Rational choice,neuroeconomy and mixed emotions

Experimental psychology has shown differences between predictions of theory of decision and human choices. Emotions like regret can partly explain these differences. Neuroimagery used in combination with behavioural economics (neuroeconomics) has been used in order to try to disentangle the different emotional and rational factors (regret, rejoicing, reward, costs, uncertainty, trade-off between positive and negative aspects of different options). Emotions then appear as much more complex and mixed affective states than usually assumed. Not only might we feel a positive affect in punishing unfair partners, but mixed emotions can, for example, combine transmutation of previous anxiety into relief and elation by comparison with another less exciting option (elating relief). At the level of complexity of these mixed emotions—which we formally represent by comparisons between ‘unexpected utilities’ and expected ones—the main biases that Kahnemann and Tversky have shown can be explained. In spite of the complexity of these mixed emotions, some of these hypotheses might be partially tested by brain imagery.     

Dream emotions, waking emotions, personality characteristics and well-being--A positive psychology approach.

The study aimed to discover whether personality characteristics and waking emotions relate to dreaming emotions. There were 123 participants, ranging in age from 17 to 82 years. It was hypothesized that participants with significant positive emotional trait and state ratings in waking life would experience more positive dreams. Data collection utilized diaries and questionnaires, including Hartmann's Boundary Questionnaire, IPIP Emotional Stability Scale, Staats' Hope Scale, Adult Dispositional Hope Scale, and the Positive and Negative Affect Schedule to assess personality and attitudinal characteristics. Participants recorded and rated their waking and dream emotions over a 3-week period. Median correlations between corresponding waking and dream emotions were .58 for positive emotions and .47 for negative emotions. There were also low, but significant correlations between some personality characteristics and participants' tendency to experience positive or negative emotions in dreams. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Herding,social influence and economic decision-making: socio-psychological and neuroscientific analyses

Typically, modern economics has steered away from the analysis of sociological and psychological factors and has focused on narrow behavioural assumptions in which expectations are formed on the basis of mathematical algorithms. Blending together ideas from the social and behavioural sciences, this paper argues that the behavioural approach adopted in most economic analysis, in its neglect of sociological and psychological forces and its simplistically dichotomous categorization of behaviour as either rational or not rational, is too narrow and stark. Behaviour may reflect an interaction of cognitive and emotional factors and this can be captured more effectively using an approach that focuses on the interplay of different decision-making systems. In understanding the mechanisms affecting economic and financial decision-making, an interdisciplinary approach is needed which incorporates ideas from a range of disciplines including sociology, economic psychology, evolutionary biology and neuroeconomics.     

Changing time and emotions

In this paper, we consider that our experience of time (to come) depends on the emotions we feel when we imagine future pleasant or unpleasant events. A positive emotion such as relief or joy associated with a pleasant event that will happen in the future induces impatience. Impatience, in our context, implies that the experience of time up to the forthcoming event expands. A negative emotion such as grief or frustration associated with an unpleasant event that will happen in the future triggers anxiety. This will give the experience of time contraction. Time, therefore, is not exogeneously given to the individual and emotions, which link together events or situations, are a constitutive ingredient of the experience of time. Our theory can explain experimental evidence that people tend to prefer to perform painful actions earlier than pleasurable ones, contrary to the predictions yielded by the standard exponential discounting framework.     

Hebbian learning and predictive mirror neurons for actions,sensations and emotions

Spike-timing-dependent plasticity is considered the neurophysiological basis of Hebbian learning and has been shown to be sensitive to both contingency and contiguity between pre- and postsynaptic activity. Here, we will examine how applying this Hebbian learning rule to a system of interconnected neurons in the presence of direct or indirect re-afference (e.g. seeing/hearing one''s own actions) predicts the emergence of mirror neurons with predictive properties. In this framework, we analyse how mirror neurons become a dynamic system that performs active inferences about the actions of others and allows joint actions despite sensorimotor delays. We explore how this system performs a projection of the self onto others, with egocentric biases to contribute to mind-reading. Finally, we argue that Hebbian learning predicts mirror-like neurons for sensations and emotions and review evidence for the presence of such vicarious activations outside the motor system.     

Computation of emotions in man and machines

The importance of emotional expression as part of human communication has been understood since Aristotle, and the subject has been explored scientifically since Charles Darwin and others in the nineteenth century. Advances in computer technology now allow machines to recognize and express emotions, paving the way for improved human–computer and human–human communications.Recent advances in psychology have greatly improved our understanding of the role of affect in communication, perception, decision-making, attention and memory. At the same time, advances in technology mean that it is becoming possible for machines to sense, analyse and express emotions. We can now consider how these advances relate to each other and how they can be brought together to influence future research in perception, attention, learning, memory, communication, decision-making and other applications.The computation of emotions includes both recognition and synthesis, using channels such as facial expressions, non-verbal aspects of speech, posture, gestures, physiology, brain imaging and general behaviour. The combination of new results in psychology with new techniques of computation is leading to new technologies with applications in commerce, education, entertainment, security, therapy and everyday life. However, there are important issues of privacy and personal expression that must also be considered.     

