Neurons in human skin perform advanced calculations

[2014-09-01] Neurons in human skin perform advanced calculations, previously believed that only the brain could perform. This is according to a study from Umeå University in Sweden published in the journal Nature Neuroscience.

A fundamental characteristic of neurons that extend into the skin and record touch, so-called first-order neurons in the tactile system, is that they branch in the skin so that each neuron reports touch from many highly-sensitive zones on the skin.

According to researchers at the Department of Integrative Medical Biology, IMB, Umeå University, this branching allows first-order tactile neurons not only to send signals to the brain that something has touched the skin, but also process geometric data about the object touching the skin.

- Our work has shown that two types of first-order tactile neurons that supply the sensitive skin at our fingertips not only signal information about when and how intensely an object is touched, but also information about the touched object's shape, says Andrew Pruszynski, who is one of the researchers behind the study.

The study also shows that the sensitivity of individual neurons to the shape of an object depends on the layout of the neuron’s highly-sensitive zones in the skin.

- Perhaps the most surprising result of our study is that these peripheral neurons, which are engaged when a fingertip examines an object, perform the same type of calculations done by neurons in the cerebral cortex. Somewhat simplified, it means that our touch experiences are already processed by neurons in the skin before they reach the brain for further processing, says Andrew Pruszynski.

For more information about the study, please contact Andrew Pruszynski, post doc at the Department of Integrative Medical Biology, IMB, Umeå University. He is English-speaking and can be reached at: 

Phone: +46 90 786 51 09; Mobile: +46 70 610 80 96

E-mail: andrew.pruszynski@umu.se

Read the study in Nature Neuroscience

ORIGINAL: Umeå University

"Brain" In A Dish Acts As Autopilot Living Computer

A glass dish contains a "brain" -- a living network of 25,000 rat brain cells connected to an array of 60 electrodes.University of Florida/Ray Carson

downloadable pdf

A University of Florida scientist has grown a living “brain” that can fly a simulated plane, giving scientists a novel way to observe how brain cells function as a network.The “brain” — a collection of 25,000 living neurons, or nerve cells, taken from a rat’s brain and cultured inside a glass dish — gives scientists a unique real-time window into the brain at the cellular level. By watching the brain cells interact, scientists hope to understand what causes neural disorders such as epilepsy and to determine noninvasive ways to intervene.

Thomas DeMarse holds a glass dish containing a living network of 25,000 rat brain cells connected to an array of 60 electrodes that can interact with a computer to fly a simulated F-22 fighter plane.

As living omputers, they may someday be used to fly small unmanned airplanes or handle tasks that are dangerous for humans, such as search-and-rescue missions or bomb damage assessments." We’re interested in studying how brains compute,” said Thomas DeMarse, the UF assistant professor of biomedical engineering who designed the study. “If you think about your brain, and learning and the memory process, I can ask you questions about when you were 5 years old and you can retrieve information. That’s a tremendous capacity for memory. In fact, you perform fairly simple tasks that you would think a computer would easily be able to accomplish, but in fact it can’t.”

While computers are very fast at processing some kinds of information, they can’t approach the flexibility of the human brain, DeMarse said. In particular, brains can easily make certain kinds of computations — such as recognizing an unfamiliar piece of furniture as a table or a lamp — that are very difficult to program into today’s computers.

“If we can extract the rules of how these neural networks are doing computations like pattern recognition, we can apply that to create novel computing systems,” he said.

DeMarse’s experimental “brain” interacts with an F-22 fighter jet flight simulator through a specially designed plate called a multi-electrode array and a common desktop computer. “It’s essentially a dish with 60 electrodes arranged in a grid at the bottom,” DeMarse said. “Over that we put the living cortical neurons from rats, which rapidly begin to reconnect themselves, forming a living neural network — a brain.” The brain and the simulator establish a two-way connection, similar to how neurons receive and interpret signals from each other to control our bodies. By observing how the nerve cells interact with the simulator, scientists can decode how a neural network establishes connections and begins to compute, DeMarse said. When DeMarse first puts the neurons in the dish, they look like little more than grains of sand sprinkled in water. However, individual neurons soon begin to extend microscopic lines toward each other, making connections that represent neural processes. “You see one extend a process, pull it back, extend it out — and it may do that a couple of times, just sampling who’s next to it, until over time the connectivity starts to establish itself,” he said. “(The brain is) getting its network to the point where it’s a live computation device.” To control the simulated aircraft, the neurons first receive information from the computer about flight conditions: whether the plane is flying straight and level or is tilted to the left or to the right.

