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When our peripheral nerves fire anywhere in our body’s extremity… they are usually trying to tell our brain something rather important: “Hey, that stove top is a little too hot for your finger tips… pull away!” or, “I think that’s kind of sharp… it might be a nail… it is! it is a nail!… step away!”
While this extended network of vital warning zaps to our brain are not enjoyable as we sense them as intense pain, the function is critical to our survival and helps keep us from doing stupid things and warn us about problems that our visual perception might be missing. However, what if these warning zaps misfire? And, what if they keep misfiring constantly? They might be trying to tell us that something is wrong… possibly internally… and sure this might be useful, but what if you can’t do anything to fix the problem and they just keep on zapping?
This ongoing misfiring of localized sections in the peripheral nervous system is so much more than an annoyance, and is a serious and painful disorder for millions of humans. [ Read more about Peripheral Nerve Disorders ] One major problem in particular is peripheral neuropathy, where actual damage has occurred to the peripheral nerves. Although damage to these nerves certainly would be problematic — maybe you don’t notice that sharp nail pressing into your heel as quickly as you once did — but, the chronic problem is the damaged nerves seem to incessantly scream at the brain like a teenager who just learned she can’t stay out past midnight with her friends.
Wouldn’t it be nice to just tell those nerves to shut up and go to bed?
This is an important example of chronic pain that so many people suffer continuously through their day-to-day activities. Drugs have been used to combat the screaming nerves, but mostly measure up to over-the-counter pain medications. To date, there has been no systematic treatment developed, although there are several dedicated research centers located throughout the United States working on the problem.
Now, there is very early stage research on a new technological approach to quieting the broken nerves. A Dallas, TX-based startup called MicroTransponder is applying a very popular technology for powering and controlling electrical devices wirelessly. This technique, called “RFID” (radio-frequency identification), is a device that detects a remote radio signal to activate its internal circuitry to perform some function. The technology is already embedded in our culture, from automated highway toll collection (EZPass) to product tracking in inventory systems and even to checking in your library book.
For this application of remote neural stimulation, the idea is to inject tiny RFID devices to float around the damaged fingers or toes. When the nerve start to scream, an external signal generator will send out a radio-frequency message to the internal devices which will then power up and provide a polite zap back to the nerve endings. The anticipation is that applying just the right pattern of miniature jolts will quiet the screaming teenager and provide some relief to the 20 million Americans suffering today.
“Tiny Implants for Treating Chronic Pain” :: Technology Review :: May 15, 2009 :: [ READ ]
The Neuropathy Association [ VISIT ]
Many research groups have been working on the challenging aspects of controlling the growth of living neural networks. Of course, the ultimate hope is to eventually develop the technology to design electrical devices that will directly integrate with the human nervous system. A variety of important approaches are being considered, including surface patterning techniques used in conventional microfluidic technology ( learn more ), optical guidance from focused laser beams called “optical tweezers”–other wise known as present-day tractor beams–( learn more ), as well as various chemical coating methods like the use of novel “self-assembled monolayers” (SAMs). Here, a specialized two-ended molecule coats a surface with one end that likes to “stick” to the surface, like a silicon chip, and the other end likes to “stick” to neurons. Where ever the SAMs stick so will a neuron.
Recently at the Division of Solid State Physics at Lund University in Sweden, an advanced approach to surface patterning has been developed using electron-beam lithography to create rows of nanowires sitting on the surface of a substrate that influences the directional growth of the neuron’s axons and bundles of nerve fibers. You might imagine future neurotech device developers using this idea to pattern a silicon wafer with a specific highway map to force the exact growth of neurons in order to generate the correct network structure for a desired neuro-device’s function.
All of this pioneering work in patterning the growth of neurons into a structured network has a long road ahead. These early developments are so critical, and progress along several, competing paths are important for developing effective methods to design and create real neurotechnolgocial devices.
And, to emphasize the importance of this research, we are beginning to develop a new Neuron News Review section to cover the past, present, and future directions in living neuron network pattern techniques.
