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The outcome of any scientific experiment or intervention will naturally unfold over time. How then should individuals make causal inferences from measurements over time? Across three experiments, we had participants observe experimental and control groups over several days posttreatment in a fictional biological research setting. We identify competing perspectives in the literature: contingency-driven accounts predict no effect of the outcome timing while the contiguity principle suggests people will view a treatment as more harmful to the extent that bad treatment outcomes occur earlier rather than later. In contrast, inference of the functional form of a treatment effect can license extrapolation beyond the measurements and lead to different causal inferences. We find participants' causal strength and direction judgments in temporal settings vary with minimal manipulations of instruction framing. When it is implied that the observations are made over a preplanned number of days, causal judgments depend strongly on contiguity. When it is implied that the observation may be ongoing, participants extrapolate current trends into the future and adapt their causal judgments accordingly. When data are revealed sequentially, participants rely on extrapolation regardless of instruction framing. Our results demonstrate human flexibility in interpreting temporal evidence for causal reasoning and emphasize human tendency to generalize from evidence in ways that are acutely sensitive to task framing. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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Most research into causal learning has focused on atemporal contingency data settings while fewer studies have examined learning and reasoning about systems exhibiting events that unfold in continuous time. Of these, none have yet explored learning about preventative causal influences. How do people use temporal information to infer which components of a causal system are generating or preventing activity of other components? In what ways do generative and preventative causes interact in shaping the behavior of causal mechanisms and their learnability? We explore human causal structure learning within a space of hypotheses that combine generative and preventative causal relationships. Participants observe the behavior of causal devices as they are perturbed by fixed interventions and subject to either regular or irregular spontaneous activations. We find that participants are capable learners in this setting, successfully identifying the large majority of generative, preventative and non-causal relationships but making certain attribution errors. We lay out a computational-level framework for normative inference in this setting and propose a family of more cognitively plausible algorithmic approximations. We find that participants' judgment patterns can be both qualitatively and quantitatively captured by a model that approximates normative inference via a simulation and summary statistics scheme based on structurally local computation using temporally local evidence.

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The self-paced reading paradigm has been popular and widely used in psycholinguistic research for several decades. The tool described in this paper, FAB (Forward and Backward reading), is a tool created to hopefully and maximally reduce the coding demands and simplify the operation costs for experimental researchers and clinical researchers who are doing experimental work, in their designing, coding, implementing, and analyzing self-paced reading tasks. Its basis in web languages (HTML, JavaScript) also promotes experimental implementation and material sharing in our era of open science. In addition, FAB has a unique forward-and-backward mode that can track regressive-like behaviors that are usually only recordable using eye-tracking or mouse-tracking equipment. In this paper, the specific application and usage of FAB is demonstrated in one laboratory and two online validation experiments. We hope this free and open-sourced tool can benefit research in a diverse range of contexts where self-paced reading is desirable.

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Research on causal cognition has largely focused on learning and reasoning about contingency data aggregated across discrete observations or experiments. However, this setting represents only the tip of the causal cognition iceberg. A more general problem lurking beneath is that of learning the latent causal structure that connects events and actions as they unfold in continuous time. In this paper, we examine how people actively learn about causal structure in a continuous-time setting, focusing on when and where they intervene and how this shapes their learning. Across two experiments, we find that participants' accuracy depends on both the informativeness and evidential complexity of the data they generate. Moreover, participants' intervention choices strike a balance between maximizing expected information and minimizing inferential complexity. People time and target their interventions to create simple yet informative causal dynamics. We discuss how the continuous-time setting challenges existing computational accounts of active causal learning, and argue that metacognitive awareness of one's inferential limitations plays a critical role for successful learning in the wild.

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Cognitive reflection is the tendency to override an intuitive response so as to engage in the reflection necessary to derive a correct response. Here, we examine the emergence of cognitive reflection in a culture that values nonanalytic thinking styles, Chinese culture. We administered a child-friendly version of the cognitive reflection test, the CRT-D, to 130 adults and 111 school-age children in China and compared performance on the CRT-D to several measures of rational thinking (belief bias syllogisms, base rate sensitivity, denominator neglect, and other-side thinking) and normative thinking dispositions (actively open-minded thinking and need for cognition). The CRT-D was a significant predictor of rational thinking and normative thinking dispositions in both children and adults, as previously found in American samples. Adults' performance on the CRT-D correlated with their performance on the original CRT, and children's performance on the CRT-D predicted rational thinking and normative thinking dispositions even after adjusting for age. These results demonstrate that cognitive reflection, rational thinking, and normative thinking dispositions converge even in a culture that emphasizes holistic, nonanalytic reasoning.

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Human adults are faster to respond to small/large numerals with their left/right hand when they judge the parity of numerals, which is known as the SNARC (spatial-numerical association of response codes) effect. It has been proposed that the size of the SNARC effect depends on response latencies. The current study introduced a perceptual orientation task, where participants were asked to judge the orientation of a digit or a frame surrounding the digit. The present study first confirmed the SNARC effect with native Chinese speakers (Experiment 1) using a parity task, and then examined whether the emergence and size of the SNARC effect depended on the response latencies (Experiments 2, 3, and 4) using a perceptual orientation judgment task. Our results suggested that (a) the automatic processing of response-related numerical-spatial information occurred with Chinese-speaking participants in the parity task; (b) the SNARC effect was also found when the task did not require semantic access; and (c) the size of the effect depended on the processing speed of the task-relevant dimension. Finally, we proposed an underlying mechanism to explain the SNARC effect in the perceptual orientation judgment task.

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Right hand responds faster than left hand when shown larger numbers and vice-versa when shown smaller numbers (the SNARC effect). Accumulating evidence suggests that the SNARC effect may not be exclusive for numbers and can be extended to other ordinal sequences (e.g., months or letters in the alphabet) as well. In this study, we tested the SNARC effect with a non-numerically ordered sequence: the Chinese notations for the color spectrum (Red, Orange, Yellow, Green, Blue, Indigo, and Violet). Chinese color word sequence reserves relatively weak ordinal information, because each element color in the sequence normally appears in non-sequential contexts, making it ideal to test the spatial organization of sequential information that was stored in the long-term memory. This study found a reliable SNARC-like effect for Chinese color words (deciding whether the presented color word was before or after the reference color word "green"), suggesting that, without access to any quantitative information or exposure to any previous training, ordinal representation can still activate a sense of space. The results support that weak ordinal information without quantitative magnitude encoded in the long-term memory can activate spatial representation in a comparison task.