Development and validation of an automated test of animal affect and welfare for laboratory rodents

NC3Rs的一个中心目标是完善实验室程序，以尽量减少动物的痛苦、折磨和持久伤害，并改善实验动物的福利。为了实现这一目标，我们必须使用经过科学验证的措施来量化实验、住房和饲养程序如何影响福利，以及改进是否确实会带来改善。因此，nc3r呼吁进行研究，以制定新的和更好的福利措施。我们的项目将提供这样一种方法来更好地评估大鼠和小鼠（2010年英国81%的实验动物）的福利。假设非人类动物可以主观地经历消极的情绪（情感）状态，因此遭受对动物福利的关注。因此，情感状态是动物福利的关键决定因素。然而，由于主观体验本质上是私人的，不能直接测量，我们需要确定间接反映动物情感状态的指标。例如，我们可以测量生理变化，如激素水平，或行为指标，如动物在未受保护的开放空间中的行为。然而，尽管这些指标很有价值，但也有重要的局限性，我们最近制定的一种方法试图解决这些局限性。人类心理学研究表明，当感觉更快乐时，人们比情绪低落时更有可能将模棱两可的事件判断为有积极的结果；他们的杯子是半满的。如果其他动物也是如此，那么通过测量它们在模棱两可的情况下做出的判断，我们也可以获得关于它们感受的有用信息。为了探索这种可能性，我们开发了一种新颖的、非语言的“判断偏差”测试，以决策的理论模型为基础。这个测试允许我们系统地研究动物是积极（“乐观”）还是消极（“悲观”）判断模棱两可的刺激。最近对老鼠、羊、狗、猴子和椋鸟的研究支持这样的假设，即处于更积极情感状态的动物确实对模棱两可的刺激表现出更“乐观”的反应，这表明这种技术可能是评估动物情绪状态的一种很好的方法。然而，现有的判断偏差测试相对耗时，涉及动物的动手训练，并且没有针对小鼠（最广泛使用的实验室物种）开发的方法。因此，我们将开发一种自动化版本的判断偏差测试，可用于实验室啮齿动物，包括小鼠。然后，我们将通过采用一系列精心挑选的药理学和环境治疗来验证这个新测试，每种治疗都旨在诱导情感状态的特定短暂变化。通过检查治疗如何影响所显示的反应的大小，我们将能够看到该方法是否可以量化情绪状态的强度。我们还将比较富裕和标准的住房条件，以及其他长期情绪状态的决定因素，看看该测试是否能检测到长期经历对情绪的累积效应。“累积痛苦”很难衡量，但对动物的终身福利至关重要，我们希望我们的方法可以很好地说明这种状态。一个工业合作伙伴表示有兴趣进一步实施我们为广泛使用而开发的测试，例如将其纳入家庭笼测试系统。这项研究还将产生关于情感状态如何随着外部事件而变化的计算模型。这些可以为模拟实验治疗对动物情感状态的影响提供基础，从而促进更好和更人性化的研究规划。我们希望这个项目将为这些模型的进一步发展奠定基础。

A central goal of NC3Rs is the refinement of laboratory procedures to minimise animal pain, suffering, and lasting harm, and to improve laboratory animal welfare. To achieve this, it is essential that we use scientifically validated measures to quantify how experimental, housing, and husbandry procedures affect welfare, and whether refinements do indeed lead to improvements. NC3Rs have therefore called for research to develop new and better welfare measures. Our project will provide such a measure to better assess the welfare of rats and mice (81% of laboratory animals used in the UK in 2010).The assumption that non-human animals can subjectively experience negative emotional (affective) states and hence suffer underpins concerns for animal welfare. Affective state is thus a key determinant of an animal's welfare. However, because subjective experiences are essentially private, and cannot be measured directly, we need to identify indicators that indirectly reflect an animal's affective state. For example, we can measure physiological changes, such as hormone levels, or behavioural indicators, such as an animal's behaviour in an unprotected open space. However, whilst valuable, such indicators have important limitations which a more recent approach that we have developed seeks to address. Human psychological studies show that, when feeling happier, people are more likely to judge an ambiguous event as having a positive outcome than when they are feeling down; their proverbial glass is half-full. If the same is true of other animals, then by measuring the judgements they make in ambiguous situations, we may gain useful information about how they are feeling too. To explore this possibility, we have developed a novel, non-verbal test of 'judgement bias' underpinned by theoretical models of decision-making. The test allows us to systematically investigate whether animals judge an ambiguous stimulus positively ('optimistic') or negatively ('pessimistic'). Recent studies of rats, sheep, dogs, monkeys, and starlings support the hypothesis that animals in a more positive affective state do indeed show a more 'optimistic' response to ambiguous stimuli, indicating that this technique may be a very good way of assessing emotional state in animals.However, existing judgement bias tests are relatively time-consuming, involving hands-on training of animals, and no methods have been developed for mice, the most widely used laboratory species. Therefore, we will develop an automated version of our judgement bias test that can be used for laboratory rodents, including mice. We will then validate this new test by employing a range of carefully-selected pharmacological and environmental treatments, each designed to induce a particular, transient change in affective state. By examining how treatments affect the size of the responses shown, we will be able to see whether the method can quantify the intensity of an emotional state. We will also compare enriched and standard housing conditions, and other determinants of long-term emotional state, to see whether the test can detect the cumulative effects of long-term experience on affect. 'Cumulative suffering' is hard to measure, yet vitally important for an animal's lifetime welfare, and we anticipate that our approach can provide a good indication of this state. An industrial partner has expressed interest in further implementing the test that we develop for widespread use, for example by incorporating it into a home-cage testing system.The study will also produce computational models of how affective states change in response to external events. These may provide the basis for modelling the effects of experimental treatments on an animal's affective state, hence facilitating better and more humane planning of studies. We hope that this project will lay the foundations for further development of such models.