“Nanotechnology helps building a highway for nerve fibers” :: Nanowerk Spotlight :: May 13, 2009 :: [ READ ]
Recently we reviewed the interesting work of FACETS, a large European collaboration developing hardware-level designs for computer circuits that mimic the architecture of our brain. Another group here in the United States at Stanford University is taking an alternate hard-wiring approach to designing a brain in silico.
They hope to create a computer that works nearly as powerfully as the human brain–and be “affordable” at the same time. In addition, they also anticipate that not only will their work take a step forward to a deeper understanding of human brain function, but it will also provide the computational power to help other neuroscientists better analyze and simulate neural activity to advance their own research.
The research team, lead by Kwabena Boahen, is developing a neuromorphic chip: a computer that is not based on the classic transistor developed in 1947, but instead is composed of individual mini-circuits designed like a human neuron, developed some 250,000 or more years ago. More specifically, the ion-flow regulated in the neuron’s membrane is replicated by electron flow in the silicon device. And with quite a bit of clever foresight, the interconnections between the “silicon neurons” are not permanently hardwired on the circuit. Instead, each silicon neuron is identified by a memory address, like in a typical RAM chip, and their electrical activity is referenced by the controlling software. This allows for the same chip to be soft-wired to model the interconnectivity of any sort of neural network that is desired to be used for a particular computational application.
Read more about the specific details of how the neuromorphic chips are designed, fabricated, and tested at the Brains in Silicon group’s website. [ VISIT ]
K Boahen, “Neuromorphic Microchips,” Scientific American, vol 292, no 5, pp 56-63, May 2005. [ READ (pdf) ]
K Boahen, “Neuromorphic Microchips,” Scientific American, vol 292, no 5, pp 56-63, May 2005. [ READ (pdf) ]
On May 5, 2009 DARPA (Defense Advanced Research Projects Agency) announced that it is preparing to begin an exciting new research program that may be the most ambitious and direct effort by the United States Government to to push human technology closer to the edge of the awaiting Singularity. The program is referred to as Physical Intelligence, and DARPA is currently soliciting interested research groups to develop project proposals for submission. The ultimate goal of the effort will be to fundamentally understand the physical phenomenon of intelligence and to then demonstrate the characteristic in a man-made electronic or chemical system.
Although you might have considered taking on this problem yourself this weekend, it’s understandable if a week’s worth of yard work and Mother’s Day preparations took a critical priority. Leaving this project to large governmental agencies and massive academic and industrial collaborations may be the best idea for your personal work-load at this time.
The funding levels for the Physical Intelligence program have not yet been set, as they will be later determined depending on the details of winning proposals. This could be an effective blank check from the Federal Government supporting a potentially mammoth project that would do nothing less than transform humanity. Why go back to th Moon when we could instead solve one of the most fundamental questions of our species. In the meantime, America could certainly regain our stature of being the primary scientific center on Planet Earth.
What is particularly interesting about this solicitation is that DARPA has explicitly limited the theoretical framework from which researchers may pursue the solution to understanding Physical Intelligence. They make the bold claim that the phenomenon of intelligence emerges directly from thermodynamic processes in the human brain or an engineered machine. Any proposal that contains alternate viewpoints will automatically be rejected from consideration for funding.
At first, it may seem that starting with thermodynamics is too limiting for theoretical progress in modeling intelligent behavior. As a basic starting point, the science of thermodynamics looks at characteristics that emerge from a system composed of effectively infinite parts. For example, the measured temperature of your steak flaming on the grill is just the collective measurement of the motion of trillions of meat atoms and molecules. At other levels, the theory models the transfer of energy between systems and measures the slightly odd variable of entropy, which essentially characterizes how messed up the observed system is. In other words, the shattered glass just knocked to the floor by your coordination-lacking infant son has a higher entropy than it did moments before while sitting peacefully on the dinning room table.
But, we aren’t just talking about heat engines that convert a hot flame into mechanical motion and the phase transition we experience every day while boiling water into steam over a hot stove. Thermodynamics and the broader field of statical mechanics represent the fundamental physics that underlie all of the relatively new ideas of self-organization, complex systems, network architecture and many other concepts that are driving the latest in brain science. Maybe DARPA really is on to something theoretical and, even if they don’t know the answers to life’s biggest questions just yet, they certainly know how to keep their funding solicitations general enough to allow for a broad range of scientific collaborators to jump on board … if they are only brave enough.
