COMPUTATIONAL MODELS OF ADAPTIVE NEURAL CIRCUITS

自适应神经电路的计算模型

• 批准号: 2850674
• 负责人: Douglas Alan Baxter
• 金额: $ 20.37万
• 依托单位: UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
• 依托单位国家: 美国
• 财政年份: 1995
• 资助国家: 美国
• 起止时间: 1995-08-17 至 2002-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2850674
• 关键词: Aplysia; association learning; computational neuroscience; ethology; membrane potentials; neural information processing; neural plasticity; neuroanatomy; nutrient intake activity; nutrition related tag; synapses

The overall objective of this research is to use computational models to analyze molecular, cellular and network processes underlying behavior and behavioral plasticity. Models will be based on empirical data from the neural circuitry that mediates feeding behavior of the marine mollusk Aplysia. This behavior is a useful model system for investigating the generation of complex rhythmic movements as well as the neural basis of motivational states and associative learning. Although many elements of the feeding circuitry have been identified an analysis of the mechanisms underlying is overall function has not yet been undertaken. The present proposal outlines studies that will investigate the extent to which the current understanding of the circuitry is sufficient to account for the features of the behavior, examine the contributions of component processes to neuronal and network dynamics, and examine how modulatory inputs and learning-induced changes in cellular properties alter the function of the circuit. In addition, this project will continue the development and distribution of the SNNAP program (Simulator for Neural networks and Action Potentials,) thereby providing a valuable research and educational tool to the scientific and academic community.

这项研究的总体目的是使用计算模型 分析分子，细胞和网络过程 行为和行为可塑性。 模型将基于 来自介导喂养的神经回路的经验数据 海洋软体动物的行为。 这种行为是有用的 用于研究复杂节奏的产生的模型系统 动机状态的运动以及神经基础 协会学习。 虽然喂养的许多元素 电路已被鉴定出对机制的分析 基础是总体功能尚未实现。 这 目前的提案概述了研究的研究程度 当前对电路的理解足以 说明行为的特征，检查贡献 组件过程到神经元和网络动态，并检查 调节输入和学习引起的细胞变化如何 属性会改变电路的功能。 此外，这 项目将继续开发和分发SNNAP 程序（神经网络和动作电位的模拟器） 从而为 科学和学术界。