by the standard methods of Reinforcement Learning, such as the method of temporal differences. We develop a heuristic model that accounts for all of the properties of the behavior in the reinforcement schedule task but whose predictions are not different from those of the standard temporal difference model in choice tasks. In the modification of temporal difference learning introduced here, the effect of schedule length emerges spontaneously from the sensitivity to the immediately preceding trial. We also introduce a policy for general Markov Decision Processes, where the decision made at each node is conditioned on the motivation to perform an instrumental action, and show that the application of our model to the reinforcement schedule task and the choice task are special cases of this general theoretical framework. Within this framework, Reinforcement Learning can approach contextual learning with the mixture of empirical findings and principled assumptions that seem to coexist in the best descriptions of animal behavior. As examples, we discuss two phenomena observed in humans that often derive from the violation of the principle of invariance: “framing,” wherein equivalent options are treated differently depending on the context in which they are presented, and the “sunk cost” effect, the greater tendency to continue an endeavor once an investment in money, effort, or time has been made. The schedule length effect might be a manifestation of these phenomena in monkeys

Structural basis of TIR-domain-assembly formation in MAL- and MyD88-dependent TLR4 signaling

Toll-like receptor (TLR) signaling is a key innate immunity response to pathogens. Recruitment of signaling adapters such as MAL (TIRAP) and MyD88 to the TLRs requires Toll/interleukin-1 receptor (TIR)-domain interactions, which remain structurally elusive. Here we show that MAL TIR domains spontaneously and reversibly form filaments in vitro. They also form cofilaments with TLR4 TIR domains and induce formation of MyD88 assemblies. A 7-Å-resolution cryo-EM structure reveals a stable MAL protofilament consisting of two parallel strands of TIR-domain subunits in a BB-loop-mediated head-to-tail arrangement. Interface residues that are important for the interaction are conserved among different TIR domains. Although large filaments of TLR4, MAL or MyD88 are unlikely to form during cellular signaling, structure-guided mutagenesis, combined with in vivo interaction assays, demonstrated that the MAL interactions defined within the filament represent a template for a conserved mode of TIR-domain interaction involved in both TLR and interleukin-1 receptor signaling

Bacterial Flagella: Twist and Stick, or Dodge across the Kingdoms

The flagellum organelle is an intricate multiprotein assembly best known for its rotational propulsion of bacteria. However, recent studies have expanded our knowledge of other functions in pathogenic contexts, particularly adherence and immune modulation, e.g., for Salmonella enterica, Campylobacter jejuni, Pseudomonas aeruginosa, and Escherichia coli. Flagella-mediated adherence is important in host colonisation for several plant and animal pathogens, but the specific interactions that promote flagella binding to such diverse host tissues has remained elusive. Recent work has shown that the organelles act like probes that find favourable surface topologies to initiate binding. An emerging theme is that more general properties, such as ionic charge of repetitive binding epitopes and rotational force, allow interactions with plasma membrane components. At the same time, flagellin monomers are important inducers of plant and animal innate immunity: variation in their recognition impacts the course and outcome of infections in hosts from both kingdoms. Bacteria have evolved different strategies to evade or even promote this specific recognition, with some important differences shown for phytopathogens. These studies have provided a wider appreciation of the functions of bacterial flagella in the context of both plant and animal reservoirs

Calcium-dependent molecular fMRI using a magnetic nanosensor

Calcium ions are ubiquitous signalling molecules in all multicellular organisms, where they mediate diverse aspects of intracellular and extracellular communication over widely varying temporal and spatial scales1. Though techniques to map calcium-related activity at a high resolution by optical means are well established, there is currently no reliable method to measure calcium dynamics over large volumes in intact tissue2. Here, we address this need by introducing a family of magnetic calcium-responsive nanoparticles (MaCaReNas) that can be detected by magnetic resonance imaging (MRI). MaCaReNas respond within seconds to [Ca2+] changes in the 0.1-1.0 mM range, suitable for monitoring extracellular calcium signalling processes in the brain. We show that the probes permit the repeated detection of brain activation in response to diverse stimuli in vivo. MaCaReNas thus provide a tool for calcium-activity mapping in deep tissue and offer a precedent for the development of further nanoparticle-based sensors for dynamic molecular imaging with MRI.National Institutes of Health (U.S.) (Grant R01-DA038642)National Institutes of Health (U.S.) (Grant DP2-OD2114)National Institutes of Health (U.S.) (Grant U01-NS090451)National Institutes of Health (U.S.) (Grant R01-EY007023)National Science Foundation (U.S.) (Grant 0070319)National Institutes of Health (U.S.) (Grant S10-OD016326