Fear generalization in humans: Impact of verbal instructions

Fear generalization lies at the heart of many anxiety problems, but little is known about the factors that can influence this phenomenon. The present study investigated whether verbal instructions about specific stimulus features can influence conditioned fear generalization. All participants were fear conditioned to a yellow triangle, using an electric shock. Participants had received pre-experimental instructions saying that the shapes (or colours) of the stimuli were informative for the occurrence of shock (group Shape and group Colour, respectively). Next, generalization was tested to presentations of a blue triangle (same shape) as well as a yellow square (same colour). Fear reactions were measured through skin conductance and online ratings of shock-expectancy. The results showed strongest generalization to the same shape stimulus in group Shape, versus the same colour stimulus in group Colour. Hence, the same learning experience can have opposite effects in terms of fear generalization, depending on verbally transmitted information about the relative importance of individual stimulus features.     

An especial skill: Support for a learned parameters hypothesis

We tested the ‘learned parameters’ hypothesis as an explanation of the ‘especial skill effect’. Outcome attainment and movement kinematics were recorded for 10 expert and 10 novice players performing basketball free-throw shots at five distances (11-19 ft) with a regular and heavy weight basketball. As predicted, experts performed better than expected relative to the regression equation at the 15 ft, free-throw line with the regular basketball, supporting the ‘especial skill effect’. This effect was not present for the experts when shooting with the heavy ball. Novices did not show an advantage at the free-throw line when performing with either ball. Although the outcome attainment scores support the ‘learned parameters’ hypotheses, kinematic analysis failed to identify differences in the movement pattern for the especial skill, suggesting that these skills (i.e., shooting at different distances) are not governed by separate motor programs.     

Novel labels support 10-month-olds’ attention to novel objects

What is the source of the mutual exclusivity bias whereby infants map novel labels onto novel objects? In an intermodal preferential looking task, we found that novel labels support 10-month-olds’ attention to a novel object over a familiar object. In contrast, familiar labels and a neutral phrase gradually reduced attention to a novel object. Markman (1989, 1990) argued that infants must recall the name of a familiar object to exclude it as the referent of a novel label. We argue that 10-month-olds’ attention is guided by the novelty of objects and labels rather than knowledge of the names for familiar objects. Mutual exclusivity, as a language-specific bias, might emerge from a more general constraint on attention and learning.     

Bayesian parameter estimation in the Expectancy Valence model of the Iowa gambling task

The purpose of the popular Iowa gambling task is to study decision making deficits in clinical populations by mimicking real-life decision making in an experimental context. Busemeyer and Stout [Busemeyer, J. R., & Stout, J. C. (2002). A contribution of cognitive decision models to clinical assessment: Decomposing performance on the Bechara gambling task. Psychological Assessment, 14, 253-262] proposed an “Expectancy Valence” reinforcement learning model that estimates three latent components which are assumed to jointly determine choice behavior in the Iowa gambling task: weighing of wins versus losses, memory for past payoffs, and response consistency. In this article we explore the statistical properties of the Expectancy Valence model. We first demonstrate the difficulty of applying the model on the level of a single participant, we then propose and implement a Bayesian hierarchical estimation procedure to coherently combine information from different participants, and we finally apply the Bayesian estimation procedure to data from an experiment designed to provide a test of specific influence.     

The exponential learning equation as a function of successful trials results in sigmoid performance

While the exponential learning equation, indicating a gradually diminishing improvement, is one of the standard equations to describe learning, a sigmoid behavior with initially increasing then decreasing improvement has also been suggested. Here we show that the sigmoid behavior is mathematically derived from the standard exponential equation when the independent variable of the equation is restricted to the successful trials alone. It is suggested that for tasks promoting success-based learning, performance is better described by the derived sigmoid curve.     

