View Sensitive Cells as a Neural Basis for the Representation of Others in a Self-Centered Frame of Reference

This work follows from a research project, in which we investigate the underlying mechanisms of human imitation and develop a neural model of its core neural circuits. The present paper presents a model of a neural mechanism by which an imitator agent can map movements of the end effector performed by other agents onto its own frame of reference. The model mechanism is validated in simulation and in a humanoid robot to perform a simple task, in which the robot imitates movements performed a human demonstrator

Three dimensional frames of reference transformations using gain modulated populations of neurons

This work investigates whether population vector coding could be a principle mechanism for sensorimotor transformations. This paper presents a formal demonstration of how population vector coding can proceed arbitrary 3- dimensional rotations and translations. The model suggests that population coding could be a possible mechanism for frames of reference transformations across multiple sensori- motor systems

Dynamic Updating of Distributed Neural Representations using Forward Models

In this paper, we present a continuous attractor network model, which we hypothesize will give some suggestion of the mechanisms underlying several neural processes, such as velocity tuning to visual stimulus, sensory discrimination, sensorimotor-transformations,motor control, motor imagery and imitation. All of these processes share the fundamental characteristic of having to deal with the dynamic integration of motor and sensory variables in order to achieve accurate sensory prediction and/or discrimination. Such principles have already been described in the literature by other high-level modeling studies. With respect to them, our work is more concerned with biologically plausible neural dynamics at a population level. Indeed, we show that a relatively simple extension of the classical neural field models can endow these networks with additional dynamic properties for updating their internal representation using external commands. Moreover, an analysis of the interactions between our model and external inputs also shows interesting properties, which we argue to be relevant for a better understanding of the neural processes of the brain

Biologically Inspired Multimodal Integration: Interferences in a Human-Robot Interaction Game

This paper presents a biologically inspired approach to multimodal integration and decision-making in the context of human-robot interactions. More specifically, we address the principle of ideomotor compatibility by which observing the movements of others influences the quality of one's own performance. This fundamental human ability is likely to be linked with human imitation abilities, social interactions, the transfer of manual skills, and probably to mind reading. We present a robotic control model capable of integrating multimodal information, decision making, and replicating a stimulus-response compatibility task, originally designed to measure the effect of ideomotor compatibility on human behavior. The model consists of a neural network based on the dynamic field approach, which is known for its natural ability for stimulus enhancement as well as cooperative and competitive interactions within and across sensorimotor representations. Finally, we discuss how the capacity for ideomotor facilitation can provide the robot with human-like behavior, but at the expense of several disadvantages, such as hesitation and even mistakes

Online learning of the body schema

We present an algorithm enabling a humanoid robot to visually learn its body schema, knowing only the number of degrees of freedom in each limb. By “body schema” we mean the joint positions and orientations and thus the kinematic function. The learning is performed by visually observing its end-effectors when moving them. With simulations involving a body schema of more than 20 degrees of freedom, results show that the system is scalable to a high number of degrees of freedom. Real robot experiments confirm the practicality of our approach. Our results illustrate how subjective space representation can develop as a result of sensorimotor contingencies

Multi-hydrogenated compounds monitoring in optical fibre manufacturing process by photoacoustic spectroscopy

Sub-ppm hydrogen chloride (HCl) and water vapour (H2O) monitoring using photoacoustic spectroscopy in optical fibre manufacturing is reported. The development and performance of a sensor based on an acoustic resonant configuration is described, and on-site measurements are presented. Two DFB lasers emitting in the 1370nm and 1740nm range were used for the detection of H2O and HCl, respectively. A detection limit (defined for a SNR=3) of 60ppb for HCl and 40ppb for H2O was achieved. Contamination sources of the carrier gas used for the fibre preform manufacturing are identified and discusse

Impact of environmental hygiene interventions on healthcare-associated infections and patient colonization: a systematic review

BACKGROUND Healthcare-associated infections (HAI) are one of the gravest threats to patient safety worldwide. The importance of the hospital environment has recently been revalued in infection prevention and control. Though the literature is evolving rapidly, many institutions still do not consider healthcare environmental hygiene (HEH) very important for patient safety. The evidence for interventions in the healthcare environment on patient colonization and HAI with multidrug-resistant microorganisms (MDROs) or other epidemiologically relevant pathogens was reviewed. METHODS We performed a systematic review according to the PRISMA guidelines using the PubMed and Web of Science databases. All original studies were eligible if published before December 31, 2019, and if the effect of an HEH intervention on HAI or patient colonization was measured. Studies were not eligible if they were conducted in vitro, did not include patient colonization or HAI as an outcome, were bundled with hand hygiene interventions, included a complete structural rebuild of the healthcare facility or were implemented during an outbreak. The primary outcome was the comparison of the intervention on patient colonization or HAI compared to baseline or control. Interventions were categorized by mechanical, chemical, human factors, or bundles. Study quality was assessed using a specifically-designed tool that considered study design, sample size, control, confounders, and issues with reporting. The effect of HEH interventions on environmental bioburden was studied as a secondary outcome. FINDINGS After deduplication, 952 records were scrutinized, of which 44 were included for full text assessment. A total of 26 articles were included in the review and analyzed. Most studies demonstrated a reduction of patient colonization or HAI, and all that analyzed bioburden demonstrated a reduction following the HEH intervention. Studies tested mechanical interventions (n = 8), chemical interventions (n = 7), human factors interventions (n = 3), and bundled interventions (n = 8). The majority of studies (21/26, 81%) analyzed either S. aureus, C. difficile, and/or vancomycin-resistant enterococci. Most studies (23/26, 88%) reported a decrease of MDRO-colonization or HAI for at least one of the tested organisms, while 58% reported a significant decrease of MDRO-colonization or HAI for all tested microorganisms. Forty-two percent were of good quality according to the scoring system. The majority (21/26, 81%) of study interventions were recommended for application by the authors. Studies were often not powered adequately to measure statistically significant reductions. INTERPRETATION Improving HEH helps keep patients safe. Most studies demonstrated that interventions in the hospital environment were related with lower HAI and/or patient colonization. Most of the studies were not of high quality; additional adequately-powered, high-quality studies are needed. Systematic registration number: CRD42020204909

Interferences in the Transformation of Reference Frames during a Posture Imitation Task

We present a biologically-inspired neural model addressing the problem of transformations across frames of reference in a posture imitation task. Our modeling is based on the hypothesis that imitation is mediated by two concurrent transformations selectively sensitive to spatial and anatomical cues. In contrast to classical approaches, we also assume that separate instances of this pair of transformations are responsible for the control of each side of the body. We also devised an experimental paradigm which allowed us to model the interference patterns caused by the interaction between the anatomical on one hand, and the spatial imitative strategy on the other hand. The results from our simulation studies thus provide predictions of real behavioral responses