How To Repair Connections Between Nerve Cells

Carbon nanotubes exhibit interesting characteristics rendering them particularly suited to the construction of special hybrid devices – consisting of biological tissue and synthetic material – planned to re-establish connections between nerve cells, for instance at spinal level, lost on account of lesions or trauma. This is the result of a piece of research published on the scientific journal Nanomedicine: Nanotechnology, Biology, and Medicine conducted by a multi-disciplinary team comprising SISSA (International School for Advanced Studies), the University of Trieste, ELETTRA Sincrotrone and two Spanish institutions, Basque Foundation for Science and CIC BiomaGUNE. More specifically, researchers have investigated the possible effects on neurons of the interaction with carbon nanotubes. Scientists have proven that these nanomaterials may regulate the formation of synapses, specialized structures through which the nerve cells communicate, and modulate biological mechanisms, such as the growth of neurons, as part of a self-regulating process. This result, which shows the extent to which the integration between nerve cells and these synthetic structures is stable and efficient, highlights the great potentialities of carbon nanotubes as innovative materials capable of facilitating neuronal regeneration or in order to create a kind of artificial bridge between groups of neurons whose connection has been interrupted. In vivo testing has actually already begun.

Scientists have proven that these nanomaterials may regulate the formation of synapses, specialized structures through which the nerve cells communicate, and modulate biological mechanisms, such as the growth of neurons, as part of a self-regulating process

Interface systems, or, more in general, neuronal prostheses, that enable an effective re-establishment of these connections are under active investigation” explain Laura Ballerini (SISSA) and Maurizio Prato (UniTSCIC BiomaGUNE), coordinating the research project. “The perfect material to build these neural interfaces does not exist, yet the carbon nanotubes we are working on have already proved to have great potentialities. After all, nanomaterials currently represent our best hope for developing innovative strategies in the treatment of spinal cord injuries“. These nanomaterials are used both as scaffolds, a supportive framework for nerve cells, and as means of interfaces releasing those signals that empower nerve cells to communicate with each other.

Source: https://eurekalert.org/

Perfect Image Of Brain Synaptic System

The human brain contains more synapses than there are galaxies in the observable universe (to put a number on it, there are perhaps 100 trillion synapses versus 100 billion galaxies), and now scientists can see them all – individually. A new imaging tool promises to open the door to all sorts of new insights about the brain and how it works. The tool can generate images at a nanoscale resolution, which is small enough to see all cellular objects and many of their sub-cellular components (so for the biology-literate, that’s stuff like neurons and the synapses that permit them to fire, plus axons, dendrites, glia, mitochondria, blood vessel cells, and so on).

 

brain-imaging-tool-nanoscale-resolution-1

Developed by researchers at the Boston University School of Medicine and Harvard University, the imaging method employs an automated tape-collecting device equipped with a diamond knife to obtain ultra-thin brain sections, which are then scanned under an electron microscope. Different colors are used to identify different cellular objects using software developed by study co-author Daniel Berger.

To demonstrate their new tool the researchers peered inside the brain of an adult mouse. They imaged a very small piece of a mouse’s neocortex at a resolution that made individual synaptic vesicles visible (these are tiny spheres of less than 40 nm diameter that store neurotransmitters, or chemical signals, for release from a synapse into a “target” neuron). The specific area they imaged is involved in receiving sensory information from mouse whiskers, which are much more sensitive than human fingertips.

Source: http://www.cell.com/
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http://www.gizmag.com/

Artificial Synapses Operate Image Classification

In what marks a significant step forward for artificial intelligence, researchers at UC Santa Barbara have demonstrated the functionality of a simple artificial neural circuit. For the first time, a circuit of about 100 artificial synapses was proved to perform a simple version of a typical human task: image classification.

“It’s a small, but important step,” said Dmitri Strukov, a professor of electrical and computer engineering. With time and further progress, the circuitry may eventually be expanded and scaled to approach something like the human brain’s, which has 1015 (one quadrillion) synaptic connections.

For all its errors and potential for faultiness, the human brain remains a model of computational power and efficiency for engineers like Strukov and his colleagues, Mirko Prezioso, Farnood Merrikh-Bayat, Brian Hoskins and Gina Adam. That’s because the brain can accomplish certain functions in a fraction of a second what computers would require far more time and energy to perform.

What are these functions? Well, you’re performing some of them right now. As you read this, your brain is making countless split-second decisions about the letters and symbols you see, classifying their shapes and relative positions to each other and deriving different levels of meaning through many channels of context, in as little time as it takes you to scan over this print. Change the font, or even the orientation of the letters, and it’s likely you would still be able to read this and derive the same meaning.

artificial synapses

In the researchers’ demonstration, the circuit implementing the rudimentary artificial neural network was able to successfully classify three letters (“z”, “v” and “n”) by their images, each letter stylized in different ways or saturated with “noise”. In a process similar to how we humans pick our friends out from a crowd, or find the right key from a ring of similar keys, the simple neural circuitry was able to correctly classify the simple images.

While the circuit was very small compared to practical networks, it is big enough to prove the concept of practicality,” said Merrikh-Bayat. According to Gina Adam, as interest grows in the technology, so will research momentum.

And, as more solutions to the technological challenges are proposed the technology will be able to make it to the market sooner,” she said.

The researchers’ findings are published in the journal Nature.

Source: http://www.news.ucsb.edu/