Facing up to Faces: Changing biases in face perception to improve emotional processing in mental health

准确地检测和识别他人情绪的能力在日常生活中非常重要。即使在这方面的能力上存在微小的差异，例如对某些情绪的相对不敏感，或对其他情绪的高度敏感，也会导致问题。例如，抑郁症患者往往对快乐的表达不太敏感，对悲伤的表达更敏感。这实际上可能有助于他们抑郁的发作或维持，因为这会导致他们对世界的看法发生扭曲，特别是对其他人。例如，如果一个人对他人的幸福感不那么敏感，他或她可能不会注意到别人对他或她的积极回应，也不会回应，从而错过了积极的社会互动的机会。模糊不清的脸，由快乐和悲伤的混合物组成，可以用来确定一个人何时停止看到一种情绪，并开始看到另一种情绪。利用这些信息，这个人可以被“训练”成更倾向于从那些模棱两可的面孔中看到快乐，而不是悲伤。这个训练过程只需要大约20分钟，可以在笔记本电脑上完成，原则上也可以通过网站、平板电脑或智能手机完成。经过几天的反复训练，可以在情绪识别方面产生显著的变化，因此个体变得更倾向于在别人的脸上看到快乐而不是悲伤。在这里，我们提出了一项研究来回答两个问题：这个过程是否会改善人们的情绪，以及这个过程涉及哪些大脑区域？我们的试点工作非常有希望。在一组抑郁症状严重的人中，四天的训练导致两周后积极情绪的明显改善。我们希望招募更大的样本，提供更明确的结果，并在6周的更长随访期内收集情绪数据，以确定这些影响的持久性。这将使我们能够在这种干预的发展中迈出关键的下一步，即从概念验证转向临床翻译。与此同时，我们想进行一项较小的研究，该研究将使用相同的训练程序，但随后将使用大脑扫描技术来识别哪些大脑区域受到该训练程序的影响。最后，我们将组织一小群经历过抑郁症的人，以了解他们是否认为像我们这样的自动化训练程序是一种可以接受的抑郁症治疗方法。我们的研究结果有可能产生一种新型的抑郁症治疗方法，可以与认知行为疗法或药物等现有治疗方法结合使用。它具有相对简单和非侵入性的优点，原则上可以通过互联网或智能手机远程交付。此外，我们将使用的技术原则上可以应用于情绪识别似乎起作用的其他心理健康问题，如行为障碍，精神分裂症和成瘾。

The ability to accurately detect and recognize emotion in other people is extremely important in everyday life. Even slight differences in the ability to do this, such as a relative insensitivity to some emotions, or heightened sensitivity to other emotions, can cause problems. For example, people with depression tend to be less sensitive to expressions of happiness, and more sensitive to expressions of sadness. This may actually contribute to the onset or maintenance of their depression, by causing distortions in how they perceive the world, and in particular other people. If someone is less sensitive to happiness in others, for example, he or she may not notice when someone is responding positively to them, and fail to reciprocate this, thereby missing out on the opportunity for a positive social interaction.We have developed a technique which allows us to subtly modify these emotion recognition biases. Faces which are ambiguous, and consist of a blend of happiness and sadness, can be used to determine when a person stops seeing one emotion and starts seeing another. Using this information, that individual can then be "trained" to be more inclined to see happiness in those ambiguous faces rather than sadness. This training procedure takes only about 20 minutes, and can be done on a laptop or, in principle, via a website or on a tablet computer or smartphone. Repeated training over a few days can produce a marked change in emotion recognition, so that the individual becomes more inclined to see happiness over sadness in other people's faces. Here we are proposing a study to answer two questions: Does this procedure improve people's mood, and what brain regions are involved in this process?Our pilot work is very promising. In a group of people selected for high levels of depressive symptoms, four days of training resulted in a noticeable improvement in positive mood two weeks later. We would like to recruit a larger sample, to provide more definitive results, and collect mood data at a longer follow-up period of six weeks, to establish the longevity of these effects. This would allow us make the critical next step in the development of this intervention, which is to move from proof of concept to clinical translation. In parallel, we would like to run a smaller study which will use the same training procedure but will then use brain scanning technology to identify which brain regions are influenced by this training procedure. Finally, we will run a small focus group of people who have experienced depression, in order to find out whether they feel that an automated training procedure such as ours would be an acceptable treatment for depression.The results of our study have the potential to give rise to a new type of treatment for depression, which could be used in conjunction with existing treatments such as cognitive behavioural therapy or medication. It has the advantage of being relatively simple and non-invasive, and in principle can be delivered remotely via the internet or a smartphone. In addition, the techniques we will be using can in principle be applied to other mental health problems where emotion recognition appears to play a role, such as conduct disorder, schizophrenia and addiction.