Vulnerability of facial attractiveness perception to early and multi-year visual deprivation

Judgments of facial attractiveness invariably accompany our perception of faces. Even neonates appear to be capable of making such judgments in a manner consistent with adults. This suggests that the processes supporting facial attractiveness require little, if any, visual experience to manifest. Here we investigate the resilience of these processes to several years of early-onset visual deprivation. Specifically, we study whether congenitally blind children treated several years after birth possess the ability to rate facial attractiveness in a manner congruent to normally sighted individuals. The data reveal significant individual variability in the way each newly sighted child perceives attractiveness. This is in marked contrast to data from normally sighted controls who exhibit strong across-subject agreement in facial attractiveness ratings. This variability may be attributable, in part, to atypical facial encoding strategies used by the newly sighted children. Overall, our results suggest that the development of facial attractiveness perception is likely to be vulnerable to early visual deprivation, pointing to the existence of a possible sensitive period early in the developmental trajectory.     

面部表情的类别知觉及其个体差异

面部表情类别知觉效应是指连续变化的表情在人脑中按照类别表征, 且不同类别的表情之间存在明显的类别界线。介绍了面部表情类别知觉效应的行为和脑电研究范式及基础研究, 综述了攻击性、抑郁症、精神分裂症、社交焦虑等对面部表情类别知觉的影响, 以及面部表情类别知觉的发展研究。综述表明, 类别知觉研究能够揭示不同人群表情知觉类别界线及其偏移情况, 有助于解释相应的社会行为。未来研究应注重对面部表情类别知觉效应的个体差异和神经生理机制的探索。     

情境对面孔表情识别的影响

长期以来,关于面孔表情识别的研究主要是围绕着面孔本身的结构特征来进行的,但是近年来的研究发现,面孔表情的识别也会受到其所在的情境背景（如语言文字、身体背景、自然与社会场景等）的影响,特别是在识别表情相似的面孔时,情境对面孔表情识别的影响更大。本文首先介绍和分析了近几年关于语言文字、身体动作、自然场景和社会场景等情境影响个体对面孔表情的识别的有关研究;其次,又分析了文化背景、年龄以及焦虑程度等因素对面孔表情识别情境效应的影响;最后,强调了未来的研究应重视研究儿童被试群体、拓展情绪的类别、关注真实生活中的面孔情绪感知等。     

动态面孔表情优势效应的心理机制及神经基础

动态面孔表情优势效应是指较静态面孔表情而言, 个体在识别动态的面孔表情时表现出较好的识别能力。动态面孔表情优势效应的心理机制主要涉及增强的构形加工、补偿角色和面孔模仿能力。此外, 该优势效应的神经网络则由核心的神经网络和扩展的神经网络组成, 前者主要负责早期的知觉编码和刺激的运动加工, 而后者与个体的面孔模仿能力、刺激的动态表征等有关。今后的研究应集中在完善延伸的神经网络、拓展其心理机制; 开展动态面孔表情优势效应的发展性研究; 考察面孔表情的刚性运动特征; 注重在虚拟现实环境下研究动态面孔表情的优势效应。     

面孔审美加工的神经机制及个体差异

外显和内隐的面孔审美加工的脑成像研究表明,美的面孔比不美的面孔导致眶额皮层、伏隔核、杏仁核等奖赏脑区更大的激活。脑电研究则发现了与面孔审美加工有关的早期负波和晚期正成分。面孔审美加工有关的脑区活动也受到性别、生理周期等个体因素的调节。未来的研究需要比较美的面孔与其它奖赏刺激加工的神经机制,探讨面孔审美加工的不同阶段及时间进程,在面孔知觉的框架下形成合理的面孔审美加工的神经模型。     

