The Stanford and Stanford BCI Accelerated Translation of Neuronal Activities into Text: A Study for a Patient with Amyotrophic Lateral Sclerosis

Willett and his colleagues developed a BCI to interpret neural activity at the cellular level and translate it into text1. They worked with a 67-year-old Pat Bennett, who has motor neuron disease, also known as amyotrophic lateral sclerosis — a condition that causes a progressive loss of muscle control, resulting in difficulties moving and speaking.

In terms of speed and accuracy, the studies were pretty much the same. When limited to a 50 word vocabulary and expanded to a 125,000 word vocabulary, the study had a 9.1 percent error rate. After about four months, the Stanford algorithm could convert brain signals to words at about 68 words per minute. The UC San Francisco and Berkeley algorithm was able to decode at a median rate of 78wpm. It had an error rate of 8.2 percent for a 119-word vocabulary and roughly a 25 percent error rate for a 1,024-word vocabulary.

Although a 23 to 25 percent error rate isn’t good enough for everyday use, it’s a significant improvement over existing tech. Edward Chang, the chair of neurological surgery at the University of California at San Francisco, and co-author of the study stated in a press conference that the rate of communication for existing technology is much slower than for natural speech.

“Sixty to 70 wpm is a real milestone for our field in general because it’s coming from two different centers and two different approaches,” Chang said at the briefing.

That said, these studies are more proof of concept than a technology that’s ready for prime time. One potential issue is that these treatments require long sessions to train the algorithm. However, researchers from both teams told press at a briefing that they were hopeful that algorithm training would be less intensive in the future.

The studies do not have a big database of data from other people. As we do more of these recordings and get more data, we should be able to transfer what the algorithms learn from other people to new people,” says Frank Willett, a research scientist at the Howard Hughes Medical Institute and co-author of the Stanford study. Willett did note that wasn’t guaranteed, however, and more research was needed.

Another issue is that the tech has to be easy enough for people to use at home, without requiring caregivers to go through complicated training. Brain implants are also invasive, and in these particular studies, the BCI had to be connected via wires to a device on the outside of the skull that was then attached to a computer. There are also concerns about the fact that these can be temporary solutions. The tech needs to be rigorously checked to get to consumer use, which can take a long time.

Brain Reading Devices Allow Paralysed People to Talk Using Their Brains: A Case Study of a 47-year-old American woman who lost her speech due to brain stem stem stroke

The potential benefit of the technology is immense if it can be safely and widelyadopted according to Chang, who says that the tech has crossed a threshold that they are both excited about. “We are thinking about that quite seriously and what the next steps are.”

The devices might be products in the near future according to Christian Herff.

“For those who are nonverbal, this means they can stay connected to the bigger world, perhaps continue to work, maintain friends and family relationships,” said Bennett in a statement to reporters.

A 47-year-old woman named Ann lost her ability to speak after a brainstem stroke 18 years ago, but in a separate study, Edward Chang and his colleagues worked with her.

Although the implants used by Willett’s team, which capture neural activity more precisely, outperformed this on larger vocabularies, it is “nice to see that with ECoG, it’s possible to achieve low word-error rate”, says Blaise Yvert, a neurotechnology researcher at the Grenoble Institute of Neuroscience in France.

Chang and his team also created customized algorithms to convert Ann’s brain signals into a synthetic voice and an animated avatar that mimics facial expressions. The voice was trained to sound like Ann before her injury.

Ann told the researchers that the simple fact of hearing a voice like your own is emotional. “When I had the ability to talk for myself was huge!”

And the participants of both studies still have the ability to engage their facial muscles when thinking about speaking and their speech-related brain regions are intact, says Herff. This won’t be the case for every patient.

Source: Brain-reading devices allow paralysed people to talk using their thoughts

How fast can Tropico Forests survive the 3.9 °C climate? An analysis of wind tunnel experiments on an octet with Willett

Willett says that they see this as a proof of concept that industry people can use to translate it into a product.

How wind-tunnel experiments could help athletes run the fastest marathon ever, and an analysis that could help explain why birds are the colours they are.

Tropico forests are facing increasing temperatures due to the warming climate. It is not known how much the trees can endure before their leaves die. A team has combined multiple data sources to try and answer this question, and suggest that a warming of 3.9 °C would lead to many leaves reaching a tipping point at which photosynthesis breaks down. This scenario would likely cause significant damage to these ecosystems’ role in vital carbon storage and as homes to significant biodiversity.