Category: Topics in Cognitive Science

Probability Theory Plus Noise: Descriptive Estimation and Inferential Judgment

Published in: Topics in Cognitive Science, Volume 10, Issue 1, 192-208 Abstract “We describe a computational model of two central aspects of people’s probabilistic reasoning: descriptive probability estimation and inferential probability judgment. This model assumes that people’s reasoning follows standard frequentist probability theory, but it is subject to random noise. This random noise has a regressive effect in descriptive probability estimation, moving probability estimates away from normative probabilities and toward the center of the probability scale. This random noise has an anti‐regressive effect in inferential judgement, however. These regressive and anti‐regressive effects explain various reliable and systematic biases seen in people’s… Read More

How Does Rumination Impact Cognition? A First Mechanistic Model

Published in: Topics in Cognitive Science, Volume 10, Issue 1, 175-191 Abstract “Rumination is a process of uncontrolled, narrowly focused negative thinking that is often self‐referential, and that is a hallmark of depression. Despite its importance, little is known about its cognitive mechanisms. Rumination can be thought of as a specific, constrained form of mind‐wandering. Here, we introduce a cognitive model of rumination that we developed on the basis of our existing model of mind‐wandering. The rumination model implements the hypothesis that rumination is caused by maladaptive habits of thought. These habits of thought are modeled by adjusting the number of… Read More

Editors’ Introduction: Cognitive Modeling at ICCM: Advancing the State of the Art

Published in: Topics in Cognitive Science, Volume 10, Issue 1, 140-143 Abstract “Cognitive modeling is the effort to understand the mind by implementing theories of the mind in computer code, producing measures comparable to human behavior and mental activity. The community of cognitive modelers has traditionally met twice every 3 years at the International Conference on Cognitive Modeling (ICCM). In this special issue of topiCS, we present the best papers from the ICCM meeting. (The full proceedings are available on the ICCM website.) These best papers represent advances in the state of the art in cognitive modeling. Since ICCM was for the… Read More

A Computational Investigation of Sources of Variability in Sentence Comprehension Difficulty in Aphasia

Published in: Topics in Cognitive Science, Volume 10, Issue 1, 161-174 Abstract “We present a computational evaluation of three hypotheses about sources of deficit in sentence comprehension in aphasia: slowed processing, intermittent deficiency, and resource reduction. The ACT‐R based Lewis and Vasishth (2005) model is used to implement these three proposals. Slowed processing is implemented as slowed execution time of parse steps; intermittent deficiency as increased random noise in activation of elements in memory; and resource reduction as reduced spreading activation. As data, we considered subject vs. object relative sentences, presented in a self‐paced listening modality to 56 individuals with aphasia… Read More

The Choreography of Group Affiliation

Published in: Topics in Cognitive Science, Volume 10, Issue 1, 80-94 Abstract “When two people move in synchrony, they become more social. Yet it is not clear how this effect scales up to larger numbers of people. Does a group need to move in unison to affiliate, in what we term unitary synchrony; or does affiliation arise from distributed coordination, patterns of coupled movements between individual members of a group? We developed choreographic tasks that manipulated movement synchrony without explicitly instructing groups to move in unison. Wrist accelerometers measured group movement dynamics and we applied cross‐recurrence analysis to distinguish the temporal features of emergent unitary synchrony (simultaneous… Read More

Building an ACT‐R Reader for Eye‐Tracking Corpus Data

Published in: Topics in Cognitive Science, Volume 10, Issue 1, 144-160 Abstract “Cognitive architectures have often been applied to data from individual experiments. In this paper, I develop an ACT‐R reader that can model a much larger set of data, eye‐tracking corpus data. It is shown that the resulting model has a good fit to the data for the considered low‐level processes. Unlike previous related works (most prominently, Engelmann, Vasishth, Engbert & Kliegl, 2013 ), the model achieves the fit by estimating free parameters of ACT‐R using Bayesian estimation and Markov‐Chain Monte Carlo (MCMC) techniques, rather than by relying on the mix of… Read More

Alternative Solutions to a Language Design Problem: The Role of Adjectives and Gender Marking in Efficient Communication

Published in: Topics in Cognitive Science, Volume 10, Issue 1, 209-224 Abstract “A central goal of typological research is to characterize linguistic features in terms of both their functional role and their fit to social and cognitive systems. One long‐standing puzzle concerns why certain languages employ grammatical gender. In an information theoretic analysis of German noun classification, Dye, Milin, Futrell, and Ramscar (2017) enumerated a number of important processing advantages gender confers. Yet this raises a further puzzle: If gender systems are so beneficial to processing, what does this mean for languages that make do without them? Here, we compare the… Read More

Perception of Human Interaction Based on Motion Trajectories: From Aerial Videos to Decontextualized Animations

Published in: Topics in Cognitive Science, Volume 10, Issue 1, 225-241 Abstract “People are adept at perceiving interactions from movements of simple shapes, but the underlying mechanism remains unknown. Previous studies have often used object movements defined by experimenters. The present study used aerial videos recorded by drones in a real‐life environment to generate decontextualized motion stimuli. Motion trajectories of displayed elements were the only visual input. We measured human judgments of interactiveness between two moving elements and the dynamic change in such judgments over time. A hierarchical model was developed to account for human performance in this task. The model… Read More

Creating Time: Social Collaboration in Music Improvisation

Published in: Topics in Cognitive Science, Volume 10, Issue 1, 95-119 Abstract “Musical collaboration emerges from the complex interaction of environmental and informational constraints, including those of the instruments and the performance context. Music improvisation in particular is more like everyday interaction in that dynamics emerge spontaneously without a rehearsed score or script. We examined how the structure of the musical context affords and shapes interactions between improvising musicians. Six pairs of professional piano players improvised with two different backing tracks while we recorded both the music produced and the movements of their heads, left arms, and right arms. The backing… Read More

Preemption in Singular Causation Judgments: A Computational Model

Published in: Topics in Cognitive Science, Volume 10, Issue 1, 242-257 Abstract “Causal queries about singular cases are ubiquitous, yet the question of how we assess whether a particular outcome was actually caused by a specific potential cause turns out to be difficult to answer. Relying on the causal power framework (Cheng, 1997), Cheng and Novick (2005) proposed a model of causal attribution intended to help answer this question. We challenge this model, both conceptually and empirically. We argue that the central problem of this model is that it treats causal powers that are probabilistically sufficient to generate the effect on a… Read More