面部表情加工的ERP成分

面部表情加工的ERP成分主要包括P1 (80~120 ms)、N170 (120~200 ms), 早期后部负电位(Early Posterior Negativity, EPN, 200~300 ms)和晚期正成分(Late Positive Potential, LPP, 300 ms以后)。这些成分代表了表情加工的不同阶段, 具有不同的心理含义。P1成分只对威胁类表情(恐惧, 厌恶和愤怒)敏感, 反映了对威胁面孔的快速探测, 具有自动加工的性质。N170成分与表情结构信息的编码有关, 同样具有自动加工的性质。EPN反映了对情绪信息的选择性注意, 具有情绪普遍性, 情绪场景图片和表情刺激都会对它产生影响, 在特定的条件下具有自动加工的性质。LPP则反映了对情绪信息的高级认知加工, 较易受注意控制的影响。在对上述成分的特性了解的基础上, 将来的研究应该探索以下问题：(1) P1是否受表情威胁程度的影响？(2) N170受到哪些自上而下因素的影响？(3)那些不能影响N170成分, 却能影响EPN成分的表情刺激是否被当成了普通的情绪刺激来看待？(4)表情加工引发的LPP是否能具有自动加工的性质？(5)不同的基本表情类型(如恐惧和厌恶)是否具有特异性的ERP成分？     

情绪面孔搜索不对称性：情绪观与知觉观的争议

情绪面孔搜索不对称性是指当负性情绪面孔作为目标, 正性情绪面孔作为分心物时, 其搜索速度比正性情绪面孔作为目标时(负性情绪面孔作为分心物)更快。对于这一现象的解释存在争议, 研究者主要从不同情绪面孔在情绪因素和知觉因素两个方面的差异进行解释。来自行为研究和认知神经科学的证据对情绪面孔搜索不对称性效应的解释主要有威胁性刺激捕获假设和情绪摆脱假设的情绪观, 以及嘴部差异说、闭合结构说、知觉组群说以及其他面部特征假设的知觉观。经过对比评价两类观点的理论异同和实验证据认为未来的研究可以整合情绪因素和知觉因素来解释该效应。     

Notes for a dialogue between psychoanalysis and neuroscience1

The author postulates that the dialogue between psychoanalysis and neuroscience is based on the assumption that both deal with virtual structures. They are two facets of the same noumenal reality, but with different phenomenal realities, and it is possible to use metapsychology as a lingua franca to develop communication between the two fi elds. In the second part of the paper, the author refl ects on the results of recent neurophysiological research which seem to offer to psychoanalysis possibilities for fi nding an anatomical‐physiological correlate of some well‐known psychic phenomena and mechanisms, such as imitation, introjection, identifi cation, empathy, identity, mother‐child communication, learning, social communication and the analyst‐patient relationship. Particular neurons, called mirror neurons, have been located in the F5 area of baboons' brains. They are also present in man's brain within Broca's area. These neurons activate our motor system during both the performance of actions and the observation of actions performed by others giving rise to an automatic response, a sort of simulation or, rather, imitation, as the process is not intentional, but automatic and unaware, that is, unconscious.     

Diagnostic causal reasoning with verbal information

In diagnostic causal reasoning, the goal is to infer the probability of causes from one or multiple observed effects. Typically, studies investigating such tasks provide subjects with precise quantitative information regarding the strength of the relations between causes and effects or sample data from which the relevant quantities can be learned. By contrast, we sought to examine people’s inferences when causal information is communicated through qualitative, rather vague verbal expressions (e.g., “X occasionally causes A”). We conducted three experiments using a sequential diagnostic inference task, where multiple pieces of evidence were obtained one after the other. Quantitative predictions of different probabilistic models were derived using the numerical equivalents of the verbal terms, taken from an unrelated study with different subjects. We present a novel Bayesian model that allows for incorporating the temporal weighting of information in sequential diagnostic reasoning, which can be used to model both primacy and recency effects. On the basis of 19,848 judgments from 292 subjects, we found a remarkably close correspondence between the diagnostic inferences made by subjects who received only verbal information and those of a matched control group to whom information was presented numerically. Whether information was conveyed through verbal terms or numerical estimates, diagnostic judgments closely resembled the posterior probabilities entailed by the causes’ prior probabilities and the effects’ likelihoods. We observed interindividual differences regarding the temporal weighting of evidence in sequential diagnostic reasoning. Our work provides pathways for investigating judgment and decision making with verbal information within a computational modeling framework.