Overcoming “The Language Rubicon": Versions, Steps and Evolutionary Mechanisms

The most plausible hypotheses explaining the breakthrough of our distant ancestors to articulate speech and consciousness include: rituals of solidarity (singing, grooming, facial expressions, gestures), the role of "labor", teaching children, changes in gender relations, recruiting (mobilization for collective action), laryngeal transformation, brain growth, mirror neurons, neuronal overlap; dominance of coalitions over loners, self-domestication, the need to coordinate decisions; joint intentionality, development of normativity. The concretization of the principle of "cultural drive" leads to the following concept: new environmental, social and communicative challenges and concerns lead to multiple trials; successful behavior is consolidated in group practices, mental structures of participants, and hereditary inclinations with multilevel selection and change of many generations. Overcoming the "language Rubicon" took place in several steps, or stages, in which the structures that have developed to provide concerns lead to new concerns that require new structures. Such concerns as pacifying social order in the group, signaling general discontent, coordinating actions, etc., the following structures emerged: egalitarian coalitions with collective practices of intimidation, sound signals uttered in unison, training and self-training, self-domestication, shared intentionality, and normative rituals. The most plausible versions supplement this concept. Сhoral singing as a ritual of solidarity promoted the ability to imitate and articulate. Mirror neurons and neural overlaps have played the role of providing mechanisms for imitation and association processes. The connection between "labor" and speech was complex and interdependent, mediated by normativity. Recruiting as signals of mobilization for collective action also made its contribution but only under the already established normative order. Social learning is in fact a special ritual of constant trial and adjustment which has grown out of a normative ritual. The establishment of a new order of sexual relations also played a role: under the prohibition of violence and rape it was necessary to involve partners. Speech replaced grooming, and those who spoke clearly, convincingly and/or sang beautifully received benefits in sexual selection. The totality of all these processes reinforced the concerns of mutual understanding which were provided by the rituals of naming with the following multiplication of protowords and further growth of linguistic complexity.

Catheter Ablation Versus Medical Therapy for Atrial Fibrillation - Penny wise Pound Foolish !

Catheter ablation for atrial fibrillation has emerged as a main stay for management of atrial fibrillation. It has been shown to be clinically effective and cost effective in multiple trials .

Mesenchymal stem/stromal cell-based therapies for severe viral pneumonia: therapeutic potential and challenges

Severe viral pneumonia is a significant cause of morbidity and mortality globally, whether due to outbreaks of endemic viruses, periodic viral epidemics, or the rarer but devastating global viral pandemics. While limited anti-viral therapies exist, there is a paucity of direct therapies to directly attenuate viral pneumonia-induced lung injury, and management therefore remains largely supportive. Mesenchymal stromal/stem cells (MSCs) are receiving considerable attention as a cytotherapeutic for viral pneumonia. Several properties of MSCs position them as a promising therapeutic strategy for viral pneumonia-induced lung injury as demonstrated in pre-clinical studies in relevant models. More recently, early phase clinical studies have demonstrated a reassuring safety profile of these cells. These investigations have taken on an added importance and urgency during the COVID-19 pandemic, with multiple trials in progress across the globe. In parallel with clinical translation, strategies are being investigated to enhance the therapeutic potential of these cells in vivo, with different MSC tissue sources, specific cellular products including cell-free options, and strategies to ‘licence’ or ‘pre-activate’ these cells, all being explored. This review will assess the therapeutic potential of MSC-based therapies for severe viral pneumonia. It will describe the aetiology and epidemiology of severe viral pneumonia, describe current therapeutic approaches, and examine the data suggesting therapeutic potential of MSCs for severe viral pneumonia in pre-clinical and clinical studies. The challenges and opportunities for MSC-based therapies will then be considered.

