Monthly Archives: April 2019
Computers and artificial intelligence continue to usher in major changes in the way people shop. It is relatively easy to train a robot’s brain to create a shopping list, but what about ensuring that the robotic shopper can easily tell the difference between the thousands of products in the store?
Purdue University researchers and experts in brain-inspired computing think part of the answer may be found in magnets. The researchers have developed a process to use magnetics with brain-like networks to program and teach devices such as personal robots, self-driving cars and drones to better generalize about different objects.
“Our stochastic neural networks try to mimic certain activities of the human brain and compute through a connection of neurons and synapses,” said Kaushik Roy, Purdue’s Edward G. Tiedemann Jr. Distinguished Professor of Electrical and Computer Engineering. “This allows the computer brain to not only store information but also to generalize well about objects and then make inferences to perform better at distinguishing between objects.”
The stochastic switching behavior is representative of a sigmoid switching behavior of a neuron. Such magnetic tunnel junctions can be also used to store synaptic weights. Roy presented the technology during the annual German Physical Sciences Conference earlier this month in Germany. The work also appeared in the Frontiers in Neuroscience.
The switching dynamics of a nano-magnet are similar to the electrical dynamics of neurons. Magnetic tunnel junction devices show switching behavior, which is stochastic in nature. The Purdue group proposed a new stochastic training algorithm for synapses using spike timing dependent plasticity (STDP), termed Stochastic-STDP, which has been experimentally observed in the rat’s hippocampus. The inherent stochastic behavior of the magnet was used to switch the magnetization states stochastically based on the proposed algorithm for learning different object representations. “The big advantage with the magnet technology we have developed is that it is very energy-efficient,” said Roy, who leads Purdue’s Center for Brain-inspired Computing Enabling Autonomous Intelligence. “We have created a simpler network that represents the neurons and synapses while compressing the amount of memory and energy needed to perform functions similar to brain computations.”
In a recent study in mice, researchers found a way to deliver specific drugs to parts of the body that are exceptionally difficult to access. Their Y-shaped block catiomer (YBC) binds with certain therapeutic materials forming a package 18 nanometers wide. The package is less than one-fifth the size of those produced in previous studies, so can pass through much smaller gaps. This allows YBCs to slip through tight barriers in cancers of the brain or pancreas.
The fight against cancer is fought on many fronts. One promising field is gene therapy, which targets genetic causes of diseases to reduce their effect. The idea is to inject a nucleic acid-based drug into the bloodstream — typically small interfering RNA (siRNA) — which binds to a specific problem-causing gene and deactivates it. However, siRNA is very fragile and needs to be protected within a nanoparticle or it breaks down before reaching its target.
“siRNA can switch off specific gene expressions that may cause harm. They are the next generation of biopharmaceuticals that could treat various intractable diseases, including cancer,” explained Associate Professor Kanjiro Miyata of the University of Tokyo, who jointly supervised the study. “However, siRNA is easily eliminated from the body by enzymatic degradation or excretion. Clearly a new delivery method was called for.”
Presently, nanoparticles are about 100 nanometers wide, one-thousandth the thickness of paper. This is small enough to grant them access to the liver through the leaky blood vessel wall. However some cancers are harder to reach. Pancreatic cancer is surrounded by fibrous tissues and cancers in the brain by tightly connected vascular cells. In both cases the gaps available are much smaller than 100 nanometers. Miyata and colleagues created an siRNA carrier small enough to slip through these gaps in the tissues.
“We used polymers to fabricate a small and stable nanomachine for the delivery of siRNA drugs to cancer tissues with a tight access barrier,” said Miyata. “The shape and length of component polymers is precisely adjusted to bind to specific siRNAs, so it is configurable.”
“In my head, I churn over every sentence ten times, delete a word, add an adjective, and learn my text by heart, paragraph by paragraph,” wrote Jean-Dominique Bauby in his memoir, “The Diving Bell and the Butterfly.” In the book, Mr. Bauby, a journalist and editor, recalled his life before and after a paralyzing stroke that left him virtually unable to move a muscle; he tapped out the book letter by letter, by blinking an eyelid.
Thousands of people are reduced to similarly painstaking means of communication as a result of injuries suffered in accidents or combat, of strokes, or of neurodegenerative disorders such as amyotrophic lateral sclerosis, or A.L.S., that disable the ability to speak.
