Societal background influences social learning in cooperative decision making

Humans owe their ecological success to their great capacities for social learning and cooperation: learning from others helps individuals adjust to their environment and can promote cooperation in groups. Classic and recent studies indicate that the cultural organization of societies shapes the influence of social information on decision making and suggest that collectivist values (prioritizing the group relative to the individual) increase tendencies to conform to the majority. However, it is unknown whether and how societal background impacts social learning in cooperative interactions. Here we show that social learning in cooperative decision making systematically varies across two societies. We experimentally compare people's basic propensities for social learning in samples from a collectivist (China) and an individualist society (United Kingdom; total n?=?540) in a social dilemma and a coordination game. We demonstrate that Chinese participants base their cooperation decisions on information about their peers much more frequently than their British counterparts. Moreover, our results reveal remarkable societal differences in the type of peer information people consider. In contrast to the consensus view, Chinese participants tend to be substantially less majority-oriented than the British. While Chinese participants are inclined to adopt peer behavior that leads to higher payoffs, British participants tend to cooperate only if sufficiently many peers do so too. These results indicate that the basic processes underlying social transmission are not universal; rather, they vary with cultural conditions. As success-based learning is associated with selfish behavior and majority-based learning can help foster cooperation, our study suggests that in different societies social learning can play diverging roles in the emergence and maintenance of cooperation.     

Choosing the greater of two goods: neural currencies for valuation and decision making

To make adaptive decisions, animals must evaluate the costs and benefits of available options. The nascent field of neuroeconomics has set itself the ambitious goal of understanding the brain mechanisms that are responsible for these evaluative processes. A series of recent neurophysiological studies in monkeys has begun to address this challenge using novel methods to manipulate and measure an animal's internal valuation of competing alternatives. By emphasizing the behavioural mechanisms and neural signals that mediate decision making under conditions of uncertainty, these studies might lay the foundation for an emerging neurobiology of choice behaviour.     

The neural systems that mediate human perceptual decision making

Perceptual decision making is the act of choosing one option or course of action from a set of alternatives on the basis of available sensory evidence. Thus, when we make such decisions, sensory information must be interpreted and translated into behaviour. Neurophysiological work in monkeys performing sensory discriminations, combined with computational modelling, has paved the way for neuroimaging studies that are aimed at understanding decision-related processes in the human brain. Here we review findings from human neuroimaging studies in conjunction with data analysis methods that can directly link decisions and signals in the human brain on a trial-by-trial basis. This leads to a new view about the neural basis of human perceptual decision-making processes.     

Tracking wetland loss to improve evidence-based wetland policy learning and decision making

At the core of any evidence-based policy analysis are accurate data and the policy analytic capacity of government agencies to use these data to develop and measure metrics of policy success. This study evaluated the government’s policy capacity to manage wetlands in Alberta, Canada, by measuring and evaluating three policy metrics: (1) no net change of wetland area; (2) permitted versus unpermitted wetland loss; and (3) an information tracking system that provides credible regulatory oversight. Using a climate-corrected wetland loss inventory, we detected the loss of 242 wetlands, totaling 71 ha, in the Beaverhill subwatershed between 1999 and 2009. The majority of the losses occurred on land that were classified as ‘developed’ (urban and industrial) or ‘agriculture’. When wetland loss was compared to government-issued wetland permit data, we found that over 80 % of the wetland area was lost without a government permit. The wetland permit data also revealed serious problems with information tracking by both government and non-government agencies responsible for policy and regulatory oversight. In order to resolve these common policy failures, governments need to commit more resources towards acquiring, effectively managing, and freely sharing information that can be used to evaluate policy outcomes to ‘open up’ wetland management and decision making to include active participation from informal institutions, local governments, and the general public as a means to drive improved regulatory oversight.     

Consensus decision making in animals

Individual animals routinely face decisions that are crucial to their fitness. In social species, however, many of these decisions need to be made jointly with other group members because the group will split apart unless a consensus is reached. Here, we review empirical and theoretical studies of consensus decision making, and place them in a coherent framework. In particular, we classify consensus decisions according to the degree to which they involve conflict of interest between group members, and whether they involve either local or global communication; we ask, for different categories of consensus decision, who makes the decision, what are the underlying mechanisms, and what are the functional consequences. We conclude that consensus decision making is common in non-human animals, and that cooperation between group members in the decision-making process is likely to be the norm, even when the decision involves significant conflict of interest.     

Training in ethical decision making

Advances in biotechnology and evolving attitudes of biomedical professionals and members of the general public toward illness, medical care, and research generate topics for ethics discussions. The author offers advice for training animal care staff in ethical decision making.     

