Computational Models of Olfactory and Spatial Cognition

该奖项为亚利桑那大学的一群神经科学家提供资金，用于购买计算机、网络硬件和相关软件。该设备将用于分析低等和高等动物的嗅觉和空间定向的对比研究得出的实验数据。通过与数学家的合作，这些研究人员计划为神经细胞相互作用建立模型，这些模型似乎是这些过程的基础。模型将基于神经系统的解剖和电生理特性。其他模型将具有明确的行为基础。这些模型将使用名为Genesis的神经网络模拟程序和计算机进行开发。种间比较传统上为理解生物过程的潜在机制提供了有用的工具。越来越多地，使用实验数据和理论方案来合成做出详细预测的模型，在现代生物学中发挥了同样重要的作用。嗅觉和空间定向都是神经生物学家一段时间以来感兴趣的神经整合问题。使用计算模型，特别是神经网络模型，来获得潜在的整合机制，是解决这些经典问题的一种有前途的方法。

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.