Damarla Saudamini Roy, Cherkassky Vladimir L, Just Marcel Adam
Department of Psychology, Center for Cognitive Brain Imaging, Carnegie Mellon University, Pittsburgh, Pennsylvania.
Hum Brain Mapp. 2016 Apr;37(4):1296-307. doi: 10.1002/hbm.23102. Epub 2016 Jan 9.
Machine learning or MVPA (Multi Voxel Pattern Analysis) studies have shown that the neural representation of quantities of objects can be decoded from fMRI patterns, in cases where the quantities were visually displayed. Here we apply these techniques to investigate whether neural representations of quantities depicted in one modality (say, visual) can be decoded from brain activation patterns evoked by quantities depicted in the other modality (say, auditory). The main finding demonstrated, for the first time, that quantities of dots were decodable by a classifier that was trained on the neural patterns evoked by quantities of auditory tones, and vice-versa. The representations that were common across modalities were mainly right-lateralized in frontal and parietal regions. A second finding was that the neural patterns in parietal cortex that represent quantities were common across participants. These findings demonstrate a common neuronal foundation for the representation of quantities across sensory modalities and participants and provide insight into the role of parietal cortex in the representation of quantity information.
机器学习或多体素模式分析（MVPA）研究表明，在物体数量以视觉方式呈现的情况下，可以从功能磁共振成像（fMRI）模式中解码出物体数量的神经表征。在此，我们应用这些技术来研究一种模态（如视觉）中所描绘数量的神经表征，是否可以从另一种模态（如听觉）中所描绘数量引发的大脑激活模式中解码出来。主要发现首次表明，由听觉音调数量引发的神经模式所训练的分类器，可以解码点的数量，反之亦然。跨模态共有的表征主要在额叶和顶叶区域右侧化。第二个发现是，代表数量的顶叶皮质神经模式在参与者之间是共有的。这些发现证明了跨感觉模态和参与者的数量表征存在共同的神经元基础，并为顶叶皮质在数量信息表征中的作用提供了见解。
