Salk研究所神经科学家发现，在视觉皮层中传播的电活动旅行波可能充当关键的计算机制，帮助大脑将感觉信息转化为内部表征1。这项研究于2026年7月21日发表在《Neuron》期刊上，表明这些波动并非仅为背景神经活动，而是感知和记忆形成的核心驱动力1。
研究团队领导者John Reynolds在2020年首次在清醒动物的视觉系统中识别出这类旅行脑波1。新研究提出了神经旅行波的四项主要功能：调整感知、转化感觉信息为内部表征、产生短期预测，以及保存和回放记忆模式1。Reynolds指出，"这在某种意义上类似于ChatGPT这样的大型语言模型所做的事情"1，暗示大脑可能本质上是一个由经验从头构建的生物生成模型1。该项研究得到了美国国立卫生研究院、Research to Prevent Blindness以及加拿大自然科学与工程研究委员会等机构的资助1。
Neuroscientists at the Salk Institute have identified a computational role for traveling waves of electrical activity that sweep across the brain's visual cortex, proposing that these waves serve as a calculating engine to convert raw sensory information into internal representations that support perception and prediction.1 Published on July 21, 2026, in the journal Neuron, the research challenges the notion that such waves are merely background noise, instead positioning them as central mechanisms underlying perception and memory.1
The discovery builds on earlier work by John Reynolds, who first identified these traveling brain waves in the visual systems of awake animals in 2020.1 According to the new framework, neural traveling waves perform four primary functions: adjusting perception, transforming sensory information into internal representations, generating short-term predictions, and storing and replaying memory patterns.1 Reynolds drew a striking parallel to how large language models like ChatGPT operate, suggesting that the brain may function as a biological generative model constructed from experience.1 The research was supported by funding from the National Institutes of Health, Research to Prevent Blindness, and the Natural Sciences and Engineering Research Council of Canada.1
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