只要测量你的脑电波就能知道你在想什么,这听起来像是科幻小说,不过英国一项最新研究已经在这方面取得了一些进展,可以初步解码具备某些属性的脑电波所代表的意义。
(图片来源于网络)
英国格拉斯哥大学的研究人员在新一期美国学术刊物《公共科学图书馆—生物学》(PLoS Biology)上报告说,他们请6名志愿者参与试验。这些人会观看一些显示高兴、害怕、惊讶等表情的人脸图像,有时这些图像会被随机遮住一部分,比如只能看到眼睛和嘴巴。受试者被要求从这种图像中判断人物表情,而他们大脑在思考过程中发出的脑电波则被仪器仔细记录下来。
研究人员随后分析了脑电波的频率、振幅和相位等不同属性在携带信息方面的作用,结果显示,频率在12赫兹左右的脑电波更多地携带与眼睛有关的信息,而频率在4赫兹左右的脑电波更多地携带与嘴巴有关的信息。此外,相位与振幅相比携带的信息量要大很多。
领导研究的菲利普·许恩斯教授说,脑电波虽然容易测量,但通常难以明白其中意义,这就像看一台信号解码有问题的电视,我们能收到信号,但看不到图像。而本次研究的目的正是帮助寻找有效的解码方式,现在已经能看到一些图像,也许将来能够完全读出脑电波所代表的内容。
他还指出,大脑使用不同频率的波来代表脸上不同部位,其好处是可以同时叠加使用多个频率的波来携带更多信息,这与现在广播通信等领域中对不同频段电波的划分方式类似。大脑与现有科技在处理信息方式上的这种相似性,使得在研发人机接口方面有很大潜力,即可能直接让大脑通过脑电波来与计算机通信。(生物谷Bioon.com)
生物谷推荐原文:
PLoS Biology DOI:10.1371/journal.pbio.1001064
Cracking the Code of Oscillatory Activity
Philippe G. Schyns, Gregor Thut, Joachim Gross
Neural oscillations are ubiquitous measurements of cognitive processes and dynamic routing and gating of information. The fundamental and so far unresolved problem for neuroscience remains to understand how oscillatory activity in the brain codes information for human cognition. In a biologically relevant cognitive task, we instructed six human observers to categorize facial expressions of emotion while we measured the observers' EEG. We combined state-of-the-art stimulus control with statistical information theory analysis to quantify how the three parameters of oscillations (i.e., power, phase, and frequency) code the visual information relevant for behavior in a cognitive task. We make three points: First, we demonstrate that phase codes considerably more information (2.4 times) relating to the cognitive task than power. Second, we show that the conjunction of power and phase coding reflects detailed visual features relevant for behavioral response—that is, features of facial expressions predicted by behavior. Third, we demonstrate, in analogy to communication technology, that oscillatory frequencies in the brain multiplex the coding of visual features, increasing coding capacity. Together, our findings about the fundamental coding properties of neural oscillations will redirect the research agenda in neuroscience by establishing the differential role of frequency, phase, and amplitude in coding behaviorally relevant information in the brain.