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Roboticists frequently turn to nature for inspiration for their inventions, reverse engineering the traits that evolution has developed over millennia. Others are taking a shortcut by simply integrating modern technology with living animals.
The idea may seem crazy, but animals and machines are not so different. Just as a network of wires carry electrical signals between a robot’s sensors, processing units and motors, the flow of action potentials around our nervous system connects our sensory organs, brain and muscles.
But while there are similarities, the natural world has come up with some intricate solutions to problems that engineers are nowhere near replicating in silicon. That has prompted some scientists to try and piggyback on evolution’s innovations by building part-animal, part-machine cyborgs. Here’s a rundown of some of the most eye-catching examples.
1. Light-controlled dragonflies
In January, R&D company Draper and the Howard Hughes Medical Institute announced a partnership aimed at turning dragon flies into miniature drones. They are relying on an approach called optogenetics, whereby the animal is genetically modified so that certain neurons feature light-sensitive ion channels.
A close-up of the electronics that fold into the dragonfly's backpack (pictured at the top of the article). Image Credit: DraperThis allows these neurons to be controlled by pulses of light, which is far more targeted than using electrical stimulus. The researchers are also developing a tiny backpack light enough for the dragonflies to carry that contains all of the necessary control electronics, as well as integrated guidance and navigation systems that could make the dragonfly-drones fully autonomous. They hope these flying cyborgs could one day carry small payloads, conduct surveillance and aid in research.
2. Joy-riding moths
Compact chemical detectors able to detect trace elements of a substance continue to elude engineers, which is why we still rely on dogs to sniff out things like drugs, bombs and disaster victims. But man’s best friend may soon face some stiff competition from moth-controlled robotic cars.
In the study, moths controlled their vehicles by moving their feet over what is effectively an upside-down computer mouse trackball. When the moths detected the scent of female moth sex pheromones they attempted to walk towards the source, and the robotic cars were able to accurately replicate their intended route. The researchers say in the future they should be able to genetically engineer the moth pilots to seek out other odors, such as those of explosives or drugs.

3. Remote-control bugs
There have been multiple efforts to create remote-controlled insects, with cockroaches taking the brunt of our experiments. You can buy a RoboRoach kit for $150 that can be attached to the animal’s back and allows you to control it by stimulating its antennae. Scientists dissatisfied with that level of control stuck electrodes into a cockroach’s nervous system for even greater precision.
For some, though, even that was not enough, and now researchers have directly wired up the leg muscles of a giant beetle and developed sequences of electrical stimulation that allowed them to control the speed with which the insects walk. The next step is to independently control all six of the bug’s legs.
4. Magnetic mind-control of mice
Using a similar approach to optogenetics, researchers introduced a protein into the neurons of mice that can trigger a nerve impulse when subjected to a magnetic field. The neurons in question were involved in the reward center of the rodents’ brains, and when placed into an enclosure, they split between magnetized and non-magnetized sections.
The mice with the so-called “Magneto” protein spent much more time in the magnetized areas than mice that did not. They also injected Magneto into the neurons of zebrafish larvae that control an escape response that causes them to coil up. When subjected to a magnetic field, they did just that.
5. Interfaced sheep
DARPA has developed a so-called stentrode — portmanteau of stent and electrode — that it injected into blood vessels in the neck of sheep. Stents are small mesh tubes normally fed into arteries then expanded to keep the passageway open to help treat cardiovascular disease.
This stentrode, on the other hand, is guided from the neck to a vein deep in the sheep’s brain, where it’s implanted to take “high-fidelity measurements” of brain cells. While sheep have found themselves the unwitting victims of DARPA’s tinkering, humans are the ultimate target, with the aim of doing things like controlling prosthetics directly from the brain. Human trials are scheduled for this year.
6. Cyborg plants
It’s not just animals that scientists seem intent on hooking up to machines. In 2015, Swedish researchers created the first “e-plant” by filling the veins of a garden rose with conductive polymer. They showed the subsequent wires could carry a current, and the leaves even slightly changed color in response to the voltage.
This year, the same went a step further by using the same approach to build energy-storing supercapacitors inside plants. Two parallel wires running through the plants’ veins were used as electrodes, and the plant material separating them acted as an electrolyte. The researchers say this could lead to plants with their own energy storage systems that could power sensors and actuators for a host of applications.
Image Credit: Draper Continue reading →

If you’ve ever played around with an old music amplifier, you probably know what a firing neuron sounds like.
A sudden burst of static? Check. A rapid string of pops, like hundreds of bursting balloons? Check. A rough, scratchy bzzzz that unexpectedly assaults your ears? Check again.
Neuroscientists have long used an impressive library of tools to eavesdrop on the electrical chattering of neurons in lab animals. Like linguists deciphering an alien communication, scientists carefully dissect the patterns of neural firing to try to distill the grammatical rules of the brain—the “neural code.”
By cracking the code, we may be able to emulate the way neurons communicate, potentially leading to powerful computers that work like the brain.
It’s been a solid strategy. But as it turns out, scientists may have been only brushing the surface—and missing out on a huge part of the neural conversation.
Recently, a team from UCLA discovered a hidden layer of neural communication buried within the long, tortuous projections of neurons—the dendrites. Rather than acting as passive conductors of neuronal signals, as previously thought, the scientists discovered that dendrites actively generate their own spikes—five times larger and more frequently than the classic spikes stemming from neuronal bodies (dubbed “soma” in academic spheres).

"It’s like suddenly discovering that cables leading to your computer’s CPU can also process information—utterly bizarre, and somewhat controversial."

