- 2018年03月24日16:30 来源：小站整理
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今日份雅思阅读内容来自经济学人，文章标题是：Brains and machines，Thought experiments(大脑与机器，思想实验)本篇雅思阅读文章建议精读时间：35分钟，阅读难度偏难，附雅思阅读高频词汇。
Brain-computer interfaces sound like the stuff of science fiction. Andrew Palmer sorts the reality from the hype
IN THE gleaming facilities of the Wyss Centre for Bio and Neuro engineering in Geneva, a lab technician takes a well plate out of an incubator. Each well contains a tiny piece of brain tissue derived from human stem cells and sitting on top of an array of electrodes. A screen displays what the electrodes are picking up: the characteristic peak-and-trough wave forms of firing neurons.
To see these signals emanating from disembodied tissue is weird. The firing of a neuron is the basic building block of intelligence. Aggregated and combined, such “action potentials” retrieve every memory, guide every movement and marshal every thought. As you read this sentence, neurons are firing all over your brain: to make sense of the shapes of the letters on the page; to turn those shapes into phonemes and those phonemes into words; and to confer meaning on those words.
This symphony of signals is bewilderingly complex. There are as many as 85bn neurons in an adult human brain, and a typical neuron has 10,000 connections to other such cells. The job of mapping these connections is still in its early stages. But as the brain gives up its secrets, remarkable possibilities have opened up: of decoding neural activity and using that code to control external devices.
A channel of communication of this sort requires a brain-computer interface (BCI). Such things are already in use. Since 2004, 13 paralysed people have been implanted with a system called Brain Gate, first developed at Brown University (a handful of others have been given a similar device). An array of small electrodes, called a Utah array, is implanted into the motor cortex, a strip of the brain that governs movement. These electrodes detect the neurons that fire when someone intends to move his hands and arms. These signals are sent through wires that poke out of the person’s skull to a decoder, where they are translated into a variety of outputs, from moving a cursor to controlling a limb.
The system has allowed a woman paralysed by a stroke to use a robotic arm to take her first sip of coffee without help from a caregiver. It has also been used by a paralysed person to type at a rate of eight words a minute. It has even reanimated useless human limbs. In a study led by Bob Kirsch of Case Western Reserve University, published in the Lancetthis year, Brain Gate was deployed artificially to stimulate muscles in the arms of William Kochevar, who was paralysed in a cycling accident. As a result, he was able to feed himself for the first time in eight years.
该系统让一名中风瘫痪的妇女在没有看护者帮助的情况下用机器人手臂喝到了第一口咖啡。还有一位瘫痪者能以每分钟八个字的速度打字。它甚至让本已无用的肢体再次活动起来。由凯斯西储大学的鲍勃·基尔希(Bob Kirsch)领导的一项研究今年在《柳叶刀》上发表了论文，为在一次骑车事故中瘫痪的威廉·科切瓦(William Kochevar)人为部署了BrainGate，以刺激他手臂上的肌肉。结果八年来他第一次能够自己吃饭了。
Interactions between brains and machines have changed lives in other ways, too. The opening ceremony of the football World Cup in Brazil in 2014 featured a paraplegic man who used a mind-controlled robotic exoskeleton to kick a ball. A recent study by Ujwal Chaudhary of the University of Tübingen and four co-authors relied on a technique called functional near-infrared spectroscopy (fNIRS), which beams infrared light into the brain, to put yes/no questions to four locked-in patients who had been completely immobilized by Lou Gehrig’s disease; the patients’ mental responses showed up as identifiable patterns of blood oxygenation.
