Stochastic integrator models of collective decision-making

描述(由申请人提供)： 大多数社会行为发生在对互动的反应中，然而规范社会群体行为的集体过程却鲜为人知。要阐明相互作用在调节社会行为中的作用，需要一个简单的模型系统来研究允许社会群体对不断变化的环境条件做出反应的动态过程。我们的长期目标是使用红色收割机蚂蚁，Pogonomyrmex barbatus，作为研究导致社会群体弹性的集体行为规范的模型。我们的项目结合了一项独特的25年来对收割机蚁群自然种群的行为和生态的研究，以及神经科学方面的理论进步。我们利用蚂蚁决定是否觅食的化学信号的积累与神经科学中突触、神经元和行为水平上决策的信号积累之间的强烈对应。蚂蚁群体在没有中央控制的情况下运作，使用简单的相互作用网络来调节觅食活动，并适应当前的生态条件。以前的工作表明，外出觅食者离开巢的概率，以及群体觅食活动的总体水平，取决于它们与返回的成功觅食者的互动率。觅食者的回报率取决于搜索时间，因此也取决于食物的供应情况。目标1调查了哪些机制允许单个蚂蚁根据与其他蚂蚁的社会接触做出觅食决定。我们将开发一个泄漏积分器模型，该模型与神经科学的随机累加器模型非常相似，用于研究单个蚂蚁如何积累信号以支持觅食决定。将使用以前工作中成功应用的方法在实地群体中对模型预测进行测试，并对模型参数进行评估。目标2试图解释蚁群觅食活动的总体比率和蚂蚁在巢内觅食池之间的贩运。利用野外的蚁群，我们将测试包括蚂蚁从储备蚂蚁到外出觅食者的运输的扩展版本的模型，使用受突触中神经递质小泡类似运输的启发的理论Aim 3调查觅食行为的可塑性，使用在Aim 1和2中开发的模型来测试蜂群是否可以根据环境条件调整参数，并评估集体决策如何决定蜂群的弹性。这项研究的发现将有助于NIH的使命，因为它提供了对集体的基本洞察 对社会行为的调节，以响应环境提示和社会互动。

DESCRIPTION (provided by applicant): Most social behavior occurs in response to interaction, yet the collective processes that regulate the behavior of social groups are poorly understood. Elucidating the role of interactions in regulating social behavior requires a simple model system in which to study the dynamical processes that allow social groups to respond to changing environmental conditions. Our long-term goal is to use the red harvester ant, Pogonomyrmex barbatus, as a model for investigating the collective regulation of behavior that leads to the resilience of social groups. Our project brings together a unique 25-year study of the behavior and ecology of a natural population of harvester ant colonies, with theoretical advances in neuroscience. We draw on the strong correspondences between the accumulation of chemical signals made by ants deciding whether to forage and the accumulation of signals that underlie decision-making at the synaptic, neuronal, and behavioral levels in neuroscience. Ant colonies operate without central control, using networks of simple interactions to regulate foraging activity and adjust to current ecological conditions. Previous work shows that the probability that outgoing foragers leave the nest, and thus the colony's overall level of foraging activity, depends on their rate of interactio with returning successful foragers. The rate of forager return depends on search time and thus on food availability. Aim 1 investigates what mechanisms allow individual ants to make foraging decisions based on social contact with other ants. We will develop a leaky integrator model, closely analogous to the stochastic accumulator models of neuroscience, for how individual ants accumulate signals in support of the decision to forage. The model predictions will be tested, and model parameters evaluated, in colonies in the field using methods applied successfully in previous work. Aim 2 seeks to explain the overall rate of colony foraging activity and trafficking of ants between forager pools inside the nest. Using colonies in the field, we will test an expanded version of the model that includes the trafficking of ants from reserve to outgoing foragers, using theory inspired by the similar trafficking of neurotransmitter vesicles in synapses Aim 3 investigates the plasticity of foraging behavior, using the models developed in Aims 1 and 2 to test whether colonies can adjust parameters in response to environmental conditions, and evaluating how collective decisions determine the resilience of the colony. Findings from this research will contribute to the mission of NIH by providing fundamental insight into the collective regulation of social behavior in response to environmental cues and social interactions.