Stochastic integrator models of collective decision-making

描述（由申请人提供）： 大多数社会行为都是在互动中发生的，但人们对调节社会群体行为的集体过程知之甚少。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使社会群体对不断变化的环境条件作出反应的动态过程。我们的长期目标是使用红色收获蚁，Pogonomyrmex cumulatus，作为一个模型，研究导致社会群体弹性的行为的集体调节。我们的项目汇集了一个独特的25年的行为和生态学的收获蚁群的自然种群的研究，在神经科学的理论进展。我们利用蚂蚁决定是否觅食所产生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所依据的信号积累之间的强烈对应关系。蚁群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。先前的研究表明，外出觅食的蚂蚁离开巢穴的概率，以及殖民地觅食活动的总体水平，取决于它们与返回的成功觅食蚂蚁的相互作用率。觅食者返回的速度取决于搜寻时间，因此也取决于食物的可获得性。目的1研究什么机制允许个体蚂蚁根据与其他蚂蚁的社会接触做出觅食决策。我们将开发一个漏积分器模型，非常类似于神经科学的随机累加器模型，用于研究个体蚂蚁如何积累信号以支持觅食决策。将使用先前工作中成功应用的方法在田间菌落中测试模型预测并评估模型参数。目的2旨在解释蚁群觅食活动的总体速率和蚂蚁在蚁巢内觅食池之间的运输。使用现场的殖民地，我们将测试模型的扩展版本，包括蚂蚁从储备到外出觅食的运输，使用由突触中神经递质囊泡的类似运输启发的理论目标3研究觅食行为的可塑性，使用目标1和2中开发的模型来测试殖民地是否可以调整参数以响应环境条件，以及评估集体决策如何决定殖民地的恢复力。这项研究的发现将有助于国家卫生研究院的使命，为集体提供基本的见解。 对环境线索和社会互动做出反应的社会行为的调节。

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.