Brain Connectivity Estimation Pitfall in Multiple Trials of EEG Data

The electroencephalography signal is well suited to calculate brain connectivity due to its high temporal resolution. When the purpose is to compute connectivity from multi-trial EEG data, confusion arises about how these trials involved in calculating the connectivity. The purpose of this paper is to study this confusing issue using simulated and experimental data. To this end, Granger causality-based connectivity measures were considered. Using simulations, two signals were generated with known AR (Auto-Regressive) coefficients and then simple MVAR (Multivariate AR) models based on different numbers of trials were extracted. For accurate estimation of the MVAR model, the data samples should be sufficient. Two Granger causality-based connectivity, GC and PDC were estimated. Estimating connectivity corresponding to small trial numbers (5 and 10 trials) resulted in an average value of connectivity that is significantly higher and also more variable over different estimates. By increasing the number of trials, the MVAR model has fitted more appropriately to the data and the connectivity values were converged. This procedure was implemented on real EEG data. The obtained results agreed well with the findings of simulated data. The results showed that the brain connectivity should calculate for each trial, and then average the connectivity values on all trials. Also, the larger the trial numbers, the MVAR model has fitted more appropriately to the data, and connectivity estimations are more reliable.

Visual feedback improves bimanual force control performances at planning and execution levels

The purpose of this study was to determine the effect of different visual conditions and targeted force levels on bilateral motor synergies and bimanual force control performances. Fourteen healthy young participants performed bimanual isometric force control tasks by extending their wrists and fingers under two visual feedback conditions (i.e., vision and no-vision) and three targeted force levels (i.e., 5%, 25%, and 50% of maximum voluntary contraction: MVC). To estimate bilateral motor synergies across multiple trials, we calculated the proportion of good variability relative to bad variability using an uncontrolled manifold analysis. To assess bimanual force control performances within a trial, we used the accuracy, variability, and regularity of total forces produced by two hands. Further, analysis included correlation coefficients between forces from the left and right hands. In addition, we examined the correlations between altered bilateral motor synergies and force control performances from no-vision to vision conditions for each targeted force level. Importantly, our findings revealed that the presence of visual feedback increased bilateral motor synergies across multiple trials significantly with a reduction of bad variability as well as improved bimanual force control performances within a trial based on higher force accuracy, lower force variability, less force regularity, and decreased correlation coefficients between hands. Further, we found two significant correlations in (a) increased bilateral motor synergy versus higher force accuracy at 5% of MVC and (b) increased bilateral motor synergy versus lower force variability at 50% of MVC. Together, these results suggested that visual feedback effectively improved both synergetic coordination behaviors across multiple trials and stability of task performance within a trial across various submaximal force levels.

Predictive Sampling Method for Spread Models in Networks

This paper proposes a novel, exploration-based network sampling algorithm called caterpillar quota walk sampling (CQWS) inspired by the caterpillar tree. Network sampling identifies a subset of nodes and edges from a network, creating an induced graph. Beginning from an initial node, exploration-based sampling algorithms grow the induced set by traversing and tracking unvisited neighboring nodes from the original network. Tunable and trainable parameters allow CQWS to maximize the sum of the degrees of the induced graph from multiple trials when sampling dense networks. A network spread model renders effective use in various applications, including tracking the spread of epidemics, visualizing information transmissions through social media, and cell-to-cell spread of neurodegenerative diseases. CQWS generates a spread model as its sample by visiting the highest-degree neighbors of previously visited nodes. For each previously visited node, a top proportion of the highest-degree neighbors fulfills a quota and branches into a new caterpillar tree. Sampling more high-degree nodes constitutes an objective among various applications. Many exploration-based sampling algorithms suffer drawbacks that limit the sum of degrees of visited nodes and thus the number of high-degree nodes visited. Furthermore, a strategy may not be adaptable to volatile degree frequencies throughout the original network architecture, which influences how deep into the original network an algorithm could sample. This paper analyzes CQWS in comparison to four other exploration-based network in tackling these two problems by sampling sparse and dense randomly generated networks.

