Collaborative Research: Computational Models for Neuroendocrine Control of Social Behavior

这个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。神经肽调节所有脊椎动物类中具有代表性的物种的社会行为。然而，物种行为上的差异使得建立清晰的机制模型变得困难。本项目采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。现场和实验室研究将结合起来，以解决重要的新兴问题神经肽调节雄性脊椎动物的行为。基于代理的建模方法特别适合解决这个问题。该模型的综合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，该项目实现了一个严格控制的实验-模型-实验循环，并为系统生物学方法开发了一个新的范式，以理解社会行为。神经肽改变多种脊椎动物的社会行为，包括亲代行为、攻击行为和繁殖行为。保守行为和化学信使将使经验结果和模型广泛适用于脊椎动物。研究结果将有助于我们进一步了解神经肽对脊椎动物行为可塑性的影响。该项目还包括一个重要的培训组成部分，涉及本科生野外生物学课程（30%少数民族组成）和在独特的跨学科环境中培训研究生。数据管理计划包括在SourceForge上存放新软件，并在PI的机构数据库中存档数字数据。

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.