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.     

Conforming to coordinate: Children use majority information for peer coordination

Humans are constantly required to coordinate their behaviour with others. As this often relies on everyone's convergence on the same strategy (e.g., driving on the left side of the road), a common solution is to conform to majority behaviour. In this study, we presented 5‐year‐old children with a coordination problem: To retrieve some rewards, they had to choose the same of four options as a peer partner – in reality a stooge – whose decision they were unable to see. Before making a choice, they watched a video showing how other children from their partner's peer group had behaved; a majority chose the same option and a minority chose a different one. In a control condition, children watched the same video but could then retrieve the reward irrespective of their partner's choice (i.e., no coordination was necessary). Children followed the majority more often when coordination was required. Moreover, conformers mostly justified their choices by referring to the majority from the video demonstration. This study is the first to show that young children are able to strategically coordinate decisions with peers by conforming to the majority.     

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.