The neurons then analyze the data and respond by sending signals to the plane’s controls. Those signals alter the flight path and new information is sent to the neurons, creating a feedback system. “Initially when we hook up this brain to a flight simulator, it doesn’t know how to control the aircraft,” DeMarse said. “So you hook it up and the aircraft simply drifts randomly. And as the datacome in, it slowly modifies the (neural) network so over time, the network gradually learns to fly the aircraft.” Although the brain currently is able to control the pitch and roll of the simulated aircraft in weather conditions ranging from blue skies to stormy, hurricane-force winds, the underlying goal is a more fundamental understanding of how neurons interact as a network, DeMarse said. “There’s a lot of data out there that will tell you that the computation that’s going on here isn’t based on just one neuron. 

The computational property is actually an emergent property of hundreds or thousands of neurons cooperating to produce the amazing processing power of the brain.” With José Principe, a UF distinguished professor of electrical engineering and director of UF’s Computational NeuroEngineering Laboratory, DeMarse has a $500,000 National Science Foundation grant to create a mathematical model that reproduces how the neurons compute. Thomas DeMarse, tdemarse@bme.ufl.edu"

ORIGINAL: U of Florida

by Jennifer Viegas  

Nov 27, 2012

Master monkey's brain controls sedated 'avatar'

The brain of one monkey has been used to control the movements of another, "avatar", monkey, US scientists report.

Brain scans read the master monkey's mind and were used to electrically stimulate the avatar's spinal cord, resulting in controlled movement.

The team hope the method can be refined to allow paralysed people to regain control of their own body.

The findings, published in Nature Communications, have been described as "a key step forward".

Figure 1: Schematic illustration of the dual-primate set-up.

The master is displayed on top and the avatar is displayed on the bottom. Note that on decoding-based sessions, the master had a joystick during training that was then disconnected during the real-time neural prosthetic trials.

Damage to the spinal cord can stop the flow of information from the brain to the body, leaving people unable to walk or feed themselves.

The researchers are aiming to bridge the damage with machinery. Match electrical activity

The scientists at Harvard Medical School said they could not justify paralysing a monkey. Instead, two were used - a master monkey and a sedated avatar.

The master had a brain chip implanted that could monitor the activity of up to 100 neurons.

During training, the physical actions of the monkey were matched up with the patterns of electrical activity in the neurons.

The avatar had 36 electrodes implanted in the spinal cord and tests were performed to see how stimulating different combinations of electrodes affected movement.

The two monkeys were then hooked up so that the brain scans in one controlled movements in real time in the other.

The sedated avatar held a joystick, while the master had to think about moving a cursor up or down.

In 98% of tests, the master could correctly control the avatar's arm.

One of the researchers, Dr Ziv Williams, told the BBC: "The goal is to take people with brain stem or spinal cord paralysis and bypass the injury.

"The hope is ultimately to get completely natural movement, I think it's theoretically possible, but it will require an exponential additional effort to get to that point."

He said that giving paralysed people even a small amount of movement could dramatically alter their quality of life. Reality or science fiction?

The idea of one brain controlling an avatar body is the stuff of blockbuster Hollywood movies.

However, Prof Christopher James, of the University of Warwick, dismissed a future of controlling other people's bodies by thought.

He said: "Some people may be concerned this might mean someone taking over control of someone else's body, but the risk of this is a no-brainer.

"Whilst the control of limbs is sophisticated, it is still rather crude overall, plus of course in an able-bodied person their own control over their limbs remains anyway, so no-one is going to control anyone else's body against their wishes any time soon."

Instead, he said this was "very important research" with "profound" implications "especially for controlling limbs in spinal cord injury, or controlling prosthetic limbs with limb amputees".

Realising that goal will face additional challenges. Moving a cursor up and down is a long way from the dextrous movement needed to drink from a cup.

