Posts Tagged ‘neurons’
Japanese Researchers Develop a Way to Turn Biological Tissue Transparent
Can be used to study brain function, or just to look cool
A new chemical reagent makes the brain see-through, allowing fluorescent tags to light up neurons and blood vessels deep inside. This enables 3-D images of entire structures, without having to cut anything away or divide anything into smaller sections.
It doesn’t work on living tissue, at least not yet — researchers at RIKEN, Japan’s major research institute, are investigating another, milder reagent that could allow them to study live tissue in this way.
The reagent, called Scale, has specific clarifying properties that do not alter the overall shape or proportion of the sample being washed, according to a . First you would have to genetically modify the sample by adding fluorescent proteins to tag certain cells. While it turns the tissue transparent, the Scale method also prevents decreasing the intensity of those fluorescent signals. So once the tissue is washed with Scale, researchers can see the fluorescent proteins flashing.
The fluorescent tags have made it possible to visualize brain regions at a depth of several millimeters, far better than before, and to reconstruct neural networks, RIKEN says. Atsushi Miyawaki and his team at the RIKEN Brain Science Institute have already used it to study neuronal networks among the cerebral cortex, hippocampus and white matter of mouse brains.
It can work on several other tissues besides the brain, the researchers say — they plan to try Scale on the heart, muscles and kidneys, and on tissues from primate and human biopsy samples. The work was published this week in Nature Neuroscience.
"Time Cells" In the Brain Keep Track of Events, Firing As Time Goes By
In a new study involving rats, researchers at Boston University monitored neurons in the hippocampus, the center of memory and learning. Howard Eichenbaum and colleagues trained rats to perform a three-part task, which included a delay in the middle, . They learned to associate an object with an scent (a ball with oregano, for instance), and then they were presented with the object. The rats entered a separate chamber for 10 seconds, after which a doorway led them to a flowerpot full of scented sand. If the scent was the same as the object they’d been shown, the rats would dig for a food reward. The 10-second delay was at the heart of the study.
Eichenbaum et. al surgically implanted electrodes in the rats’ hippocampus, and monitored signals from 300 distinct neurons as the rats completed their work. During the delay, the researchers watched about a third of the cells continue to fire in a cascading pattern — suggesting the neurons were keeping track as time went by.
The hippocampus is known to have “place cells,” which keep track of locations and recalibrate when spatial cues are altered, the . In the same way, the time neurons continued to fire when the researchers lengthened the delay, “retiming” when temporal cues are altered. The hippocampus is considered the brain’s memory center, so it makes sense that there would be some mechanism for monitoring the variables that memory depends upon.
The neurons kept track of time in varying tests, but their firing patterns and the specific groups involved changed slightly, depending on which object was presented. This shows the neurons disambiguate different events, the researchers say: “(They) compose unique, temporally organized representations of specific experiences.” The research is reported in the journal Neuron.
So next time you say you’ve lost track of time, remember that you really haven’t — your biological clock has been ticking all the while.
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New Computer Chip Modeled on a Living Brain Can Learn and Remember
IBM, with help from DARPA, has built two working prototypes of a "neurosynaptic chip." Based on the neurons and synapses of the brain, these first-generation cognitive computing cores could represent a major leap in power, speed and efficiency
About a year ago, we told you about IBM’s project to map the , the most complex brain networking project of its kind. Big Blue wasn’t doing it just for the sake of science — the goal was to reverse-engineer neural networks, helping pave the way to cognitive computer systems that can think as efficiently as the brain. Now they’ve made just such a system — two, actually — and they’re calling them neurosynaptic chips.
Built on 45 nanometer silicon/metal oxide semiconductor platform, both chips have 256 neurons. One chip has 262,144 programmable synapses and the other contains 65,536 learning synapses — which can remember and learn from their own actions. IBM researchers have used the compute cores for experiments in navigation, machine vision, pattern recognition, associative memory and classification, the company says. It’s a step toward redefining computers as adaptable, holistic learning systems, rather than yes-or-no calculators.
“This new architecture represents a critical shift away form today’s traditional von Neumann computers, to extremely power-efficient architecture,” Dharmendra Modha, project leader for IBM Research, said in an interview. “It integrates memory with processors, and it is fundamentally massively parallel and distributed as well as event-driven, so it begins to rival the brain’s function, power and space.”
