The Problem of Other Minds

This paper reimagines the traditional problem of other minds. On a Cartesian view, the problem involves humans’ inability to perceive other persons’ minds. Similarly, Gilbert Ryle claims that we cannot directly access another’s mind. The paper’s rethinking of the problem of other minds moves beyond these questions of perceptibility and accessibility. It asks whether there are certain groups of people whose minds are systematically misinterpreted, or even denied mentality. It argues that there are. This claim builds off recent work in philosophy and social psychology on epistemic injustice and the role of social categories in mental state attribution. The paper proposes the Problem of the Other’s Mind: the phenomenon of a (relatively) socially privileged person’s inability or lack of desire to understand the mind of a (relatively) socially underprivileged person.     

A sad thumbs up: incongruent gestures and disrupted sensorimotor activity both slow processing of facial expressions

Recognising a facial expression is more difficult when the expresser's body conveys incongruent affect. Existing research has documented such interference for universally recognisable bodily expressions. However, it remains unknown whether learned, conventional gestures can interfere with facial expression processing. Study 1 participants (N?=?62) viewed videos of people simultaneously producing facial expressions and hand gestures and reported the valence of either the face or hand. Responses were slower and less accurate when the face-hand pairing was incongruent compared to congruent. We hypothesised that hand gestures might exert an even stronger influence on facial expression processing when other routes to understanding the meaning of a facial expression, such as with sensorimotor simulation, are disrupted. Participants in Study 2 (N?=?127) completed the same task, but the facial mobility of some participants was restricted, which disrupted face processing in prior work. The hand-face congruency effect from Study 1 was replicated. The facial mobility manipulation affected males only, and it did not moderate the congruency effect. The present work suggests the affective meaning of conventional gestures is processed automatically and can interfere with face perception, but does not suggest that perceivers rely more on gestures when sensorimotor face processing is disrupted.     

Models and mechanisms in network neuroscience

This paper considers the way mathematical and computational models are used in network neuroscience to deliver mechanistic explanations. Two case studies are considered: Recent work on klinotaxis by Caenorhabditis elegans, and a long-standing research effort on the network basis of schizophrenia in humans. These case studies illustrate the various ways in which network, simulation, and dynamical models contribute to the aim of representing and understanding network mechanisms in the brain, and thus, of delivering mechanistic explanations. After outlining this mechanistic construal of network neuroscience, two concerns are addressed. In response to the concern that functional network models are nonexplanatory, it is argued that functional network models are in fact explanatory mechanism sketches. In response to the concern that models which emphasize a network’s organization over its composition do not explain mechanistically, it is argued that this emphasis is both appropriate and consistent with the principles of mechanistic explanation. What emerges is an improved understanding of the ways in which mathematical and computational models are deployed in network neuroscience, as well as an improved conception of mechanistic explanation in general.     

Embodied simulation: From neurons to phenomenal experience

The same neural structures involved in the unconscious modeling of our acting body in space also contribute to our awareness of the lived body and of the objects that the world contains. Neuroscientific research also shows that there are neural mechanisms mediating between the multi-level personal experience we entertain of our lived body, and the implicit certainties we simultaneously hold about others. Such personal and body-related experiential knowledge enables us to understand the actions performed by others, and to directly decode the emotions and sensations they experience. A common functional mechanism is at the basis of both body awareness and basic forms of social understanding: embodied simulation. It will be shown that the present proposal is consistent with some of the perspectives offered by phenomenology.     

Classical Test Theory as a first-order Item Response Theory: Application to true-score prediction from a possibly nonparallel test

We give an account of Classical Test Theory (CTT) in terms of the more fundamental ideas of Item Response Theory (IRT). This approach views classical test theory as a very general version of IRT, and the commonly used IRT models as detailed elaborations of CTT for special purposes. We then use this approach to CTT to derive some general results regarding the prediction of the true-score of a test from an observed score on that test as well from an observed score on a different test. This leads us to a new view of linking tests that were not developed to be linked to each other. In addition we propose true-score prediction analogues of the Dorans and Holland measures of the population sensitivity of test linking functions. We illustrate the accuracy of the first-order theory using simulated data from the Rasch model, and illustrate the effect of population differences using a set of real data.This research is collaborative in every respect and the order of authorship is alphabetical. It was begun when both authors were on the faculty of the Graduate School of Education at the University of California, Berkeley.We would like to thank both Neil Dorans, Skip Livingston and two anonymous referees for many suggestions that have greatly improved this paper.     

