One night in October, 2009, a young man lay in an fMRI scanner in Liège, Belgium. Five years earlier, he'd suffered a head trauma in a motorcycle accident, and since then he hadn't spoken. He was said to be in a "vegetative state." A neuroscientist named Martin Monti sat in the next room, along with a few other researchers. For years, Monti and his postdoctoral adviser, Adrian Owen, had been studying vegetative patients, and they had developed two controversial hypotheses.

For the roughly 50 million people worldwide with epilepsy, the exchange of electrical signals between cells in their brain can sometimes go haywire and cause a seizure--often with little to no warning. Two researchers at the University of Louisiana at Lafayette have developed a new AI-powered model that can predict the occurrence of seizures up to one hour before onset with 99.6 percent accuracy. "Due to unexpected seizure times, epilepsy has a strong psychological and social effect on patients," explains Hisham Daoud, a researcher who co-developed the new model. Detecting seizures ahead of time could greatly improve the quality of life for patients with epilepsy and provide them with enough time to take action, he says. Notably, seizures are controllable with medication in up to 70 percent of these patients.

AI algorithms can help scientists process brain waves and convert them directly into speech, according to new research. "Our voices help connect us to our friends, family and the world around us, which is why losing the power of one's voice due to injury or disease is so devastating," said Nima Mesgarani, senior author of the paper published in Scientific Reports and a researcher at Columbia University. "With today's study, we have a potential way to restore that power. We've shown that, with the right technology, these people's thoughts could be decoded and understood by any listener." Neurons in our brain's auditory cortex are excited whenever we listen to people speak – or even imagine people speaking.

If you've ever wished for an extra arm to carry out a complex task, researchers may have the answer. Researchers in Japan have taught volunteers to use a mind controlled robotic arm to help them out in doing two things at once. They say the system could revolutionise factory and construction work. Researchers in Japan have taught volunteers to use a mind controlled robotic arm to help them out in doing two things at once. Engineers from Kyoto's Advanced Telecommunications Research Institute showed some people can be taught to control a third robotic arm with their brains, even using the limb to multitask.

Children who learn two languages as they grow up find it easier to learn a third in later life, a study found. They learn faster than their monolingual counterparts, confirming the theory bilinguals are better at picking up another language, researchers say. Researchers found boosted brain activity in brain scans of bilingual people which showed they learned an extra language using brain processes usually reserved for their native tongue. Children who learn two languages as they grow up find it easier to learn a third in later life, a study found. Learning to speak a second language at any point could help keep your brain sharp as you age, a 2015 study found.

Music follows a set of patterns that can extract feelings from its listeners and provoke emotional responses. While machines can now make music too, they don't give much consideration to the emotional response of their audience. But now a team of researchers has developed a machine-learning device that can detect the emotional state of listeners and make new songs that provoke new feelings. In the study, participants listened to music while wearing wireless headphones that contained brain wave sensors. The team of researchers, under the support of Osaka University's Center of Innovation (COI) program, developed the AI that detects users' brain state and provides a means for activating it through music.

MIT Sloan Management Review posed this question to 15 of the world's foremost experts on the intersection of technology and management who responded in a series of essays now available from MIT SMR. The essays were commissioned to explore how technology is reshaping the practice of management. The impact of digital technology on how businesses design and produce goods, interact with their supply chains, manage internal communication, and connect with customers is a rich topic that has been, and continues to be, broadly addressed in both commercial and academic business media. But as the digital revolution enters its next phase, we find ourselves confronting a new set of questions about the relationship between technology and management. What happens to marketing when marketers can map consumers' brain patterns?

Using a combination of artificial intelligence (AI) and brain scanning technology, a team of researchers has developed a novel method that can help remove specific fears from the brain. The new technique that could read and identify a fear memory can pave way of treating patients with conditions such as post-traumatic stress disorder (PTSD) and phobias, the study said. Neuroscientists, from the University of Tokyo, developed'Decoded Neurofeedback' -- which used brain scanning to monitor activity in the brain, and identify complex patterns of activity that resembled a specific fear memory. In the study, the team included 17 healthy volunteers in whom a fear memory was created by administering a brief electric shock when they saw a certain computer image. Using brain scanner, the researchers monitored the volunteers' mental activity and were able to spot signs of that specific fear memory. Using AI algorithms, they also developed a fast and accurate method of reading the fear.

Words, like people, can achieve a lot more when they work together than when they stand on their own. Words working together make sentences, and sentences can express meanings that are unboundedly rich. How the human brain represents the meanings of sentences has been an unsolved problem in neuroscience, but my colleagues and I recently published work in the journal Cerebral Cortex that casts some light on the question. Here, my aim is to give a bigger-picture overview of what that work was about, and what it told us that we did not know before. To measure people's brain activation, we used fMRI (functional Magnetic Resonance Imaging).

Until we open our mouths to speak, it is possible for most of us to keep our thoughts to ourselves. But computers could soon be able to predict what you are thinking by looking for distinct patterns of activity in your brain that relate to sentences. Researchers have developed a computer program that is able to search for the brain activity related to certain words and then use this to predict a sentence being thought even it hasn't seen it before. Scientists have created a computer model that can predict unspoken sentences by looking at the neural activity in the brain. They say the system is able to get the predictions right around 70 per cent of the time.