Scientists Turn Memories Off and On With Flip of Switch

Scientists Turn Memories Off and On With Flip of Switch

  8:10:00 PM    Science Lover

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Scientists have developed a way to turn memories on and off -- literally with the flip of a switch. Using an electronic system that duplicates the neural signals associated with memory, they managed to replicate the brain function in rats associated with long-term learned behavior, even when the rats had been drugged to forget.

In the experiment, the researchers had rats learn a task, 
pressing one lever rather than another to receive a reward. 
Using embedded electrical probes, the experimental research 
team recorded changes in the rat's brain activity between 
the two major internal divisions of the hippocampus, known 
as subregions CA3 and CA1. The experimenters then blocked 
the normal neural interactions between the two areas using 
pharmacological agents. The previously trained rats then 
no long displayed the long-term learned behavior. But long-
term memory capability returned to the pharmacologically 
blocked rats when the team activated the electronic device 
programmed to duplicate the memory-encoding function. 
(Credit: USC Viterbi School of Engineering)

"Flip the switch on, and the rats remember. Flip it off, and the rats forget," said Theodore Berger of the USC Viterbi School of Engineering's Department of Biomedical Engineering.

Berger is the lead author of an article that will be published in the Journal of Neural Engineering. His team worked with scientists from Wake Forest University in the study, building on recent advances in our understanding of the brain area known as the hippocampus and its role in learning.



In the experiment, the researchers had rats learn a task, pressing one lever rather than another to receive a reward. Using embedded electrical probes, the experimental research team, led by Sam A. Deadwyler of the Wake Forest Department of Physiology and Pharmacology, recorded changes in the rat's brain activity between the two major internal divisions of the hippocampus, known as subregions CA3 and CA1. During the learning process, the hippocampus converts short-term memory into long-term memory, the researchers prior work has shown.

"No hippocampus," says Berger, "no long-term memory, but still short-term memory." CA3 and CA1 interact to create long-term memory, prior research has shown.

In a dramatic demonstration, the experimenters blocked the normal neural interactions between the two areas using pharmacological agents. The previously trained rats then no longer displayed the long-term learned behavior.

"The rats still showed that they knew 'when you press left first, then press right next time, and vice-versa,'" Berger said. "And they still knew in general to press levers for water, but they could only remember whether they had pressed left or right for 5-10 seconds."

Using a model created by the prosthetics research team led by Berger, the teams then went further and developed an artificial hippocampal system that could duplicate the pattern of interaction between CA3-CA1 interactions.

Long-term memory capability returned to the pharmacologically blocked rats when the team activated the electronic device programmed to duplicate the memory-encoding function.

In addition, the researchers went on to show that if a prosthetic device and its associated electrodes were implanted in animals with a normal, functioning hippocampus, the device could actually strengthen the memory being generated internally in the brain and enhance the memory capability of normal rats.

"These integrated experimental modeling studies show for the first time that with sufficient information about the neural coding of memories, a neural prosthesis capable of real-time identification and manipulation of the encoding process can restore and even enhance cognitive mnemonic processes," says the paper.

Next steps, according to Berger and Deadwyler, will be attempts to duplicate the rat results in primates (monkeys), with the aim of eventually creating prostheses that might help the human victims of Alzheimer's disease, stroke or injury recover function.

The paper is entitled "A Cortical Neural Prosthesis for Restoring and Enhancing Memory." Besides Deadwyler and Berger, the other authors are, from USC, BME Professor Vasilis Z. Marmarelis and Research Assistant Professor Dong Song, and from Wake Forest, Associate Professor Robert E. Hampson and Post-Doctoral Fellow Anushka Goonawardena.

Berger, who holds the David Packard Chair in Engineering, is the Director of the USC Center for Neural Engineering, Associate Director of the National Science Foundation Biomimetic MicroElectronic Systems Engineering Research Center, and a Fellow of the IEEE, the AAAS, and the AIMBE

"A Cortical Neural Prosthesis for Restoring and Enhancing Memory." (Berger et al 2011 J. Neural Eng. 8 046017)

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'Smart cars' that are actually, well, smart

'Smart cars' that are actually, well, smart

  8:57:00 PM    Science Lover

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Since 2000, there have been 110 million car accidents in the United States, more than 443,000 of which have been fatal — an average of 110 fatalities per day. These statistics make traffic accidents one of the leading causes of death in this country, as well as worldwide.

The researchers test their algorithm using a miniature
autonomous vehicle traveling along a track that partially
overlaps with a second track for a human-controlled vehicle,
observing incidences of collision and collision avoidance.
Photo: Melanie Gonick

Engineers have developed myriad safety systems aimed at preventing collisions: automated cruise control, a radar- or laser-based sensor system that slows a car when approaching another vehicle; blind-spot warning systems, which use lights or beeps to alert the driver to the presence of a vehicle he or she can’t see; and traction control and stability assist, which automatically apply the brakes if they detect skidding or a loss of steering control.

