How intention and monitoring your thoughts influence characteristics of autobiographical memories

Involuntary autobiographical memories come to mind effortlessly and unintended, but the mechanisms of their retrieval are not fully understood. We hypothesize that involuntary retrieval depends on memories that are highly accessible (e.g., intense, unusual, recent, rehearsed), while the elaborate search that characterizes voluntary retrieval also produces memories that are mundane, repeated or distant – memories with low accessibility. Previous research provides some evidence for this ‘threshold hypothesis’. However, in almost every prior study, participants have been instructed to report only memories while ignoring other thoughts. It is possible that such an instruction can modify the phenomenological characteristics of involuntary memories. This study aimed to investigate the effects of retrieval intentionality (i.e., wanting to retrieve a memory) and selective monitoring (i.e., instructions to report only memories) on the phenomenology of autobiographical memories. Participants were instructed to (1) intentionally retrieve autobiographical memories, (2) intentionally retrieve any type of thought (3) wait for an autobiographical memory to spontaneously appear, or (4) wait for any type of thought to spontaneously appear. They rated the mental content on a number of phenomenological characteristics both during retrieval and retrospectively following retrieval. The results support the prediction that highly accessible memories mostly enter awareness unintended and without selective monitoring, while memories with low accessibility rely on intention and selective monitoring. We discuss the implications of these effects.     

内隐联想测验：信度、效度及原理

内隐联想测验（Implicit Association Test）是一种评估个体对两个概念的自动化联系强度的间接测量方法,近年来被广泛应用于内隐社会认知研究。有很多证据显示,较之于外显测验,IAT能为研究提供更多新的信息,但其信度、效度指标都有待改善,而且不同学者对其测验原理仍有不同解释。因此,研究者对IAT的应用及对其结果的解释需持谨慎态度。另外,文章还简单介绍了IAT数据处理的新方法和一些IAT的变式。     

归类不确定时人们的推理方式研究

该研究采用集中呈现样例的研究范式,探讨了归类不确定情况下,人们的推理方式。实验1控制特征联结频次,考察人们的推理方式是否是基于类别的推理。实验2控制类别中特征的基本概率,考察人们推理方式是否是基于特征联结的推理。实验结果表明,特征推理前不预先归类直接推理时,人们的推理根据目标特征与预测特征联结的频次进行,是基于特征联结的推理;特征推理前预先要求被试归类时,人们的特征推理是基于类别的推理。     

Stochastic matching and the voluntary nature of choice

Attempts to characterize voluntary behavior have been ongoing for thousands of years. We provide experimental evidence that judgments of volition are based upon distributions of responses in relation to obtained rewards. Participants watched as responses, said to be made by "actors," appeared on a computer screen. The participant's task was to estimate how well each actor represented the voluntary choices emitted by a real person. In actuality, all actors' responses were generated by algorithms based on Baum's (1979) generalized matching function. We systematically varied the exponent values (sensitivity parameter) of these algorithms: some actors matched response proportions to received reinforcer proportions, others overmatched (predominantly chose the highest-valued alternative), and yet others undermatched (chose relatively equally among the alternatives). In each of five experiments, we found that the matchingactor's responses were judged most closely to approximate voluntary choice. We found also that judgments of high volition depended upon stochastic (or probabilistic) generation. Thus, stochastic responses that match reinforcer proportions best represent voluntary human choice.     