Revisiting the role of bad news in maintaining human observing behavior

Results from studies of observing responses have suggested that stimuli maintain observing owing to their special relationship to primary reinforcement (the conditioned-reinforcement hypothesis), and not because they predict the availability and nonavailability of reinforcement (the information hypothesis). The present article first reviews a study that challenges that conclusion and then reports a series of five brief experiments that provide further support for the conditioned-reinforcement view. In Experiments 1 through 3, participants preferred occasional good news (a stimulus correlated with reinforcement) or no news (a stimulus uncorrelated with reinforcement) to occasional bad news (a stimulus negatively correlated with reinforcement). In Experiment 4 bad news was preferred to no news when the absence of stimulus change following a response to the bad-news option was reliably associated with good news. When this association was weakened in Experiment 5 the results were intermediate. The results support the conclusion that information is reinforcing only when it is positive or useful. As required by the conditioned-reinforcement hypothesis, useless information does not maintain observing.     

Conditioned reinforcement and response strength

Stimuli associated with primary reinforcers appear themselves to acquire the capacity to strengthen behavior. This paper reviews research on the strengthening effects of conditioned reinforcers within the context of contemporary quantitative choice theories and behavioral momentum theory. Based partially on the finding that variations in parameters of conditioned reinforcement appear not to affect response strength as measured by resistance to change, long-standing assertions that conditioned reinforcers do not strengthen behavior in a reinforcement-like fashion are considered. A signposts or means-to-an-end account is explored and appears to provide a plausible alternative interpretation of the effects of stimuli associated with primary reinforcers. Related suggestions that primary reinforcers also might not have their effects via a strengthening process are explored and found to be worthy of serious consideration.     

A PARADIGM FOR OPERANT CONDITIONING IN BLOW FLIES (PHORMIA TERRAE NOVAE ROBINEAU‐DESVOIDY, 1830)

An operant conditioning situation for the blow fly (Protophormia terrae novae) is described. Individual flies are trained to enter and reenter a hole as the operant response. Only a few sessions of contingent reinforcement are required to increase response rates. When the response is no longer followed by food, the rate of entering the hole decreases. Control procedures revealed that rate of responding is not a simple overall result of feeding or of aging. The flies entered into the hole only if the response was required to obtain the food.     

A Bayesian-optimal principle for learner-friendly adaptation in learning games

Adaptive learning games should provide opportunities for the student to learn as well as motivate playing until goals have been reached. In this paper, we give a mathematically rigorous treatment of the problem in the framework of Bayesian decision theory. To quantify the opportunities for learning, we assume that the learning tasks that yield the most information about the current skills of the student, while being desirable for measurement in their own right, would also be among those that are efficient for learning. Indeed, optimization of the expected information gain appears to naturally avoid tasks that are exceedingly demanding or exceedingly easy as their results are predictable and thus uninformative. Still, tasks that are efficient for learning may be experienced as too challenging, and the resulting failures can lower motivation. Therefore, in addition to quantifying the expected informational benefit for learning of any prospective task to be presented next, we also model the expected motivational cost of its presentation, measured simply as the estimated probability of failure in our example model. We propose a “learner-friendly” adaptation algorithm that chooses the learning tasks by optimizing the expected benefit divided by the expected cost. We apply this algorithm to a Rasch-like student model implemented within a real-world application and present initial results of a pilot experiment.     

Implicit learning of social predictions

Humans exchange a range of nonverbal social signals in every interaction. It is an open question whether people use these signals, consciously or unconsciously, to guide social behavior. This experiment directly tested whether participants could learn to predict another person’s behavior using nonverbal cues in a single interaction, and whether explicit knowledge of the cue-outcome relationship was necessary for successful prediction. Participants played a computerized game of rock-paper-scissors against an avatar they believed was another participant. Sometimes the avatar generated a predictive facial cue before the play. On these trials, participants’ win-frequency increased over time, even if they did not acquire explicit knowledge of the predictive cue. The degree to which participants could predict the avatar (wins on cued trials) related to their self-reported liking of the avatar. These findings demonstrate the importance of implicit associative learning mechanisms in guiding social behavior on a moment-to-moment basis during interaction.