Still, more progress must be made to achieve the long-term goal of “intelligent transportation”: cars that can “see” and communicate with other vehicles on the road, making them able to prevent crashes virtually 100 percent of the time.

Of course, any intelligent transportation system (ITS), even one that becomes a mainstream addition to new cars, will have to contend with human-operated vehicles as long as older cars remain on the road — that is, for the foreseeable future. To this end, MIT mechanical engineers are working on a new ITS algorithm that takes into account models of human driving behavior to warn drivers of potential collisions, and ultimately takes control of the vehicle to prevent a crash.

The theory behind the algorithm and some experimental results will be published in the journal IEEE Robotics and Automation Magazine. The paper is co-authored by Rajeev Verma, who was a visiting PhD student at MIT this academic year, and Domitilla Del Vecchio, assistant professor of mechanical engineering and W. M. Keck Career Development Assistant Professor in Biomedical Engineering.

Avoiding the car that cried wolf

According to Del Vecchio, a common challenge for ITS developers is designing a system that is safe without being overly conservative. It’s tempting to treat every vehicle on the road as an “agent that’s playing against you,” she says, and construct hypersensitive systems that consistently react to worst-case scenarios. But with this approach, Del Vecchio says, “you get a system that gives you warnings even when you don’t feel them as necessary. Then you would say, ‘Oh, this warning system doesn’t work,’ and you would neglect it all the time.”

That’s where predicting human behavior comes in. Many other researchers have worked on modeling patterns of human driving. Following their lead, Del Vecchio and Verma reasoned that driving actions fall into two main modes: braking and accelerating. Depending on which mode a driver is in at a given moment, there is a finite set of possible places the car could be in the future, whether a tenth of a second later or a full 10 seconds later. This set of possible positions, combined with predictive models of human behavior — when and where drivers slow down or speed up around an intersection, for example — all went into building the new algorithm.

The result is a program that is able to compute, for any two vehicles on the road nearing an intersection, a “capture set,” or a defined area in which two vehicles are in danger of colliding. The ITS-equipped car then engages in a sort of game-theoretic decision, in which it uses information from its onboard sensors as well as roadside and traffic-light sensors to try to predict what the other car will do, reacting accordingly to prevent a crash.

When both cars are ITS-equipped, the “game” becomes a cooperative one, with both cars communicating their positions and working together to avoid a collision.

Steering clear of the ‘bad set’

Del Vecchio and Verma tested their algorithm with a laboratory setup involving two miniature vehicles on overlapping circular tracks: one autonomous and one controlled by a human driver. Eight volunteers participated, to account for differences in individual driving styles. Out of 100 trials, there were 97 instances of collision avoidance. The vehicles entered the capture set three times; one of these times resulted in a collision.

In the three “failed” trials, Del Vecchio says the trouble was largely due to delays in communication between ITS vehicles and the workstation, which represents the roadside infrastructure that captures and transmits information about non-ITS-equipped cars. In these cases, one vehicle may be making decisions based on information about the position and speed of the other vehicle that is off by a fraction of a second. “So you may end up actually being in the capture set while the vehicles think you are not,” Del Vecchio says.



One way to handle this problem is to improve the communication hardware as much as possible, but the researchers say there will virtually always be delays, so their next step is to make the system robust to these delays — that is, to ensure that the algorithm is conservative enough to avoid a situation in which a communication delay could mean the difference between crashing and not crashing.

Jim Freudenberg, a professor of electrical and computer engineering at the University of Michigan, says that although it’s nearly impossible to correctly predict human behavior 100 percent of the time, Del Vecchio and Verma’s approach is promising. “Human-controlled technologies and computer-controlled technologies are coming more and more into contact with one other, and we have to have some way of making assumptions about the human — otherwise, you can’t do anything because of how conservative you have to be,” he says.

The researchers have already begun to test their system in full-size passenger vehicles with human drivers. In addition to learning from these real-life trials, future work will focus on incorporating human reaction-time data to refine when the system must actively take control of the car and when it can merely provide a passive warning to the driver.

Eventually, the researchers also hope to build in sensors for weather and road conditions and take into account car-specific manufacturing details — all of which affect handling — to help their algorithm make even better informed decisions.

This story is republished courtesy of MIT News (http://web.mit.edu/newsoffice/), a popular site that covers news about MIT research, innovation and teaching.

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Artificial Foot Recycles Energy for Easier Walking

Artificial Foot Recycles Energy for Easier Walking

  1:01:00 AM    Science Lover

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An artificial foot that recycles energy otherwise wasted in between steps could make it easier for amputees to walk, its developers say.

