Most cognitive processes are studied using abstract or synthetic stimuli with specific features to fully control what is presented to subjects. However, recent studies have revealed enhancements of cognitive capacities (such as working memory) when processing naturalistic versus abstract stimuli. Using abstract stimuli constructed from distinct visual features (e.g., color and shape), we have recently shown that human subjects can learn multidimensional stimulus-reward associations via initially estimating reward value of individual features (feature-based learning) before gradually switching to learning about reward value of individual stimuli (object-based learning). Here, we examined whether similar strategies are adopted during learning about naturalistic stimuli that are clearly perceived as objects (instead of a combination of features) and contain both task-relevant and irrelevant features. We found that similar to learning about abstract stimuli, subjects initially adopted feature-based learning more strongly before transitioning to object-based learning. However, there were three key differences between learning about naturalistic and abstract stimuli. First, compared with abstract stimuli, the initial learning strategy was less feature-based for naturalistic stimuli. Second, subjects transitioned to object-based learning faster for naturalistic stimuli. Third, unexpectedly, subjects were more likely to adopt feature-based learning for naturalistic stimuli, both at the steady state and overall. These results suggest that despite the stronger tendency to perceive naturalistic stimuli as objects, which leads to greater likelihood of using object-based learning as the initial strategy and a faster transition to object-based learning, the influence of individual features on learning is stronger for these stimuli such that ultimately the object-based strategy is adopted less. Overall, our findings suggest that feature-based learning is a general initial strategy for learning about reward value of all types of multi-dimensional stimuli.

大多数认知过程都是使用具有特定功能的抽象或合成刺激来研究，以完全控制呈现给受试者的东西。但是，最近的研究表明，在处理自然刺激与抽象刺激时，认知能力（例如工作记忆）的增强。最近，我们使用由独特的视觉特征（例如颜色和形状）构成的抽象刺激，证明了人类受试者可以通过逐步估计个体特征的奖励价值（基于特征的学习）来学习多维刺激-奖励关联，然后逐渐转向学习。单个刺激的奖励价值（基于对象的学习）。这里，我们研究了在学习自然主义刺激过程中是否采用了类似的策略，这些策略显然被视为对象（而不是特征的组合），并且既包含任务相关的特征又包含无关的特征。我们发现，与学习抽象刺激相似，受试者最初更倾向于采用基于特征的学习，然后再过渡到基于对象的学习。但是，学习自然主义和抽象刺激之间存在三个主要区别。首先，与抽象刺激相比，自然学习刺激的初始学习策略较少基于特征。其次，受试者可以更快地过渡到基于对象的学习以获得自然主义的刺激。第三，出乎意料的是，受试者在稳态和总体上都更可能采用基于特征的学习来进行自然主义的刺激。这些结果表明，尽管人们倾向于将自然主义的刺激视为对象，这导致使用基于对象的学习作为初始策略的可能性更大，并且更快地过渡到基于对象的学习，但个体特征对学习的影响更大。这些刺激使得最终较少采用基于对象的策略。总体而言，我们的发现表明，基于特征的学习是学习所有类型的多维刺激的奖励价值的一般初始策略。在这些刺激下，个体特征对学习的影响更大，因此最终较少采用基于对象的策略。总体而言，我们的发现表明，基于特征的学习是学习所有类型的多维刺激的奖励价值的一般初始策略。在这些刺激下，个体特征对学习的影响更强，因此最终较少采用基于对象的策略。总体而言，我们的发现表明，基于特征的学习是学习所有类型的多维刺激的奖励价值的一般初始策略。