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Neural Mechanisms of Nutritional Homeostasis

Neural Mechanisms of Nutritional Homeostasis
营养稳态的神经机制
批准号:
9808400
负责人:
Rhanor Gillette
金额:
$27.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
1998
资助国家:
美国
项目状态:
已结题
起止时间:
1998-08-01 至 2001-07-31

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中文摘要
翻译
动机过程,特别是饥饿,是行为决策的驱动影响;然而,目前尚不清楚神经网络如何调节进食或其他动机行为是由饥饿的生理介质组织的。一种重要的神经化学物质是生物胺5-羟色胺(5-HT),它调节脊椎动物和无脊椎动物的情绪和觉醒。在一个简单的模型系统中,5-HT刺激进食准备作用于进食运动网络,以增强神经元兴奋性的特定方面。有证据表明,5-羟色胺刺激一氧化氮(NO)的产生,一氧化氮是许多动物神经活动的关键调节剂。本提案概述了阐明5-羟色胺在调节NO生成酶的作用和机制,从而调节饥饿/饱腹状态的计划。这些研究将行为和电测量与单细胞中5-羟色胺和no相关化合物的分析结合起来。这些研究接近了调节所有运动动物营养稳态的反馈回路的基本组织,并可以更全面地了解饥饿/饱食的机制。它们与厌食症和肥胖症中体重控制的健康问题直接相关。了解这些因素可能对能够在嘈杂环境中做出最小可能错误决策的自主机器人的发展以及人工智能的发展具有重要意义,人工智能的优化功能基于动机的过程可以提供目标相关活动的关键调节,就像它们在真实的智能系统中所做的那样。
英文摘要
LAY ABSTRACT IBN-9808400 Neural Mechanisms of Nutritional Homeostasis Motivational processes, in particular hunger, are driving influences in behavioral decision-making; however, it is not known how neural networks mediating feeding or other motivated behaviors are organized by the physiological mediators of hunger. One critically involved neurochemical is the biogenic amine serotonin (5-HT), which modulates affect and arousal in vertebrates and invertebrates alike. In a simple and accessible model system, 5-HT stimulates readiness to feed acting in the feeding motor network to enhance specific aspects of neuron excitability. Evidence suggests that 5-HT stimulates production of nitric oxide (NO), a critical modulator of neural activity in many animals. This proposal outlines plans to elucidate the role and mechanisms of action of 5-HT in regulating the enzyme that makes NO, and thereby hunger/satiation state. These studies combine behavioral and electrical measures with analysis of 5-HT and NO-related chemical compounds in single cells. These studies approach the basic organization of the feedback loops regulating nutritional homeostasis in all motile animals and can lead to a fuller understanding of mechanisms of hunger/satiation. They relate directly to health issues of weight-control in anorexia and obesity. Knowledge of these factors is likely to be significant to the development of autonomous robots capable of making least- probable-error decisions in a noisy environment, and to the evolution of artificial intelligence for whose optimal function motivation-based processes can provide the critical regulation of goal related activity, just as they do in real intelligence systems.
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