The size of monkey brains are influenced by social interactions, a new study revealed, finding more friends in a group leads to larger social regions in the brain. A team of researchers from the University of Pennsylvania in Philadelphia, studied the brains, and social interactions of a group of rhesus macaques living on Cayo Santiago, an island off the coast of Puerto Rico. They found that the number of social connections predicted the size of key nodes in parts of the brain responsible for social decision-making and empathy. Though all these findings relate specifically to free-ranging rhesus macaques, they have possible implications for human behavior, in particular to understanding neuro-developmental disorders like autism, according to the team. Researchers determined that, for macaques with more grooming partners, the mid–superior temporal sulcus (STS) and ventral-dysgranular insula grew larger.

The world's first high-resolution 3D image of a monkey brain has been revealed, in a breakthrough that could pave the way for treatments for human diseases including Parkinson's. A detailed map of a complete macaque monkey brain was created using fluorescent imaging techniques by a team from the Chinese Academy of Sciences in Beijing. The team used a new technique to show how nerve cells are organised and connected within the monkey brain at a'micron resolution'. The human brain comprises nearly a hundred billion nerve cells with delicate and complex connections, and while up to 17 times larger than that of a macaque, it is similar enough for comparisons to be made between the two, researchers claim. Until now, a mouse brain was the largest to be mapped, taking days to create a complete 3D image, but the new technique made it possible to move up to a macaque brain, which is about 200 times larger in volume than that of a mouse.

A simulation that runs faster on a commercial graphics card than on some supercomputers could drastically cut the cost of studying how our brains work. Researchers have long used digital models to better understand our brains in the hope of developing cures for diseases such as Alzheimer's or Parkinson's, but simulating the number of neurons and synapses of even the simplest creature is enormously computationally intensive, meaning even supercomputers struggle.

In a recent podcast discussion Elon Musk had with AI expert Lex Fridman about artificial intelligence, consciousness, and Musk's brain-computer interface company Neuralink, an interesting question arose about Tesla's role as an educator in that realm. Referring specifically to the Smart Summon feature that's part of the company's Version ten firmware, Fridman asked Musk whether he felt the burden of being an AI communicator by exposing people for the first time (on a large scale) to driverless cars. To be honest, Musk's response wasn't really, well, responsive. He deferred to the more commercial-oriented goals of the company: "We're just trying to make people's lives easier with autonomy." The long-term goals of Neuralink are pretty scary for mainstream humans, so to me, this question really deserves a long sit-and-think. After all, we're talking computer self-awareness and capabilities well beyond what we'd consider superhuman and beyond the ability of humans to control after a certain point.

Welcome to a FREE preview of our weekly exclusive! Each week our team goes'Beyond the News' and handcrafts a special edition that includes our thoughts on the biggest stories, why it matters, and how it could impact the future. You can receive this newsletter along with all of our other members-exclusive newsletters, become a premium member for just $3/month. Your support goes a long way for us behind the scenes! In a recent podcast discussion Elon Musk had with AI expert Lex Fridman about artificial intelligence, consciousness, and Musk's brain-computer interface company Neuralink, an interesting question arose about Tesla's role as an educator in that realm.

Failing 15 per cent of the time is the best recipe for success, even more so than not failing at all, finds research. A study led by researchers at the University of Arizona proposed a mathematically devised optimum level of failure. Educational experts have long agreed that there is a'sweet spot' when it comes to learning, reasoning that people learn best when they are challenged to grasp something just outside the bounds of our existing knowledge. When a challenge is too simple, we don't learn anything new. Likewise, our knowledge doesn't improve when a challenge is so hard that we give up entirely.

Artificial intelligence can share our natural ability to make numeric snap judgments. Researchers observed this knack for numbers in a computer model composed of virtual brain cells, or neurons, called an artificial neural network. After being trained merely to identify objects in images -- a common task for AI -- the network developed virtual neurons that respond to specific quantities. These artificial neurons are reminiscent of the "number neurons" thought to give humans, birds, bees and other creatures the innate ability to estimate the number of items in a set (SN: 7/7/18, p. 7). This intuition is known as number sense.

Monkey brains have sections dedicated solely to social interactions, a new finding that researchers say could help us better understand the human mind. Scientists scanning the brains of rhesus macaques found that certain parts were active when the monkeys watched videos of social interactions between other monkeys, but that same network was largely inactive in response to other images. A study in the journal Science said those brain regions that were purely analyzing social interactions are in the same places as the ones in the human brain that are associated with similar processes, like the ones that help us understand other people's intentions and what they are thinking, which is called the theory of mind. As the scientists were showing the monkeys the social videos and scanning their brains, they also followed the monkey's gaze to see where the primates were looking (tracked by a red dot in the gif below). The results were "both unexpected and mind-boggling," researcher Winrich Freiwald said in a statement from Rockefeller University, referring in part to the concept that a brain network would power down when, in the words of the university, it is "denied its preferred input."