The analog memory storage system builds upon past work developed by scientists that programed cells to flip DNA sections when events – like exposure to specific chemicals – occurred. What sets the new research apart, however, is the addition exposure duration and intensity to the cell-reported information.
The older research has also largerly been relegated to bacteria. Moving the technology to human cells means, among other things, a potential method for studying the ways in which cellular events like gene regulation impact disease, according to MIT associate professor of electrical engineering and computer science, and of biological engineering, Timothy Lu.
The researchers are also able to get a bit fancier with things, with cells capable of recording multiple different input sources – in the case of this demo, doxycycline (an antibiotic and the lactose-like molecule, IPTG.
All of the information allows for a much closure study on the impact of infections and diseases like cancer. It could also potentially be used to follow the role of specialized cells during development from an embryo to full grown adult.
— Source [MIT]: MIT engineers human cells to store ‘memories’ in DNA
In an attempt to better understand neuromuscular conditions like ALS, engineers at MIT have developed a quarter-sized chip housing a muscle strip and some motor neurons. The setup is designed to recreate the neuromuscular junction, the bit of chemical synapse where neurons and muscle fibers meet.
The team has developed a method for creating muscle response by shining a light onto the neuron set, creating a twitch or contraction. The chip is designed to better understand the junction and the diseases that impact it.
The device was created using mice cells, which were separated out into motor neurons and muscle components and fused into those parts. Pillars were inserted into the muscle fiber dring the process to help visualize displacement and create a a method for detecting the force that was exerted during muscle contraction.
That, in turn, was inserted into a gel-filled device designed to simulate an in vitro environment, creating a more realistic space than the traditional petri dish that could help duplicate the natural separation between nerves and muscles that occurs in the human body.
— Source [MIT]: Replicating the connection between muscles and nerves
What you see is a wireless sensor, and someday, doctors could slip it into our bodies to monitor our organs like a microscopic Fitbit or even to give quadri- and paraplegics the power to control robotic arms or legs. A team of scientists from the University of California, Berkeley have developed an early iteration of the sensor that’s about the size of a grain of rice. Each sensor has a piezoelectric crystal that can convert ultrasound vibrations into energy. It also allows the teensy device to beam back data collected from nerve cells in the brain if it’s used to control bionic limbs.
While the current version, which is only 3 millimeters long with a 1 millimeter cube attached to it, is already tiny, the team plans to shrink it down further. They’re looking to create a version that’s half the width of human hair — they are calling the sensors “neural dust,” after all — using components that can last inside a human body forever. That way, people who need prosthetics won’t have to deal with relatively humongous implantable electrodes that can only last for a year or two.
Team member Ryan Neely said:
The original goal of the neural dust project was to imagine the next generation of brain-machine interfaces, and to make it a viable clinical technology. If a paraplegic wants to control a computer or a robotic arm, you would just implant this electrode in the brain and it would last essentially a lifetime.
Besides monitoring organs and controlling prosthetics, the team believes the sensors could also be used to keep an eye on tumors and even on the efficacy of cancer therapies. They also think a version of the sensor could be developed to stimulate nerves and muscles or even to treat disorders like epilepsy. It would most likely take some time before they can develop all these applications, though. They’ve already (successfully) tested the current version on lab rats, but they still have to figure out how to achieve their 50-micron target size.
— Source [UC Berkeley]: Sprinkling of neural dust opens door to electroceuticals
Computers have long been compared to artificial brains, but now IBM has followed the comparison and built a working artificial neuron. The tech giant’s research center in Zurich created 500 of them to simulate a signal transfer similar to how the process works in an organic brain.
As other research in artificial signaling demonstrate, the real milestones are had when elements can be shrunk down to microscopic scale and still work. That’s what makes IBM’s accomplishment significant: their faux neurons are built out of well-known materials that can scale down to a few nanometers but can still activate with low energy.
Organic neurons have membranes acting as signal gates that take a certain amount of energy to absorb. In the IBM version, that role is taken by a square of Germanium-Antimony-Tellerium (GST), a common ingredient in optical disks. Heat the GST enough and it changes its physical phase, from an amorphous insulator to a crystalline conductor. In other words, signal passes through when the faux membrane is hit with enough electricity to change into its crystal phase, then it resets to its amorphous one.
But the scientists needed the artificial neuron to have another characteristic of its organic counterpart: stochiasticity, or some randomness in when signals will fire. IBM says its neurons achieve this because its GST membranes never reset to the same configuration. This lets groups of them unexpectedly accomplish things that they could not if their results were perfectly predictable.
With these neurons, scientists may be able to create computers mimicking the efficient, parallel processing design of organic brains and apply its style of approach to decision-making and processing sensory information; but as point out, constructing it might be the easy point: writing software for that kind of setup will be another challenge entirely.
— Source [IBM]: IBM researcher builds a phase-change capable artificial neuron