Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08540, USA.
Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08540, USA.
Cell. 2024 Mar 14;187(6):1476-1489.e21. doi: 10.1016/j.cell.2024.01.041. Epub 2024 Feb 23.
Attention filters sensory inputs to enhance task-relevant information. It is guided by an "attentional template" that represents the stimulus features that are currently relevant. To understand how the brain learns and uses templates, we trained monkeys to perform a visual search task that required them to repeatedly learn new attentional templates. Neural recordings found that templates were represented across the prefrontal and parietal cortex in a structured manner, such that perceptually neighboring templates had similar neural representations. When the task changed, a new attentional template was learned by incrementally shifting the template toward rewarded features. Finally, we found that attentional templates transformed stimulus features into a common value representation that allowed the same decision-making mechanisms to deploy attention, regardless of the identity of the template. Altogether, our results provide insight into the neural mechanisms by which the brain learns to control attention and how attention can be flexibly deployed across tasks.
注意过滤器对感觉输入进行筛选，以增强与任务相关的信息。它由一个“注意模板”指导，该模板代表当前相关的刺激特征。为了了解大脑如何学习和使用模板，我们训练猴子执行一项视觉搜索任务，要求它们反复学习新的注意模板。神经记录发现，模板以一种结构化的方式在额顶叶和顶叶皮层中得到表示，即感知上相邻的模板具有相似的神经表示。当任务改变时，通过逐步将模板向奖励特征移动，新的注意模板被学习。最后，我们发现注意力模板将刺激特征转化为共同的价值表示，从而允许相同的决策机制部署注意力，而不管模板的身份如何。总之，我们的结果提供了关于大脑如何学会控制注意力的神经机制的深入了解，以及注意力如何在不同任务中灵活部署。
