Connecting the dots from a distance: Does mentally traveling through space and time increase searching for life’s meaning?

As humans, we have the ability to travel beyond the present moment by considering past and future times as well as locations that are distant from oneself. An interesting possibility is that such mental travel to far-away times and places (vs. focusing on times and places closer to the present) may increase people’s desire to search for their lives’ meaning. Since searching for meaning involves the integration of separate life events into a coherent life story, mentally traveling farther away from the present may make people aware that their life stories include more than what is happening at this very minute. Such awareness, then, may increase their desire to ‘connect the dots’ between their life events by searching for some underlying meaning. Three experiments (N = 838) tested this prediction and found that greater (vs. lower) mental travel through space or time increased the search for life’s meaning.     

Two-Stage maximum likelihood estimation in the misspecified restricted latent class model

The maximum likelihood classification rule is a standard method to classify examinee attribute profiles in cognitive diagnosis models (CDMs). Its asymptotic behaviour is well understood when the model is assumed to be correct, but has not been explored in the case of misspecified latent class models. This paper investigates the asymptotic behaviour of a two-stage maximum likelihood classifier under a misspecified CDM. The analysis is conducted in a general restricted latent class model framework addressing all types of CDMs. Sufficient conditions are proposed under which a consistent classification can be obtained by using a misspecified model. Discussions are also provided on the inconsistency of classification under certain model misspecification scenarios. Simulation studies and a real data application are conducted to illustrate these results. Our findings can provide some guidelines as to when a misspecified simple model or a general model can be used to provide a good classification result.     

Subjective,physiological, and behavioural responses towards evaluatively conditioned stimuli

Evaluative Conditioning (EC) is commonly defined as the change in liking of a stimulus (conditioned stimulus, CS) due to its pairings with an affective unconditioned stimulus (US). In Experiment 1, we investigated effects of repeated stimulus pairings on affective responses, i.e. valence and arousal ratings, pupil size, and duration estimation. After repeatedly pairing the CSs with affective USs, a consistent pattern of affective responses emerged: The CS_negative was rated as being more negative and more arousing, resulted in larger pupils, and was temporally overestimated compared to the CS_neutral. In Experiment 2, the influence of a mere instruction about the contingency between a CS and US on affective responses was examined. After mere instruction about upcoming pairings between the CS and US, subjective ratings also changed, but there was neither evidence for differential pupillary responses nor for differential temporal processing. The results indicate that EC via pairings or instructions can change the affective responses towards formerly neutral stimuli and introduce pupil size as a physiological measure in EC research. However, Experiment 2 suggests that there might be moderating factors based on the type of EC procedure involved.     

Image memorability across longer time intervals

You may find some images easier to remember than others. Recent studies of visual memory have found remarkable levels of consistency for this inter-item variability across observers, suggesting that memorability can be considered an intrinsic image property. The current study replicated and extended previous results, while adopting a more traditional visual long-term memory task with retention intervals of 20 min, one day, and one week, as opposed to the previously used repeat-detection task, which typically relied on short retention intervals (5 min). Our memorability rank scores show levels of consistency across observers in line with those reported in previous research. They correlate strongly with previous quantifications and appear stable over time. Furthermore, we show that the way consistency of memorability scores increases with the number of responses per image follows the Spearman–Brown formula. Interestingly, our results also seem to show an increase in consistency with an increase in retention interval. Supported by simulated data, this effect is attributed to a decrease of extraneous influences on recognition over time. Finally, we also provide evidence for a log-linear, rather than linear, decline of the raw memorability scores over time, with more memorable images declining less strongly.     

How Cross‐Linguistic Differences in the Grammaticalization of Future Time Reference Influence Intertemporal Choices

According to Chen's (2013) Linguistic Savings Hypothesis (LSH), our native language affects our economic behavior. We present three studies investigating how cross‐linguistic differences in the grammaticalization of future‐time reference (FTR) affect intertemporal choices. In a series of decision scenarios about finance and health issues, we let speakers of altogether five languages that represent FTR with increasing strength, that is, Chinese, German, Danish, Spanish, and English, choose between hypothetical sooner‐smaller and later‐larger reward options. While the LSH predicts a present‐bias that increases with FTR‐strength, our decision makers preferred later‐larger options and this future‐bias increased with FTR‐strength. In multiple regressions, the FTR‐strength effect persisted when controlled for socioeconomic and cultural differences. We discuss why our findings deviate from the LSH and ask in how far the FTR‐strength effect represents a habitual constitution of linguistic relativity or an instance of online decision framing.     

