The computational basis of foraging

觅食的计算基础

• 批准号: BB/X013111/1
• 负责人: Mark Humphries
• 金额: $ 25.79万
• 依托单位: University of Nottingham
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FX013111%2F1
• 关键词: computational; basis; foraging

You are at a party talking to a work colleague, who is nice but perhaps a little boring. There are other people you could be talking to, but how do you decide when to leave that conversation and move around the room to find someone else? Although a benign everyday example, the decision of whether to stay engaged in a current location or travel to find rewards elsewhere is a fundamental problem that all foraging animals, including humans, have to solve to collect food, drink, materials, and other resources, and seek mates, nesting grounds, places to sleep, and other essentials in their environment. Computational cognitive neuroscience has made great strides in helping us understand how choices are made between two or more fixed options, and the biological mechanisms underlying those choices. However, far less is known about foraging decisions: whether to stay or leave. There is mounting evidence that foraging choices differ across species, change across the lifespan, and that people with poor mental health differ in when they choose to stay or leave. However, we do not yet understand the computations in the brain that underlie these stay-or-leave choices, and this is holding back neuroscience research aimed at understanding the biology of these choices and why they differ between people. Our aim is to make a major advance in understanding the algorithms governing these choices, to unlock the potential for understanding how foraging choices are made in the brain.We will provide a new understanding of the computations underlying foraging decisions and provide tools that will let researchers infer these computations from the behavioural data they collect from any species. To do this, we will develop new brain-inspired algorithms for learning and making stay-or-leave decisions. These will draw on a wide range of AI algorithms that have successfully given insight into the processes in the brain in other decision-making problems. We will test if these new algorithms can replicate the well-established behaviours of foragers, like foraging for longer in a location with lots of reward. Then we will examine which of these models can best explain the detailed trial-by-trial decisions observed in existing datasets of foraging tasks tackled by humans, non-human primates, and rodents.By doing so, we can test whether different brain computations are used in different types of foraging tasks or in different species. Further, we can test hypotheses for why foragers often make apparently non-optimal choices, such as a tendency to stay too long in locations that have become depleted of reward.To maximise the impact of our work, we will form a foraging interest group, who will meet at strategic points of the grant to offer input and for us to share the knowledge we have gained. Several researchers across different career stages, fields (ecology, psychology, psychiatry and neuroscience), and model species (rodents, primates, and insects), as well as an industrial partner (Opteran Limited) have agreed to take part. Alongside this, the code base for all models will be made freely available, with instructions of how to use them on different types of foraging task. This grant will make major scientific advances in helping us understand why animals and humans make stay-leave decisions in the way that they do. Moreover, it will offer a range of tools and theoretical platform that can be used by ecologists, psychologists, neuroscientists and psychiatric researchers to understand how the brain makes decisions across species, both in health and disease.

你在一个聚会上和一个同事聊天，他很好，但可能有点无聊。你可以和其他人交谈，但你如何决定何时离开谈话，在房间里四处走动，去找其他人呢？虽然这是一个良性的日常例子，但决定是留在当前位置还是前往其他地方寻找奖励是所有觅食动物（包括人类）必须解决的基本问题，以收集食物，饮料，材料和其他资源，并在环境中寻找配偶，筑巢地，睡觉的地方和其他必需品。计算认知神经科学在帮助我们理解如何在两个或多个固定选项之间做出选择以及这些选择背后的生物机制方面取得了长足的进步。然而，关于觅食决定的了解要少得多：是留下还是离开。越来越多的证据表明，觅食的选择在不同物种之间存在差异，在整个生命周期中都会发生变化，心理健康状况不佳的人在选择留下或离开时也会有所不同。然而，我们还不了解这些留下或离开选择背后的大脑计算，这阻碍了旨在了解这些选择的生物学以及为什么它们在人与人之间存在差异的神经科学研究。我们的目标是在理解支配这些选择的算法方面取得重大进展，以释放理解觅食选择是如何在大脑中做出的潜力。我们将提供对觅食决策背后的计算的新理解，并提供工具，让研究人员从他们从任何物种收集的行为数据中推断这些计算。为此，我们将开发新的大脑启发算法，用于学习和做出留下或离开的决定。这些将利用广泛的人工智能算法，这些算法已经成功地洞察了大脑在其他决策问题中的过程。我们将测试这些新算法是否可以复制觅食者的成熟行为，比如在奖励丰厚的地方觅食更长时间。然后，我们将研究哪些模型能够最好地解释在人类、非人类灵长类动物和啮齿动物的觅食任务的现有数据集中观察到的详细的逐个试验的决定，通过这样做，我们可以测试不同的大脑计算是否用于不同类型的觅食任务或不同的物种。此外，我们还可以测试为什么觅食者经常做出明显非最佳选择的假设，例如在奖励已经耗尽的地方停留太长时间的倾向。为了最大限度地发挥我们工作的影响，我们将组建一个觅食兴趣小组，他们将在赠款的战略点会面，提供投入，并让我们分享我们获得的知识。来自不同职业阶段、不同领域（生态学、心理学、精神病学和神经科学）和模型物种（啮齿动物、灵长类动物和昆虫）的几位研究人员以及一家工业合作伙伴（Opteran Limited）已同意参加。除此之外，所有模型的代码库都将免费提供，并说明如何在不同类型的觅食任务中使用它们。这笔赠款将使重大的科学进步，帮助我们了解为什么动物和人类作出留离开决定的方式，他们这样做。此外，它将提供一系列工具和理论平台，可供生态学家，心理学家，神经科学家和精神病学研究人员使用，以了解大脑如何在健康和疾病方面做出跨物种的决策。