1～6秒时距认知分段性特征

时距认知分段性指不同长度时距的加工机制和表征方式是不同的。以往研究者对1 s以上时距认知的分段性仍存在分歧,为了探讨这一主题,本研究设计了实验1和实验2。实验1采用时间复制任务比较高、低工作记忆容量被试在完成1~6 s视、听时距加工的成绩,结果发现,时距长度与工作记忆容量或通道均存在交互作用,被试在复制1 s、2 s的平均复制时距、复制比率及变异系数没有随工作记忆容量或通道而变化,而复制3 s、4 s、5 s及6 s时,高WMC组较低WMC组或听觉组较视觉组,平均复制时距显著更长、复制比率显著更高、变异系数显著更小。实验2采用时间产生任务比较高、低工作记忆容量被试在完成1~6 s视、听时距加工的成绩,结果也发现,时距长度与工作记忆容量或通道均存在交互作用,被试在产生1 s、2 s的平均产生时距、产生比率及变异系数没有随工作记忆容量或通道而变化,而产生3 s、4 s、5 s及6 s时,高WMC组较低WMC组或听觉组较视觉组,平均产生时距显著更短、产生比率显著更低、变异系数显著更小。这意味着1~6 s的时距认知存在分段性,大约2~3 s可能为分段临界点。时间认知的分段性可以用时间工作记忆说解释,该假说是时间认知分段综合模型解释短时距加工分段性的具体表现形式。     

Time to leave? The interaction of temporal focus and turnover intentions in explaining voluntary turnover behaviour

Although turnover intentions are the strongest predictors of voluntary turnover behaviours, many employees who express intentions to leave do not. To explain why some employees translate turnover intentions into behaviour and others do not, this study examines the moderating effect of temporal focus (i.e. the degree to which one thinks about the past, present and future) between turnover intentions and voluntary turnover, using the lens of theory of planned behaviour. Data were collected from 683 full-time employees in a range of organisations at three points in time. Results show that past temporal focus conditions the positive relationship between turnover intention and turnover, such that the relationship is stronger when past temporal focus is high. Future temporal focus has an opposite moderating effect, such that the relationship between turnover intention and turnover is weaker when future temporal focus is high. Results show no significant moderating effect of current temporal focus. Overall, temporal focus helps explain why some employees leave and others stay by conditioning the likelihood of translating turnover intentions into quitting. We speculate that a dominant, unspoken paradigm in turnover research is an assumption that individuals are current focused, yet our results suggest scholars should explicitly examine this assumption.     

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.