Now, scientists are reporting that they have developed a virtual prosthetic voice, a system that decodes the brain’s vocal intentions and translates them into mostly understandable speech, with no need to move a muscle, even those in the mouth. (The physicist and author Stephen Hawking used a muscle in his cheek to type keyboardcharacters, which a computer synthesized into speech.)
“It’s formidable work, and it moves us up another level toward restoring speech” by decoding brain signals, said Dr. Anthony Ritaccio, a neurologist and neuroscientist at the Mayo Clinic in Jacksonville, Fla., who was not a member of the research group.
The new system, described on Wednesday in the journal Nature,deciphers the brain’s motor commands guiding vocal movement during speech — the tap of the tongue, the narrowing of the lips — and generates intelligible sentences that approximate a speaker’s natural cadence. Experts said the new work represented a “proof of principle,” a preview of what may be possible after further experimentation and refinement. The system was tested on people who speak normally; it has not been tested in people whose neurological conditions or injuries, such as common strokes, could make the decoding difficult or impossible. For the new trial, scientists at the University of California, San Francisco, and U.C. Berkeley recruited five people who were in the hospital being evaluated for epilepsy surgery.
Many people with epilepsy do poorly on medication and opt to undergo brain surgery. Before operating, doctors must first locate the “hot spot” in each person’s brain where the seizures originate; this is done with electrodes that are placed in the brain, or on its surface, and listen for telltale electrical storms. Pinpointing this location can take weeks. In the interim, patients go through their days with electrodes implanted in or near brain regions that are involved in movement and auditory signaling. These patients often consent to additional experiments that piggyback on those implants.
Five such patients at U.C.S.F. agreed to test the virtual voice generator. Each had been implanted with one or two electrode arrays: stamp-size pads, containing hundreds of tiny electrodes, that were placed on the surface of the brain. As each participant recited hundreds of sentences, the electrodes recorded the firing patterns of neurons in the motor cortex. The researchers associated those patterns with the subtle movements of the patient’s lips, tongue, larynx and jaw that occur during natural speech. The team then translated those movements into spoken sentences.
When Mile Gu boots up his new computer, he can see the future. At least, 16 possible versions of it — all at the same time. Gu, an assistant professor of physics at Nanyang Technological University in Singapore, works in quantum computing. This branch of science uses the weird laws that govern the universe’s smallest particles to help computers calculate more efficiently.
Tiny particles of light can travel in a superposition of many different states at the same time. Researchers used this quantum quirk to design a prototype computer that can predict 16 different futures at once.
Unlike classical computers, which store information as bits (binary digits of either 0 or 1), quantum computers code information into quantum bits, or qubits. These subatomic particles, thanks to the weird laws of quantum mechanics, can exist in a superposition of two different states at the same time.
Just as Schrödinger‘s hypothetical cat was simultaneously dead and alive until someone opened the box, a qubit in a superposition can equal both 0 and 1 until it’s measured. Storing multiple different outcomes into a single qubit could save a ton of memory compared to traditional computers, especially when it comes to making complicated predictions.
In a study published April 9 in the journal Nature Communications, Gu and his colleagues demonstrated this idea using a new quantum simulator that can predict the outcomes of 16 different futures (the equivalent of, say, flipping a coin four times in a row) in a quantum superposition. These possible futures were encoded in a single photon (a quantum particle of light) which moved down multiple paths simultaneously while passing through several sensors. Then, the researchers went one step further, firing two photons side-by-side and tracking how each photon’s potential futures diverged under slightly different conditions.
“It’s sort of like Doctor Strange in the ‘Avengers: Infinity War‘” movie, Gu told Live Science. Before a climactic battle in that film, the clairvoyant doctor looks forward in time to see 14 million different futures, hoping to find the one where the heroes defeat the big baddie. “He does a combined computation of all these possibilities to say, ‘OK, if I changed my decision in this small way, how much will the future change?’ This is the direction our simulation is moving forwards to.”
Imagine a future technology that would provide instant access to the world’s knowledge and artificial intelligence, simply by thinking about a specific topic or question. Communications, education, work, and the world as we know it would be transformed. Writing in Frontiers in Neuroscience, an international collaboration led by researchers at UC Berkeley and the US Institute for Molecular Manufacturing predicts that exponential progress in nanotechnology, nanomedicine, AI, and computation will lead this century to the development of a “Human Brain/Cloud Interface” (B/CI), that connects neurons and synapses in the brain to vast cloud-computing networks in real time.
