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Children and adults show preferences for native speakers and judge them to be more credible sources of information than non-native speakers. Previous research with children has attributed this bias to a preference for in-group members. The present study investigated the role of processing fluency on children’s social judgements. Children were shown two speakers (one with a native accent and the other with a non-native accent) relaying a message from another individual. They were then asked to make credibility and social judgements about the speakers and their messages. Children were also asked a processing fluency question, and a question about the speakers’ comprehension of the original message. Responses to the processing fluency question and question about the speakers’ comprehension predicted credibility judgements, but did not predict preference. These findings suggest that processing fluency may play a role in developing biases towards non-native accented speakers. Implications are discussed.

CogSci 2021

Broken Telephone: Children&#39;s Judgments of Messages Delivered by Non-Native Speakers are Influenced by Processing Fluency

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**Dear Colleagues,**

Welcome to the 43rd Annual Conference of the Cognitive Science Society! 

This year’s conference brings together the latest research from all Cognitive Science and also highlights this year’s theme **Comparative Cognition: Animal Minds.** 

The program features four plenary speakers: Friederike Range (University of Veterinary Medicine, Vienna), Onur Güntürkün (Ruhr University Bochum), Julia Fischer (University of Göttingen), and Erich Jarvis (The Rockefeller University). The keynotes and invited symposia showcase the broad spectrum of ideas that encompass the conference theme of comparative cognition. 

Further, the program includes the Rumelhart Prize keynote presentation by Susan Goldin-Meadow (University of Chicago), and symposia to celebrate the winner of the Elman Prize: Wei Ji Ma (New York University), the Heineken Award winner Robert Zatorre (McGill University), and the Robert J. Glushko Dissertation Prizes session.

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The Cognitive Science Society brings together researchers from around the world who hold a common goal: understanding the nature of the human mind. The mission of the Society is to promote Cognitive Science as a discipline, and to foster scientific interchange among researchers in various areas of study, including Artificial Intelligence, Linguistics, Anthropology, Psychology, Neuroscience, Philosophy, and Education. The Society is a non-profit professional organization and its activities include sponsoring an annual conference and publishing the journals Cognitive Science and TopiCS.

Broken Telephone: Children's Judgments of Messages Delivered by Non-Native Speakers are Influenced by Processing Fluency

poster

Despite the increase in studies investigating people’s explana- tory preferences in the domains of psychology and philoso- phy, little is known about their preferences in more applied do- mains, such as the criminal justice system. We show that when people evaluate competing legal accounts of the same evidence that vary in complexity, their explanatory preferences are af- fected by: i) whether they are required to draw causal mod- els of the evidence, and ii) the actual structure that is drawn. Although previous research has shown that people can reason correctly about causality, ours is one of the first studies that shows that generating and drawing causal models directly af- fects people’s evaluations of explanations.

The role of causal models in evaluating simple and complex legal explanations

Keeping track of time is essential for everyday behavior. Theoretical models have proposed a wide variety of neural processes that could tell time, but it is unclear which ones the brain actually uses. Low-level neural models are specific, but rarely explicate how cognitive processes, such as attention and memory, modulate prospective and retrospective timing. Here we develop a neurocomputational model of prospective and retrospective timing, using a spiking recurrent neural network. The model captures behavior of individual spiking neurons and population dynamics when producing and perceiving time intervals, thus bridging low- and high-level phenomena. When interrupting events are introduced, the model delays responding in a similar way to pigeons and rats. Crucially, the model also explains why attending incoming stimuli decreases prospective estimates and increases retrospective estimates of time. In sum, our model offers a neurocomputational account of prospective and retrospective timing, from low-level neural dynamics to high-level cognition.

A Neurocomputational Model of Prospective and Retrospective Timing

This paper examines whether advanced law students are resistant to the blame blocking effect—a tendency to assign higher punishments for failed attempts than failed attempts with independent causal chains leading to intended harm (Cushman, 2008). This effect goes against the criminal law principle that intentionally acting towards committing a crime, and not accidental outcomes, determine liability for attempts. To further investigate whether advanced students of law are judging blame blocking scenarios correctly (in line with their legal expertise), in two experiments, we compared their punishment responses with four populations: beginning law students, advanced philosophy students, advanced natural science students, and laypeople with no academic background. We did not observe the blame blocking effect in either of the four student populations, and it was only partially present in the lay population. We discuss the implications of these findings for research on legal expertise and the blame blocking effect in general.