A plausible neural circuit for decision making and its formation based on reinforcement learning

A human’s, or lower insects’, behavior is dominated by its nervous system. Each stable behavior has its own inner steps and control rules, and is regulated by a neural circuit. Understanding how the brain influences perception, thought, and behavior is a central mandate of neuroscience. The phototactic flight of insects is a widely observed deterministic behavior. Since its movement is not stochastic, the behavior should be dominated by a neural circuit. Based on the basic firing characteristics of biological neurons and the neural circuit’s constitution, we designed a plausible neural circuit for this phototactic behavior from logic perspective. The circuit’s output layer, which generates a stable spike firing rate to encode flight commands, controls the insect’s angular velocity when flying. The firing pattern and connection type of excitatory and inhibitory neurons are considered in this computational model. We simulated the circuit’s information processing using a distributed PC array, and used the real-time average firing rate of output neuron clusters to drive a flying behavior simulation. In this paper, we also explored how a correct neural decision circuit is generated from network flow view through a bee’s behavior experiment based on the reward and punishment feedback mechanism. The significance of this study: firstly, we designed a neural circuit to achieve the behavioral logic rules by strictly following the electrophysiological characteristics of biological neurons and anatomical facts. Secondly, our circuit’s generality permits the design and implementation of behavioral logic rules based on the most general information processing and activity mode of biological neurons. Thirdly, through computer simulation, we achieved new understanding about the cooperative condition upon which multi-neurons achieve some behavioral control. Fourthly, this study aims in understanding the information encoding mechanism and how neural circuits achieve behavior control. Finally, this study also helps establish a transitional bridge between the microscopic activity of the nervous system and macroscopic animal behavior.     

Aging and consumer decision making

Research on consumer decision making and aging is especially important for fostering a better understanding of ways to maintain consumer satisfaction and high decision quality across the life span. We provide a review of extant research on the effects of normal aging on cognition and decision processes and how these age-related processes are influenced by task environment, meaningfulness of the task, and consumer expertise. We consider how research centered on these topics generates insights about changes in consumption decisions that occur with aging and identify a number of gaps and directions for future research.     

Rough sets and genetic algorithms in learning cellular neural networks cloning template for decision making system

We purpose to find a new beneficial method for accelerating the Decision-Making and classifier support applied on imprecise data. This acceleration can be done by integration between Rough Sets theory, which gives us the minimal set of decision rules, and the Cellular Neural Networks. Our method depends on Genetic Algorithms for designing the cloning template for more accuracy. Some illustrative examples are given to demonstrate the effectiveness of the proposed method, whose advantages and limitations are also discussed.     

Genetic disruptions of Drosophila Pavlovian learning leave extinction learning intact

Individuals who experience traumatic events may develop persistent posttraumatic stress disorder. Patients with this disorder are commonly treated with exposure therapy, which has had limited long‐term success. In experimental neurobiology, fear extinction is a model for exposure therapy. In this behavioral paradigm, animals are repeatedly exposed in a safe environment to the fearful stimulus, which leads to greatly reduced fear. Studying animal models of extinction already has lead to better therapeutic strategies and development of new candidate drugs. Lack of a powerful genetic model of extinction, however, has limited progress in identifying underlying molecular and genetic factors. In this study, we established a robust behavioral paradigm to study the short‐term effect (acquisition) of extinction in Drosophila melanogaster. We focused on the extinction of olfactory aversive 1‐day memory with a task that has been the main workhorse for genetics of memory in flies. Using this paradigm, we show that extinction can inhibit each of two genetically distinct forms of consolidated memory. We then used a series of single‐gene mutants with known impact on associative learning to examine the effects on extinction. We find that extinction is intact in each of these mutants, suggesting that extinction learning relies on different molecular mechanisms than does Pavlovian learning.     

Associative learning: Pavlovian conditioning without awareness

Can Pavlovian conditioning occur outside of awareness? Yes, according to a new study showing that, under a particular set of circumstances, visual stimuli can become associated with aversive outcomes without participants ever seeing the stimuli.     

Temporal decision making in complex environments

The basic hypothesis of the author is that under the influence of technological development and market pressure, situations take on temporal characteristics that are more and more difficult for the operator to control. The temporal strategies traditionally installed by the operator disappear, are transferred or transformed. Far from counterbalancing these phenomena, the displays, as they are designed in the workplace, obliterate the temporal dimension. The errors that are seen to appear are the product of a mismatch between the characteristics of the situation and the operator's resources. Four mechanisms of time estimation are discussed. Field study results on temporal strategies, such as anticipation, assessment of a process evolution and planning adjustment are developed.     

Childhood malignancies and decision making.

Failure to obtain "adequate" medical care for a child constitutes child neglect, which may be used as the basis for prosecution of parents, removal of the child from the home, or court-ordered medical treatment. "Adequate" care is usually construed as that which is given by a licensed physician, but, in case of dispute, courts almost never engage in choosing one medical approach over another. The principle that parents may not refuse medical care, however, is made very difficult when children have malignancies--the long-term nature of the treatment means that, if the child is left at home, court order or not, the parents may flee with their child. Removing the child from the home, however, adds that trauma to the ill child's burdens. Questions should be asked before making a request to a court to order a therapy which will prolong but not save a child's life if the parents would prefer to spare their child the side effects. Parents, however, may always refuse to permit their child to participate in research studies, no matter how promising. Adolescents are increasingly believed to be capable of medical decision making; most courts, however, would not allow an adolescent to refuse life-saving treatment.