灵长类杏仁体神经元对多个奖励属性的动态编码和顺序集成
Fabian Grabenhorst1, Raymundo Báez-Mendoza2
1Department of Experimental Psychology, University of Oxford, Oxford, UK. fabian.grabenhorst@psy.ox.ac.uk.
杏仁体在神经元中整合了奖励概率和大小信号,创建了灵活的价值代码. 这些神经元还通过计算预期的奖励差异来量化风险,这与价值不同.
科学领域:
- 神经科学是一个神经科学.
- 决策神经科学 决策神经科学
- 计算神经科学是一种神经科学.
背景情况:
- 视觉刺激指导重要的认知功能,如学习,决策和动机.
- 刺激值通常由多个属性决定,但神经集成机制尚不清楚.
- 杏仁体在处理来自复杂线索的价值和风险方面的作用需要进一步阐明.
研究的目的:
- 研究杏仁体神经元如何从顺序线索中提取和整合不同的价值组件 (概率和大小).
- 确定杏仁体神经元是否编码奖励概率和价值的抽象表示.
- 探索杏仁体内的风险计算的神经基础.
主要方法:
- 在两只雄性子中记录了杏仁体神经元的单单元活动.
- 子看到连续的视觉线索,指定奖励概率和大小.
- 分析神经元对编码概率,大小,值和风险 (变异) 的反应.
主要成果:
- 杏仁体神经元表现出抽象的,刺激独立的奖励概率编码.
- 许多神经元显示双相反应,将概率和大小集成到动态值代码中.
- 特定的神经元通过量化预期的奖励差异来编码风险,与价值信号分开.
结论:
- 杏仁体神经元对于将多个奖励属性连续集成到价值表示中至关重要.
- 杏仁体动态集成概率和大小,形成灵活的价值代码.
- 独特的杏仁体神经元群体编码价值和风险,有助于复杂的决策.
更多相关视频
09:49Combined Optogenetic and Freeze-fracture Replica Immunolabeling to Examine Input-specific Arrangement of Glutamate Receptors in the Mouse Amygdala
Published on: April 15, 2016
09:36Combined In Vivo Anatomical and Functional Tracing of Ventral Tegmental Area Glutamate Terminals in the Hippocampus
Published on: September 9, 2020
相关概念视频
Functional Brain Systems: Limbic System
Neural Circuits
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
Role of Amygdala in Memory
One of the...
The Role of Ion Channels in Neuronal Computation
Sometimes a single EPSP is strong enough to induce an action potential in the postsynaptic neuron. However, multiple presynaptic inputs must often create EPSPs around the same time for the postsynaptic neuron to be sufficiently depolarized to fire an action potential....
Timing and Consequences on Behavior
Humans, however, can respond to delayed reinforcers. We often make decisions between immediate small rewards and delayed larger rewards. This ability to delay gratification is a significant...
Diencephalon: Thalamus and Information Relay
