Deep image reconstruction now allows computers to read our minds

Imagine a reality where computers can visualize what you are thinking.

Sound far out? It’s now closer to becoming a reality thanks to four scientists at Kyoto University in Kyoto, Japan. In late December, Guohua Shen, Tomoyasu Horikawa, Kei Majima and Yukiyasu Kamitani released the results of their recent research on using artificial intelligence to decode thoughts on the scientific platform, BioRxiv.

Click to access 240317.full.pdf

Machine learning has previously been used to study brain scans (MRIs, or magnetic resonance imaging) and generate visualizations of what a person is thinking when referring to simple, binary images like black and white letters or simple geographic shapes.

But the scientists from Kyoto developed new techniques of “decoding” thoughts using deep neural networks (artificial intelligence). The new technique allows the scientists to decode more sophisticated “hierarchical” images, which have multiple layers of color and structure, like a picture of a bird or a man wearing a cowboy hat, for example.

“We have been studying methods to reconstruct or recreate an image a person is seeing just by looking at the person’s brain activity,” Kamitani, one of the scientists, tells CNBC Make It. “Our previous method was to assume that an image consists of pixels or simple shapes. But it’s known that our brain processes visual information hierarchically extracting different levels of features or components of different complexities.”

And the new AI research allows computers to detect objects, not just binary pixels. “These neural networks or AI model can be used as a proxy for the hierarchical structure of the human brain,” Kamitani says.

For the research, over the course of 10 months, three subjects were shown natural images (like photographs of a bird or a person), artificial geometric shapes and alphabetical letters for varying lengths of time.

In some instances, brain activity was measured while a subject was looking at one of 25 images. In other cases, it was logged afterward, when subjects were asked to think of the image they were previously shown.

Once the brain activity was scanned, a computer reverse-engineered (or “decoded”) the information to generate visualizations of a subjects’ thoughts.

The flowchart, embedded below, is made by the research team at the Kamitani Lab at Kyoto University and breaks down the science of how a visualization is “decoded.”

The two charts embedded below show the results the computer reconstructed for subjects whose activity was logged while they were looking at natural images and images of letters.

As for the subjects’ whose brain waves were measured based on remembering the images, the scientists had another breakthrough.

“Unlike previous methods, we were able to reconstruct visual imagery a person produced by just thinking of some remembered images,” Kamitani says.

As seen in the chart embedded below, when decoding brain signals resulting from a subject remembering images, the AI system had a harder time reconstructing. That’s because it’s more difficult for a human to remember an image of a cheetah or a fish exactly as it was seen.

“The brain is less activated” in that scenario, Kamitani explains to CNBC Make It.

As the accuracy of the technology continues to improve, the potential applications are mind-boggling. The visualization technology would allow you to draw pictures or make art simply by imagining something; your dreams could be visualized by a computer; the hallucinations of psychiatric patients could be visualized aiding in their care; and brain-machine interfaces may one day allow communication with imagery or thoughts, Kamitani tells CNBC Make It.

While the idea of computers reading your brain may sound positively Jetson-esque, the Japanese researchers aren’t alone in their futuristic work to connect the brain with computing power.

For example, former GoogleX-er Mary Lou Jepsen is working to build a hat that will make telepathy possible within the decade, and entrepreneur Bryan Johnson is working to build computer chips to implant in the brain to improve neurological functions.

https://www.cnbc.com/2018/01/08/japanese-scientists-use-artificial-intelligence-to-decode-thoughts.html

Graphene successfully interfaced with neurons in the brain

Scientists have long been on a quest to find a way to implant electrodes that interface with neurons into the human brain. If successful, the idea could have huge implications for the treatment of Parkinson’s disease and other neurological disorders. Last month, a team of researchers from Italy and the UK made a huge step forward by showing that the world’s favorite wonder-material, graphene, can successfully interface with neurons.

Previous efforts by other groups using treated graphene had created an interface with a very low signal to noise ratio. But an interdisciplinary collaborative effort by the University of Trieste and the Cambridge Graphene Centre has developed a significantly improved electrode by working with untreated graphene.

“For the first time we interfaced graphene to neurons directly,” said Professor Laura Ballerini of the University of Trieste in Italy. “We then tested the ability of neurons to generate electrical signals known to represent brain activities, and found that the neurons retained their neuronal signaling properties unaltered. This is the first functional study of neuronal synaptic activity using uncoated graphene based materials.”

Prior to experimenting with graphene-based substrates (GBS), scientists implanted microelectrodes based on tungsten and silicon. Proof-of-concept experiments were successful, but these materials seem to suffer from the same fatal flaws. The body’s reaction to the insertion trauma is to form scarring tissue, inhibiting clear electrical signals. The structures were also prone to disconnecting, due to the stiffness of the materials, which were unsuitable for a semi-fluid organic environment.

Pure graphene is promising because it is flexible, non-toxic, and does not impair other cellular activity.

The team’s experiments on rat brain cell cultures showed that the untreated graphene electrodes interfaced well with neurons, transmitting electrical impulses normally with none of the adverse reactions seen previously.

The biocompatibility of graphene could allow it to be used to make graphene microelectrodes that could help measure, harness and control an impaired brain’s functions. It could be used to restore lost sensory functions to treat paralysis, control prosthetic devices such a robotic limbs for amputees and even control or diminish the impact of the out-of-control electrical impulses that cause motor disorders such as Parkinson’s and epilepsy.

“We are currently involved in frontline research in graphene technology towards biomedical applications,” said Professor Maurizio Prato from the University of Trieste. “In this scenario, the development and translation in neurology of graphene-based high-performance bio-devices requires the exploration of the interactions between graphene nano and micro-sheets with the sophisticated signaling machinery of nerve cells. Our work is only a first step in that direction.”

The results of this research were recently published in the journal ACS Nano. The research was funded by the Graphene Flagship, a European initiative that aims to connect theoretical and practical fields and reduce the time that graphene products spend in laboratories before being brought to market.

http://www.cam.ac.uk/research/news/graphene-shown-to-safely-interact-with-neurons-in-the-brain