Peptide Modulation of Physiology and Behavior
生理和行为的肽调节
基本信息
- 批准号:9357612
- 负责人:
- 金额:$ 39.46万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2011
- 资助国家:美国
- 起止时间:2011-09-15 至 2020-06-30
- 项目状态:已结题
- 来源:
- 关键词:Afferent NeuronsAmerican Society of HematologyAminationAminesAnimalsBehaviorBehavioralBiological ModelsCaenorhabditis elegansCellsClinicalComplexComputer SimulationDangerousnessDecision MakingDesiccationDiseaseDrug AddictionEatingEconomicsEnvironmentEquilibriumFoodFood deprivation (experimental)G-Protein-Coupled ReceptorsGene CombinationsGeneticGoalsHealthHumanHungerImageInterneuronsLeadLocomotionMammalsMediatingModelingMolecularMotorNematodaNervous system structureNeuronsNeuropeptidesOdorsPathologicPathway interactionsPeptidesPhysical ExercisePhysiologicalPhysiologyPigmentsResolutionRewardsRoleSensorySignal PathwaySignal TransductionSourceSynapsesTestingTimeTyramineautocrinebaseexperimental studyin vivoincreased appetiteknockout genemultisensoryneurogeneticsneuromechanismoptogeneticspredictive modelingrelating to nervous systemsensory input
项目摘要
To navigate complex natural environments containing both dangerous and valuable items, animals must
make economic decisions on the basis of information transduced by multiple senses. Such decisions underlie
key health-related behaviors, such as eating and locomotion. Even pathological behaviors, like drug addiction,
are based on economic decisions, albeit maladaptive ones. It is thus essential for both basic and translational
purposes to better understand the neural substrates that underlie the balancing of threat and reward. However,
mammalian nervous systems are extremely complex, and this has hindered progress in uncovering
fundamental neural principles of decision making. In contrast, the experimentally accessible nervous system of
the nematode worm C. elegans contains only a few hundred identified neurons of defined synaptic connectivity
and implements a variety of robust adaptive sensory-guided behaviors. Here we propose to use genetic,
physiological, and behavioral approaches in C. elegans to pursue the long-term goal of elucidating the cellular
and molecular mechanisms underlying economic decision making. Our preliminary studies lead to a model in
which a higher-order sensorimotor interneuron controls the balance of threat and reward in a multisensory
decision task by top-down aminergic signaling to the primary sensory neuron that detects danger to tune its
sensitivity, and this aminergic signal is itself modulated by an autocrine neuropeptidergic signal acting on the
higher-order interneuron. The proposed studies deploy a combination of neurogenetic, behavioral, and
physiological approaches to test the detailed predictions of this model and to elucidate how internal
physiological state influences economic decision making by regulating the top-down peptide-amine relay
circuit.
为了在包含危险物品和贵重物品的复杂自然环境中航行,动物必须
根据多种感官转换的信息做出经济决策。这些决定的基础
与健康相关的关键行为,例如饮食和运动。甚至病态行为,如吸毒成瘾,
都是基于经济决策,尽管这些决策是不适应的。因此,无论是基础知识还是翻译知识,都至关重要。
目的是更好地理解威胁与奖励平衡背后的神经基础。然而,
哺乳动物的神经系统极其复杂,这阻碍了揭示这一过程的进展
决策的基本神经原理。相比之下,实验上可访问的神经系统
线虫秀丽隐杆线虫仅包含数百个具有明确突触连接的已识别神经元
并实现各种鲁棒的自适应感官引导行为。在这里我们建议使用遗传,
线虫的生理和行为方法,以追求阐明细胞的长期目标
和经济决策背后的分子机制。我们的初步研究得出了一个模型
高阶感觉运动中间神经元控制多感觉中威胁和奖励的平衡
通过自上而下的胺能信号向初级感觉神经元发出决策任务,初级感觉神经元检测到危险并调整其神经元
敏感性,并且这种胺能信号本身是由作用于
高阶中间神经元。拟议的研究结合了神经遗传学、行为学和
生理学方法来测试该模型的详细预测并阐明内部如何
生理状态通过调节自上而下的肽-胺中继影响经济决策
电路。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Michael Nitabach其他文献
Michael Nitabach的其他文献
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{{ truncateString('Michael Nitabach', 18)}}的其他基金
Biological Mechanisms of Food-Related Decision Making
食品相关决策的生物学机制
- 批准号:
10707023 - 财政年份:2022
- 资助金额:
$ 39.46万 - 项目类别:
Biological Mechanisms of Food-Related Decision Making
食品相关决策的生物学机制
- 批准号:
10405938 - 财政年份:2022
- 资助金额:
$ 39.46万 - 项目类别:
Synaptic Microcircuits Underlying Associative Learning
关联学习背后的突触微电路
- 批准号:
10642762 - 财政年份:2014
- 资助金额:
$ 39.46万 - 项目类别:
Synaptic Microcircuits Underlying Associative Learning
关联学习背后的突触微电路
- 批准号:
10427181 - 财政年份:2014
- 资助金额:
$ 39.46万 - 项目类别:
Synaptic Microcircuits Underlying Associative Learning
关联学习背后的突触微电路
- 批准号:
10187661 - 财政年份:2014
- 资助金额:
$ 39.46万 - 项目类别: