Neural Decoding of Visual Imagery During Sleep
Neural Decoding of Visual Imagery During Sleep
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DOI：
10.1126/science.1234330
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发表时间：
2013-05-03
期刊：
影响因子：
56.9
通讯作者：
Kamitani, Y.
中科院分区：
文献类型：
--
作者：
Horikawa, T.;Tamaki, M.;Kamitani, Y.
长期以来，睡眠中的视觉图像一直是人们持续猜测的话题，但其私人性质阻碍了客观分析。在这里，我们提出了一种神经解码方法，在该方法中，机器学习模型预测视觉图像的内容，在睡眠发作期间，给定测量的大脑活动，通过发现人类功能磁共振成像模式和口头报告之间的联系与词汇和图像数据库的帮助。在视觉皮层区域刺激诱导的大脑活动上训练的解码模型显示出准确的分类，检测和识别内容。我们的研究结果表明，在睡眠中的特定视觉体验是由刺激感知共享的大脑活动模式表示的，提供了一种方法来揭示梦的主观内容，使用客观的神经测量。
Visual imagery during sleep has long been a topic of persistent speculation, but its private nature has hampered objective analysis. Here we present a neural decoding approach in which machine-learning models predict the contents of visual imagery during the sleep-onset period, given measured brain activity, by discovering links between human functional magnetic resonance imaging patterns and verbal reports with the assistance of lexical and image databases. Decoding models trained on stimulus-induced brain activity in visual cortical areas showed accurate classification, detection, and identification of contents. Our findings demonstrate that specific visual experience during sleep is represented by brain activity patterns shared by stimulus perception, providing a means to uncover subjective contents of dreaming using objective neural measurement.