现在，采用功能磁共振成像和计算模型，科学家已经可以通过分析大脑，“重现”人们观看到的电影画面。好莱坞不少科幻片里的场面正一步步成为现实。
美国加州大学伯克利分校的科学家们采用这种先进技术，已成功解码并重现了人们大脑的动态视觉感受。在9月22日发表于《当代生物学》中的一篇研究成果报告中，科学家们称他们重现了志愿者看过的一段好莱坞电影预告片。他们希望，有一天能通过这一技术看到昏迷患者脑中的想法，或是通过视频看到某人所做的梦境到底是什么。
加州大学的神经科学家杰克·格拉特说，志愿者在磁共振成像仪中必须保持静止几个小时去观看一段视频。然后研究者对志愿者大脑各个部位的活跃度进行测试，大脑每一秒的活跃度都被采样，并且所观看过视频的每一个片段都被独立地重构。
用脑扫描技术重建人们看到的画面，其难点在于，要观测的大脑中血流情况比编码电影中动态信息的神经信号速度要慢得多。因此过去多数类似尝试用的都是静态图像。(生物谷 Bioon.com)
doi:10.1016/j.cub.2011.08.031
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Reconstructing Visual Experiences from Brain Activity Evoked by Natural Movies
Shinji Nishimoto, An T. Vu, Thomas Naselaris, Yuval Benjamini, Bin Yu, Jack L. Gallant
Quantitative modeling of human brain activity can provide crucial insights about cortical representations and can form the basis for brain decoding devices. Recent functional magnetic resonance imaging (fMRI) studies have modeled brain activity elicited by static visual patterns and have reconstructed these patterns from brain activity.However, blood oxygen level-dependent (BOLD) signals measured via fMRI are very slow ,so it has been difficult to model brain activity elicited by dynamic stimuli such as natural movies. Here we present a new motion-energy encoding model that largely overcomes this limitation. The model describes fast visual information and slow hemodynamics by separate components. We recorded BOLD signals in occipitotemporal visual cortex of human subjects who watched natural movies and fit the model separately to individual voxels. Visualization of the fit models reveals how early visual areas represent the information in movies. To demonstrate the power of our approach, we also constructed a Bayesian decoder by combining estimated encoding models with a sampled natural movie prior. The decoder provides remarkable reconstructions of the viewed movies. These results demonstrate that dynamic brain activity measured under naturalistic conditions can be decoded using current fMRI technology.