There are also differences in the muscles of people after paralysis; they tend to become more rigid. And fluctuating blood pressure may make restoring control more challenging.

Prof Bernard Conway, head of biomedical engineering at the University of Strathclyde, said: "The work is a key step forward that demonstrates the potential of brain machine interfaces to be used in restoring purposeful movement to people affected by paralysis. 

"However, significant work still remains to be done before this technology will be able to be offered to the people who need it."


ORIGINAL: BBC Mundo

By James Gallagher Health and science reporter, BBC News 

18 February 2014

Beautiful 3-D brain scans show every synapse

Ultrathin slices of mouse brains offer a mesmerizing look at how brain cells communicate at the tiniest scale. This research may offer clues about how the dance of our own synapses guides and animates us.

 
http://www.youtube.com/user/NationalGeographic?feature=watch

ORIGINAL: Science Dump
by Jur
02/01/2014

Significant Science of 2013: Brain Mapping Gets a Big Boost

ORIGINAL: PBS

by Allison Eck 

27 Dec 2013

Significant Science of 2013: Brain Mapping Gets a Big Boost

One terabyte of data. That’s what it took for scientists to make a comprehensive 3D map of the post-mortem human brain.

That, plus ten years of research, 7,000 slices of brain tissue from a healthy 65-year-old woman, and 1,000 hours of digitization. Sound difficult? For neuroscientists, this is only the beginning of a long journey that hopes to map the cogs and gears of the mind.

The project—dubbed BigBrain—was part of the European Human Brain Project, a joint effort by Canadian and German neuroscientists. While it bears no relation to President Obama’s BRAIN Initiative, BigBrain is certainly the kind of work that could propel the audacious federal project forward. For one, scientists can use this generic model in order to see how a normal brain compares with ones afflicted by neurological conditions like Alzheimer’s or Parkinson’s. BigBrain also captured the brain in incredible detail, revealing structures once invisible to even the most advanced technologies. 

Scientists hope to use BigBrain along with other data to help map connections between different regions of the brain.

Back in June, this is how NOVA Next contributor Teal Burrell described the significance of BigBrain:

Prior to this study, MRI provided the most detailed 3D peek into a human brain. If you think of the brain as a map of a country, the resolution of MRI—about 1 millimeter—would make towns visible, but nothing smaller than that would be. BigBrain, on the other hand, “does 50 times better in each dimension than the typical 1-millimeter resolution of MRI,” says Katrin Amunts, a neuroscientist at the Institute of Neuroscience and Medicine in Jülich, Germany, and lead author of the paper. Specifically, BigBrain’s 20-micron resolution is fine enough to pick out individuals of certain types of cells, but not all; the smallest neurons in the brain are only about 10 microns across. Still, if this were a map, the level of detail provided by BigBrain greatly exceeds MRI, allowing us to see not just towns, but the houses within them.

What’s still missing from BigBrain are the connections between neurons—the techniques used for this project weren’t suitable for developing a connectome. But it can help, serving as a scaffold over which connectivity data can be overlaid.

It’s likely, too, that BigBrain will help contribute to discoveries made in the BRAIN Initiative. Like the Human Genome Project, the BRAIN Initiative will stand on the shoulders of smaller projects. It will be a while before BRAIN ramps up—President Obama requested funds starting in 2014—but in the meantime, BigBrain is certain to give neuroscientists a more intimate picture of the human mind.

Navigating through the right hemisphere of BigBrain. Explore the brain using other types of imagery, using NOVA’s "Mapping the Brain" interactive.

Tell us what you think on Twitter #novanext, Facebook, or email.

ORIGINAL: PBS

by Allison Eck 

27 Dec 2013

Optogenetics: Lighting Up the Brain

ORIGINAL: OxBridgeBiotech
Friday, 21st June 2013

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As a child, the year 2000 seemed utterly distant and futuristic to me. The realization that I would likely live to see it filled me with awe. Surely, in the coming age we would have flying cars, personal jetpacks, and teleportation!

A dozen years into the new millennium, I am still waiting for my jetpack. But some of the technologies that I encounter as a scientist make me think that perhaps my childhood visions were not that far off after all. Take optogenetics – a revolutionary technique that would have sounded like something straight out of science fiction not too long ago.

