Department of Neuroscience, Columbia University, New York, USA.
Mortimer B. Zuckerman Mind Brain and Behavior Institute, Columbia University, New York, USA.
Sci Rep. 2023 Jan 20;13(1):1126. doi: 10.1038/s41598-023-27662-9.
In the real world, making sequences of decisions to achieve goals often depends upon the ability to learn aspects of the environment that are not directly perceptible. Learning these so-called latent features requires seeking information about them. Prior efforts to study latent feature learning often used single decisions, used few features, and failed to distinguish between reward-seeking and information-seeking. To overcome this, we designed a task in which humans and monkeys made a series of choices to search for shapes hidden on a grid. On our task, the effects of reward and information outcomes from uncovering parts of shapes could be disentangled. Members of both species adeptly learned the shapes and preferred to select tiles expected to be informative earlier in trials than previously rewarding ones, searching a part of the grid until their outcomes dropped below the average information outcome-a pattern consistent with foraging behavior. In addition, how quickly humans learned the shapes was predicted by how well their choice sequences matched the foraging pattern, revealing an unexpected connection between foraging and learning. This adaptive search for information may underlie the ability in humans and monkeys to learn latent features to support goal-directed behavior in the long run.
在现实世界中,为了实现目标而做出一系列决策往往依赖于学习环境中那些无法直接感知的方面的能力。学习这些所谓的潜在特征需要寻求有关它们的信息。先前研究潜在特征学习的努力通常使用单一决策,使用的特征很少,并且无法区分寻求奖励和寻求信息之间的区别。为了克服这一点,我们设计了一项任务,人类和猴子通过一系列选择来搜索隐藏在网格上的形状。在我们的任务中,可以将揭示形状部分的奖励和信息结果分开。两个物种的成员都熟练地学习了这些形状,并更喜欢在试验中选择比之前奖励的更有可能提供信息的瓷砖,直到他们的结果低于平均信息结果,从而搜索网格的一部分,这种模式与觅食行为一致。此外,人类学习形状的速度可以通过其选择序列与觅食模式的匹配程度来预测,这揭示了觅食和学习之间出人意料的联系。这种对信息的适应性搜索可能是人类和猴子能够学习潜在特征以支持长期目标导向行为的基础。