Occasion setting is specific to the CS-US association

In Experiment 1, rats were trained on a discrimination in which one occasion setter, A, signaled that one cue (conditioned stimulus, CS), x, would be followed by one outcome, p (unconditioned stimulus, US), and a second CS, y, by a different outcome, q (x → p and y → q); a second occasion setter, B signalled the reverse CS-outcome relations (x → q and y → p). In a subsequent stage, the animals were divided into two groups, and trained as before, except that both A and B were presented in compound with a novel occasion setter, C. For Group S (same) the CS-outcome relations following A and B were identical to those in the pretraining stage, whereas in Group D (different) they were reversed. In a subsequent test, stimulus C was shown to be a more effective occasion setter in Group D than in Group S. In Experiment 2, rats were trained on a negative occasion-setting discrimination in which CS x signaled outcome p, and y outcome q; when x and y were signaled by the occasion setter A then no outcome followed (x → p, y → q, A:x-, and A:y-). In a subsequent stage, A was now trained as a positive occasion setter, signaling reinforcement of x and y. In Group S, x and y signaled the same outcomes as in the prior training stage (x-, y-, A:x → p, and A:y → q), whereas in Group D they signaled the opposite outcomes (x, y, A:x → q, and A:y → p); more efficient test performance was seen in the latter group. These results suggest that the each occasion setter conveyed information about the specific combination of CS and US paired in its presence (i.e., x → p and y → q, or x → no p and y → no q). These results are consistent with the suggestion that occasion setters operate, at least in part, on a specific CS-US association.     

测验情境对错误记忆的影响

本研究采用DRM范式,通过两个实验考察测验情境对错误记忆的影响,结果发现：（1）在两个实验中均产生了错误记忆现象：实验一关键诱饵的错误再认率为M=0．514,SD=0233;实验二关键诱饵的总错误再认率M=0．510,SD=0．215：（2）学习词表的语义关联越大,错误再认率越低：实验一项目语义关联程度主效应显著,F（1,84）=6．145．MSE=0．312．P=0．015;实验二,F（1,84）=5．143,MSE=0．225,P=0．026;（3）关键诱饵的位置造成了不同的情境效应：实验一,关键诱饵出现在第一个位置和第二个位置之间错误再认率差异显著（P=0．024）;实验二,关键诱饵出现第二个位置和第三个位置之间的错误再认率边缘显著（P=0．052）。该研究揭示了情境对错误记忆的影响。     

物理线索缺失下的错误记忆

本研究采用基于语义关联的DRM范式,通过改变测试词语的字体来探究语义痕迹和物理线索对错误记忆的影响。结果表明,语义关联产生的要义痕迹依然是错误记忆产生的重要因素,而对物理线索的操作则使真实记忆和错误记忆发生了分离,在字体改变的条件下,被试的错误记忆更加严重。     

Self-face advantage is modulated by social threat - Boss effect on self-face recognition

Human adults usually respond faster to self-face than to faces of others. The self-face advantage has been associated with an implicit positive association with the self. The current work investigated whether social threats modulate self-face recognition by asking graduate students to identify orientations of self-face in a high-threat context, in which self-face and a faculty advisor’s face were presented in one block of trials, or in a low-threat context, in which self-face and a face of another faculty member were presented in one block of trials. We found a self-face advantage in the low-threat context but a self-face disadvantage in the high-threat context (i.e., slower responses to self-face compared to the advisor’s face). Moreover, the self-face disadvantage positively correlated with the degree of fear of negative evaluations from advisors. Our findings suggest that self-face recognition is strongly modulated by social interactions with influential superiors within social hierarchies.     

Accounting for auto-dependency in binary dyadic time series data: A comparison of model- and permutation-based approaches for testing pairwise associations

Many theories have been put forward on how people become synchronized or co-regulate each other in daily interactions. These theories are often tested by observing a dyad and coding the presence of multiple target behaviours in small time intervals. The sequencing and co-occurrence of the partners’ behaviours across time are then quantified by means of association measures (e.g., kappa coefficient, Jaccard similarity index, proportion of agreement). We demonstrate that the association values obtained are not easy to interpret, because they depend on the marginal frequencies and the amount of auto-dependency in the data. Moreover, often no inferential framework is available to test the significance of the association. Even if a significance test exists (e.g., kappa coefficient) auto-dependencies are not taken into account, which, as we will show, can seriously inflate the Type I error rate. We compare the effectiveness of a model- and a permutation-based framework for significance testing. Results of two simulation studies show that within both frameworks test variants exist that successfully account for auto-dependency, as the Type I error rate is under control, while power is good.