Global disruption in excitation-inhibition balance can cause localized network dysfunction and Schizophrenia-like context-integration deficits

Poor context integration, the process of incorporating both previous and current information in decision making, is a cognitive symptom of schizophrenia. The maintenance of the contextual information has been shown to be sensitive to changes in excitation-inhibition (EI) balance. Many regions of the brain are sensitive to EI imbalances, however, so it is unknown how systemic manipulations affect the specific regions that are important to context integration. We constructed a multi-structure, biophysically-realistic agent that could perform context-integration as is assessed by the dot pattern expectancy task. The agent included a perceptual network, a memory network, and a decision making system and was capable of successfully performing the dot pattern expectancy task. Systemic manipulation of the agent’s EI balance produced localized dysfunction of the memory structure, which resulted in schizophrenia-like deficits at context integration. When the agent’s pyramidal cells were less excitatory, the agent fixated upon the cue and initiated responding later than the default agent, which were like the deficits one would predict that individuals on the autistic spectrum would make. This modelling suggests that it may be possible to parse between different types of context integration deficits by adding distractors to context integration tasks and by closely examining a participant’s reaction times.     

Metacognition and mentalizing are associated with distinct neural representations of decision uncertainty

Metacognition and mentalizing are both associated with meta-level mental state representations. Conventionally, metacognition refers to monitoring one’s own cognitive processes, while mentalizing refers to monitoring others’ cognitive processes. However, this self-other dichotomy is insufficient to delineate the 2 high-level mental processes. We here used functional magnetic resonance imaging (fMRI) to systematically investigate the neural representations of different levels of decision uncertainty in monitoring different targets (the current self, the past self [PS], and others) performing a perceptual decision-making task. Our results reveal diverse formats of internal mental state representations of decision uncertainty in mentalizing, separate from the associations with external cue information. External cue information was commonly represented in the right inferior parietal lobe (IPL) across the mentalizing tasks. However, the internal mental states of decision uncertainty attributed to others were uniquely represented in the dorsomedial prefrontal cortex (dmPFC), rather than the temporoparietal junction (TPJ) that also represented the object-level mental states of decision inaccuracy attributed to others. Further, the object-level and meta-level mental states of decision uncertainty, when attributed to the PS, were represented in the precuneus and the lateral frontopolar cortex (lFPC), respectively. In contrast, the dorsal anterior cingulate cortex (dACC) represented currently experienced decision uncertainty in metacognition, and also uncertainty about the estimated decision uncertainty (estimate uncertainty), but not the estimated decision uncertainty per se in mentalizing. Hence, our findings identify neural signatures to clearly delineate metacognition and mentalizing and further imply distinct neural computations on internal mental states of decision uncertainty during metacognition and mentalizing.

The relationship between metacognition and mentalizing is still a matter of debate, as both are associated with meta-representations. This study adapts a task paradigm used in metacognition to apply in mentalizing and compares the neural representations of decision uncertainty in metacognition and mentalizing.     

Parents’ Agendas in Paediatric Clinical Trial Recruitment Are Different from Researchers’ and Often Remain Unvoiced: A Qualitative Study

Ensuring parents make an informed decision about their child’s participation in a clinical trial is a challenge for practitioners as a parent’s comprehension of a trial may differ from that intended by the practitioners responsible for recruitment. We explored what issues parents consider important when making a decision about participation in a paediatric clinical trial and their comprehension of these issues to inform future recruitment practice. This qualitative interview and observational study examined recruitment in four placebo-controlled, double-blind randomised clinical trials of medicines for children. Audio-recorded trial recruitment discussions between practitioners and parents (N = 41) were matched with semi-structured interviews with parents (N = 41). When making a decision about trial entry parents considered clinical benefit, child safety, practicalities of participation, research for the common good, access to medication and randomisation. Within these prioritised issues parents had specific misunderstandings, which had the potential to influence their decisions. While parents had many questions and concerns about trial participation which influenced their decision-making, they rarely voiced these during discussions about the trials with practitioners. Those involved in the recruitment of children to clinical trials need to be aware of parents’ priorities and the sorts of misunderstandings that can arise with parents. Providing trial information that is tailored to what parents consider important in making a decision about a clinical trial may improve recruitment practice and ultimately benefit evidence-based paediatric medicine.     