As its name suggests, optogenetics combines tools from optics and genetics; the result is the awe-inspiring ability to control brain cell activity using light. While the “cool” factor is undeniable, optogenetics was developed to address very practical problems. To figure out how neurons, the nerve cells that make up our brain, influence various biological functions and diseases, it is not enough just to observe their activity during certain behaviors or illnesses. After all, while it is possible that a given neuronal activity caused a behavior, it could just as easily be that the behavior caused the neurons’ firing pattern, or that some third factor independently caused both – correlation does not prove causation, as the saying goes. However, if researchers can directly trigger a certain neuronal firing pattern, and it always produces a given behavior, they can conclude with much greater confidence that the neuronal activity indeed contributes to the behaviour.

Previous approaches to controlling neuron activity all had significant limitations. Inserting electrodes into the brain allows researchers to stimulate neurons directly. However, there are a wide variety of different types of neurons, often tightly intermingled in a given brain region. Zapping an area of the brain with an electrode will stimulate all of the different neuron types in the vicinity, making it difficult to untangle which of them actually produced the observed effects. Alternatively, researchers can chemically stimulate neurons with drugs targeted at specific neuron types. However, the effects of drugs stretch over minutes or even hours – eternities compared to the rhythms of neuron signals, which last for milliseconds.

Photo: Stanford, Karl Deisseroth's Lab

Enter optogenetics. 

While early forms of optogenetics made use of a range of light-sensitive molecules, modern incarnations mainly rely on so-called ‘channel rhodopsins’ (ChRs), a type of ion channel. Ion channels sit on the cell membrane surrounding the neuron and allow certain kinds of electrically charged particles – ions – to enter or leave the cell. By doing so, they can alter the neuron’s electrical charge, which in turn can trigger the neuron to fire. In contrast to most ion channels, which open and close in response to chemical signals, ChRs open in response to light. If ChRs are inserted into the membrane of a neuron, the neuron can then be prompted to fire by shining light onto it. Researchers can use various genetic tools to ensure that only a specific neuron type is “enhanced” with ChRs. For example, they can insert the ChR gene behind a promoter (a kind of genetic “on switch”) that is only activated in the neuron of interest, or they can use selective viruses to “smuggle” the ChR genetic material into specific neuron types. With computer-generated rapid light flashes, researchers can then control the activity of only their selected neuron type down to a few milliseconds.

If that is not exciting enough, different ChRs respond to different wavelengths of light. Thanks to both naturally occurring varieties and bioengineered manipulations, researchers now have a toolbox of different ChRs that open only in response to, say, blue, green, or yellow light. Moreover, similar molecules called ion pumps can be used to silence neurons instead of stimulating them. By inserting the right ChRs and light-sensitive ion pumps into specific neuron types, a researcher can, for example, create a situation in which blue light stimulates all neurons of type A while keeping all neurons of type B from firing, whereas yellow light causes all type B neurons to fire while silencing all type A neurons.

With a neuron grown inside a cell culture dish, experimenters can simply shine the light directly onto the dish. In the case of live organisms, more sophisticated hardware is needed. Thin optical fibers can be inserted into the relevant brain area to conduct light to the neurons being studied. Often, these fibers are connected to an external light source by a cable; the animal is therefore “leashed” during the study, although it still has some freedom of movement. More recently, using miniature LEDs (light-emitting diodes) and batteries, researchers have constructed small, self-contained light sources that can be attached to the animal and allow completely free motion. Optical, chemical or electrical sensors may also be inserted into the same area to allow measurement of neuron activity and how it is changed by light stimulation.

Using optogenetics, neuroscientists have been able to show conclusively that the activity of specific neurons can produce certain behaviors. For example, when experimenters in Karl Deisseroth’s lab at Stanford made a type of “reward” neurons fire rapidly using optogenetics whenever animals were placed in a certain environment, these animals began to prefer this environment over others. And simply activating these neurons was not enough – the pattern of signals mattered. When the same neurons were made to fire more slowly, the effect disappeared. Similar studies have helped scientists to further unravel the mechanisms underlying brain disorders like Parkinson’s disease, addiction, and depression. In the future, optogenetics may even yield new treatments for these diseases. Of course, many obstacles remain before optogenetics can be used in humans. Safe ways to insert ChRs into human neurons would be needed, along with less invasive methods of delivering light pulses into relevant brain regions. Nonetheless, at least one biotechnology company, Circuit Therapeutics, is focusing on the development of optogenetic therapies.

