Self-Other Mergence in the Frontal Cortex during Cooperation and Competition

This is the final version. Available on open access from Elsevier via the DOI in this recordTo survive, humans must estimate their own ability and the abilities of others. We found that, although people estimated their abilities on the basis of their own performance in a rational manner, their estimates of themselves were partly merged with the performance of others. Reciprocally, their ability estimates for others also reflected their own, as well as the others’, performance. Self-other mergence operated in a context-dependent manner: interacting with high or low performers, respectively, enhanced and diminished own ability estimates in cooperative contexts, but the opposite occurred in competitive contexts. Self-other mergence not only influenced subjective evaluations, it also affected how people subsequently objectively adjusted their performance. Perigenual anterior cingulate cortex tracked one’s own performance. Dorsomedial frontal area 9 tracked others’ performances, but also integrated contextual and self-related information. Self-other mergence increased with the strength of self and other representations in area 9, suggesting it carries interdependent representations of self and other.Wellcome Trus

Human-robot swarm interaction with limited situational awareness

This paper studies how an operator with limited situational awareness can collaborate with a swarm of simulated robots. The robots are distributed in an environment with wall obstructions. They aggregate autonomously but are unable to form a single cluster due to the obstructions. The operator lacks the bird’s-eye perspective, but can interact with one robot at a time, and influence the behavior of other nearby robots. We conducted a series of experiments. They show that untrained participants had marginal influence on the performance of the swarm. Expert participants succeeded in aggregating 85% of the robots while untrained participants, with bird’s-eye view, succeeded in aggregating 90%. This demonstrates that the controls are sufficient for operators to aid the autonomous robots in the completion of the task and that lack of situational awareness is the main difficulty. An analysis of behavioral differences reveals that trained operators learned to gain superior situational awareness

Inferring metabolic mechanisms of interaction within a defined gut microbiota

The diversity and number of species present within microbial communities create the potential for a multitude of interspecies metabolic interactions. Here, we develop, apply, and experimentally test a framework for inferring metabolic mechanisms associated with interspecies interactions. We perform pairwise growth and metabolome profiling of co-cultures of strains from a model mouse microbiota. We then apply our framework to dissect emergent metabolic behaviors that occur in co-culture. Based on one of the inferences from this framework, we identify and interrogate an amino acid cross-feeding interaction and validate that the proposed interaction leads to a growth benefit in vitro. Our results reveal the type and extent of emergent metabolic behavior in microbial communities composed of gut microbes. We focus on growth-modulating interactions, but the framework can be applied to interspecies interactions that modulate any phenotype of interest within microbial communities

Scalable target detection for large robot teams

In this paper, we present an asynchronous display method, coined image queue, which allows operators to search through a large amount of data gathered by autonomous robot teams. We discuss and investigate the advantages of an asynchronous display for foraging tasks with emphasis on Urban Search and Rescue. The image queue approach mines video data to present the operator with a relevant and comprehensive view of the environment in order to identify targets of interest such as injured victims. It fills the gap for comprehensive and scalable displays to obtain a network-centric perspective for UGVs. We compared the image queue to a traditional synchronous display with live video feeds and found that the image queue reduces errors and operator's workload. Furthermore, it disentangles target detection from concurrent system operations and enables a call center approach to target detection. With such an approach we can scale up to very large multi-robot systems gathering huge amounts of data that is then distributed to multiple operators. Copyright 2011 ACM

Caracterização do Perfil do Consumidor de Leite de Búfala em Feiras no Rio Grande do Sul.

bitstream/item/144558/1/Circular-163.pd

A novel mouse model of Campylobacter jejuni enteropathy and diarrhea

Campylobacter infections are among the leading bacterial causes of diarrhea and of ‘environmental enteropathy’ (EE) and growth failure worldwide. However, the lack of an inexpensive small animal model of enteric disease with Campylobacter has been a major limitation for understanding its pathogenesis, interventions or vaccine development. We describe a robust standard mouse model that can exhibit reproducible bloody diarrhea or growth failure, depending on the zinc or protein deficient diet and on antibiotic alteration of normal microbiota prior to infection. Zinc deficiency and the use of antibiotics create a niche for Campylobacter infection to establish by narrowing the metabolic flexibility of these mice for pathogen clearance and by promoting intestinal and systemic inflammation. Several biomarkers and intestinal pathology in this model also mimic those seen in human disease. This model provides a novel tool to test specific hypotheses regarding disease pathogenesis as well as vaccine development that is currently in progress