How People Use Social Information to Find out What to Want in the Paradigmatic Case of Inter-temporal Preferences

The weight with which a specific outcome feature contributes to preference quantifies a person’s ‘taste’ for that feature. However, far from being fixed personality characteristics, tastes are plastic. They tend to align, for example, with those of others even if such conformity is not rewarded. We hypothesised that people can be uncertain about their tastes. Personal tastes are therefore uncertain beliefs. People can thus learn about them by considering evidence, such as the preferences of relevant others, and then performing Bayesian updating. If a person’s choice variability reflects uncertainty, as in random-preference models, then a signature of Bayesian updating is that the degree of taste change should correlate with that person’s choice variability. Temporal discounting coefficients are an important example of taste–for patience. These coefficients quantify impulsivity, have good psychometric properties and can change upon observing others’ choices. We examined discounting preferences in a novel, large community study of 14–24 year olds. We assessed discounting behaviour, including decision variability, before and after participants observed another person’s choices. We found good evidence for taste uncertainty and for Bayesian taste updating. First, participants displayed decision variability which was better accounted for by a random-taste than by a response-noise model. Second, apparent taste shifts were well described by a Bayesian model taking into account taste uncertainty and the relevance of social information. Our findings have important neuroscientific, clinical and developmental significance.     

Collective unary decision-making by decentralized multiple-robot systems applied to the task-sequencing problem

When a complex mission must be undertaken, it often can be simplified by dividing it into a sequence of smaller subtasks, which are then completed in order. This strategy implicitly requires a system to recognize the completion of each subtask and make the decision to begin work on the next one. Decentralized multiple-robot systems can tackle many tasks, but their behavior is typified by continuous responses to stimuli. Task sequencing, however, demands a controlled, self-induced phase change in collective behavior—working on one task one moment and then on a different task the next—which is nontrivial for an emergent system. The main contribution of this study is a collective decision-making framework for decentralized multiple-robot systems that enables such a system to cooperatively decide that a current task has been completed and thus focus its attention on the next one in a sequence using only anonymous local communication. Central to the framework is the use of consensus, whereby task sequencing is delayed until a prespecified proportion of a system’s robots agree that the current task is complete, reducing the likelihood of premature decisions. Two low-cost consensus estimation strategies are presented, both of which are practical for the extremely simple robots that are expected to compose large decentralized systems. Experiments in simulation and with real robots demonstrate that the proposed decision-making framework performs as predicted. Although the specific application of collective decision-making in this work is the cooperative task-sequencing problem, the proposed decision-making framework potentially has many additional applications.     

You Have My Word: Reciprocity Expectation Modulates Feedback-Related Negativity in the Trust Game

Promise is one of the most powerful tools producing trust and facilitating cooperation, and sticking to the promise is deemed as a key social norm in social interactions. The present study explored the extent to which promise would influence investors’ decision-making in the trust game where promise had no predictive value regarding trustees’ reciprocation. In addition, we examined the neural underpinnings of the investors’ outcome processing related to the trustees’ promise keeping and promise breaking. Consistent with our hypothesis, behavioral results indicated that promise could effectively increase the investment frequency of investors. Electrophysiological results showed that, promise induced larger differentiated-FRN responses to the reward and non-reward discrepancy. Taken together, these results suggested that promise would promote cooperative behavior, while breach of promise would be regarded as a violation of the social norm, corroborating the vital role of non-enforceable commitment in social decision making.     

Diauxic lags explain unexpected coexistence in multi‐resource environments

How the coexistence of species is affected by the presence of multiple resources is a major question in microbial ecology. We experimentally demonstrate that differences in diauxic lags, which occur as species deplete their own environments and adapt their metabolisms, allow slow‐growing microbes to stably coexist with faster‐growing species in multi‐resource environments despite being excluded in single‐resource environments. In our focal example, an Acinetobacter species (Aci2) competitively excludes Pseudomonas aurantiaca (Pa) on alanine and on glutamate. However, they coexist on the combination of both resources. Experiments reveal that Aci2 grows faster but Pa has shorter diauxic lags. We establish a tradeoff between Aci2’s fast growth and Pa’s short lags as their mechanism for coexistence. We model this tradeoff to accurately predict how environmental changes affect community composition. We extend our work by surveying a large set of competitions and observe coexistence nearly four times as frequently when the slow‐grower is the fast‐switcher. Our work illustrates a simple mechanism, based entirely on supplied‐resource growth dynamics, for the emergence of multi‐resource coexistence.     