The Physical Intelligence program is organized around three levels of critical milestones. The first step is to develop a mathematical theory of the thermodynamics of intelligence and then to represent this theory in a producible system. Second, the aforementioned engineered system must be built and successfully demonstrate intelligence. Third, and finally, additional tools must be developed and designed to further analyze and monitor the created intelligent systems.
The other key limitation to this solicitation is that proposers must be able to submit plans that cover not just a portion of these three milestones, but they must be prepared to take the project all the way to home plate. This is Nobel Prize territory, folks, and anyone who is prepared to tackle human species-altering projects must be ready for the ride of a lifetime.
The boldness of the program is nothing less than what would be expected from proud United States scientists, and the American society is certainly ready for another “One small step for man… one giant leap for mankind.” It certainly is an exciting moment to see the interest, dedication, and–of course, most importantly–financial backing of the Federal Government be honed onto the advancement of machines that match, or even exceed, the level of human intelligence that we effortlessly demonstrate every day.
Our brain is like a uniquely powerful computer. It’s in a class of technology that no typical serial or parallel processor today can replicate. Many scientists have tried to develop computer code that attempts to mimic through simulations, such as the current Blue Brain Project, but the computing power for these approaches are becoming immense.
Alternatively, a large European Union collaboration called FACETS has been working on the design, fabrication, and implementation of a new kind of transistor-based computer chip that structurally mimics the neural networks of the human brain.
The goal of the project is to create a unique computing architecture that uses what we already know of the structure of the human brain as a foundational design concept. The anticipation is that by creating this new hardware, we might gain a significant advancement in computational technology that might keep us moving upward along the classical Moore’s Law path even after traditional transistor-based architectures reach their lowest physical size limit.
The current scale of these brain-like computer chips are far from the level of the interconnectivity of the human brain. At this time, they have developed chips with around 200,000 transistor-styled “neurons” utilizing 50 million mimicking “synapses”. This is a far cry from the human brain’s nearly 100 billion neurons and countless synapses.
This project is not necessarily trying to build a silicon brain… but is wisely trying to take the structural concept of the human brain and apply it to a new hard-wired approach to develop the next-next-next generation of desktop computers.
Humanity may undergo an evolutionary phase transition within this century at the very moment our computational creations develop a level of intelligence that surpasses that of the typical human being. This predicted development is referred to as The Singularity. This transitional event might be considered a true evolutionary development for our species because our primary evolutionary advantage over the rest of the natural kingdom–high-level tool-making–is driving our engineering of ever-more powerful robots and computing machines.
However, we do often forge ahead in our technological developments with pure brute force in an attempt to make as much progress as possible in as short a time as possible. Notably, the classic Moore’s Law, an idea suggested by the co-founder of Intel, has accurately predicted the advancement of computing power over many decades. This exponential “law” is still expected to continue, and is a key predictive element for the coming Singularity Event.
However, bottlenecks for technical advancements in silicon-chip development that conforms with Moore’s Law have been foreseen in the past–and have been overcome. Making transistors ever smaller has been the primary brute-force method of increasing computational power, but there must be an ultimate limit: the scale of a single atom.
So, if silicon chips with transistors still larger than a single atom do not provide enough computing power to bring about The Singularity, what fork in the road of this bottleneck might we diverge onto? The human brain clearly does not have a circuitry that mimics the traditional structure of the computer chip. Even massively parallel computing systems do not come close to replicating the network structure of our brain. And it is the morphological structure of our networked neurons that ultimately gives rise to the emergent computational power of the mind… it’s just that we don’t yet understand this complex network structure.
A brief commentary on this potential bottleneck in reaching The Singularity with a call to consider alternate approaches was presented recently in a New York Times guest column. How will we finally reach The Singularity? A new technological approach may be necessary; a new philosophical approach may be necessary; a new, more complete understanding of the structure of our own brains will certainly be necessary.
“Computers vs. Brains” :: Guest Column from The Wild Side, The New York Times:: March 31, 2009 :: [ READ ]
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