Blame Blocking and Expertise Effects Revisited

The associative theory of creativity proposes that creative ability relies on the organization of semantic memory, yet the relationships between semantic memory structure and brain connectivity, in relation to creativity, remain poorly understood. Here, we explored the relationships between the network properties of individual semantic memory, patterns of functional brain connectivity, and real-life creativity. To this end, we acquired functional magnetic resonance imaging data while participants underwent a semantic relatedness judgment task. Participants’ relatedness ratings between word-pairs were used to estimate their individual semantic networks, whose network properties were significantly related to their real-life creativity. Using a connectome-based predictive modeling approach, we identified patterns of on-task functional connectivity that predicted creativity-related semantic memory network properties in novel individuals. Furthermore, the predicted semantic network properties partially mediated the relationship between functional connectivity and real-life creativity. These results provide new insights on how brain connectivity supports the associative mechanisms of creativity.

Brain Connectivity-Based Prediction of Semantic Network Properties Related to Creativity

The question of whether bilingual language experience confers a cognitive advantage remains open. Controversy arises from assertions that putative advantages can instead be explained by differences in culture, socioeconomic class, or immigration status, as well as the classification of bilingual experience as a fixed variable rather than a random effect. The present study addresses these issues by assessing the impact of variability in English (L2) language experience on executive function in a group of Mandarin-English speakers (n = 41) from Shenzhen. Participants reported on demographic details, language history, perceived stress, and performed a Simon task online. Data were analysed using Linear Mixed Effects (LME) models to test for individual differences on Simon task performance. Results showed higher levels of L2 proficiency were associated with reduced Simon effects, suggesting a cognitive advantage.

Internet-based Assessment of an Inhibitory Control Advantage in Bilingual Chinese High School Students

In three experiments (total N = 1302) we investigated whether causal proximity affects moral judgments. We manipulated causal proximity by varying the length of chains mediating between actions and outcomes, and by varying the strengths of causal links. We demonstrate that moral judgments are affected by causal proximity with longer chains or weaker links leading to more lenient moral evaluations. Moreover, we identify outcome foreseeability as the crucial factor linking causal proximity and moral judgments. While effects of causal proximity on moral judgments were small when controlling for factors that were confounded in previous studies, knowledge about the presence of causal links substantially alters judgments of permissibility and responsibility. The experiments demonstrate a tight coupling between causal representations, inferences about mental states, and moral reasoning.

A Causal Proximity Effect in Moral Judgment

Learning the contingencies of a complex experiment is hard, and animals likely revise their strategies multiple times during the process. Individuals learn in an idiosyncratic manner and may even end up with different asymptotic strategies. 
Modeling such long-run acquisition requires a flexible and extensible structure which can capture radically new behaviours as well as slow changes in existing ones. To this end, we suggest a dynamic input-output infinite hidden Markov model whose latent states capture behaviours. We fit this model to data collected from mice who learnt a contrast detection task over tens of sessions and thousands of trials. Different stages of learning are quantified via the number and psychometric nature of prevalent behavioural states. Our model indicates that initial learning proceeds via drastic changes in behavior (i.e. new states), whereas later learning consists of adaptations to existing states, even if the task structure changes notably at this time.

Exploring learning trajectories with dynamic infinite hidden Markov models

Modus tollens is a rule of inference in classical, two-valued logic which allows to derive the negation of the antecedent from a conditional and the negation of its consequent. In this paper, we investigate when humans draw such conclusions and what modulates the application of modus tollens. We consider conditionals which may or may not be obligations and which may or may not have necessary antecedents. We show that humans make significantly more modus tollens inferences in case of obligation conditionals and that the time to make a modus tollens inference is shorter than the time to answer ``nothing follows''. We illustrate how these differences can be modeled within the weak completion semantics.

When are Humans Reasoning with Modus Tollens?

Text skimming is a common reading behavior that occurs when readers scan text at a faster than normal rate to attempt to form understanding when not able to read at normal speed. Research has suggested that reading time varies across a skimmed text, guided by attention and comprehension goals. However, do individual differences in the ability to manage attention affect skimming? Are those better at managing attention (i.e., high working memory) also better at managing text skimming? Two experiments were conducted where participants who varied in WMC were asked to skim an unfamiliar expository text, both on a computer, and while being eyetracked. In both experiments, while participants did spend more time reading earlier portions of the text, this did interact with WMC. Those higher in WMC balanced their reading efforts more equally across the entire text, suggesting that text skimming behavior is sensitive to differences in WMC.

Readers text skimming behavior changes with variation in working memory capacity

What can stories teach us about the real world? How can stories change our behavior? From research on cognitive maps, we know that hippocampal neurons form maps of physical space and time. Here, we propose that the same neural processes underlie engagement with fictional stories: during story processing we create cognitive maps of various domains—spatial, social, moral, etc.—that we can later use for real-world navigation. This perspective can also inspire new methodological tools for assessing story processing, and we give an example showing how a story can be modeled as paths taken on a cognitive map. In summary, we see stories as affording paths that guide our navigation through multiple dimensions of life, which raises the implication that the function of stories, including their moral content, is not only to be understood at the level of abstract and linguistically coherent propositions, but at the fundamental level of navigation.

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The role of causal models in evaluating simple and complex legal explanations

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