SOMETIMES LESS IS MORE

Effects of phonetically variable input (PVI) for processing instruction (PI) training and the number of training items were tested with a picture-selection eye-tracking task. Intermediate second language (L2) learners of French (n = 174) were tested before and after they received either a short (24 items), medium (48), or long (96) training on the causative structure with either single- or multivoice input. PI improved picture-selection accuracy from about 10% to above 50% regardless of the training size. Eye-tracking data showed a reduction in looks to the incorrect picture only after the short and medium training: it surfaced regardless of voice variability after the short training, whereas multivoice training led to a greater reduction after the medium training. Long training did not yield a reliable reduction of incorrect looks regardless of voice variability. Taken together, PVI does not hinder L2 syntactic learning. Learners may benefit more from a relatively shorter training with PVI.

Hierarchical Active Tracking Control for UAVs via Deep Reinforcement Learning

Active tracking control is essential for UAVs to perform autonomous operations in GPS-denied environments. In the active tracking task, UAVs take high-dimensional raw images as input and execute motor actions to actively follow the dynamic target. Most research focuses on three-stage methods, which entail perception first, followed by high-level decision-making based on extracted spatial information of the dynamic target, and then UAV movement control, using a low-level dynamic controller. Perception methods based on deep neural networks are powerful but require considerable effort for manual ground truth labeling. Instead, we unify the perception and decision-making stages using a high-level controller and then leverage deep reinforcement learning to learn the mapping from raw images to the high-level action commands in the V-REP-based environment, where simulation data are infinite and inexpensive. This end-to-end method also has the advantages of a small parameter size and reduced effort requirements for parameter turning in the decision-making stage. The high-level controller, which has a novel architecture, explicitly encodes the spatial and temporal features of the dynamic target. Auxiliary segmentation and motion-in-depth losses are introduced to generate denser training signals for the high-level controller’s fast and stable training. The high-level controller and a conventional low-level PID controller constitute our hierarchical active tracking control framework for the UAVs’ active tracking task. Simulation experiments show that our controller trained with several augmentation techniques sufficiently generalizes dynamic targets with random appearances and velocities, and achieves significantly better performance, compared with three-stage methods.

Limited Add-On Effects of Unilateral and Bilateral Transcranial Direct Current Stimulation on Visuo-Motor Grip Force Tracking Task Training Outcome in Chronic Stroke. A Randomized Controlled Trial

Background: This randomized controlled trial investigated if uni- and bihemispheric transcranial direct current stimulation (tDCS) of the motor cortex can enhance the effects of visuo-motor grip force tracking task training and transfer to clinical assessments of upper extremity motor function.Methods: In a randomized, double-blind, sham-controlled trial, 40 chronic stroke patients underwent 5 days of visuo-motor grip force tracking task training of the paretic hand with either unilateral or bilateral (N = 15/group) or placebo tDCS (N = 10). Immediate and long-term (3 months) effects on training outcome and motor recovery (Upper Extremity Fugl-Meyer, UE-FM, Wolf Motor Function Test, and WMFT) were investigated.Results: Trained task performance significantly improved independently of tDCS in a curvilinear fashion. In the anodal stimulation group UE-FM scores were higher than in the sham group at day 5 (adjusted mean difference: 2.6, 95%CI: 0.6–4.5, p = 0.010) and at 3 months follow up (adjusted mean difference: 2.8, 95%CI: 0.8–4.7, p = 0.006). Neither training alone, nor the combination of training and tDCS improved WMFT performance.Conclusions: Visuo-motor grip force tracking task training can facilitate recovery of upper extremity function. Only minimal add-on effects of anodal but not dual tDCS were observed.Clinical Trial Registration:https://clinicaltrials.gov/ct2/results?recrs=&cond=&term=NCT01969097&cntry=&state=&city=&dist=, identifier: NCT01969097, retrospectively registered on 25/10/2013.

Sensitivity to changes in rate of heartbeats as a measure of interoceptive ability

Individuals vary in their ability to perceive, as conscious sensations, signals like the beating of the heart. Tests of such interoceptive ability are, however, constrained in nature and reliability. Performance of the heartbeat tracking task, a widely used test of cardiac interoception, often corresponds well with individual differences in emotion and cognition, yet is susceptible to reporting bias and influenced by higher order knowledge, e.g. of expected heart rate. The present study introduces a new way of assessing cardiac interoceptive ability, focusing on sensitivity to short-term, naturalistic changes in frequency of heartbeats. At rest, such heart rate variability typically reflects the dominant influence of respiration on vagus parasympathetic control of the sinoatrial pacemaker. We observed an overall tendency of healthy participants to report feeling fewer heartbeats during increases in heart rate, which we speculate reflects a reduction in heartbeat strength and salience during inspiratory periods when heart rate typically increases to maintain a stable cardiac output. Within-participant performance was more variable on this measure of cardiac interoceptive sensitivity relative to the 'classic' heartbeat tracking task. Our findings indicate that cardiac interoceptive ability, rather than reflecting the veridical monitoring of subtle variations in physiology, appears to involve more interpolation wherein interoceptive decisions are informed by dynamic working estimates derived from the integration of afferent signalling and higher order predictions.

Comparative Study of Different Algorithms for a Flight Control System Design and the Potentiality of Their Integration with a Sidestick

The modern trend of developing highly automated aircraft is characterized by a transition from traditional methods and technical solutions to innovative approaches in order to control the system, inceptor and display design. This paper deals with the development and comparison of flight control system algorithms based on inverse dynamics, H-infinity and traditional feedback methods. The integration of a controller based on inverse dynamics with a novel type of sidestick, shaping the pilot output signal such that it is proportional to the control force (force sensing control—FSC), is studied. The inverse dynamics-based controller is chosen, as it provides a variance of error that is up to 2.3 times less than that of the feedback gains and up to 1.5 times less than that of the H-infinity controller in a pitch tracking task. The synergetic effect arising from the proposed integration is also evaluated. The evaluation of the effectiveness of the methods is carried out through mathematical modeling of the pilot–aircraft system and ground-based simulations on a helicopter mathematical model in a pitch tracking task.