You can read up on Von Neumann architecture , but essentially it is a system with two data portals, which are shared by the input instructions and output data. This creates a bottleneck that will fundamentally limit the speed of memory transfer. IBM’s system eliminates that bottleneck by putting the circuits for data computation and storage together, allowing the system to compute information from multiple sources at the same time with greater efficiency. Also like the brain, the chips have synaptic plasticity, meaning certain regions can be reconfigured to perform tasks to which they were not initially assigned.
IBM’s long-term goal is to build a chip system with 10 billion neurons and 100 trillion synapses that consumes just one kilowatt-hour of electricity and fits inside a shoebox, Modha said.
The project is funded by DARPA’s SyNAPSE initiative, and IBM just completed phases 0 and 1. IBM’s project, which involves collaborators from Columbia University, Cornell University, the University of California-Merced and the University of Wisconsin-Madison, just received another $21 million in funding for phase 2, the company said.
Computer scientists have been working for some time on systems that can emulate the brain’s massively parallel, low-power computing prowess, and they’ve made several breakthroughs. Last year, computer engineer Steve Furber described a that consists of tens of thousands of cellphone chips.
The most notable computer-brain achievements have been in the field of . As their name implies, a memory resistor can “remember” the last resistance that it possessed when current was flowing through it — so after current is turned back on, the resistance of the circuit will be the same. We will not attempt to delve too deeply here, but this basically makes a system much more efficient.
Hewlett-Packard has been since first describing them in 2008, and has also been part of the SyNAPSE project. Last spring, HP engineers described a titanium dioxide memristor that uses low power.
For a brain-based computer system, memristors can function as a computer analogue for a synapse, which also stores information about previous data transfer. IBM's chip doesn't use a memristor architecture, but it does integrate memory with computation power — and it uses computer neurons and axons to do it. The building blocks are simple, but the architecture is unique, said Rajit Manohar, associate dean for research and graduate studies in the engineering school at Cornell.
"When a neuron changes its state, the state it is modifying is its own state, not the state of something else. So you can physically co-locate the circuit to do the computation, and the circuit to store the state. They can be very close to each other, so that cooperation becomes very efficient," he said.
Modha said it is just a new way to store memory.
"A bit is a bit is a bit. You could store a bit in a memristor, or a phase-change memory, or a nano-electromechanical switch, or SRAM, or any form of memory that you please. But by itself, that does not a complete architecture make," Modha said. "It has no computational capability."
But this new chip does have that power, he said. It integrates memory with processor capability on a typical SOI-CMOS platform, using traditional transistors in a new design. Along with integrated memory to stand in for synapses, the neurosynaptic “core” uses typical transistors for input-output capability, i.e. neurons.
This new architecture will not replace traditional computers, however. “Both will be with us for a long time to come, and continue to serve humanity,” Modha predicted.
The idea is that future powerful chips based on this brain-network design will be able to ingest and compute information from multiple inputs and make sense of it all — just like the brain does.
A cognitive computer monitoring the oceans could record and compute variables like temperature, wave height and acoustics, and decide whether to issue tsunami or hurricane warnings. Or a grocer stocking shelves could use a special glove that monitors scent, texture and sight to flag contaminated produce, Modha said. Modern computers can’t handle that level of detail from so many inputs, he said. But our brains do it all the time — grab a rotting peach, and your senses of touch, smell and sight work in concert instantaneously to determine that the fruit is bad.
To do this, the brain uses electrical signals between some 150 trillion synapses, all while sipping energy — our brains need about 20 watts to function. Understanding how this works is key to building brain-based computers, which is why IBM has been working with neuroscientists to study monkey and . That research is progressing, Modha said.
But it will be quite some time before computer chips can truly match the ultra-efficient computational powerhouses that nature gave us.
CalTech Researchers Find a Toggle Switch for Mouse, and Perhaps Human, Aggression
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 ). 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.
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Scientists Create Tiny Artificial Brain That Exhibits 12 Seconds of Short Term Memory
Developed by a team at the University of Pittsburgh, the brain was created in an attempt to artificially nurture a working brain into existence so that researchers could study neural networks and how our brains transmit electrical signals and store data so efficiently. The did so by attaching a layer of proteins to a silicon disk and adding brain cells from embryonic rats that attached themselves to the proteins and grew to connect with one another in the ring seen above.
