Learning optimizes decision templates in the human visual cortex.
Learning optimizes decision templates in the human visual cortex.
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DOI：
10.1016/j.cub.2013.07.052
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发表时间：
2013-09-23
期刊：
影响因子：
--
通讯作者：
Kourtzi Z
中科院分区：
文献类型：
--
作者：
Kuai SG;Levi D;Kourtzi Z
将感觉信息转化为感知决策是大脑面临的一个核心挑战。这种能力被理解为依赖于权衡感官证据，以便形成物体之间关键差异的心理模板。研究表明，学习可以优化这些模板，以提高任务的效率，但这种改进背后的神经机制尚不清楚。在这里，我们确定了大脑通过经验来实现感知决策模板的机制。我们训练观察者辨别被噪音随机干扰的视觉形式。为了描述观察者在执行该任务时学习的内部刺激模板，我们采用了分类图像方法（例如）来分析行为和功能磁共振成像数据。通过将行为和多体素模式反应与噪声刺激试验反向相关，我们确定了决定观察者选择的关键图像部分。观察者学会了跨位置整合信息，并对有区别的图像部分进行加权。训练增强了枕侧区域的形状处理，这反映了信息图像部分的大小不变表示。我们的研究结果表明，学习通过调整腹侧高级皮层中信息图像部分的表征来优化感知决策的心理模板。
Translating sensory information into perceptual decisions is a core challenge faced by the brain. This ability is understood to rely on weighting sensory evidence in order to form mental templates of the critical differences between objects. Learning is shown to optimize these templates for efficient task performance, but the neural mechanisms underlying this improvement remain unknown. Here, we identify the mechanisms that the brain uses to implement templates for perceptual decisions through experience. We trained observers to discriminate visual forms that were randomly perturbed by noise. To characterize the internal stimulus template that observers learn when performing this task, we adopted a classification image approach (e.g.,) for the analysis of both behavioral and fMRI data. By reverse correlating behavioral and multivoxel pattern responses with noisy stimulus trials, we identified the critical image parts that determine the observers’ choice. Observers learned to integrate information across locations and weight the discriminative image parts. Training enhanced shape processing in the lateral occipital area, which was shown to reflect size-invariant representations of informative image parts. Our findings demonstrate that learning optimizes mental templates for perceptual decisions by tuning the representation of informative image parts in higher ventral cortex.
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