The B/CI concept was initially proposed by futurist-author-inventor Ray Kurzweil, who suggested that neural nanorobots – brainchild of Robert Freitas, Jr., senior author of the research – could be used to connect the neocortex of the human brain to a “synthetic neocortex” in . Our wrinkled neocortex is the newest, smartest, ‘conscious’ part of the brain. Freitas’ proposed neural nanorobots would provide direct, real-time monitoring and control of signals to and from brain cells.
“These devices would navigate the human vasculature, cross the blood-brain barrier, and precisely autoposition themselves among, or even within brain cells,” explains Freitas. “They would then wirelessly transmit encoded information to and from a cloud-based supercomputer network for real-time brain-state monitoring and data extraction.”
This cortex in the cloud would allow “Matrix“-style downloading of information to the brain, the group claims. “A human B/CI system mediated by neuralnanorobotics could empower individuals with instantaneous access to all cumulative human knowledge available in the cloud, while significantly improving human learning capacities and intelligence,” says lead author Dr. Nuno Martins.
B/CI technology might also allow us to create a future “global superbrain” that would connect networks of individual human brains and AIs to enable collective thought. “While not yet particularly sophisticated, an experimental human ‘BrainNet’ system has already been tested, enabling thought-driven information exchange via the cloud between individual brains,” explains Martins. “It used electrical signals recorded through the skull of ‘senders’ and magnetic stimulation through the skull of ‘receivers,’ allowing for performing cooperative tasks. “With the advance of neuralnanorobotics, we envisage the future creation of ‘superbrains’ that can harness the thoughts and thinking power of any number of humans and machines in real time. This shared cognition could revolutionize democracy, enhance empathy, and ultimately unite culturally diverse groups into a truly global society.”
According to the group’s estimates, even existing supercomputers have processing speeds capable of handling the necessary volumes of neural data for B/CI – and they’re getting faster, fast. Rather, transferring neural data to and from supercomputers in the cloud is likely to be the ultimate bottleneck in B/CI development. “This challenge includes not only finding the bandwidth for global data transmission,” cautions Martins, “but also, how to enable data exchange with neurons via tiny devices embedded deep in the brain.”
One solution proposed by the authors is the use of ‘magnetoelectric nanoparticles‘ to effectively amplify communication between neurons and the cloud. “These nanoparticles have been used already in living mice to couple external magnetic fields to neuronal electric fields – that is, to detect and locally amplify these magnetic signals and so allow them to alter the electrical activity of neurons,” explains Martins. “This could work in reverse, too: electrical signals produced by neurons and nanorobots could be amplified via magnetoelectric nanoparticles, to allow their detection outside of the skull.” Getting these nanoparticles – and nanorobots – safely into the brain via the circulation, would be perhaps the greatest challenge of all in B/CI.
“A detailed analysis of the biodistribution and biocompatibility of nanoparticles is required before they can be considered for human development. Nevertheless, with these and other promising technologies for B/CI developing at an ever-increasing rate, an ‘internet of thoughts’ could become a reality before the turn of the century,” Martins concludes.
Researchers at Tel Aviv University have managed to 3D print a heart using a patient’s cells and biological materials — a first. Scientists have previously built synthetic hearts and bio-engineered tissues using a patient’s cells. But the latest feat is the first time scientists have created a complex organ with biological materials.
“This is the first time anyone anywhere has successfully engineered and printed an entire heart replete with cells, blood vessels, ventricles and chambers,” lead researcher Tal Dvir, a material scientist and professor of molecular cell biology at TAU, said in a news release.
The proof-of-concept feat could pave the way for a new type of organ transplant. For patients with late stage heart failure, a heart transplant is the only solution. But there is a lack of heart donors.
“This heart is made from human cells and patient-specific biological materials. In our process these materials serve as the bioinks, substances made of sugars and proteins that can be used for 3D printing of complex tissue models,” Dvir said. “Our results demonstrate the potential of our approach for engineering personalized tissue and organ replacement in the future.”
The heart scientists printed couldn’t be used in a human transplant operation. Though completely vascularized, it’s too small at about the size of a rabbit heart. “But larger human hearts require the same technology.” Dvir said.
Researchers detailed their breakthrough this week in the journal Advanced Science.