A Monte Carlo investigation of conjoint analysis index-of-fit: Goodness of fit,significance and power

Researchers in the field of conjoint analysis know the index-of-fit values worsen as the judgmental error of evaluation increases. This simulation study provides guidelines on the goodness of fit based on distribution of index-of-fit for different conjoint analysis designs. The study design included the following factors: number of profiles, number of attributes, algorithm used and judgmental model used. Critical values are provided for deciding the statistical significance of conjoint analysis results. Using these cumulative distributions, the power of the test used to reject the null hypothesis of random ranking is calculated. The test is found to be quite powerful except for the case of very small residual degrees of freedom.The authors thank the editor, the three reviewers and Ellen Foxman for helpful comments on the paper. Sanjay Mishra was a doctoral student at Washington State University at the time this research was completed. He is currently in the Department of Marketing at the University of Kansas.     

Modeling cyclist acceleration process for bicycle traffic simulation using naturalistic data

Cycling is a healthy and sustainable form of transportation. The recent increase of daily cyclists in Sweden has triggered broad interest in finding how policies and measures may facilitate the planning of bicycle traffic in the urban area. However, in comparison to car traffic, bicycle traffic is still far from well understood. This study is part of the research effort to investigate microscopic cyclist behavior, model bicycle traffic and finally build a simulation tool for applications in transport planning. In particular, the paper focuses on representing bicycle movements when the cyclist doesn’t interact with others. The cyclist acceleration behavior is modeled using naturalistic GPS data collected by eleven recruited commuter cyclists. After filtering the large amount of data, cyclist trajectories are obtained and acceleration profiles are abstracted. A mathematical model is proposed based on the dataset, and three model forms are estimated using the maximum likelihood method with Laplace and Normal error terms. While the model with more parameters shows superior performance, the simplified ones are still capable of capturing the trends in the acceleration profiles. On the other hand, the study also introduces social economic characteristics of cyclists to explain the model parameters and they show significant effects. However, the cyclist population being investigated in the study is still limited, and more convincing results can be obtained when the data collection effort is extended to larger population with more variable cyclist characteristics.     

The functions of internal dialogs and their connection with personality

In previous studies, seven key functions in internal dialogs were identified: Support, Substitution, Exploration, Bond, Self‐improvement, Insight, and Self‐guiding. It was also established that internal dialogs vary in the intensity of these functions. The presented research aimed to test if there are configurations of personality variables that allow us to predict specific patterns of functions performed by internal dialogs. Canonical correlation analysis revealed that the higher the intensity of neuroticism and anxious attachment and the lower the intensity of openness and the tendency to spontaneously adopt the viewpoints of others, the more strongly a person's internal dialogs perform the Substitution function and the weaker the Insight and Support functions are. The reverse configuration of personality characteristics intensifies Insight and Support and minimized Substitution. The results are presented in the context of the status of dialogicality and discussed in the light of other studies on internal dialogs.     

A Comparison of ML,WLSMV, and Bayesian Methods for Multilevel Structural Equation Models in Small Samples: A Simulation Study

Multilevel structural equation models are increasingly applied in psychological research. With increasing model complexity, estimation becomes computationally demanding, and small sample sizes pose further challenges on estimation methods relying on asymptotic theory. Recent developments of Bayesian estimation techniques may help to overcome the shortcomings of classical estimation techniques. The use of potentially inaccurate prior information may, however, have detrimental effects, especially in small samples. The present Monte Carlo simulation study compares the statistical performance of classical estimation techniques with Bayesian estimation using different prior specifications for a two-level SEM with either continuous or ordinal indicators. Using two software programs (Mplus and Stan), differential effects of between- and within-level sample sizes on estimation accuracy were investigated. Moreover, it was tested to which extent inaccurate priors may have detrimental effects on parameter estimates in categorical indicator models. For continuous indicators, Bayesian estimation did not show performance advantages over ML. For categorical indicators, Bayesian estimation outperformed WLSMV solely in case of strongly informative accurate priors. Weakly informative inaccurate priors did not deteriorate performance of the Bayesian approach, while strong informative inaccurate priors led to severely biased estimates even with large sample sizes. With diffuse priors, Stan yielded better results than Mplus in terms of parameter estimates.     

What is the answer? And come to that, what are the questions?

In recent years, the topic of car-following has become of increased importance in traffic engineering and safety research. Models of this phenomenon, which describe the interaction between (typically) adjacent vehicles in the same lane, now form the cornerstone for many important areas of research including (a) simulation modelling, where the car-following model (amongst others) controls the motion of the vehicles in the network, and (b) the functional definition of advanced vehicle control and safety systems (AVCSS), which are being introduced as a driver safety aid in an effort to mimic driver behaviour but remove human error. Despite the importance of this area however, no overview of the models availability and validity exists. It is the intent of this paper therefore to briefly assess the range of options available in the choice of car-following model, and assess just how far work has proceeded in our understanding of what, at times, would appear to be a simple process.