Controlling the brain with light. It’s no personal jetpack, but it does make me feel like I am already living in the future.

Complex brain function depends on flexibility

ORIGINAL: MIT News
Anne Trafton, MIT News Office
May 19, 2013

Neurons that can multitask greatly enhance the brain’s computational power, study finds.

An artist's impression depicting a network of neurons of the nervous system. Image: Maurizio De Angelis/Wellcome Images

Over the past few decades, neuroscientists have made much progress in mapping the brain by deciphering the functions of individual neurons that perform very specific tasks, such as recognizing the location or color of an object.

However, there are many neurons, especially in brain regions that perform sophisticated functions such as thinking and planning, that don’t fit into this pattern. Instead of responding exclusively to one stimulus or task, these neurons react in different ways to a wide variety of things. MIT neuroscientist Earl Miller first noticed these unusual activity patterns about 20 years ago, while recording the electrical activity of neurons in animals that were trained to perform complex tasks.

“We started noticing early on that there are a whole bunch of neurons in the prefrontal cortex that can’t be classified in the traditional way of one message per neuron,” recalls Miller, the Picower Professor of Neuroscience at MIT and a member of MIT’s Picower Institute for Learning and Memory.

In a paper appearing in Nature on May 19, Miller and colleagues at Columbia University report that these neurons are essential for complex cognitive tasks, such as learning new behavior. The Columbia team, led by the study’s senior author, Stefano Fusi, developed a computer model showing that without these neurons, the brain can learn only a handful of behavioral tasks.

“You need a significant proportion of these neurons,” says Fusi, an associate professor of neuroscience at Columbia. “That gives the brain a huge computational advantage.”

Lead author of the paper is Mattia Rigotti, a former grad student in Fusi’s lab.

Multitasking neurons

Miller and other neuroscientists who first identified this neuronal activity observed that while the patterns were difficult to predict, they were not random. “In the same context, the neurons always behave the same way. It’s just that they may convey one message in one task, and a totally different message in another task,” Miller says.

For example, a neuron might distinguish between colors during one task, but issue a motor command under different conditions.

Miller and colleagues proposed that this type of neuronal flexibility is key to cognitive flexibility, including the brain’s ability to learn so many new things on the fly. “You have a bunch of neurons that can be recruited for a whole bunch of different things, and what they do just changes depending on the task demands,” he says.

At first, that theory encountered resistance “because it runs against the traditional idea that you can figure out the clockwork of the brain by figuring out the one thing each neuron does,” Miller says.

For the new Nature study, Fusi and colleagues at Columbia created a computer model to determine more precisely what role these flexible neurons play in cognition, using experimental data gathered by Miller and his former grad student, Melissa Warden. That data came from one of the most complex tasks that Miller has ever trained a monkey to perform: The animals looked at a sequence of two pictures and had to remember the pictures and the order in which they appeared.

During this task, the flexible neurons, known as “mixed selectivity neurons,” exhibited a great deal of nonlinear activity — meaning that their responses to a combination of factors cannot be predicted based on their response to each individual factor (such as one image).

Expanding capacity

Fusi’s computer model revealed that these mixed selectivity neurons are critical to building a brain that can perform many complex tasks. When the computer model includes only neurons that perform one function, the brain can only learn very simple tasks. However, when the flexible neurons are added to the model, “everything becomes so much easier and you can create a neural system that can perform very complex tasks,” Fusi says.

The flexible neurons also greatly expand the brain’s capacity to perform tasks. In the computer model, neural networks without mixed selectivity neurons could learn about 100 tasks before running out of capacity. That capacity greatly expanded to tens of millions of tasks as mixed selectivity neurons were added to the model. When mixed selectivity neurons reached about 30 percent of the total, the network’s capacity became “virtually unlimited,” Miller says — just like a human brain.