Modeling Nonstationary Emotion Dynamics in Dyads using a Time-Varying Vector-Autoregressive Model

Emotion dynamics are likely to arise in an interpersonal context. Standard methods to study emotions in interpersonal interaction are limited because stationarity is assumed. This means that the dynamics, for example, time-lagged relations, are invariant across time periods. However, this is generally an unrealistic assumption. Whether caused by an external (e.g., divorce) or an internal (e.g., rumination) event, emotion dynamics are prone to change. The semi-parametric time-varying vector-autoregressive (TV-VAR) model is based on well-studied generalized additive models, implemented in the software R. The TV-VAR can explicitly model changes in temporal dependency without pre-existing knowledge about the nature of change. A simulation study is presented, showing that the TV-VAR model is superior to the standard time-invariant VAR model when the dynamics change over time. The TV-VAR model is applied to empirical data on daily feelings of positive affect (PA) from a single couple. Our analyses indicate reliable changes in the male’s emotion dynamics over time, but not in the female’s—which were not predicted by her own affect or that of her partner. This application illustrates the usefulness of using a TV-VAR model to detect changes in the dynamics in a system.     

Integrating Covariates into Social Relations Models: A Plausible Values Approach for Handling Measurement Error in Perceiver and Target Effects

The Social Relations Model (SRM) is a conceptual and analytical approach to examining dyadic behaviors and interpersonal perceptions within groups. In an SRM, the perceiver effect describes a person's tendency to perceive other group members in a certain way, whereas the target effect measures the tendency to be perceived by others in certain ways. In SRM research, it is often of interest to relate these individual SRM effects to covariates. However, the estimated individual SRM effects might not provide a very reliable measure of the true, unobserved SRM effects, resulting in distorted estimates of associations with other variables. This article introduces a plausible values approach that allows users to correct for measurement error when assessing the association of individual SRM effects with other individual difference variables. In the plausible values approach, the latent, true individual SRM effects are treated as missing values and are imputed from an imputation model by applying Bayesian estimation techniques. In a simulation study, the statistical properties of the plausible values approach are compared with two approaches that have been used in previous research. A data example from educational psychology is presented to illustrate how the plausible values approach can be implemented with the software WinBUGS.     

Time–Frequency Cross Mutual Information Analysis of the Brain Functional Networks Underlying Multiclass Motor Imagery

To study the physiologic mechanism of the brain during different motor imagery (MI) tasks, the authors employed a method of brain-network modeling based on time–frequency cross mutual information obtained from 4-class (left hand, right hand, feet, and tongue) MI tasks recorded as brain–computer interface (BCI) electroencephalography data. The authors explored the brain network revealed by these MI tasks using statistical analysis and the analysis of topologic characteristics, and observed significant differences in the reaction level, reaction time, and activated target during 4-class MI tasks. There was a great difference in the reaction level between the execution and resting states during different tasks: the reaction level of the left-hand MI task was the greatest, followed by that of the right-hand, feet, and tongue MI tasks. The reaction time required to perform the tasks also differed: during the left-hand and right-hand MI tasks, the brain networks of subjects reacted promptly and strongly, but there was a delay during the feet and tongue MI task. Statistical analysis and the analysis of network topology revealed the target regions of the brain network during different MI processes. In conclusion, our findings suggest a new way to explain the neural mechanism behind MI.     

情绪确定性对学习判断的影响

为了揭示情绪的确定性维度对学习判断的影响,本研究通过使用即时学习判断范式的两个实验,分别探讨了高确定性情绪(愤怒、快乐)和低确定性情绪(恐惧、惊喜)的被试在学习判断中的表现。结果显示:(1)愤怒组和快乐组花费在项目学习上的时间显著少于恐惧组和惊喜组;(2)愤怒组的学习判断值显著高于恐惧组;(3)愤怒组的学习判断准确性显著低于恐惧组。从而证明了情绪的确定性维度与学习判断之间的因果关系。     

In the grip of fear: Dissociations in attentional processing of animal fearful individuals

Using a modified attention paradigm we investigated specific attentional mechanisms in processing animal feared stimuli. In this paradigm arrays of four pictures were displayed and after its disappearance from view a probe (a letter, X or P) then followed unpredictably in the location of one of the four pictures. The results showed that discriminations of probes tended to be impeded by spider stimuli, compared to snake stimuli. This effect was potentiated by high anxiety but only for those individuals fearful of spiders, since no such effect was observed for snake fearful individuals. Moreover, the discrimination of the probes was not facilitated when presented after the feared stimuli. The implications of these findings are discussed as a function of the cognitive bias involved in specific fear.