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Posts Tagged ‘neurology’

At the center of these findings is a cluster of cells in the hypothalamus, specifically in the ventromedial hypothalamus (VMH), an area that previous studies have associated with sexual behaviors (for a longer, more detailed account, we highly recommend clicking through to SciAm’s story on this). With the help of a “sexually experienced” male mouse that is also known for being quite territorial, a team of CalTech researchers was able to get a firm scientific grip on the role of the VMH in aggression as well as sexual behaviors.

That may sound somewhat intuitive, but the way it came about is perfectly fascinating, mainly because the researchers found that while the urges to fight and to mate come from the same part of the brain, they come from intermingled yet separate clusters of neurons in the VMH. Overlap was only something like 20 percent.

The researchers made this discovery by inserting electrodes near the VMH and listening in during several mouse-to-mouse encounters. In some cases, they would introduce a sexually receptive female into their test subject’s cage, at which point mating would ensue. In other instances, they would introduce another male, leading to violence. And they found that generally the brain can make love or make war, but it can’t really do both at the same time; there is an interplay between the two actions, but for the most part different neurons light up for each activity (and the neurons that initiate the other are suppressed).

But even more interestingly, the researchers found that aggression is triggered by a specific tangle of neurons. By inserting a bunch of custom-made viruses carrying a modified piece of DNA into the mouse’s brain, the researchers were able to make this region photosensitive to blue light. In other words, the researchers could now turn it on and off like a switch. With their blue light switched on, the researchers found that no matter what they put in the cage or what kind of threat it represented--another male mouse, a female mouse, an anesthetized mouse, a dummy--their test subject would attack indiscriminately.

The opposite also held. By silencing that nerve cluster, the researchers could render their mouse non-aggressive, even in the presence of a threatening male.

The point being, aggression and the violence it often spawns seems to be controlled by a specific cluster of neurons. This of course has implications for human behavior as well, helping to explain sudden explosions of aggression and violence that seem to be triggered by nothing at all. It could explain why some people can control themselves, and others fly off the handle--occasionally with disastrous or tragic results. Click through below for a more thorough explanation of the science behind this, we promise it’s not too long a read.

[Scientific American]

A team there has found that mouse nerve cells will connect with each other across a network of tiny tubes threaded through a semiconductor material. It’s not exactly clear at this point how the nerve cells are functioning, but what is clear is that the cells seem to have an affinity for the tiny tubes, and that alone has some interesting implications.

To create the nerve-chip hybrid, the researchers created tubes of layered silicon and germanium that are large enough for the nerve cells’ tendrils to navigate but too small for the actual body of the cell to pass through. They then introduced nerve cells to the tubes and found that the cells will readily thread their tendrils through them--even through complex geometries like helical curves--to connect with each other physically.

What isn’t clear is whether or not the cells are actually communicating with each other they way they would naturally. Going forward, the team aims to get sensors into the chips to see exactly how they are interacting. But the fact that nerve cells will follow the tubes along a preset path designed by researchers belies thrilling prospects.

For instance, nerve-electronic hybrid chips would make great places to test neurological drugs or to study the way nerve cells afflicted with disorders like Parkinson’s communicate. But even more tantalizing is the idea of a nerve-computer interface that would enable the kind of Skywalker-esque control of artificial limbs that is the holy grail prosthetics research.

[Discovery News]

The device, known as C3Vision (cortically coupled computer vision) taps into the fast processing power of the brain to help computer programs manage complex problem, particularly those posed by image recognition. An electroencephalogram (EEG) cap on the head of a human user is used to detect neurological signals in the brain. The computer then flashes images up on the screen at a rate of about ten per second. The conscious brain doesn’t even have time to adequately consider each image, but the subconscious is hard at work.

The system is great at working our problems that computer language has a problem tackling. For instance, it’s easy enough to search for a picture of a bicycle on the Web, but it’s far more difficult for a search engine like Google or Bing to search for something that looks “odd” or perhaps “silly.” The brain, however, can take these less-defined, more abstract qualifiers and very quickly assess whether or not an image fits the term.

The conscious brain doesn’t even have to get involved. The images flash too quickly for a person to rate his or her interest in each one, but the visual pathways in the brain move much more quickly. Machine-learning algorithms can quickly detect the neurological signals that represent the brain’s interest in a given image, and helps the computer to rank the images for interest. If the person sees something interesting or different, the computer knows it even if the person does not.

As such, the system has been used in tests to accurately scan satellite images for the presence of surface-to-air missiles faster than either a human or a machine could alone. Which accounts for DARPA’s interest in the technology; the DoD research arm has sunk $4.6 million into the development of the tech via a spinoff from the university. But the tech could also be used for a variety of other tasks that require the analysis of large volumes of visual data.

[Technology Review]

Manipulating the brain to enhance warfighting capabilities and maintain mental acuity on the battlefield has long been a topic of interest for DARPA and various military research labs, but the technology to do so remains limited. Deep brain stimulation (DBS), for instance, requires surgically implanted electrodes to stimulate neural tissues, while less-invasive methods like transcranial magnetic stimulation (TMS) possess limited reach and low spatial resolution.

