Science：电脑模拟预测神经活动模式
专题：Science报道
功能性核磁共振（fMRI）以两个步骤激活任意名词。
生物谷报道：当你在想一个人、地方或事情的时候，你的脑中会显示出与该特别画面有关的独特的活动模式。据5月29日的《科学》（Science）杂志刊载的研究论文，现在有一种电脑模拟可以预测这些神经活动模式在人的头脑中是如何显示的，而这一过程取决于这个人所思想的是什么名词。这一进展可帮助研究人员探索长期存在的有关知识是如何在人脑中表现的种种问题，并有可能导向更深地理解并更好地治疗语言缺陷和学习障碍。
Tom Mitchell及其同事对一个计算模式进行了60种神经模式的“训练”，这些神经模式是用功能性核磁共振（fMRI）成像采集自人类受试者的。这些神经模式所表现的恰好是人脑是如何解读并表达60种不同名词画面的。研究人员发现，他们的模型此后能够预测与其它名词有关但没有被包括在训练套数之内的名词的神经活动模式。在开发这一模型的时候，研究人员应用了一个理论将名词描绘成具有25个维度的物体，而每一维度具有一个感觉-运动的特征，如进食或嗅闻。这一在练习中非常描述性地表现名词的方法使得该模型能够非常精确地预测在人脑中表达的数千种其它新画面的神经模式。（生物谷www.bioon.com）
生物谷推荐原始出处：
Science，Vol. 320. no. 5880, pp. 1191 - 1195，Tom M. Mitchell，Marcel Adam Just
Predicting Human Brain Activity Associated with the Meanings of Nouns
The question of how the human brain represents conceptual knowledge has been debated in many scientific fields. Brain imaging studies have shown that different spatial patterns of neural activation are associated with thinking about different semantic categories of pictures and words (for example, tools, buildings, and animals). We present a computational model that predicts the functional magnetic resonance imaging (fMRI) neural activation associated with words for which fMRI data are not yet available. This model is trained with a combination of data from a trillion-word text corpus and observed fMRI data associated with viewing several dozen concrete nouns. Once trained, the model predicts fMRI activation for thousands of other concrete nouns in the text corpus, with highly significant accuracies over the 60 nouns for which we currently have fMRI data.
1 Machine Learning Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
2 Department of Psychology, University of South Carolina, Columbia, SC 29208, USA.
3 Center for Cognitive Brain Imaging, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
4 Language Technologies Institute, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
5 Cognitive Science Department, University of California, San Diego, La Jolla, CA 92093, USA.
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