Looking into your eyes: observed pupil size influences approach-avoidance responses

The eyes reveal important social messages, such as emotions and whether a person is aroused and interested or bored and fatigued. A growing body of research has also shown that individuals with large pupils are generally evaluated positively by observers, while those with small pupils are perceived negatively. Here, we examined whether observed pupil size influences approach-avoidance tendencies. Participants performed an Approach-Avoidance Task using faces with large and small pupil sizes. Results showed that pupil size influences the accuracy of arm movements. Specifically, individuals were less prone to approach a face with small pupils than a face with large pupils. Conversely, participants were less prone to avoid a face with large pupils than a face with small pupils. Collectively, these findings suggest that perceivers attend to a facial cue – pupil size – when interacting with others.     

错觉轮廓的适应效应

错觉轮廓反映知觉的主动建构过程, 考察其是否存在适应效应有助于理解视觉系统反馈调节的特性。我们采用Kanizsa这种典型的错觉轮廓来研究其适应过程, 结果发现：Kanizsa错觉轮廓具有适应效应, 并且这种适应主要是由主观形成的整体轮廓造成的, 而不是由Pac-Man上的线条引起的。表明依赖于高级视觉皮层反馈调节的主观建构过程和自下而上的神经元信息一样, 会随呈现时间的增加, 神经活动减弱, 体现为适应效应。     

亚健康的心理危险因素:模型与进展

自上世纪80年代以来,亚健康的研究热潮已经持续了二十多年,亚健康的概念在我国已经被广泛认知和使用,然而人们对亚健康的概念、诊断、病理的认识仍然模糊,在国际学术界也始终没有出现被普遍使用的对应的专业名词,在这种情况下,迫切需要识别和应用危险因素以服务于临床的预防、筛查、干预。本文从"危险因素"的概念入手,借鉴"素质-应激"模型,区分了"危险信号"与其他因素,将亚健康的心理危险因素纳入"易感素质-危险诱因-心理危险信号"模型中,在此理论架构下,详细回顾了亚健康在心理易感素质、应激、心理危险信号方面的研究进展,阐述了亚健康的心理病理机制,支持了在亚健康的预防、干预中重视心理因素的价值。最后,文章对未来的研究方向提出建议。     

文章标记对阅读理解困难学生信息保持的促进研究

根据阅读理解困难学生不能合理分配注意资源的特点,设置了文章标记这一能引导注意分配的外在线索,并以高层次的主题信息回忆和低层次的从属信息回忆为指标,考察阅读理解正常与困难学生接受标记影响的不同特点。结果表明:(1)文章标记对于阅读理解正常和困难学生的主题信息的回忆均有显著的促进效果,而对于阅读理解困难者的促进作用更为明显。(2)文章标记只促进了阅读理解困难者的从属信息的回忆,对于阅读正常者来说,文章标记反而有损于对从属信息的回忆。     

Emotions as signals of normative conduct

Social interactions are heavily norm-based and these norms need to be learned. For this, the emotional reactions of other's in response to a norm transgression can serve as signals. We were able to show that when a group responds with anger to a norm transgressing behaviour, participants were better able to correctly infer the norm than when the group responded with sadness or emotional neutrality. We further tested a process-model showing that this inference is based on the participants' understanding of the groups' appraisals of the behaviour. That is, participants who were able to reverse engineer the underlying appraisal of norm-incompatibility from the emotion expressions inferred the norm more readily. Humans as a social species, require efficient means to quickly adapt to new situations and to perform flawlessly in social contexts. Emotion information is one of the instruments that can be used in this quest.     

Predicting Individuals’ Experienced Fear From Multimodal Physiological Responses to a Fear-Inducing Stimulus

Emotions are experienced differently by individuals, and thus, it is important to account for individuals’ experienced emotions to understand their physiological responses to emotional stimuli. The present study investigated the physiological responses to a fear-inducing stimulus and examined whether these responses can predict experienced fear. A total of 230 participants were presented with neutral and fear-inducing film clips, after which they self-rated their experienced emotions. Physiological measures (skin conductance level and response: SCL, SCR, heart rate: HR, pulse transit time: PTT, fingertip temperature: FT, and respiratory rate: RR) were recorded during the stimuli presentation. We examined the correlations between the physiological measures and the participants’ experienced emotional intensity, and performed a multiple linear regression to predict fear intensity based on the physiological responses. Of the participants, 92.5% experienced the fear emotion, and the average intensity was 5.95 on a 7-point Likert scale. Compared to the neutral condition, the SCL, SCR, HR, and RR increased significantly during the fear-inducing stimulus presentation whereas FT and PTT decreased significantly. Fear intensity correlated positively with SCR and HR and negatively with SCL, FT, PTT, and RR. The multiple linear regression demonstrated that fear intensity was predicted by a combination of SCL, SCR, HR, FT, and RR. Our findings indicate that the physiological responses to experiencing fear are associated with cholinergic, sympathetic, and α-adrenergic vascular activation as well as myocardial β-sympathetic excitation, and support the use of multimodal physiological signals for quantifying emotions.