The psychological distance of memories: Examining causal relations with mood and self-esteem in young,middle-aged and older adults

Three studies examined the self-enhancement function of autobiographical memory (measured with subjective temporal distance of memories). Participants recalled a memory of an attained and a failed goal and rated the subjective distance between each memory and the present. Study 1 showed that young adults with higher self-esteem felt closer to memories of attained goals and farther from failure memories than those with lower self-esteem. In Study 2, young, middle-aged and older adults with higher self-esteem felt closer to success memories, whereas self-esteem was unrelated to the temporal distance of failure memories. In both studies, feeling closer to success memories (and far from failure) led to enhanced mood. In Study 3, state self-esteem was experimentally manipulated. The manipulation had no effect on young and older adults, but middle-aged adults whose self-esteem was decreased, felt closer to success memories than failure memories. Results are discussed in relation to the temporal self-appraisal theory.     

The discovery and comparison of symbolic magnitudes

Humans and other primates are able to make relative magnitude comparisons, both with perceptual stimuli and with symbolic inputs that convey magnitude information. Although numerous models of magnitude comparison have been proposed, the basic question of how symbolic magnitudes (e.g., size or intelligence of animals) are derived and represented in memory has received little attention. We argue that symbolic magnitudes often will not correspond directly to elementary features of individual concepts. Rather, magnitudes may be formed in working memory based on computations over more basic features stored in long-term memory. We present a model of how magnitudes can be acquired and compared based on BARTlet, a representationally simpler version of Bayesian Analogy with Relational Transformations (BART; Lu, Chen, & Holyoak, 2012). BARTlet operates on distributions of magnitude variables created by applying dimension-specific weights (learned with the aid of empirical priors derived from pre-categorical comparisons) to more primitive features of objects. The resulting magnitude distributions, formed and maintained in working memory, are sensitive to contextual influences such as the range of stimuli and polarity of the question. By incorporating psychological reference points that control the precision of magnitudes in working memory and applying the tools of signal detection theory, BARTlet is able to account for a wide range of empirical phenomena involving magnitude comparisons, including the symbolic distance effect and the semantic congruity effect. We discuss the role of reference points in cognitive and social decision-making, and implications for the evolution of relational representations.     

Iterative Spatial Updating During Forward Linear Walking Revealed Using a Continuous Pointing Task

Abstract

The continuous pointing task uses target-directed pointing responses to determine how perceived distance traveled is estimated during forward linear walking movements. To more precisely examine the regulation of this online process, the current study measured upper extremity joint angles and step-cycle kinematics in full vision and no-vision continuous pointing movements. Results show perceptual under-estimation of traveled distance in no-vision trials compared to full vision trials. Additionally, parsing of the shoulder plane of elevation trajectories revealed discontinuities that reflected this perceptual under-estimation and that were most frequently coupled with the early portion of the right foot swing phase of the step-cycle. This suggests that spatial updating may be composed of discrete iterations that are associated with gait parameters.     

How numbers mean: Comparing random walk models of numerical cognition varying both encoding processes and underlying quantity representations

How do people derive meaning from numbers? Here, we instantiate the primary theories of numerical representation in computational models and compare simulated performance to human data. Specifically, we fit simulated data to the distributions for correct and incorrect responses, as well as the pattern of errors made, in a traditional “relative quantity” task. The results reveal that no current theory of numerical representation can adequately account for the data without additional assumptions. However, when we introduce repeated, error-prone sampling of the stimulus (e.g., Cohen, 2009) superior fits are achieved when the underlying representation of integers reflects linear spacing with constant variance. These results provide new insights into (i) the detailed nature of mental numerical representation, and, (ii) general perceptual processes implemented by the human visual system.     

The temporal-relevance temporal-uncertainty model of prospective duration judgment

A model aimed at explaining prospective duration judgments in real life settings (as well as in the laboratory) is presented. The model is based on the assumption that situational meaning is continuously being extracted by humans’ perceptual and cognitive information processing systems. Time is one of the important dimensions of situational meaning. Based on the situational meaning, a value for Temporal Relevance is set. Temporal Relevance reflects the importance of temporal aspects for enabling adaptive behavior in a specific moment in time. When Temporal Relevance is above a certain threshold a prospective duration judgment process is evoked automatically. In addition, a search for relevant temporal information is taking place and its outcomes determine the level of Temporal Uncertainty which reflects the degree of knowledge one has regarding temporal aspects of the task to be performed. The levels of Temporal Relevance and Temporal Uncertainty determine the amount of attentional resources allocated for timing by the executive system. The merit of the model is in connecting timing processes with the ongoing general information processing stream. The model rests on findings in various domains which indicate that cognitive-relevance and self-relevance are powerful determinants of resource allocation policy. The feasibility of the model is demonstrated by analyzing various temporal phenomena. Suggestions for further empirical validation of the model are presented.     

Intelligence and Extraversion in the neural evaluation of delayed rewards

Temporal discounting (TD), the preference for earlier, smaller rewards over delayed, larger rewards, is a pervasive phenomenon that covaries with Big Five personality traits and Intelligence (IQ). This study provides novel insight by identifying correlates for IQ and Extraversion in the neural representation of TD preferences. An intertemporal choice task was employed, where offers were sequentially presented, distinguishing between one evaluation phase (first offer is presented) and one comparison phase (second offer is presented and values are compared). IQ correlated with responses of caudate nucleus to the subjective values of the offers, suggesting a role of cognitive abilities in modulating reward responses. Extraversion correlated with the strength of functional connectivity of a reward evaluation network centered on ventromedial prefrontal cortex.     

Distance de pouvoir et auto-évaluation de l’efficacité d’une équipe de travail

We introduce a study concerning relation between power and the evaluation of the effectiveness of working teams (Savoie & Brunet, 2000). The power model of Mulder lead to postulate a relation between power distance in the team and the evaluation of the effectiveness. We collected a series of measurements in working teams composed of students engineers. Results allow proving such relation.     

Modeling the emergence of informational content by adaptive networks for temporal factorisation and criterial causation

Propagated activation of neurons through their network is an important process in the brain. Another crucial part of neural processing concerns adaptation over time of characteristics of this network such as connection strengths or excitability thresholds. This adaptation can be slow, as in learning from a multiple experiences, or it can be fast, as in memory formation. These adaptive network characteristics can be considered informational criteria for activation of a neuron. This then is viewed as a form of emergent information formation. Activation of neurons is determined by such information via a process termed criterial causation. In the current paper, the relationship of criterial causation with the principle of temporal factorisation for the dynamics of the world in general is explored. Temporal factorisation describes how the world represents information about its past in its present state, which then in turn determines the world’s future. In the paper, it is shown how these processes are analysed in more detail and modeled by (adaptive) network models.