Mixed selectivity neurons are especially dominant in the prefrontal cortex, where most thought, learning and planning takes place. This study demonstrates how these mixed selectivity neurons greatly increase the number of tasks that this kind of neural network can perform, says John Duncan, a professor of neuroscience at Cambridge University.

“Especially for higher-order regions, the data that have often been taken as a complicating nuisance may be critical in allowing the system actually to work,” says Duncan, who was not part of the research team.

Miller is now trying to figure out how the brain sorts through all of this activity to create coherent messages. There is some evidence suggesting that these neurons communicate with the correct targets by synchronizing their activity with oscillations of a particular brainwave frequency.

“The idea is that neurons can send different messages to different targets by virtue of which other neurons they are synchronized with,” Miller says. “It provides a way of essentially opening up these special channels of communications so the preferred message gets to the preferred neurons and doesn’t go to neurons that don’t need to hear it.”

The research was funded by the Gatsby Foundation, the Swartz Foundation and the Kavli Foundation.

See-through brains clarify connections

ORIGINAL: Nature

Helen Shen

10 April 2013

Technique to make tissue transparent offers three-dimensional view of neural networks. 

Mind readers 

Nature Video reveals how Karl Deisseroth and his team created 3D visualizations of mouse brains. 

A chemical treatment that turns whole organs transparent offers a big boost to the field of ‘connectomics’ — the push to map the brain’s fiendishly complicated wiring. Scientists could use the technique to view large networks of neurons with unprecedented ease and accuracy. The technology also opens up new research avenues for old brains that were saved from patients and healthy donors. 

“This is probably one of the most important advances for doing neuroanatomy in decades,” says Thomas Insel, director of the US National Institute of Mental Health in Bethesda, Maryland, which funded part of the work. Existing technology allows scientists to see neurons and their connections in microscopic detail — but only across tiny slivers of tissue. Researchers must reconstruct three-dimensional data from images of these thin slices. Aligning hundreds or even thousands of these snapshots to map long-range projections of nerve cells is laborious and error-prone, rendering fine-grain analysis of whole brains practically impossible. 

Related stories

• Big Neuroscience: Billions and Billions (Maybe) to Unravel Mysteries of the Brain
• Mapping brain networks: Fish-bowl neuroscience
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The new method instead allows researchers to see directly into optically transparent whole brains or thick blocks of brain tissue. Called CLARITY, it was devised by Karl Deisseroth and his team at Stanford University in California. “You can get right down to the fine structure of the system while not losing the big picture,” says Deisseroth, who adds that his group is in the process of rendering an entire human brain transparent. 

The technique, published online in Nature on 10 April, turns the brain transparent using the detergent SDS, which strips away lipids that normally block the passage of light (K. Chung et al. Nature http://dx.doi.org/10.1038/nature12107; 2013). Other groups have tried to clarify brains in the past, but many lipid-extraction techniques dissolve proteins and thus make it harder to identify different types of neurons. Deisseroth’s group solved this problem by first infusing the brain with acryl­amide, which binds proteins, nucleic acids and other biomolecules. When the acrylamide is heated, it polymerizes and forms a tissue-wide mesh that secures the molecules. The resulting brain–hydrogel hybrid showed only 8% protein loss after lipid extraction, compared to 41% with existing methods. 

resulting brain–hydrogel hybrid showed only 8% protein loss after lipid extraction, compared to 41% with existing methods. 

Applying CLARITY to whole mouse brains, the researchers viewed fluorescently labelled neurons in areas ranging from outer layers of the cortex to deep structures such as the thalamus. They also traced individual nerve fibres through 0.5-millimetre-thick slabs of formalin-preserved autopsied human brain — orders of magnitude thicker than slices currently imaged. 

Neurons in an intact mouse hippocampus visualized using CLARITY and fluorescent labelling. Kwanghun Chung & Karl Deisseroth, HHMI/Stanford Univ. 

