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FMRI activity patterns in human LOC carry information about object exemplars within category

机译:人类LOC中的FMRI活动模式携带有关类别内对象样本的信息

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摘要

The lateral occipital complex (LOC) is a set of areas in human occipito-temporal cortex responding to objects as opposed to low-level control stimuli. Conventional fMRI analysis methods based on regional averages could not detect signals discriminative of different types of objects in this region. Here, we examined fMRI signals using multivariate pattern recognition (support vector classification), to systematically explore the nature of object-related information available in fine-grained activity patterns in LOC. Distributed fMRI BOLD signals from LOC allowed for above chance discrimination not only of the category, but also of within-category exemplars of everyday man-made objects, and such exemplar-specific information generalised across changes in stimulus size and viewpoint, particularly in posterior subregions. Object identity could also be predicted from responses of the early visual cortex, even significantly across the changes in size and viewpoint used here. However, a dissociation was observed between these two regions of interest in the degree of discrimination for objects relative to size: In the early visual cortex two different sizes of the same object were even better discriminated than two different objects (in accordance with measures of pixelwise stimulus similarity), whereas the opposite was true in the LOC. These findings provide the first evidence that direct evoked fMRI activity patterns in LOC can be different for individual object exemplars (within a single category). We propose that pattern recognition methods as used here may provide an alternative approach to study mechanisms of neuronal representation based on aspects of the fMRI response independent of those assessed in adaptation paradigms.
机译:枕骨外侧复合体(LOC)是人枕颞皮层中一组响应对象的区域,与低水平控制刺激相反。基于区域平均值的常规功能磁共振成像分析方法无法检测到可区分该区域不同类型物体的信号。在这里,我们使用多元模式识别(支持向量分类)检查了功能磁共振成像信号,以系统地探索LOC中细粒度活动模式中可用的对象相关信息的性质。来自LOC的分布式fMRI BOLD信号不仅可以对类别进行分类,而且还可以对日常人造物体的类别内样本进行机会上的区分,并且此类样本特定的信息会在刺激大小和视点的变化中普遍存在,尤其是在后分区。还可以根据早期视觉皮层的响应来预测对象的身份,甚至在此处使用的大小和视点的变化中也可以显着地预测对象。但是,观察到这两个感兴趣区域之间在对象相对于大小的区分程度上存在分离:在早期视觉皮层中,同一对象的两个不同大小甚至比两个不同对象有更好的区分(根据像素方向的度量)刺激相似性),而在LOC中则相反。这些发现提供了第一个证据,表明LOC中直接诱发的fMRI活动模式对于单个对象样本(在一个类别内)可能有所不同。我们建议,此处使用的模式识别方法可提供一种替代方法,以基于功能磁共振成像反应的各个方面来研究神经元表示的机制,而与在适应性范式中评估的方面无关。

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