大脑和机器之间的互动还以其他方式改变了人们的生活。2014年，在巴西举行的世界杯足球赛开幕式上，一名截瘫男子用思维控制机器人外骨骼来踢球。在最近的一项研究中，图宾根大学的乌吉瓦·乔杜里(Ujwal Chaudhary)和四位合著者使用一种可将红外光束照进大脑的“近红外光谱”(fNIRS)技术，向四名因卢·贾里格症(Lou Gehrig's disease，又称肌萎缩性脊髓侧索硬化症、渐冻症)而完全失去行动能力的闭锁综合症患者提出是非问题，患者的思维反应表现为可辨认的血氧模式。
Neural activity can be stimulated as well as recorded. Cochlear implants convert sound into electrical signals and send them into the brain. Deep-brain stimulation uses electrical pulses, delivered via implanted electrodes, to help control Parkinson’s disease. The technique has also been used to treat other movement disorders and mental-health conditions. NeuroPace, a Silicon Valley firm, monitors brain activity for signs of imminent epileptic seizures and delivers electrical stimulation to stop them.
It is easy to see how brain-computer interfaces could be applied to other sensory inputs and outputs. Researchers at the University of California, Berkeley, have deconstructed electrical activity in the temporal lobe when someone is listening to conversation; these patterns can be used to predict what word someone has heard. The brain also produces similar signals when someone imagines hearing spoken words, which may open the door to a speech-processing device for people with conditions such as aphasia (the inability to understand or produce speech).
Researchers at the same university have used changes in blood oxygenation in the brain to reconstruct, fuzzily, film clips that people were watching. Now imagine a device that could work the other way, stimulating the visual cortex of blind people in order to project images into their mind’s eye.
If the possibilities of BCIs are enormous, however, so are the problems. The most advanced science is being conducted in animals. Tiny silicon probes called Neuropixels have been developed by researchers at the Howard Hughes Institute, the Allen Institute and University College London to monitor cellular-level activity in multiple brain regions in mice and rats. Scientists at the University of California, San Diego, have built a BCI that can predict from prior neural activity what song a zebra finch will sing. Researchers at the California Institute of Technology have worked out how cells in the visual cortex of macaque monkeys encoded 50 different aspects of a person’s face, from skin color to eye spacing. That enabled them to predict the appearance of faces that monkeys were shown from the brain signals they detected, with a spooky degree of accuracy. But conducting scientific research on human brains is harder, for regulatory reasons and because they are larger and more complex.
Even when BCI breakthroughs are made on humans in the lab, they are difficult to translate into clinical practice. Wired magazine first reported breathlessly on the then new Brain Gate system back in 2005. An early attempt to commercialize the technology, by a company called Cyberkinetics, foundered. It took NeuroPace 20 years to develop its technologies and negotiate regulatory approval, and it expects that only 500 people will have its electrodes implanted this year.
Current BCI technologies often require experts to operate them. “It is not much use if you have to have someone with a masters in neural engineering standing next to the patient,” says Leigh Hochberg, a neurologist and professor at Brown University, who is one of the key figures behind BrainGate. Whenever wires pass through the skull and scalp, there is an infection risk. Implants also tend to move slightly within the brain, which can harm the cells it is recording from; and the brain’s immune response to foreign bodies can create scarring around electrodes, making them less effective.
Moreover, existing implants record only a tiny selection of the brain’s signals. The Utah arrays used by the BrainGate consortium, for example, might pick up the firing of just a couple of hundred neurons out of that 85bn total. In a paper published in 2011, Ian Stevenson and Konrad Kording of Northwestern University showed that the number of simultaneously recorded neurons had doubled every seven years since the 1950s (see chart). This falls far short of Moore’s law, which has seen computing power double every two years.
而且，现有的植入物只记录了大脑信号中很小的一部分。例如，BrainGate财团使用的犹他阵列也许仅仅拾取了几百个神经元放电的信号，而神经元总计有850亿个。在2011年发表的一篇论文中，西北大学的伊恩·史蒂文森(Ian Stevenson)和康拉德·科尔丁(Konrad Kording)提出，自20世纪50年代以来，能一次被同时记录的神经元数量每七年翻一番(见图表)。这与摩尔定律也就是计算能力每两年翻一番相差甚远。
Neuro engineering 神经工程