Learning the microstructure of successful behavior.

Learning the microstructure of successful behavior.
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DOI:
10.1038/nn.2748
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发表时间:
2011-03
影响因子:
25
通讯作者:
Brainard, Michael S.
Brainard, Michael S.
中科院分区:
医学1区
文献类型:
--
作者:
Charlesworth, Jonathan D.;Tumer, Evren C.;Warren, Timothy L.;Brainard, Michael S.

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已知表明成功或失败的强化信号会改变在不同行为之间进行选择的概率。然而,许多运动技能的成功表现,如说话清晰,也需要学习随时间不断变化的行为轨迹。在这里,我们研究了时间离散的强化信号如何塑造连续的行为轨迹,即成年孟加拉雀鸣叫的基本频率。我们只在歌曲的某一点上根据基频的表现提供了强化。学习到的基频变化在这一点上是最大的,但在基频轨迹的早期和后期也会扩展。一个简单的原理预测了学习的详细结构;鸟类学会了产生与成功结果相关的行为轨迹的平均值。这条学习规则准确地预测了毫秒级的学习结构,表明神经系统记录了成功行为的细粒度细节,并利用这些信息来指导学习。
Reinforcement signals indicating success or failure are known to alter the probability of selecting between distinct actions. However, successful performance of many motor skills, such as speech articulation, also requires learning behavioral trajectories that vary continuously over time. Here, we investigated how temporally discrete reinforcement signals shape a continuous behavioral trajectory, the fundamental frequency of adult Bengalese finch song. We provided reinforcement contingent on fundamental frequency performance only at one point in song. Learned changes to fundamental frequency were maximal at this point, but also extended both earlier and later in the fundamental frequency trajectory. A simple principle predicted the detailed structure of learning; birds learn to produce the average of the behavioral trajectories associated with successful outcomes. This learning rule accurately predicts the structure of learning at a millisecond time scale, demonstrating that the nervous system records fine-grained details of successful behavior and uses this information to guide learning.
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