Monte Carlo Planning Method Estimates Planning Horizons during Interactive Social Exchange

Reciprocating interactions represent a central feature of all human exchanges. They have been the target of various recent experiments, with healthy participants and psychiatric populations engaging as dyads in multi-round exchanges such as a repeated trust task. Behaviour in such exchanges involves complexities related to each agent’s preference for equity with their partner, beliefs about the partner’s appetite for equity, beliefs about the partner’s model of their partner, and so on. Agents may also plan different numbers of steps into the future. Providing a computationally precise account of the behaviour is an essential step towards understanding what underlies choices. A natural framework for this is that of an interactive partially observable Markov decision process (IPOMDP). However, the various complexities make IPOMDPs inordinately computationally challenging. Here, we show how to approximate the solution for the multi-round trust task using a variant of the Monte-Carlo tree search algorithm. We demonstrate that the algorithm is efficient and effective, and therefore can be used to invert observations of behavioural choices. We use generated behaviour to elucidate the richness and sophistication of interactive inference.     

Subjective optimality in finite sequential decision-making

Many decisions in life are sequential and constrained by a time window. Although mathematically derived optimal solutions exist, it has been reported that humans often deviate from making optimal choices. Here, we used a secretary problem, a classic example of finite sequential decision-making, and investigated the mechanisms underlying individuals’ suboptimal choices. Across three independent experiments, we found that a dynamic programming model comprising subjective value function explains individuals’ deviations from optimality and predicts the choice behaviors under fewer and more opportunities. We further identified that pupil dilation reflected the levels of decision difficulty and subsequent choices to accept or reject the stimulus at each opportunity. The value sensitivity, a model-based estimate that characterizes each individual’s subjective valuation, correlated with the extent to which individuals’ physiological responses tracked stimuli information. Our results provide model-based and physiological evidence for subjective valuation in finite sequential decision-making, rediscovering human suboptimality in subjectively optimal decision-making processes.     

Bayesian Analysis for Uncertainty and Risk in a Groundwater Numerical Model's Predictions

Groundwater modeling typically relies on some hypothesis and approximations of reality, as the real hydrologic systems are far more complex than we can mathematically characterize. This kind of a model's errors cannot be neglected in the uncertainty analysis for a model's predictions in practical issues. As the scale and complexity increase, the associated uncertainties boost dramatically. In this study, a Bayesian uncertainty analysis method for a deterministic model's predictions is presented. The geostatistics of hydrogeologic parameters obtained from site characterization are treated as the prior parameter distribution in the Bayes’ theorem. Then the Markov-Chain Monte Carlo method is used to generate the posterior statistical distribution of the model's predictions, conditional to the observed hydrologic system behaviors. Finally, a series of synthetic examples are given by applying this method to a MODFLOW pumping test model, to test its capability and efficiency in order to assess various sources of the model's prediction uncertainty. The impacts of the model's parameter sensitivity, simplification, and observation errors to predict uncertainty are evaluated, respectively. The results are analyzed statistically to provide deterministic predictions with associated prediction errors. Risk analysis is also derived from the Bayesian results to draw tradeoff curves for decision-making about exploitation of groundwater resources.     