“The work is spectacular. The results are unlike anything else in the field,” says Van Wedeen, a neuroscientist at the Massachusetts General Hospital in Boston and a lead investigator on the US National Institutes of Health’s Human Connectome Project (HCP), which aims to chart the brain’s neuronal communication networks. The new technique, he says, could reveal important cellular details that would complement data on large-scale neuronal pathways that he and his colleagues are mapping in the HCP’s 1,200 healthy participants using magnetic resonance imaging. 

Francine Benes, director of the Harvard Brain Tissue Resource Center at McLean Hospital in Belmont, Massachusetts, says that more tests are needed to assess whether the lipid-clearing treatment alters or damages the fundamental structure of brain tissue. But she and others predict that CLARITY will pave the way for studies on healthy brain wiring, and on brain disorders and ageing. 

Researchers could, for example, compare circuitry in banked tissue from people with neurological diseases and from controls whose brains were healthy. Such studies in living people are impossible, because most neuron-tracing methods require genetic engineering or injection of dye in living animals. Scientists might also revisit the many specimens in repositories that have been difficult to analyse because human brains are so large. 

The hydrogel–tissue hybrid formed by CLARITY — stiffer and more chemically stable than untreated tissue — might also turn delicate and rare disease specimens into re­usable resources, Deisseroth says. One could, in effect, create a library of brains that different researchers check out, study and then return. Nature 496, 151 (11 April 2013) doi:10.1038/496151a

Proposed Brain Activity Map may also advance nanotechnology

ORIGINAL: Foresight

(credit: Comp. Cog. Neurosci Lab
/ Olaf Sporns, Indiana Univ.)

A proposal alluded to by President Obama in his State of the Union address to construct a dynamic “functional connectome” Brain Activity Map (BAM) would leverage current progress in neuroscience, synthetic biology, and nanotechnology to develop a map of each firing of every neuron in the human brain—a hundred billion neurons sampled on millisecond time scales. Although not the intended goal of this effort, a project on this scale, if it is funded, should also indirectly advance efforts to develop artificial intelligence and atomically precise manufacturing. In his blog, Robert L. Blum provides an excellent overview and brief introduction. From “BAM: Brain Activity Map: Every Spike from Every Neuron“:

A recent research proposal called BAM for Brain Activity Map Project generated much excitement. (The BAM proposal, published in Neuron in June 2012 is online, and an earlier draft with far greater detail is also online.)

(Addendum: 18 Feb 2013: I started drafting this story in Nov, 2012. Today it was headline news when it was made public that THIS is the very proposal that President Obama alluded to in his recent State of the Union address. See John Markoff’s NY Times piece. NIH is drafting a 3 billion dollar, 10 year proposal to fund this project. Also see this 25 Feb 2013 NY Times follow-up by Markoff.) …

The essence of the BAM proposal is to create the technology over the coming decade to be able to record every spike from every neuron in the brain of a behaving organism. While this notion seems insanely ambitious, coming from a group of top investigators, the paper deserves scrutiny. At minimum it shows what might be achieved in the future by the combination of nanotechnology and neuroscience. …

The Neuron article cited by Blum argues that in addition to breakthroughs in basic science with large medical and economic benefits, the BAM project will advance technology in terms of important general capabilities.

Many technological breakthroughs are bound to arise from the BAM Project, as it is positioned at the convergence of biotechnology and nanotechnology. These new technologies could include optical techniques to image in 3D; sensitive, miniature, and intelligent nanosystems for fundamental investigations in the life sciences, medicine, engineering, and environmental applications; capabilities for storage and manipulation of massive data sets; and development of biologically inspired, computational devices.

I think the emphasis on nanosystems of nanodevices integrated to provide complex functions is very important, even if many or most of those devices will, in the beginning, not be atomically precise. The more detailed description of the BAM proposal cited by Blum above hints at how nanoparticle-based sensors could be developed to noninvasively provide micrometer-scale spatial resolution and millisecond-scale temporal resolution to groups of millions of neurons deep inside the brain of a living, active animal (or human). The mention combining semiconductor quantum dots and nanodiamonds with organic nanostructures to functionalize them, so that they may be directed to and embedded in neural membranes to monitor synapses. In addition, nanotubes or nanowires could be developed to deliver photons to specific locations, or collect or release specific chemicals. Further, they suggest developing graphene into membrane patches for detailed monitoring of neurons. Taken together, the requirements for this ambitious project entail the need to develop a variety of nanoparticles for specific applications, and then integrating multifunctional nanoprobes, nanoparticles, and nanodevices into large functional systems, and producing such nanosystems en masse.