But as if the growing of a tiny, functioning, donut-shaped brain in a petri dish wasn’t enough, the team found that when they stimulate the neurons with electricity, the pulse would circulate the microbrain for a full 12 seconds. That’s roughly 12 seconds longer than they thought it would (they expected the pulse to live for about a quarter of a second).
That’s essentially short-term memory. The neurons were relaying the signal in sequence, persistently, mimicking the activity we know as working memory (though admittedly we don’t understand it that well). The brain is basically storing the stimulus long after the stimulus is no more, which is a big deal for a tiny brain grown in a dish.
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Tiny Fractal-Shaped Eye Implants Could Mimic Neurons, Allowing Blind Patients to See
Some vision disorders, like macular degeneration, damage the eyes’ rods and cones but leave the neurons intact. Implants work by communicating with those neurons, sending visual information to the brain to be processed. But camera chips and eyes do not work the same way, and there are insufficient connections between the neurons and the implanted photodiode light receptors.
This is because neurons follow a branched, fractal structure, and chips utilize straight paths, explains Richard Taylor, a physics professor at the University of Oregon who is working on improved implants. Fractals are self-similar repeating patterns.
His solution is to embed a nanoscale clump of material onto the photodiode, which would self-assemble into fractal shapes. The clump would be deposited onto a photodiode using an inert gas. Eye surgeons would implant the fractal-enhanced devices inside the eyes of patients who have lost their vision, and the improved neuron interface would enable more light information to be relayed to the optic nerve. It would work with almost 100 percent efficiency, according to a University of Oregon news release.
This summer, Taylor and doctoral students in his lab are starting a year-long project to study the metals to be used for fractal assembly. The researchers will look for metals with strong biocompatibility and efficiency, among other attributes.
The project stemmed from Taylor’s interest in the similarities and differences between the human eye and digital cameras, according to a . He describes his work in an article in .
The cones in your eye are concentrated at the center, so your eye tends to see items directly in front of it — this means you have to continually move your eyes around to see small areas. But a camera’s photoreceptors are distributed evenly, allowing a camera to see everything in its field of view. If our eyes saw like a camera, with a uniform distribution of receptors, there would be so much stimuli in our view that our brains could never process it all, according to Taylor.
Instead, our eyes exploit fractal patterns found throughout nature to make information-processing simpler. Retinal implant designs should account for these differences, Taylor wrote.
“Remarkably, implants based purely on camera designs might allow blind people to see, but they might only see a world devoid of stress-reducing beauty. This flaw emphasizes the subtleties of the human visual system and the potential downfalls of adopting, rather than adapting, camera technology for eyes,” he wrote.
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Hooking a 9-Volt Battery To Your Brain Improves Your Video Game Skills, Researcher Finds
(But don't try this at home)
Neuroscientists at the University of New Mexico asked volunteers to play a video game called “DARWARS Ambush!”, developed to help train American military personnel. Half of the players received 2 milliamps of electricity to the scalp, using a device powered by a simple 9-volt battery, and they played twice as well as those receiving a much tinier jolt. The DARPA-funded study suggests direct current applied to the brain could improve learning.
This type of brain stimulation, called transcranial direct current stimulation (tDCS), is controversial but could show promise for treatment of various neurological disorders and cognitive impairments. Click through to for a thorough overview.
It’s different from , in which a magnetic coil running at high voltage is positioned close to the head. The magnets stimulate electrical responses in the brain. Transcranial direct current stimulation is just what it sounds, applying the current directly to the brain.
We’ve been hearing quite a lot about these methods lately, and the scientific literature indicates the fields — tDCS in particular — are experiencing a revival, Nature News points out. Scientists hope the methods could be used to treat depression, post-traumatic stress disorder, stroke and autism, as well as to improve learning by increasing the brain’s plasticity.
Researchers are beginning to understand how an external electrical current affects brain function, including by inducing changes to the flow of electricity across neurons and increasing the expression of certain synapse proteins.
Apparently, it takes very little electricity to do all this. But please, don’t start hooking up 9-volt batteries to your brain — leave that to the scientific studies.
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