But Dr. William J. Tyler, an assistant professor of life sciences at ASU, writes on the DoD’s “Armed With Science” blog: “To overcome the above limitations, my laboratory has engineered a novel technology which implements transcranial pulsed ultrasound to remotely and directly stimulate brain circuits without requiring surgery. Further, we have shown this ultrasonic neuromodulation approach confers a spatial resolution approximately five times greater than TMS and can exert its effects upon subcortical brain circuits deep within the brain.”

Tyler’s technology, packaged in a warfighter’s helmet, would allow soldiers to flip a switch to stimulate different regions of their brains, helping them relieve battle stress when it’s time to get some rest, or to boost alertness during long periods without sleep. Grunts could even relieve pain from injuries or wounds without resorting to pharmaceutical drugs. More importantly, in the periods after brain trauma ultrasound technology could reduce swelling and metabolic damage that is often the root cause of lasting brain damage.

[Armed With Science via Danger Room]

The method leaves a lot of room for improvement, but it does prove out some technology that could make thought-to-speech technology more reliable for patients suffering from traumatic brain injuries or illnesses that render them unable to communicate with others. Using two grids of 16 microelectrodes placed over two regions of the brain known to generate human speech, the team was able to record brain signals for 10 useful words – yes, no, hot, cold, thirsty, hungry, goodbye, hello, more and less – and use that data to discern between any two words a patient was thinking between 76 and 90 percent of the time.

But when they tried to distinguish between all ten words at the same time, that success rate dropped to between 28 percent and 48 percent. That’s better than chance – which would be one-in-ten or just 10 percent – but less than reasonably useful.

The electrodes used were non-penetrating, meaning they sit between the patient’s brain and skull, but do not actually poke into the brain. That means they are closer and more sensitive to specific brain waves than externally worn EEG caps, but are less invasive than penetrating electrodes. These electrodes can pick up on weak electrical signals within the brain, meaning they are more nuanced than other brain monitoring sensors and could possibly provide the technological sensitivity needed to get reliable thought-to-speech translation working.

But first the researchers will have to refine their translation techniques to raise the success rates from one-in-four to something more like three-in-four, and ideally be able to distinguish between more than just 10 words. To get to that point, the next round of tests will involve larger, 11-by-11 arrays containing 121 electrodes each. Those larger implants should yield much more brain signal data that could in turn improve translation accuracy to the point that thought-to-speech translation could become a viable clinical solution.

[Medical Daily]

A significant stride towards reverse-engineering the darn thing

Focusing on a long-distance network connecting 383 brain regions and 6,602 long-distance connections that function like highways to connect disparate regions of the brain. Shorter, more localized connections were found to carry signals within regions.

But most importantly, they found what they describe in a paper published in PNAS as a "tightly integrated core" that might be they key to cognition in higher-thinking biological creatures. That core might be what gives us consciousness (we won't get into the philosophical implications there). Further, the core isn't located in one, or even two regions. The researchers found it stretches through the premotor cortex, prefrontal cortex, temporal lobe, thalamus, visual cortex and a handful of other regions.

Another surprising find: the prefrontal cortex, though at the front of the brain, might actually serve as its central information hub that distributes information throughout the brain.

The study included mapping of four times as many regions and three times the number of connections than the largest previous attempt. Those findings could finally help researchers mimic the brain -- which, even in this seemingly advanced era, is something of a mystery to us. That in turn could lead to network architecture and computer chips that process and move information as quickly and seamlessly as our brains do.

[Kurzweil AI]

In a study published last week, they showed neural signals can predict future behavior more accurately than people's own best guesses. This has major implications for everything from advertisers, who would very much like to anticipate what you'll do, to educators, who could predict how much knowledge students will actually retain.

The researchers studied brain activity of people who watched public-service announcements about the importance of wearing sunscreen. They focused on two brain regions, the medial prefrontal cortex and the precuneus, which are both associated with self-awareness. The subjects -- mostly UCLA students -- were asked how they felt about sunscreen and how likely they were to use it. The researchers gave the subjects sunscreen to be sure they'd have access to it.

A week later, the participants reported how much sunscreen they actually used. About half had been able to accurately predict their behavior.

The neuroscientists developed a model that compared the subjects' brain activity to their own predictions, and found the model was accurate 75 percent of the time. In other words, it was more accurate than the students' own ability to predict how they would act. The findings were published last week in the Journal of Neuroscience.

Matthew Lieberman, a UCLA psychology and psychiatry professor who led the study, said people are not very good judges of what they will actually do.

"Many people 'decide' to do things but then don't do them," he says.

The study involved a small sample size -- just 20 students -- and more work needs to be done to understand the disconnect between your intentions and your actions. But the study could pave the way for neurologically informed marketing, education and even public health campaigns, UCLA says.

[UCLA via Singularity Hub]