What Determines Visual Statistical Learning Performance? Insights From Information Theory

In order to extract the regularities underlying a continuous sensory input, the individual elements constituting the stream have to be encoded and their transitional probabilities (TPs) should be learned. This suggests that variance in statistical learning (SL) performance reflects efficiency in encoding representations as well as efficiency in detecting their statistical properties. These processes have been taken to be independent and temporally modular, where first, elements in the stream are encoded into internal representations, and then the co‐occurrences between them are computed and registered. Here, we entertain a novel hypothesis that one unifying construct—the rate of information in the sensory input—explains learning performance. This theoretical approach merges processes related to encoding of events and those related to learning their regularities into a single computational principle. We present data from two large‐scale experiments with over 800 participants tested in support for this hypothesis, showing that rate of information in a visual stream clearly predicts SL performance, and that similar rate of information values leads to similar SL performance. We discuss the implications for SL theory and its relation to regularity learning.     

Shedding new light on an old problem: The estimation of shadow sizes in children and adults

Two experiments using the 'projection of shadows' paradigm investigated multidimensional reasoning, implicit and explicit knowledge, and the nonlinearity concept in 5-, 9-, and 13-year-olds and adults. Participants estimated the resulting shadow lengths of differently sized objects, placed at varying distances from a light source. Experiment 1 (N=80) revealed that, on the group level, 5-year-olds took both object size and light-object distance into account when estimating shadow size. Moreover, half of the children in this age group even considered the subordinate distance dimension. In addition, we found a large discrepancy between implicit and explicit knowledge about shadows in 5-year-olds that decreased with age. Finally, only a minority of older participants and very few younger children recognized the nonlinear relationship between light-object distance and shadow size, suggesting domain dependence of the nonlinearity concept. Experiment 2 (N=20) predominately replicated the findings for 5-year-olds using slightly different stimuli.     

Online Information and Communication Systems to Enhance Health Outcomes Through Communication Convergence

The growing use of digital health communication channels has produced dramatic changes, providing broad access to information for making health decisions and addressing users' emotional needs. Digital health communication channels combine mass and interpersonal communication in different ways. Type 1 convergence occurs sequentially: Individuals obtain health information online that they discuss interpersonally with health providers. Type 2 convergence involves discussions occurring via online health information systems. The effectiveness of these systems depends upon seven communication design and implementation strategies. Emerging interactive health information systems provide customized responses tailored to individuals' specific needs and situations. All these forms of media convergence can improve health education, health promotion, and health behavior change.     

Accuracy and performance of the state-based Φ and liveliness measures of information integration

A number of people have suggested that there is a link between information integration and consciousness, and a number of algorithms for calculating information integration have been put forward. The most recent of these is Balduzzi and Tononi’s state-based Φ algorithm, which has factorial dependencies that severely limit the number of neurons that can be analyzed. To address this issue an alternative state-based measure known as liveliness has been developed, which uses the causal relationships between neurons to identify the areas of maximum information integration. This paper outlines the state-based Φ and liveliness algorithms and sets out a number of test networks that were used to compare their accuracy and performance. The results show that liveliness is a reasonable approximation to state-based Φ for some network topologies, and it has a much more scalable performance than state-based Φ.     

Changing commuters’ behavior using rewards: A study of rush-hour avoidance

In a 13-week field study conducted in The Netherlands, participants were provided with daily rewards – monetary and in-kind, in order to encourage them to avoid driving during the morning rush-hour. Participants could earn a reward (money or credits to keep a Smartphone handset), by driving to work earlier or later, by switching to another mode or by teleworking. The collected data, complemented with pre and post measurement surveys, were analyzed using longitudinal techniques and mixed logistic regression. The results assert that the reward is the main extrinsic motivation for discouraging rush-hour driving. The monetary reward exhibits diminishing sensitivity, whereas the Smartphone has endowment qualities. Although the reward influences the motivation to avoid the rush-hour, the choice how to change behavior is influenced by additional factors including education, scheduling, habitual behavior, attitudes, and travel information availability.     

Effects of unit formation on the perception of a changing sound

The effects of subunit formation on adult listeners' ability to notice changes in a continuous spectral gradient of sound were studied. Results of this experiment support the idea that the auditory system processes information differently within a unit, and that this processing does not occur unless the perceptual system detects unit boundaries. In this experiment, silences were inserted into a continuously changing sound to cause the formation of short units. Listeners noticed the change earlier in conditions with silences inserted than in to conditions where the transition was either unbroken or broken by loud noise bursts. Results are discussed in terms of two processes, one that accentuates stimulus properties present at moments of onset and offset, and a second that uses onsets and offsets to signal the beginnings and ends of units and reduces the change perceived within units.     

Risk aversion in information seeking

The information gain model argues that participants select alternatives with a larger expected value of information gain. The present study investigated risk aversion in information seeking to examine whether the expected value always determines information-seeking behaviour. For this investigation, we used a scale method selection task in which participants were required to select one of two scales for weighing coins in order to find an underweight coin. Two experiments showed that participants more frequently selected the alternative that provided information gain without risk, although its expected information gain was smaller. This finding indicates the presence of risk aversion in information seeking, suggesting that information-seeking behaviour is affected by risk associated with obtaining information gain.     

Digit Span and Articulatory Suppression: A Cross-linguistic Comparison

Information Reduction, a performance-enhancing cognitive strategy which develops with practice, is thought to be consciously and abruptly adopted and then applied consistently. Previous investigations used an Alphabet Verification Task where one observation was that not everyone adopts the strategy, but reasons for this are unclear. We demonstrated Information Reduction in three other tasks, confirming that it is not task-specific. Post-testing questionnaires probed verbally expressible knowledge, to gauge conscious awareness of any strategy. Overall, results indicate considerable variation in Information Reduction usage: Some individuals discovered and used the strategy and could verbally express this, others chose not to use it and some appeared to use it without awareness of doing so. Results also indicate that Information Reduction is not consistently applied, suggesting it is less robust than has been proposed. Our results may be better explained by a theory of practice learning which incorporates both data-driven automaticity and top-down controlled processes.