Collaborative Research: Computational Models for Neuroendocrine Control of Social Behavior

该研究项目的长期目标是确定控制行为的化学信使之间的相互作用。神经肽调节来自所有脊椎动物纲的代表性物种的社会行为。然而，物种行为的差异使得开发明确的机制模型变得困难。这个项目使用动物实验和计算模型相结合的方法来研究行为机制的复杂性。现场研究和实验室研究将结合起来，解决神经肽对雄性脊椎动物行为的调节方面出现的重要问题。基于主体的建模方法特别适合于解决这一问题。使用该模型的合成实验允许探索在经验测试中不切实际或不可能的条件。该模型有望提出神经肽控制行为的新机制。因此，这个项目实现了一个严格控制的实验-模型-实验循环，并为理解社会行为的系统生物学方法开发了一种新的范式。神经肽改变脊椎动物的各种社会行为，包括亲代行为、攻击性行为和生殖行为。保守的行为和化学信使将使实验结果和模型广泛适用于脊椎动物。这些结果将极大地促进我们对神经肽对脊椎动物行为可塑性的影响的理解。该项目还包括一个重要的培训部分，包括一个本科生实地生物学班(少数民族占30%)，以及在独特的跨学科环境中对研究生进行培训。数据管理计划包括在SourceForge存放新软件和将数字数据存档到PI的机构数据库。

The long-term objective of this research project is to identify the interactions among chemical messengers that control behaviors. Neuropeptides regulate social behaviors in representative species from all vertebrate classes. Species differences in behavior, however, have made development of clear mechanistic models difficult. This project investigates the complexity of behavioral mechanisms using a combination of animal experiments and computational models. Field and laboratory studies will be combined to address important emerging questions on neuropeptide modulation of male vertebrate behaviors. The agent-based modeling approach is especially well-suited to address this problem. Synthetic experiments with the model allow for exploration of conditions impractical or impossible in empirical tests. The model is expected to propose novel mechanisms underlying neuropeptide control of behavior. This project thus implements a tightly controlled experiment-model-experiment loop and develops a new paradigm for a systems biology approach towards understanding social behavior. Neuropeptides alter a variety of vertebrate social behaviors, including parental, aggressive, and reproductive behaviors. Conserved behaviors and chemical messengers will make the empirical results and the model broadly applicable to vertebrates. Results will significantly advance our understanding of the effect of neuropeptides on vertebrate behavioral plasticity. This project also includes a significant training component, with involvement of an undergraduate field biology class (with a 30% minority makeup) and training of graduate students in a unique inter-disciplinary environment. The data management plan includes deposition of new software at SourceForge and archiving of digital data in the PI's institutional databases.