Task difficulty and the specificity of perceptual learning
Task difficulty and the specificity of perceptual learning
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DOI：
10.1038/387401a0
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发表时间：
1997-05-22
期刊：
影响因子：
64.8
通讯作者：
Hochstein, S
中科院分区：
文献类型：
--
作者：
Ahissar, M;Hochstein, S
练习简单的视觉任务会导致执行这些任务的显着改善。这种学习是特定于用于训练的刺激的。我们在这里表明，特异性的程度取决于训练条件的难度。我们发现，特定性的模式映射到模式的接受持有的选择性沿着视觉通路。在简单的条件下，学习概括了方向和视网膜位置，与高级视觉区域的空间概括相匹配。随着任务难度的增加，学习在方向和位置方面变得更加具体，与较低区域表现出的精细空间视网膜反应相匹配。因此，我们尽可能地享受学习泛化的好处，并在必要时享受细粒度但特定的训练。学习的动力学表现出相应的特征。改进从简单的情况开始（当受试者被允许长时间处理时），然后才进行到更难的情况。这种学习级联意味着容易的条件引导学习困难的条件。总的来说，这种特异性和动态性表明，学习过程是沿着皮层层级的逆流。改进从更高的概括水平开始，这反过来又将较难的条件学习引导到较低水平输入的子域。正如这个反向层次模型所预测的那样，学习可以有效地使用困难的试验，但在学习开始之前已经启用的条件下，一个单一的延长演示足以启动学习。我们把这种一次相遇的促成效应称为“尤里卡”。
Practising simple visual tasks leads to a dramatic improvement in performing them. This learning is specific to the stimuli used for training. We show here that the degree of specificity depends on the difficulty of the training conditions. We find that the pattern of specificities maps onto the pattern of receptive held selectivities along the visual pathway. With easy conditions, learning generalizes across orientation and retinal position, matching the spatial generalization of higher visual areas. As task difficulty increases, learning becomes more specific with respect to both orientation and position, matching the fine spatial retinotopy exhibited by lower areas. Consequently, we enjoy the benefits of learning generalization when possible, and of fine grain but specific training when necessary. The dynamics of learning show a corresponding feature. Improvement begins with easy cases (when the subject is allowed long processing times) and only subsequently proceeds to harder cases. This learning cascade implies that easy conditions guide the learning of hard ones. Taken together, the specificity and dynamics suggest that learning proceeds as a countercurrent along the cortical hierarchy. Improvement begins at higher generalizing levels, which, in turn, direct harder-condition learning to the subdomain of their lower-level inputs. As predicted by this reverse hierarchy model, learning can be effective using only difficult trials, but on condition that learning onset has previously been enabled, A single prolonged presentation suffices to initiate learning. We call this single-encounter enabling effect 'eureka'.