Reliability of Repeated Trials Protocols for Body Composition Assessment by Air Displacement Plethysmography

Air displacement plethysmography (ADP) is fast, accurate, and reliable. Nevertheless, in about 3% of the cases, standard ADP tests provide rogue results. To spot these outliers and improve precision, repeated trials protocols have been devised, but few works have addressed their reliability. This study was conducted to evaluate the test–retest reliabilities of two known protocols and a new one, proposed here. Ninety-two healthy adults (46 men and 46 women) completed six consecutive ADP tests. To evaluate the reliability of single measurements, we used the results of the first two tests; for multiple measures protocols, we computed the test result from trials 1–3 and the retest result from trials 4–6. Bland–Altman analysis revealed that the bias and the width of the 95% interval of agreement were smaller for multiple trials than for single ones. For percent body fat (%BF)/fat-free mass, the technical error of measurement was 1% BF/0.68 kg for single trials and 0.62% BF/0.46 kg for the new protocol of multiple trials, which proved to be the most reliable. The minimal detectable change (MDC) was 2.77% BF/1.87 kg for single trials and 1.72% BF/1.26 kg for the new protocol.

EMG-informed neuromusculoskeletal models accurately predict knee loading measured using instrumented implants

<p>We investigated three different methods for simulating neuromusculoskeletal (NMS) control to generate estimates of knee joint loading which were compared to in-vivo measured loads. The major contributions of this work to the literature are in generalizing EMG-informed and probabilistic methods for modelling NMS control.</p> <p>A single calibration function for EMG-informed NMS modelling was identified which accurately estimated knee loads for multiple people across multiple trials. Using a stochastic approach to NMS modelling, we investigated the range of possible solutions for knee joint loading during walking, showing the method's generalizability and capability to generate solutions which encompassed the measured knee loads. Through this stochastic approach, we were able to show that a single degree of freedom planar knee is suited to estimating total knee loading, but is insufficient for estimating the directional components of load.</p> <p> </p>

EMG-informed neuromusculoskeletal models accurately predict knee loading measured using instrumented implants

<p>We investigated three different methods for simulating neuromusculoskeletal (NMS) control to generate estimates of knee joint loading which were compared to in-vivo measured loads. The major contributions of this work to the literature are in generalizing EMG-informed and probabilistic methods for modelling NMS control.</p> <p>A single calibration function for EMG-informed NMS modelling was identified which accurately estimated knee loads for multiple people across multiple trials. Using a stochastic approach to NMS modelling, we investigated the range of possible solutions for knee joint loading during walking, showing the method's generalizability and capability to generate solutions which encompassed the measured knee loads. Through this stochastic approach, we were able to show that a single degree of freedom planar knee is suited to estimating total knee loading, but is insufficient for estimating the directional components of load.</p> <p> </p>

Auditory perceptual learning depends on temporal regularity and certainty

Detecting and learning structure in sounds is fundamental to human auditory perception. Evidence for such auditory perceptual learning comes from previous studies where listeners were better at detecting repetitions of a short noise snippet embedded in longer, ongoing noise when the same snippet recurred across trials compared to when the snippet was novel in each trial. However, previous work has mainly used (a) temporally regular presentations of the repeating noise snippet and (b) highly predictable inter-trial onset timings for the snippet sequences. As a result, it is unclear how these temporal features affect perceptual learning. In five online experiments, participants judged whether or not a repeating noise snippet was present, unaware that the snippet could be unique to that trial or used in multiple trials. In two experiments, temporal regularity was manipulated by jittering the timing of noise-snippet repetitions within a trial. In two subsequent experiments, temporal onset certainty was manipulated by varying the onset time of the entire snippet sequence across trials. We found that both temporal jittering and onset uncertainty reduced auditory perceptual learning. In addition, we observed that these reductions in perceptual learning were ameliorated when the same snippet occurred in both temporally manipulated and unmanipulated trials. Our study demonstrates the importance of temporal regularity and onset certainty for auditory perceptual learning.