Selectivity in social and asocial learning: investigating the prevalence,effect and development of young children's learning preferences

Culture evolution requires both modification and faithful replication of behaviour, thus it is essential to understand how individuals choose between social and asocial learning. In a quasi-experimental design, 3- and 5-year-olds (176), and adults (52) were presented individually with two novel artificial fruits, and told of the apparatus'' relative difficulty (easy versus hard). Participants were asked if they wanted to attempt the task themselves or watch an experimenter attempt it first; and then had their preference either met or violated. A significant proportion of children and adults (74%) chose to learn socially. For children, this request was efficient, as observing a demonstration made them significantly quicker at the task than learning asocially. However, for 5-year-olds, children who selected asocial learning were also found to be highly efficient at the task, showing that by 5 years children are selective in choosing a learning strategy that is effective for them. Adults further evidenced this trend, and also showed selectivity based on task difficulty. This is the first study to examine the rates, performance outcomes and developmental trajectory of preferences in asocial and social learning, ultimately informing our understanding of innovation.     

Success-biased social learning: Cultural and evolutionary dynamics

Success bias is a social learning strategy whereby learners tend to acquire the cultural variants of successful individuals. I develop a general model of success-biased social learning for discrete cultural traits with stochastic payoffs, and investigate its dynamics when only two variants are present. I find that success bias inherently favors rare variants, and consequently performs worse than unbiased imitation (i.e. random copying) when success payoffs are at least mildly stochastic and the optimal variant is common. Because of this weakness, success bias fails to replace unbiased imitation in an evolutionary model when selection is fairly weak or when the environment is relatively stable, and sometimes fails to invade at all. I briefly discuss the optimal strength of success bias, the complicated nature of defining success in social learning contexts, and the value of variant frequency as an important source of information to social learners. I conclude with predictions regarding the prevalence of success bias in different behavioral domains.     

Counterfactual choice and learning in a neural network centered on human lateral frontopolar cortex

Decision making and learning in a real-world context require organisms to track not only the choices they make and the outcomes that follow but also other untaken, or counterfactual, choices and their outcomes. Although the neural system responsible for tracking the value of choices actually taken is increasingly well understood, whether a neural system tracks counterfactual information is currently unclear. Using a three-alternative decision-making task, a Bayesian reinforcement-learning algorithm, and fMRI, we investigated the coding of counterfactual choices and prediction errors in the human brain. Rather than representing evidence favoring multiple counterfactual choices, lateral frontal polar cortex (lFPC), dorsomedial frontal cortex (DMFC), and posteromedial cortex (PMC) encode the reward-based evidence favoring the best counterfactual option at future decisions. In addition to encoding counterfactual reward expectations, the network carries a signal for learning about counterfactual options when feedback is available-a counterfactual prediction error. Unlike other brain regions that have been associated with the processing of counterfactual outcomes, counterfactual prediction errors within the identified network cannot be related to regret theory. Furthermore, individual variation in counterfactual choice-related activity and prediction error-related activity, respectively, predicts variation in the propensity to switch to profitable choices in the future and the ability to learn from hypothetical feedback. Taken together, these data provide both neural and behavioral evidence to support the existence of a previously unidentified neural system responsible for tracking both counterfactual choice options and their outcomes.     

Mathematical properties of neuronal TD-rules and differential Hebbian learning: a comparison

A confusingly wide variety of temporally asymmetric learning rules exists related to reinforcement learning and/or to spike-timing dependent plasticity, many of which look exceedingly similar, while displaying strongly different behavior. These rules often find their use in control tasks, for example in robotics and for this rigorous convergence and numerical stability is required. The goal of this article is to review these rules and compare them to provide a better overview over their different properties. Two main classes will be discussed: temporal difference (TD) rules and correlation based (differential hebbian) rules and some transition cases. In general we will focus on neuronal implementations with changeable synaptic weights and a time-continuous representation of activity. In a machine learning (non-neuronal) context, for TD-learning a solid mathematical theory has existed since several years. This can partly be transfered to a neuronal framework, too. On the other hand, only now a more complete theory has also emerged for differential Hebb rules. In general rules differ by their convergence conditions and their numerical stability, which can lead to very undesirable behavior, when wanting to apply them. For TD, convergence can be enforced with a certain output condition assuring that the δ-error drops on average to zero (output control). Correlation based rules, on the other hand, converge when one input drops to zero (input control). Temporally asymmetric learning rules treat situations where incoming stimuli follow each other in time. Thus, it is necessary to remember the first stimulus to be able to relate it to the later occurring second one. To this end different types of so-called eligibility traces are being used by these two different types of rules. This aspect leads again to different properties of TD and differential Hebbian learning as discussed here. Thus, this paper, while also presenting several novel mathematical results, is mainly meant to provide a road map through the different neuronally emulated temporal asymmetrical learning rules and their behavior to provide some guidance for possible applications.     