Developers say that an artificial foot that recycles energy otherwise wasted in between steps could make it easier for amputees to walk. (Credit: Image courtesy of University of Michigan)

"For amputees, what they experience when they're trying to walk normally is what I would experience if I were carrying an extra 30 pounds," said Art Kuo, professor in the University of Michigan departments of Biomedical Engineering and Mechanical Engineering.

Compared with conventional prosthetic feet, the new prototype device significantly cuts the energy spent per step.

A paper about the device is published in the Feb. 17 edition of in the journal PLoS ONE. The foot was created by Kuo and Steve Collins, who was then a U-M graduate student. Now Collins is an associate research fellow at Delft University of Technology in the Netherlands.

The human walking gait naturally wastes energy as each foot collides with the ground in between steps.

A typical prosthesis doesn't reproduce the force a living ankle exerts to push off of the ground. As a result, test subjects spent 23 percent more energy walking with a conventional prosthetic foot, compared with walking naturally. To test how stepping with their device compared with normal walking, the engineers conducted their experiments with non-amputees wearing a rigid boot and prosthetic simulator.

In their energy-recycling foot, the engineers put the wasted walking energy to work enhancing the power of ankle push-off. The foot naturally captures the dissipated energy. A microcontroller tells the foot to return the energy to the system at precisely the right time.

Based on metabolic rate measurements, the test subjects spent 14 percent more energy walking in energy-recycling artificial foot than they did walking naturally. That's a significant decrease from the 23 percent more energy they used in the conventional prosthetic foot, Kuo says.

"We know there's an energy penalty in using an artificial foot," Kuo said. "We're almost cutting that penalty in half."

He explained how this invention differs from current technologies.

"All prosthetic feet store and return energy, but they don't give you a choice about when and how. They just return it whenever they want," Kuo said. "This is the first device to release the energy in the right way to supplement push-off, and to do so without an external power source."

Other devices that boost push-off power use motors and require large batteries.

Because the energy-recycling foot takes advantage of power that would otherwise be lost, it uses less than 1 Watt of electricity through a small, portable battery.

"Individuals with lower limb amputations, such as veterans of the conflicts in Iraq and Afghanistan or patients suffering from diabetes, often find walking a difficult task. Our new design may restore function and reduce effort for these users," Collins said. "With further progress, robotic limbs may yet beat their biological forerunners."

This paper demonstrates that the engineers' idea works. They are now testing the foot on amputees at the Seattle Veterans Affairs Medical Center. Commercial devices based on the technology are under development by an Ann Arbor company. This research was funded by the National Institutes of Health and the Department of Veterans Affairs.

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Heart Cells on Lab Chip Display 'Nanosense' That Guides Behavior

Heart Cells on Lab Chip Display 'Nanosense' That Guides Behavior

  11:30:00 PM    Science Lover

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Johns Hopkins biomedical engineers, working with colleagues in Korea, have produced a laboratory chip with nanoscopic grooves and ridges capable of growing cardiac tissue that more closely resembles natural heart muscle. Surprisingly, heart cells cultured in this way used a "nanosense" to collect instructions for growth and function solely from the physical patterns on the nanotextured chip and did not require any special chemical cues to steer the tissue development in distinct ways.

Johns Hopkins researchers developed this chip to culture heart cells that more closely resemble natural cardiac tissue. (Credit: Will Kirk/homewoodphoto.jhu.edu)

The scientists say this tool could be used to design new therapies or diagnostic tests for cardiac disease.

The device and experiments using it were described online in the Early Edition of Proceedings of the National Academy of Sciences. The work, a collaboration with Seoul National University, represents an important advance for researchers who grow cells in the lab to learn more about cardiac disorders and possible remedies.

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RNA Network Seen in Live Bacterial Cells for First Time

RNA Network Seen in Live Bacterial Cells for First Time

  12:49:00 AM    Science Lover

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Scientists who study RNA have faced a formidable roadblock: trying to examine RNA's movements in a living cell when they can't see the RNA. Now, a new technology has given scientists the first look ever at RNA in a live bacteria cell -- a sight that could offer new information about how the molecule moves and works.

These are fluorescent images of E. coli bacterial cells with visualized RNA. The bar denotes 2 microns. (Credit: Image courtesy of Natalia E. Broude, Ph.D. / Department of Biomedical Engineering, Boston University)

Interest in RNA, which plays a key role in manufacturing proteins, has increased in recent years, due in large part to its potential in new drug therapies. RNA localization and movement in bacterial cell are poorly understood. The problem has been finding a way to mark RNA in a living cell so that scientists can track it, says Natasha Broude, a research associate professor at Boston University's Department of Biomedical Engineering.

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