Computational Models of Olfactory and Spatial Cognition

该奖项为一组神经科学家提供资金， 亚利桑那大学买了一台电脑 网络硬件和相关软件。 本设备 将用于分析实验数据， 嗅觉与空间定向的比较研究 高等动物。 通过与数学家的合作， 这些研究人员计划生成神经细胞模型 对这些过程至关重要的相互作用。 模型 将基于解剖和电生理特性 的神经系统。其他模型将有一个明确的 行为基础。 这些模型将使用神经网络模拟开发 一个叫做Genesis的程序和计算机。 种间比较传统上提供了一个 这是一个有用的工具，有助于了解 生物过程。 越来越多地使用实验数据 和理论方案的综合模型，使 详细的预测也发挥了同样重要的作用， 现代生物学 嗅觉和空间定位都是 神经整合的问题， 神经生物学家一段时间。 使用计算模型， 特别是神经网络模型， 整合机制是一个有前途的方法，这些经典的 问题

This award provides funds to a group of neuroscientists at the University of Arizona for the purchase of a computer, networking hardware, and associated software. This equipment will be used to analyze experimental data resulting from comparative studies of olfaction and spatial orientation in lower and higher animals. Though collaborations with mathematicians, these investigators plan to generate models for nerve cell interactions that appear fundamental to these processes. Models will be based on anatomical and electrophysiological properties of the nervous system. Other models will have an explicitly behavioral basis. The models will developed using a neural network simulation program called GENESIS and the computer. Interspecific comparisons have traditionally provided a useful tool in understanding the underlying mechanisms of biological processes. Increasingly, the use of experimental data and theoretical schemes for the synthesis of models that make detailed predictions has played an equally important role in modern biology. Olfaction and spatial orientation are both problems of nervous integration that have interested neurobiologists for some time. The use of computational models, in particular neural network models, to get at the underlying integrative mechanisms is a promising approach to these classical problems.