In his NY Times report John Markoff notes the possible effect of this project on the development of artificial intelligence: “Moreover, the project holds the potential of paving the way for advances in artificial intelligence.” Indeed, the information to be provided by BAM about how circuits of thousands or millions of neurons work should advance Ray Kurzweil’s program of reverse engineering the human brain to develop artificial general intelligence, as described in his new book How to Create a Mind: The Secret of Human Thought Revealed.

The next best thing to large program to develop molecular manufacturing is a large program aimed at other worthy and useful goals that also makes heavy use of nanotechnology and may promote some of the same or similar enabling technologies that will lead toward productive nanosystems.

—James Lewis, PhD

This entry was posted on Friday, March 1st, 2013 

A Near-Whole Brain Activity Map in Fish

ORIGINAL: MIT Review

Susan Young

March 18, 2013

Neuron-level whole-brain activity maps could one day help explain brain function and disfunction.

Image: Neurons glow red as they fire in this whole zebrafish larva brain. Credit: Misha Ahrens and Philipp Keller

Researchers have for the first time been able to image most of an entire vertebrate brain at the level of single cells, reports Nature.

A study from the Howard Hughes Medical Institute’s Janelia Farm Research Campus, published in Nature Methods, shows that modifications to existing microscopy techniques enable researchers to take snap shots of neuron-by-neuron activity in the whole brain of a living zebrafish larvae. The zebrafish larvae, whose bodies are transparent and brains are tiny, were genetically engineered to produce a protein in their neurons that glows in response to the chemical changes that occur when that neuron fires.

With conventional techniques, capturing the activity of even 2,000 neurons at once is difficult. With the modified fish and microscopy methods, the researchers were able to capture the activity of at least 80 percent of the baby fish’s 100,000 neurons over a time period of just 1.3 seconds. 

The result is an encouraging announcement for proponents of the Brain Activity Map project, a still-developing scientific collaboration to establish new technologies that can record the activity of all individual neurons in a brain circuit simultaneously (see “The Brain Activity Map”). According to Nature News, Rafael Yuste, a neurobiologist at Columbia University in New York and leader of the Brain Activity Map project, thinks the zebrafish results are “phenomenal.”

“It is a bright star now in the literature, suggesting that it is not crazy to map every neuron in the brain of an animal,” [says Yuste].

Minds of Mice Read With Glowing Proteins

ORIGINAL: LiveScience
by LiveScience Staff

19 February 2013

Neurons in the brain communicate via electrical impulses and neurotransmitters.
CREDIT: iDesign, Shutterstock

Scientists were able to read the minds of mice by lacing their brains with fluorescent proteins and looking at which parts glowed as the critters ran around a cage.

Using gene therapy techniques, the researchers engineered a green fluorescent protein that lit up in a mouse's brain when certain neurons were activated. A tiny microscope also was installed just above the hippocampus, a brain region thought to play a key role in spatial memory and navigation.

The microscope relayed information from about 700 neurons to a computer screen, where the scientists could watch the digital fireworks show and look for patterns in the bursts of activity as a mouse ran around its enclosure.

"We can literally figure out where the mouse is in the arena by looking at these lights," said Stanford researcher Mark Schnitzer in a statement. "The hippocampus is very sensitive to where the animal is in its environment, and different cells respond to different parts of the arena. Imagine walking around your office. Some of the neurons in your hippocampus light up when you're near your desk, and others fire when you're near your chair. This is how your brain makes a representative map of a space."

The researchers said specific neurons fired when the mouse was scratching at a wall in one section of the arena, but then faded when it scurried to a different part and another brain cell lit up. What's more, the same patterns in brain activity were observed in experiments that took place a month apart, the researchers said.

The team believes their research could be a starting point to test new therapies for human neurodegenerative diseases, such as Alzheimer's disease, which might make certain neurons stop functioning.

The research was detailed Feb. 10 in the online edition of the journal Nature Neuroscience.

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