BCI Device Spells Your Brain’s Thoughts Out脑机接口设备读心有术

One of the great tragedies of anarthria， the loss of speech， is that many people who suffer the condition can still think clearly. They just can’t express themselves the way most of us do， with words. Especially if they’re also paralyzed and can’t type out their thoughts on a tablet.

言语讷吃，即丧失言语能力的疾病。患上此病的一大悲剧在于，许多患者仍然能够清晰地思考，只是不能像我们大多数人一样用语言表达自我。如果他们同时还瘫痪了，不能在平板电脑上打出他们的想法，情况就愈加凄惨。

For years， scientists have been trying to help anarthric people—in particular paralyzed ones—speak through technology. The latest approach is to implant devices， in or near the brains of anarthric people， that can literally read the electrical impulses that comprise their thoughts—and beam text to a device that either displays it or sounds it out.

多年来，科学家们一直试图通过技术帮助言语讷吃患者，特别是其中瘫痪的患者，帮他们开口说话。最新的方法是在言语讷吃患者的大脑中或大脑附近植入设备，直接读取构成他们思想的电脉冲，并将文本传送到一个可以显示或者念出该文本的设备上。

These brain-computer interfaces， or BCIs， have been getting more and more sophisticated. But they still have a big accuracy problem. In a major experiment four years ago， one leading BCI prototype mistranslated the thoughts of around a quarter of the trial’s participants.

这些脑机接口（或称BCI）变得越来越精密，但准确度仍然是一个很大的问题。在4年前的一项重要试验中，一个顶级BCI原型误译了大约1/4试验参与者的想法。

In other words， every fourth phrase the users were thinking… ended up wrong on the screen. That’s almost as if every fourth line of text you wrote in an email conversation just ended up being automatically rewritten as gibberish1.

换句话说，用户想到的短语里，每隔3组就会在屏幕上显示出1组错误短语。这几乎就像你写来往电子邮件时，每写完3行，第4行就会被自动改写为胡言乱语。

The same team that oversaw that 2019 trial， the Chang Lab at University of California， San Francisco， is now trying a different approach. The lab， led by top neuroscientist Edward Chang， has developed a new BCI that translates individual letters instead of whole words or phrases. Users spell out their thoughts， one letter at a time.

主持2019年那项试验的团队，即加州大学旧金山分校的张氏实验室，现在正在尝试一种不同的方法。该实验室由顶尖神经科学家张复伦领导。他们已经开发出一种新的BCI，可以翻译单个字母，而不是整个单词或短语。用户一个字母一个字母地拼写出自己的想法。

The initial results are encouraging. The BCI was able to correctly translate and present about 94 percent of the letters being thought out by participants. The Chang Lab’s new spelling-BCI could help advance brain implant technology， bringing it closer to everyday use by large numbers of people， and giving a voice to the voiceless.

试验的初步结果令人鼓舞。该BCI能够正确翻译并呈现参与者想出的约94%的字母。张氏实验室的这个新型拼写BCI有助于推动大脑植入技术的发展，使其向大规模日常应用迈进一步，让无声者得以发声。

The Chang Lab made headlines four years ago when it demoed its BrainNet BCI. In the experiment， two volunteers wore electroencephalogram electrodes on their heads—the kind neurologists use to detect epilepsy. Unlike older， cruder BCIs， BrainNet did not require invasive surgery to implant sensors dir-ectly into the brain.

4年前，张氏实验室因演示其基于“大脑网络”技术的BCI而登上头条。在当时的试验中，两名志愿者头戴脑电图电极，就是神经学家用来检查癫痫的那种电极。与较粗糙的老式BCI不同，“大脑网络”技术不需要通过侵入性外科手术将传感器直接植入大脑。

The volunteers silently concentrated on certain simple thoughts. The EE headsets detected their brain waves through their skulls， and an algorithm matched these waves to a “dictionary” of phrases the lab had written by asking volunteers to utter phrases， then recording the resulting neurological activity.

志愿者们默默地专注于某些简单的想法。脑电耳机透过他们的头骨探测脑电波，再由一种算法将这些脑电波与一本“词典”中的短语进行比对。这本“词典”是实验室提前编写好的，编写方法是让志愿者说出短语，然后记下由此产生的神经活动。

That BrainNet worked at all was impressive. But its 76-percent peak accuracy left a lot of room for improvement. “A major challenge for these approaches is achieving high single-trial accuracy rates，” Chang and his team conceded.

“大脑网络”技术能起到作用已经令人印象深刻，但其76%的峰值准确率仍有很大的进步空间。张复伦及其团队承认：“这些方法面临的一个主要挑战就是在单次试验中达到较高的准确率。”

Spelling out thoughts one letter at a time would certainly be slower than feeding whole thoughts into a BCI， but could it be more accurate？ To find out， the Chang Lab recruited a volunteer who， back in 2019， had an electrocor-ticography array—a postcard-size patch of 16 electrodes—implanted under his skull. The volunteer suffers from “severe limb and vocal-tract paralysis，” according to the lab.

一个字母一个字母地拼写出想法肯定比把整个想法输入BCI要慢，但前者会更准确吗？为了得到答案，张氏实验室招募了一名志愿者——早在2019年，这名志愿者颅内就植入了一个明信片大小、包含16个电极的脑皮层电极阵列芯片。张氏实验室称，这名志愿者患有“严重的肢体和声道麻痹”。

Chang and his teammates， including UCSF neuroscientists Sean Metzger and David Moses， taught the subject the NATO phonetic alphabet. They instructed the volunteer to spell out thoughts by thinking of each letter’s NATO code word.

张复伦和他的团队成员，包括加州大学旧金山分校的神经科学家肖恩·梅茨格和戴维·摩西，一起教受试志愿者北约音标字母。他们让受试志愿者在脑子里想出每个字母对应的北约音标代码，以此拼出想法。

The BCI read the brain waves. An algorithm did its best to match the waves to a 1，152-word dictionary. Thoughts—at least， the algorithm’s best translation of one’s thoughts—scrolled across a computer screen at a rate of 29 letters per minute.

BCI读取受试志愿者的脑电波，再由一种算法尽力将其脑电波与一本“词典”中的1152个单词进行比对。想法，或者说至少是算法对想法的最佳翻译，以每分钟29个字母的速度在电脑屏幕上滚动出现。

The system was pretty accurate. During both instances when the subject thought， “Thank you，” the translated text came out onscreen as， well， “thank you.”

该系统的正确率比较高。受试志愿者有两次想的是thank you（谢谢你），翻译后的文本在屏幕上显示出来的就是thank you（谢谢你）。

But it wasn’t perfect. “Good morning” came out as “good morning” on the first try and “good for legs” on the second try. And “you are not going to believe this” totally befuddled2 the BCI and its algorithm， getting a garbled translation as “you plan to go in on a bit love this” on the first attempt， and as “ypuaranpdggingloavlinesoeb” on the second attempt.