Museum learning: a study of motivation and learning achievement

According to Reinmann-Rothmeier and Mandl (2001), learning environments should provide an ideal balance between constructivist and instructive elements. Most interesting for constructivist learning processes is the combination of the cognitive and the motivational domain. In an empirical study with 207 fifth-graders of the highest stratification level, we evaluated three different approaches to the learning process based on a visit to the Natural History Museum in Berlin: the three approaches were principally characterised by closed, open and mixed tasks. One objective of our study was to as-sess learning achieved through the visit and the effect of different treatments. Another goal was to evaluate the motivation of the three treatment groups. We conducted a pre/post-test study with follow-up measurement. The test instruments consisted of 26 open and closed questions in the cognitive domain and a further 12 items (subdivided into four subsections) for measuring motivation according to self-determination theory. In contrast to our hypotheses based on constructivist theories, open tasks were less successful for gaining knowledge and less intrinsically motivating.     

Three models of song learning: Evidence from behavior

Research on avian song learning has traditionally been based on an instructional model, as exemplified by the sensorimotor model of song development. Several large-scale, species-wide field studies of learned birdsongs have revealed that variation is narrowly restricted to certain aspects of song structure. Other aspects are sufficiently stereotyped and so widely shared by species' members that they qualify as species-specific universals. The limitations on natural song variation are difficult to reconcile with a fully open, instructive model of song learning. An alternative model based on memorization by selection postulates a system of innate neural templates that facilitate the recognition and rapid memorization of conspecific song patterns. Behavioral evidence compatible with this model includes learning preferences, rapid conspecific song learning, and widespread ocurrence of species-specific song universals that are recognized innately but fail to develop in songs of social isolates. A third model combines instruction, in the memorization phase, with selection during song production. An overproduced repertoire of plastic songs previously memorized by instruction is winnowed by selection imposed during social interactions at the time of adult song crystallization. Selection during production is well established as a factor in the song development of several species, in the form of action-based learning. The possible role of selective processes in song memorization merits further neurobiological investigation. © 1997 John Wiley & Sons, Inc. J Neurobiol 33: 501–516, 1997     

BI-stability of emotions and motivations: An evolutionary consequence of the open-ended capacity for learning

Species, endowed with an open-ended capacity for learning, which is one of the highest evolutionary achievements,will profit most from this ability, if they are urged one way or other to invest any surplus of energy in expanding and refining their behavioural repertoire and in adapting it to prevailing circumstances, while incurring as little risk and stress as possible. It is therefore argued that an open-ended capacity for learning is maximally adding to survival if paired to two distinct tendencies:

1. a tendency to seek high-arousal evoking situations whenever surplus energy is available, and
2. a tendency to seek arousal reducing situations as soon as the surplus energy is exhausted.

This suggests that a bi-stable “telic/paratelic” system of prefered levels of arousal, as described for humans by Apter & Smith's theory of motivational reversals, and as expressed in Kortmulder's model of the “centripetal/centrifugal” bi-polarity of animal behavioural tendencies, can be considered an Evolutionarily Stable Strategy (E.S.S.), as compared to homeostatic systems of arousal and motivation.     

Prosimian learning capacities

A survey of the literature on learning by prosimian primates contradicts a traditional view that they are untrainable. They learn simple operants such as bar pressing readily, work well for the usual rewards, and respond in predictable fashion on schedules of partial reinforcement. Two-dimensional visual discriminations involving pattern and brightness also are learned, as are three-dimensional object discriminations. In the area of complex learning, they not only acquire a variety of difficult tasks, but they also reach a final level of performance that is at or near the level of anthropoids. In each of the following areas, at least one experiment is described in which a prosimian species did as well as one or more anthropoid species: object discrimination learning set, discrimination reversal, delayed response, instrumentation, oddity, and relational problems. The anthropoids to which they are most apt to compare favorably are New World monkeys, a group which they resemble physically, especially with respect to degree of manipulativeness, cortical development, and visual acuity.     