“Knowing [dendrites] are much more active than the soma fundamentally changes the nature of our understanding of how the brain computes information,” says Dr. Mayank Mehta, who led the study.
These findings suggest that learning may be happening at the level of dendrites rather than neurons, using fundamentally different rules than previously thought, Mehta explained to Singularity Hub.
Recording pains
How has such a wealth of computational power previously escaped scientists’ watchful eyes?
Part of it is mainstream neuroscience theory. According to standard teachings, dendrites are passive cables that shuttle electrical signals to the neuronal body, where all the computation occurs. If the integrated signals reach a certain threshold, the cell body generates a sharp electrical current—a spike—that can be measured by sophisticated electronics and amplifiers. These cell body spikes are believed to be the basis of our cognitive abilities, so of course, neuroscientists have turned their focus to deciphering their meanings.
But recent studies in brain slices suggest that the story’s more complicated. When recording from dendrites on neurons in a dish, scientists noticed telltale signs that they may also generate spikes, independent of the cell body. It’s like suddenly discovering that cables leading to your computer’s CPU can also process information—utterly bizarre, and somewhat controversial.
Although these dendritic spikes (or “dendritic action potentials”) have been observed in slices and anesthetized animals, whether they occur in awake animals and contribute to behavior is an open question, explains the team in their paper.
To answer the question, the team decided to record from dendrites in animals going about their daily business. It’s a gigantic challenge: the average diameter of a dendrite is 100 times smaller than a single human hair—imagine trying to hit one with an electrode amongst a jungle of intertwined projections in the brain, without damaging anything else, while the animal is walking around!
Then there’s the actual recording aspect. Scientists usually carefully puncture the membrane with a sharp electrode to pick up signals from the cell body. Do the same to a delicate dendrite, and it shreds into tiny bits.
To get around all these issues, the UCLA team devised a method that allows them to place their electrode near, rather than inside, the dendrites of rats. After a slew of careful experiments to ensure that they were in fact picking up dendritic signals, the team finally had a tool to eavesdrop on their activity—and stream it live to computers—for the first time.
Dendritic curiosities
For four days straight, the team monitored their recordings while the rats ate, slept and navigated their way around a maze. The team implanted electrodes into a brain area that’s responsible for planning movements, called the posterior parietal cortex, and patiently waited for signs of chitchatting dendrites.
Overnight, signals appeared on the team’s computer monitor that looked like jagged ocean waves, with each protrusion signaling a spike. Not only were the dendrites firing off action potentials, they were doing so in droves. As the rats slept, the dendrites were chatting away, spiking five times more than the cell bodies from which they originate. When awake and exploring the maze, the firing rate jacked up to ten-fold.
What’s more, the dendrites were also “smart” in that they adapted their firing with time—a kind of plasticity that’s only been observed in neuronal bodies before. Since learning fundamentally relies on the ability to adapt and change, this suggests that the branches may potentially be able to “learn” on their own.
Because the dendrites are so much more active than the cell body, it suggests that a lot of activity and information processing in a neuron is happening in the dendrites without informing the cell body, says Mehta.

"Based purely on volume, because dendrites are 100 times larger than the cell body, it could mean that brains have 100 times more processing capacity than we previously thought."

This semi-independence raises a tantalizing idea: that each dendritic branch can act as a computational unit and process information, much like the US states having their own governance that works in parallel with federal oversight.
Neuroscientists have always thought that learning happens when the cell body of two neurons “fire together, wire together.” But our results indicate that learning takes place when the input neuron and dendritic spike—rather than cell body spike—happen at the same time, says Mehta.
“This is a fundamentally different learning rule,” he adds.
Curiouser and curiouser
What’s even stranger is how the dendrites managed their own activity. Neuron spikes—the cell body type—is often considered “all or none,” in that you either have an action potential or not.
Zero or one; purely digital.
While dendrites can fire digitally, in addition, they also generated large, graded fluctuations roughly twice as large as the spikes themselves.
“This large range…shows analog computation in the dendrite. This has never been seen before in any neural activity patterns,” says Mehta.
So if dendrites can compute, what are they calculating?
The answer seems to be the here and now. The team looked at how both cell body and dendrites behaved while the rats explored the maze. While the cell body shot off spikes in anticipation of a behavior—turning a corner, stopping or suddenly rushing forward—the dendrites seemed to perform their computations right when the animal does something.
“Our findings suggest [that] individual cortical neurons take information about the current state of the world, present in the dendrites, and form an anticipatory, predictive response at the soma,” explain the authors, adding that this type of computation is often seen in artificial neural network models.
The team plans to take their dendritic recordings to virtual reality in future studies, to understand how networks of neurons learn abstract concepts such as space and time.
The secret lives of neurons
What this study shows is that we’ve been underestimating the computational power of the brain, says Mehta. Based purely on volume, because dendrites are 100 times larger than the cell body, it could mean that brains have 100 times more processing capacity than we previously thought, at least for rats.
But that’s just a rough estimate. And no doubt the number will change as scientists dig even deeper into the nuances of how neurons function.
This hybrid digital-analog, dendrite-soma, duo-processor parallel computing “is a major departure from what neuroscientists have believed for about 60 years,” says Mehta. It’s like uncovering a secret life of neurons, he adds.
These findings could galvanize other fields that aim to emulate the brain, like artificial intelligence or engineering new kinds of neuron-like computer chips to dramatically boost their computational prowess.
And if repeated by other researchers in the field, our neuroscience textbooks are set with a massive overhaul.
Neurons will no longer be the basic computational unit of the brain—dendrites, with their strange analog-digital hybrid code, will take that throne.
Image Credit: NIH/NICHD/FlickrCC Continue reading →

"Technophobes"—people who fear robots, artificial intelligence and new technology that they don't understand—are much more likely to be afraid of losing their jobs to technology and to suffer anxiety-related mental health issues, a Baylor University study found. Continue reading →