State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.
J Neurosci. 2010 Sep 15;30(37):12323-8. doi: 10.1523/JNEUROSCI.0704-10.2010.
Visual perceptual learning models, as constrained by orientation and location specificities, propose that learning either reflects changes in V1 neuronal tuning or reweighting specific V1 inputs in either the visual cortex or higher areas. Here we demonstrate that, with a training-plus-exposure procedure, in which observers are trained at one orientation and either simultaneously or subsequently passively exposed to a second transfer orientation, perceptual learning can completely transfer to the second orientation in tasks known to be orientation-specific. However, transfer fails if exposure precedes the training. These results challenge the existing specific perceptual learning models by suggesting a more general perceptual learning process. We propose a rule-based learning model to explain perceptual learning and its specificity and transfer. In this model, a decision unit in high-level brain areas learns the rules of reweighting the V1 inputs through training. However, these rules cannot be applied to a new orientation/location because the decision unit cannot functionally connect to the new V1 inputs that are unattended or even suppressed after training at a different orientation/location, which leads to specificity. Repeated orientation exposure or location training reactivates these inputs to establish the functional connections and enable the transfer of learning.
视觉感知学习模型受到方向和位置特异性的限制，提出学习要么反映了 V1 神经元调谐的变化，要么重新加权特定的 V1 输入，无论是在视觉皮层还是更高的区域。在这里，我们证明了，通过一种训练加暴露的程序，其中观察者在一个方向上进行训练，同时或随后被动地暴露于第二个转移方向，感知学习可以在已知是方向特异性的任务中完全转移到第二个方向。然而，如果暴露先于训练，则转移失败。这些结果通过提出一种更通用的感知学习过程，挑战了现有的特定感知学习模型。我们提出了一种基于规则的学习模型来解释感知学习及其特异性和转移。在这个模型中，高级大脑区域中的一个决策单元通过训练学习重新加权 V1 输入的规则。然而，这些规则不能应用于新的方向/位置，因为决策单元不能在不同的方向/位置进行训练后，与未注意到的甚至被抑制的新的 V1 输入建立功能连接，这导致了特异性。重复的方向暴露或位置训练重新激活这些输入，以建立功能连接并实现学习的转移。