Virtual bargaining: a theory of social decision-making

An essential element of goal-directed decision-making in social contexts is that agents'' actions may be mutually interdependent. However, the most well-developed approaches to such strategic interactions, based on the Nash equilibrium concept in game theory, are sometimes too broad and at other times ‘overlook’ good solutions to fundamental social dilemmas and coordination problems. The authors propose a new theory of social decision-making—virtual bargaining—in which individuals decide among a set of moves on the basis of what they would agree to do if they could openly bargain. The core principles of a formal account are outlined (vis-à-vis the notions of ‘feasible agreement’ and explicit negotiation) and further illustrated with the introduction of a new game, dubbed the ‘Boobytrap game’ (a modification on the canonical Prisoner''s Dilemma paradigm). In the first empirical data of how individuals play the Boobytrap game, participants'' experimental choices accord well with a virtual bargaining perspective, but do not match predictions from a standard Nash account. Alternative frameworks are discussed, with specific empirical tests between these and virtual bargaining identified as future research directions. Lastly, it is proposed that virtual bargaining underpins a vast range of human activities, from social decision-making to joint action and communication.     

Ten simple rules for finding and selecting R packages

R is an increasingly preferred software environment for data analytics and statistical computing among scientists and practitioners. Packages markedly extend R’s utility and ameliorate inefficient solutions to data science problems. We outline 10 simple rules for finding relevant packages and determining which package is best for your desired use. We begin in Rule 1 with tips on how to consider your purpose, which will guide your search to follow, where, in Rule 2, you’ll learn best practices for finding and collecting options. Rules 3 and 4 will help you navigate packages’ profiles and explore the extent of their online resources, so that you can be confident in the quality of the package you choose and assured that you’ll be able to access support. In Rules 5 and 6, you’ll become familiar with how the R Community evaluates packages and learn how to assess the popularity and utility of packages for yourself. Rules 7 and 8 will teach you how to investigate and track package development processes, so you can further evaluate their merit. We end in Rules 9 and 10 with more hands-on approaches, which involve digging into package code.     

Nicotine Increases Impulsivity and Decreases Willingness to Exert Cognitive Effort despite Improving Attention in “Slacker” Rats: Insights into Cholinergic Regulation of Cost/Benefit Decision Making

Successful decision making in our daily lives requires weighing an option’s costs against its associated benefits. The neuromodulator acetylcholine underlies both the etiology and treatment of a number of illnesses in which decision making is perturbed, including Alzheimer’s disease, attention-deficit/hyperactivity disorder, and schizophrenia. Nicotine acts on the cholinergic system and has been touted as a cognitive enhancer by both smokers and some researchers for its attention-boosting effects; however, it is unclear whether treatments that have a beneficial effect on attention would also have a beneficial effect on decision making. Here we utilize the rodent Cognitive Effort Task (rCET), wherein animals can choose to allocate greater visuospatial attention for a greater reward, to examine cholinergic contributions to both attentional performance and choice based on attentional demand. Following the establishment of baseline behavior, four drug challenges were administered: nicotine, mecamylamine, scopolamine, and oxotremorine (saline plus three doses for each). As per previous rCET studies, animals were divided by their baseline preferences, with “worker” rats choosing high-effort/high-reward options more than their “slacker” counterparts. Nicotine caused slackers to choose even fewer high-effort trials than at baseline, but had no effect on workers’ choice. Despite slackers’ decreased willingness to expend effort, nicotine improved their attentional performance on the task. Nicotine also increased measures of motor impulsivity in all animals. In contrast, scopolamine decreased animals’ choice of high-effort trials, especially for workers, while oxotremorine decreased motor impulsivity for all animals. In sum, the cholinergic system appears to contribute to decision making, and in part these contributions can be understood as a function of individual differences. While nicotine has been considered as a cognitive enhancer, these data suggest that its modest benefits to attention may be coupled with impulsiveness and decreased willingness to work hard, especially in individuals who are particularly sensitive to effort costs (i.e. slackers).     

Organ Donation After Acute Brain Death: Addressing Limitations of Time and Resources in the Emergency Department

It is not unusual for emergency physicians to quickly identify whether a patient would have wanted to be resuscitated or intubated in a cardiac arrest situation, but patients’ other preferences for end-of-life care or organ donation are less commonly ascertained in the emergency department. Typically, the decision process regarding such goals at end of life may be “deferred” to the intensive care unit. We present a case illustrative of the complexity of discussing organ donation in the emergency department and suggest that patients who die in the emergency department should be afforded the respect and consideration provided in other parts of the hospital, including facilitation of organ transplantation. As circulatory determination of death becomes a more common antecedent to organ transplantation, specific questions may arise in the emergency department setting. When in the emergency department, how should organ donation be addressed and by whom? Should temporary organ preservation be initiated in the setting of uncertainty regarding a patient’s wishes? To better facilitate discussions about organ donation when they arise in emergency settings, we propose increased coordination between organ procurement organizations and emergency physicians to improve awareness of organ transplantation.     

