Natural scene categories revealed in distributed patterns of activity in the human brain.
Natural scene categories revealed in distributed patterns of activity in the human brain.
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DOI：
10.1523/jneurosci.0559-09.2009
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发表时间：
2009-08-26
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影响因子：
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通讯作者：
Beck DM
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文献类型：
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作者：
Walther DB;Caddigan E;Fei-Fei L;Beck DM
人类主体在对自然场景进行分类方面非常有效，尽管不同类别的自然场景通常具有相似的图像统计数据。然而，到目前为止，我们还不知道复杂的自然场景类别在大脑中的编码和区分位置以及方式。我们使用功能性磁共振成像（fMRI）和分布式模式分析来询问大脑的哪些区域可以区分自然场景类别（例如森林、山脉和海滩）。使用六个自然场景类别的完全不同的样本进行训练和测试，确保分类算法学习与类别相关的模式，而不是特定的样本。我们发现，V1区，海马旁位置区（PPA），压后皮质（RSC），枕叶外侧复合体（ESTA）都包含的信息，区分自然场景的类别。更重要的是，与人类行为实验的相关性表明，PPA，RSC，和ESTA中存在的信息很可能有助于人类对自然场景的分类。具体而言，基于这些区域的fMRI信号的预测的错误模式与受试者的行为错误显著相关。此外，行为分类性能和预测PPA表现出显着下降的准确性时，场景呈现上下颠倒。这些结果表明，包括PPA，RSC和ESTA在内的区域网络有助于人类对自然场景进行分类。
Human subjects are extremely efficient at categorizing natural scenes, despite the fact that different classes of natural scenes often share similar image statistics. Thus far, however, it is unknown where and how complex natural scene categories are encoded and discriminated in the brain. We used functional magnetic resonance imaging (fMRI) and distributed pattern analysis to ask what regions of the brain can differentiate natural scene categories (such as forests vs mountains vs beaches). Using completely different exemplars of six natural scene categories for training and testing ensured that the classification algorithm was learning patterns associated with the category in general and not specific exemplars. We found that area V1, the parahippocampal place area (PPA), retrosplenial cortex (RSC), and lateral occipital complex (LOC) all contain information that distinguishes among natural scene categories. More importantly, correlations with human behavioral experiments suggest that the information present in the PPA, RSC, and LOC is likely to contribute to natural scene categorization by humans. Specifically, error patterns of predictions based on fMRI signals in these areas were significantly correlated with the behavioral errors of the subjects. Furthermore, both behavioral categorization performance and predictions from PPA exhibited a significant decrease in accuracy when scenes were presented up-down inverted. Together these results suggest that a network of regions, including the PPA, RSC, and LOC, contribute to the human ability to categorize natural scenes.