Human Interaction with Robot Swarms: A Survey

Recent advances in technology are delivering robots of reduced size and cost. A natural outgrowth of these advances are systems comprised of large numbers of robots that collaborate autonomously in diverse applications. Research on effective autonomous control of such systems, commonly called swarms, has increased dramatically in recent years and received attention from many domains, such as bioinspired robotics and control theory. These kinds of distributed systems present novel challenges for the effective integration of human supervisors, operators, and teammates that are only beginning to be addressed. This paper is the first survey of human–swarm interaction (HSI) and identifies the core concepts needed to design a human–swarm system. We first present the basics of swarm robotics. Then, we introduce HSI from the perspective of a human operator by discussing the cognitive complexity of solving tasks with swarm systems. Next, we introduce the interface between swarm and operator and identify challenges and solutions relating to human–swarm communication, state estimation and visualization, and human control of swarms. For the latter, we develop a taxonomy of control methods that enable operators to control swarms effectively. Finally, we synthesize the results to highlight remaining challenges, unanswered questions, and open problems for HSI, as well as how to address them in future works

Polarity of uncertainty representation during exploration and exploitation in ventromedial prefrontal cortex

Environments furnish multiple information sources for making predictions about future events. Here we use behavioural modelling and functional magnetic resonance imaging to describe how humans select predictors that might be most relevant. First, during early encounters with potential predictors, participants’ selections were explorative and directed towards subjectively uncertain predictors (positive uncertainty effect). This was particularly the case when many future opportunities remained to exploit knowledge gained. Then, preferences for accurate predictors increased over time, while uncertain predictors were avoided (negative uncertainty effect). The behavioural transition from positive to negative uncertainty-driven selections was accompanied by changes in the representations of belief uncertainty in ventromedial prefrontal cortex (vmPFC). The polarity of uncertainty representations (positive or negative encoding of uncertainty) changed between exploration and exploitation periods. Moreover, the two periods were separated by a third transitional period in which beliefs about predictors’ accuracy predominated. The vmPFC signals a multiplicity of decision variables, the strength and polarity of which vary with behavioural context

Diabetes is a Risk Factor for Pulmonary Tuberculosis: A Case-Control Study from Mwanza, Tanzania.

Diabetes and TB are associated, and diabetes is increasingly common in low-income countries where tuberculosis (TB) is highly endemic. However, the role of diabetes for TB has not been assessed in populations where HIV is prevalent. A case-control study was conducted in an urban population in Tanzania among culture-confirmed pulmonary TB patients and non-TB neighbourhood controls. Participants were tested for diabetes according to WHO guidelines and serum concentrations of acute phase reactants were measured. The association between diabetes and TB, and the role of HIV as an effect modifier, were examined using logistic regression. Since blood glucose levels increase during the acute phase response, we adjusted for elevated serum acute phase reactants. Among 803 cases and 350 controls the mean (SD) age was 34.8 (11.9) and 33.8 (12.0) years, and the prevalence of diabetes was 16.7% (95% CI: 14.2; 19.4) and 9.4% (6.6; 13.0), respectively. Diabetes was associated with TB (OR 2.2, 95% CI: 1.5; 3.4, p<0.001). However, the association depended on HIV status (interaction, p = 0.01) due to a stronger association among HIV uninfected (OR 4.2, 95% CI: 1.5; 11.6, p = 0.01) compared to HIV infected (OR 0.1, 95% CI: 0.01; 1.8, p = 0.13) after adjusting for age, sex, demographic factors and elevated serum acute phase reactants. Diabetes is a risk factor for TB in HIV uninfected, whereas the association in HIV infected patients needs further study. The increasing diabetes prevalence may be a threat to TB control

Confirmation bias in the utilization of others' opinion strength

Humans tend to discount information that undermines past choices and judgments. This confirmation bias has significant impact on domains ranging from politics to science and education. Little is known about the mechanisms underlying this fundamental characteristic of belief formation. Here we report a mechanism underlying the confirmation bias. Specifically, we provide evidence for a failure to use the strength of others' disconfirming opinions to alter confidence in judgments, but adequate use when opinions are confirmatory. This bias is related to reduced neural sensitivity to the strength of others' opinions in the posterior medial prefrontal cortex when opinions are disconfirming. Our results demonstrate that existing judgments alter the neural representation of information strength, leaving the individual less likely to alter opinions in the face of disagreement