Could the Decision of Trial Participation Precede the Informed Consent Process? Evidence From Burkina Faso

Background

Over the last years, the number of clinical trials carried out in low-income countries with poor medical infrastructure and limited access to health care has increased. In these settings, the decision of participating in a clinical study may be influenced by factors related to participants’ vulnerability that limit the efficacy of the informed consent.

Methods

A mixed methods social science study, based on the triangulation of qualitative and quantitative data, was carried out in a socio-economically disadvantaged and semi-urban area of Bobo Dioulasso, Burkina Faso. The study aimed at assessing the relevance of the informed consent procedure on the decision-making process of the parents and/or guardians of potential participants in a pediatric malaria trial.

Results

For most parents (70.4%), the decision of participating had already been taken before undergoing the informed consent process and was based on the information conveyed through the community. Access to free and good quality health care often inspired this decision. In addition, the parents’ willingness to have their child included in the trial made them develop active strategies to achieve this purpose.

Discussion

In a context of socio-economic vulnerability and poor access to free health care, the process of informed consent does not always accomplish its goal of informing people and enabling them to make a free and informed decision. This information role is somehow anticipated by the community and trial participation becomes a strategic action to secure otherwise unavailable health resources leading community members to decide on participation even prior to the informed consent process.     

Fostering accessible online education using Galaxy as an e-learning platform

The COVID-19 pandemic is shifting teaching to an online setting all over the world. The Galaxy framework facilitates the online learning process and makes it accessible by providing a library of high-quality community-curated training materials, enabling easy access to data and tools, and facilitates sharing achievements and progress between students and instructors. By combining Galaxy with robust communication channels, effective instruction can be designed inclusively, regardless of the students’ environments.     

Preschool Children’s Behavioral Tendency toward Social Indirect Reciprocity

Social indirect reciprocity seems to be crucial in enabling large-scale cooperative networks among genetically unrelated individuals in humans. However, there are relatively few studies on social indirect reciprocity in children compared to adults. Investigating whether young children have a behavioral tendency toward social indirect reciprocity will help us understand how and when the fundamental ability to form cooperative relationships among adults is acquired. Using naturalistic observation at a nursery school, this study examined whether 5- to 6-year-olds show a behavioral tendency to engage in social indirect reciprocity in response to their peers’ prosocial behavior toward a third party. The results revealed that bystander children tended to display prosocial behavior toward their peers more frequently after observing these peers’ prosocial behavior toward third-party peers, compared with control situations; this suggests that 5- to 6-year-olds may have an essential behavioral tendency to establish social indirect reciprocity when interacting with peers in their daily lives. In addition, bystanders tended to display affiliative behavior after observing focal children’s prosocial behavior. In other words, observing peers’ prosocial behavior toward third-party peers evoked bystanders’ positive emotions toward the helpers. Considering both the present results and previous findings, we speculate that in preschoolers, such positive emotions might mediate the increase in the bystander’s prosocial behavior toward the helper. In addition, an intuitional emotional process plays an important role in the preschooler’s behavioral tendency toward social indirect reciprocity in natural interactions with peers.     