Simulated Trust: A cheap social learning strategy

Animals use heuristic strategies to determine from which conspecifics to learn socially. This leads to directed social learning. Directed social learning protects them from copying non-adaptive information. So far, the strategies of animals, leading to directed social learning, are assumed to rely on (possibly indirect) inferences about the demonstrator’s success. As an alternative to this assumption, we propose a strategy that only uses self-established estimates of the pay-offs of behavior. We evaluate the strategy in a number of agent-based simulations. Critically, the strategy’s success is warranted by the inclusion of an incremental learning mechanism. Our findings point out new theoretical opportunities to regulate social learning for animals. More broadly, our simulations emphasize the need to include a realistic learning mechanism in game-theoretic studies of social learning strategies, and call for re-evaluation of previous findings.     

Learning strategies in matching to sample: if-then and configural learning by pigeons

Pigeons learned a matching-to-sample task with a split training-set design in which half of the stimulus displays were untrained and tested following acquisition. Transfer to the untrained displays along with no novel-stimulus transfer indicated that these pigeons learned the task (partially) via if-then rules. Comparisons to other performance measures indicated that they also partially learned the task via configural learning (learning the gestalt of the whole stimulus display). Differences in the FR-sample requirement (1 vs. 20) had no systematic effect on the type of learning or level of learning obtained. Differences from a previous study [Wright, A.A., 1997. Concept learning and learning strategies. Psychol. Sci. 8, 119-123] are discussed, including the effect of displaying the stimuli vertically (traditional display orientation) or horizontally from the floor.     

Evolution of social learning: a mathematical analysis

Social learning is an important ability seen in a wide range of animals including humans. It has been argued that individual learning, social learning, and innate determination of behavior are favored by natural selection when environmental changes occur at short, intermediate, and long intervals, respectively. Only recently, however, has the hypothesis been examined by means of mathematical models. In this paper, we construct a simple model in which each organism uses one of three genetically determined strategies--it is an individual learner, a social learner or an "innate"--and the three types of organisms are in direct competition with each other. A reduced model, involving only the individual learners and innates, is effectively linear, and we show that by solving the eigenvalue problem of this reduced system we arrive at a good approximation to the global dynamics of the full model. We also study the effect of stochastic environmental changes and reversible mutations among the three strategies. Our results are consistent with the predictions of previous studies. In addition, we identify a critical level of environmental constancy below which only individual and social learners are present.     

Replacing lectures by textbased flexible learning: students' performance and perceptions

This paper presents the results of an extended evaluation programme designed to test the effectiveness of text-based flexible learning as a replacement to 30 – 50% of the lectures in certain modules in conventional undergraduate courses within the School of Life Sciences at Napier University. For examinations in which students answered both types of question, marks for questions based on topics taught by flexible learning were equivalent to marks for questions based on topics taught by conventional teaching methods. Marks for examinations in which at least 50% of the answers were based on topics taught by flexible learning were equivalent to marks for examinations in which questions were based on topics taught by conventional teaching methods. Rates of achievement of a mark of 40% or more at first attempt for examinations in which at least 50% of the answers were based on topics taught by flexible learning were significantly better than rates of achievement of a mark of 40% or more at first attempt for questions based on topics taught by conventional teaching methods. Students gave positive feedback on flexible learning, both verbally and by questionnaire, and showed highly significant bias in favour of topics taught by flexible learning in their choice of questions in examinations. The flexible learning programme studied here has satisfied the various quality assurance criteria in place within the University throughout the time that it has been in operation. The evaluation has demonstrated that the textbased flexible learning programme studied here was an effective alternative to lectures.     

An experimental comparison of human social learning strategies: payoff-biased social learning is adaptive but underused

Analytical models have identified a set of social learning strategies that are predicted to be adaptive relative to individual (asocial) learning. In the present study, human participants engaged in an ecologically valid artifact-design task with the opportunity to engage in a range of social learning strategies: payoff bias, conformity, averaging and random copying. The artifact (an arrowhead) was composed of multiple continuous and discrete attributes which jointly generated a complex multimodal adaptive landscape that likely reflects actual cultural fitness environments. Participants exhibited a mix of individual learning and payoff-biased social learning, with negligible frequencies of the other social learning strategies. This preference for payoff-biased social learning was evident from the initial trials, suggesting that participants came into the study with an intrinsic preference for this strategy. There was also a small but significant increase in the frequency of payoff-biased social learning over sessions, suggesting that strategy choice may itself be subject to learning. Frequency of payoff-biased social learning predicted both absolute and relative success in the task, especially in a multimodal (rather than unimodal) fitness environment. This effect was driven by a minority of hardcore social learners who copied the best group member on more than half of trials. These hardcore social learners were also above-average individual learners, suggesting a link between individual and social learning ability. The lower-than-expected frequency of social learning may reflect the existence of information producer–scrounger dynamics in human populations.