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Neural computations underlying value learning in the ventral tegmental area and orbitofrontal cortex of rhesus macaques.

机译：恒河猴猕猴腹侧被盖区和眶额皮质的价值学习基础的神经计算。

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摘要

The study of how the brain computes value is essential to understanding the decision making process that organisms engage in throughout their life span. In the 90's, Schultz and colleagues (1997) proposed a pivotal theory describing how dopamine neurons encode a reward prediction error (RPE). The RPE theory elegantly characterized the learning process involved in associating a stimulus or action and reward (Bush and Mosteller 1951; Sutton and Barto 1998; Rescorla and Wagner 1972). The discovery of RPE and its role in reinforcement learning launched a division of decision-making research that has focused on dopamine neurons and its efferents. The following research takes cues from the field and investigates the neural computation of dopamine neurons in value learning and explores the value signals arising from a dopamine neuron efferent, the orbitofrontal cortex.;The primary data supporting the idea that dopaminergic activity encodes an RPE signal has been correlative, showing that dopaminergic firing rates match quantitative predictions of reinforcement learning (RL) models (Schultz et al, 1997; Bayer and Glimcher, 2005; Nakahara et al. 2004). We provide causal evidence for the RPE theory by electrically activating dopamine neurons directly following reward. In our task we observed learning in real time and found that the subject allocated a continuously increasing fraction of its choices to the stimulation-associated action and that this effect was dependent on D2 receptor activation.;The monkey orbitofrontal cortex has been the subject of scrutiny during the last decade by scholars interested in its role in decision-making. Studies have given rise to the notion that neurons in the OFC encode the properties of rewards in their firing rates but that these firing rates are independent of the actions required to obtain those rewards (Padoa-Schioppa & Cai, 2011). We set out to specifically test the hypothesis that OFC value-related neurons in area 13m do not carry information about the action required to obtain that reward. Our detailed analysis of the response fields indicates that these neurons are insensitive to the amplitude or direction of the saccade required to obtain these rewards.
机译：对大脑如何计算价值的研究对于理解生物在整个生命周期中参与的决策过程至关重要。在90年代，Schultz及其同事（1997年）提出了一种关键理论，描述了多巴胺神经元如何编码奖励预测误差（RPE）。 RPE理论优雅地描述了与刺激或行动和奖励相关的学习过程（Bush和Mosteller 1951； Sutton和Barto 1998； Rescorla和Wagner 1972）。 RPE的发现及其在强化学习中的作用启动了决策研究的一个部门，该研究侧重于多巴胺神经元及其传出。以下研究从领域中汲取了线索，并研究了价值学习中多巴胺神经元的神经计算，并探索了由多巴胺神经元传出的眶额皮层产生的价值信号;支持多巴胺能活动编码RPE信号这一思想的主要数据有两者之间具有相关性，表明多巴胺能射击率与强化学习（RL）模型的定量预测相符（Schultz等，1997； Bayer和Glimcher，2005； Nakahara等，2004）。我们通过直接激活奖励后的电激活多巴胺神经元来为RPE理论提供因果证据。在我们的任务中，我们观察到了实时学习，发现该对象将其选择中不断增加的部分分配给了与刺激相关的动作，并且这种作用取决于D2受体的激活。在过去的十年中，学者对它在决策中的作用感兴趣。研究提出了这样一种观念，即OFC中的神经元在激励率中编码奖励的属性，但这些激励率与获得这些奖励所需的动作无关（Padoa-Schioppa＆Cai，2011）。我们着手专门测试以下假设：13m区域中与OFC值相关的神经元不携带有关获得该奖励所需的动作的信息。我们对响应场的详细分析表明，这些神经元对获得这些奖励所需的扫视幅度或方向不敏感。

著录项

  • 作者

    Grattan, Lauren Elizabeth.;

  • 作者单位

    New York University.;

  • 授予单位 New York University.;
  • 学科 Biology Neuroscience.
  • 学位 Ph.D.
  • 年度 2014
  • 页码 153 p.
  • 总页数 153
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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