Human Sensorimotor Communication: A Theory of Signaling in Online Social Interactions

Although the importance of communication is recognized in several disciplines, it is rarely studied in the context of online social interactions and joint actions. During online joint actions, language and gesture are often insufficient and humans typically use non-verbal, sensorimotor forms of communication to send coordination signals. For example, when playing volleyball, an athlete can exaggerate her movements to signal her intentions to her teammates (say, a pass to the right) or to feint an adversary. Similarly, a person who is transporting a table together with a co-actor can push the table in a certain direction to signal where and when he intends to place it. Other examples of “signaling” are over-articulating in noisy environments and over-emphasizing vowels in child-directed speech. In all these examples, humans intentionally modify their action kinematics to make their goals easier to disambiguate. At the moment no formal theory exists of these forms of sensorimotor communication and signaling. We present one such theory that describes signaling as a combination of a pragmatic and a communicative action, and explains how it simplifies coordination in online social interactions. We cast signaling within a “joint action optimization” framework in which co-actors optimize the success of their interaction and joint goals rather than only their part of the joint action. The decision of whether and how much to signal requires solving a trade-off between the costs of modifying one’s behavior and the benefits in terms of interaction success. Signaling is thus an intentional strategy that supports social interactions; it acts in concert with automatic mechanisms of resonance, prediction, and imitation, especially when the context makes actions and intentions ambiguous and difficult to read. Our theory suggests that communication dynamics should be studied within theories of coordination and interaction rather than only in terms of the maximization of information transmission.     

Young Children’s Sensitivity to Their Own Ignorance in Informing Others

Prior research suggests that young children selectively inform others depending on others’ knowledge states. Yet, little is known whether children selectively inform others depending on their own knowledge states. To explore this issue, we manipulated 3- to 4-year-old children’s knowledge about the content of a box and assessed the impact on their decisions to inform another person. Moreover, we assessed the presence of uncertainty gestures while they inform another person in light of the suggestions that children''s gestures reflect early developing, perhaps transient, epistemic sensitivity. Finally, we compared children’s performance in the informing context to their explicit verbal judgment of their knowledge states to further confirm the existence of a performance gap between the two tasks. In their decisions to inform, children tend to accurately assess their ignorance, whereas they tend to overestimate their own knowledge states when asked to explicitly report them. Moreover, children display different levels of uncertainty gestures depending on the varying degrees of their informational access. These findings suggest that children’s implicit awareness of their own ignorance may be facilitated in a social, communicative context.     

Communicating and Dealing with Uncertainty in General Practice: The Association with Neuroticism

Background

Diagnostic reasoning in primary care setting where presented problems and patients are mostly unselected appears as a complex process. The aim was to develop a questionnaire to describe how general practitioners (GPs) deal with uncertainty to gain more insight into the decisional process. The association of personality traits with medical decision making was investigated additionally.

Methods

Raw items were identified by literature research and focus group. Items were improved by interviewing ten GPs with thinking-aloud-method. A personal case vignette related to a complex and uncertainty situation was introduced. The final questionnaire was administered to 228 GPs in Germany. Factorial validity was calculated with explorative and confirmatory factor analysis. The results of the Communicating and Dealing with Uncertainty (CoDU) – questionnaire were compared with the scales of the ‘Physician Reaction to Uncertainty’ (PRU) questionnaire and with the personality traits which were determined with the Big Five Inventory (BFI-K).

Results

The items could be assigned to four scales with varying internal consistency, namely ‘communicating uncertainty’ (Cronbach alpha 0.79), ‘diagnostic action’ (0.60), ‘intuition’ (0.39) and ‘extended social anamnesis’ (0.69). Neuroticism was positively associated with all PRU scales ‘anxiety due to uncertainty’ (Pearson correlation 0.487), ‘concerns about bad outcomes’ (0.488), ‘reluctance to disclose uncertainty to patients’ (0.287), ‘reluctance to disclose mistakes to physicians’ (0.212) and negatively associated with the CoDU scale ‘communicating uncertainty’ (−0.242) (p<0.01 for all). ‘Extraversion’ (0.146; p<0.05), ‘agreeableness’ (0.145, p<0.05), ‘conscientiousness’ (0.168, p<0.05) and ‘openness to experience’ (0.186, p<0.01) were significantly positively associated with ‘communicating uncertainty’. ‘Extraversion’ (0.162), ‘consciousness’ (0.158) and ‘openness to experience’ (0.155) were associated with ‘extended social anamnesis’ (p<0.05).

Conclusion

The questionnaire allowed describing the diagnostic decision making process of general practitioners in complex situations. Personality traits are associated with diagnostic reasoning and communication with patients, which might be important for medical education and quality improvement purposes.