Simulating behavior to help researchers build experiments

Creating web applications for online psychological experiments: A hands-on technical guide including a template

The present tutorial provides a technical overview of how to create web applications for online psychological experiments from scratch via the HTML/CSS/JavaScript framework. This approach allows virtually unlimited flexibility in accomplishing anything in an online experiment that a regular computer (or smartphone, etc.) is capable of. Apart from offering a fast introduction for complete beginners, this tutorial may also serve as a helpful guideline for more experienced programmers and researchers. Connected to the tutorial, a specific implementation is also given via the free and open-source template project at https://github.com/gasparl/expapp , intended to be improved by the community to always follow the latest technological advancements and general good practices.

People's thinking plans adapt to the problem they're trying to solve

Much of our thinking focuses on deciding what to do in situations where the space of possible options is too large to evaluate exhaustively. Previous work has found that people do this by learning the general value of different behaviors, and prioritizing thinking about high-value options in new situations. Is this good-action bias always the best strategy, or can thinking about low-value options sometimes become more beneficial? Can people adapt their thinking accordingly based on the situation? And how do we know what to think about in novel events? Here, we developed a block-puzzle paradigm that enabled us to measure people's thinking plans and compare them to a computational model of rational thought. We used two distinct response methods to explore what people think about-a self-report method, in which we asked people explicitly to report what they thought about, and an implicit response time method, in which we used people's decision-making times to reveal what they thought about. Our results suggest that people can quickly estimate the apparent value of different options and use this to decide what to think about. Critically, we find that people can flexibly prioritize whether to think about high-value options (Experiments 1 and 2) or low-value options (Experiments 3, 4, and 5), depending on the problem. Through computational modeling, we show that these thinking strategies are broadly rational, enabling people to maximize the value of long-term decisions. Our results suggest that thinking plans are flexible: What we think about depends on the structure of the problems we are trying to solve.

What's next?: Time is subjectively dilated not only for 'oddball' events, but also for events immediately after oddballs

Our experience of time is strikingly plastic: Depending on contextual factors, the same objective duration can seem to fly by or drag on. Perhaps the most direct demonstration of such subjective time dilation is the oddball effect: when seeing identical objects appear one after another, followed by an "oddball" (e.g., a disc that suddenly grows in size, in a sequence of otherwise static discs), observers experience this oddball as having lasted longer than its nonoddball counterparts. Despite extensive work on this phenomenon, a surprisingly foundational question remains unasked: What actually gets dilated? Beyond the oddball, are the objects just before (or just after) the oddball also dilated? As in previous studies, observers viewed sequences of colored discs, one of which could be the oddball-and subsequently reproduced the oddball's duration. Unlike previous studies, however, there were also critical trials in which observers instead reproduced the duration of the disc immediately before or after the oddball. A clear pattern emerged: oddball-induced time dilation extended to the post-oddball disc, but not the pre-oddball disc. Whence this temporal asymmetry? We suggest that an oddball's sudden appearance may induce uncertainty about what will happen next, heightening attention until after the uncertainty is resolved.