We Are All Cyborgs Now: Soft-Material Memristor Brain Augmentation

One of the most-discussed memristor characteristic is its synaptic biomimesis. “State-of-the-art computers have difficulty mimicking the operation of the brain,” [NCSU Professor] Dickey notes. “Memristors, on the other hand, are effective at mimicking synapses. If you were interested in only mimicking brain function, then solid-state memristors would be more practical because they contain many more memory elements and are much more optimized at this point. One of the things distinguishing our work is that the device behaves like a memristor and has other properties similar to the brain. Conventional electronics tend to be rigid, 2-D, moisture-intolerant, and operate using electrons; the brain, in contrast, is soft, 3-D, wet, and operates using ions and in addition to adopting many of these properties, our device is composed of biocompatible hydrogels.” _Physorg

Human brains are marvelous biological machines, but they could be a lot better. It will prove easier to augment the human brain technologically than to replace it altogether with a cognitive machine. The invention of a soft-material, biocompatible computing architecture would allow the implantation of computing devices into the human body. North Carolina State University scientists and engineers have begun to invent what they hope can be such a material -- the soft-material memristor.

Prof. Orin Velev, Prof. Michael Dickey, and graduate students Hyung-Jun Koo and Ju-Hee So, have devised a new class of easily fabricated memristors based entirely on so-called soft matter – hydrogels doped with polyelectrolytes sandwiched with liquid metal electrodes – that operate using ionic conductance in aqueous systems rather than conventional electron transport.

...In essence, this suggests that in addition to having the potential to realize memristor-based neuromorphic structures, the polysaccharide hydrogel core of these devices is biocompatible, could possibly be interfaced with live neural and other tissue, and could lead to three-dimensional soft circuits and their in vivo operations.

...Going forward, Dickey continues, “We hope to take advantage of the fact the water-based gels in the device are biocompatible, and could in principle be integrated with biological species, such as cells, enzymes, proteins, and tissues. We also made no attempt to optimize the memory capacity in our prototypes, which is an area for improvement. Finally, we’re working to understand the subtle aspects of the operating mechanism.” _PO

They are still in the very early stages, but the possibility of an implantable soft, biocompatible brain augment is too important to overlook.

Quite a few different interfacing techniques could be used, but the optical approach would seem to be the least intrusive for tissues such as the brain, which are sensitive to electromaqnetic forces. Optical materials have high bandwidth and may be less likely to be bio-rejected than electrically conductive materials. Some people have discussed optical brain control in the context of optogenetics.

Another fascinating type of bio-to-machine interface is the piezoelectric interface being developed at Georgia Tech. The piezoelectric interface can be operated by exquisitely subtle mechanical movements, such as a muscle fibre twitch. In other words, a thought -- even a subconscious though -- could cause a pattern of muscle twitches which would activate a particular machine command or subroutine via the piezoelectric interface.

The human brain was not evolved for the ultra-long lifetime of a next level human. Cell debris accumulates, DNA repair mechanisms begin to fail, immune systems weaken, hormonal support falls off, etc. Scientists are learning a lot about how normal aging leads to memory loss in even the sharpest minded senior citizens. The intricate network of cellular connections in the brain slowly loses definition and resolving power.

Well-designed brain implants could sense this process occurring and engineer work-arounds to compensate for the changes. Long term solutions would require a rejuvenation treatment to restore -- or improve -- the resolving power of brain networks, but sometimes work-arounds are the best one can do at the time.

Where would you place your soft bio-compatible brain implant? There isn't a lot of room inside the skull itself, but implants could be placed under the scalp in a relatively unobtrusive manner as long as they were not too large. Alternatively, some women might choose to place their augments in the breast area, and some men might choose augments shaped to serve as muscle implants. If the connections to the interface are via optical fibre, the distance from anywhere on the human body to the brain is negligible, in terms of the speed of light. The interface itself would need to be placed close to the brain.

Depending upon its sophistication, an implanted brain augment could come to know how an individual's brain works quite well, over a period of time. Such augments could even learn how to simulate their hosts in a rudimentary way. The possibilities arising from such pseudo-emulation are worth considering, but perhaps not here and now. (See Old Man's War by John Scalzi)

It is important to stress that these NCSU memristors are not at all close to anything that could be used as a brain augment. But it seems to be the goal of the researchers there to develop biocompatible sensors and intelligent interfaces using these materials. It is not a long stretch from there to an implantable computer augmentation for the brain.

Although memristors are often referred to as neuromimetic or synaptomimetic, in the aggregate, memristor computing devices will function nothing like the brain. But they will not need to. They will only need to function like competent and clever computers that provide reliable memory and I/O capability for mental computations, speculations, and interfacing with the outside world -- including the ability to control machines mentally and to communicate remotely with machines and other individuals who have similar augments.

Human Brain Project Moves Toward Human Cortex Model

Spiegel
Henry Markram's Human Brain Project in Lausanne, is competing for funding from the FET Flagship Initiative, to the tune of 1 billion Euros, disbursed over a ten year period. Markram's goals are extremely ambitious, and unprecedented. He aims to model the human cerebral cortex to an exquisite degree of precision. Markram expects that his model of the human brain will be so exact, that he will be able to study inaccessible brain diseases and devise impossible brain cures by using his model. He may be right. But in only ten years?

Scientists are paying particular attention to the cerebral cortex. This layer on the outside of brain, only a few millimeters thick, is the most important condition of it evolution. It is the starting point for efforts to understand what makes us tick -- and for endeavors to find solutions when things go wrong. Our brain builds its version of the universe in the cerebral cortex. The vast majority of what we see doesn't enter the brain through the eye. It is instead is based on the impressions, experiences and decisions in our brain.

Markham already completed important preparatory work for the computer modeling of the brain with his Blue Brain Project, an attempt to understand and model the molecular makeup of the mammalian brain. He modeled a tiny part of a rat brain, a so-called neocortical column, at the cell level. To understand what one of these columns does, it's helpful to imagine the cerebral cortex as a giant piano. There are millions of neocortical columns on the surface, and each of them produces a tone, in a manner of speaking. When they are simulated, the columns produce a symphony together. Understanding the design of these neocortical columns is a holy grail of sorts for neuroscientists.

It is important to understand the rules of communication among the nerve cells. The individual cells do not communicate at random, but instead seek specifically targeted communication partners. The axes of nerve cells intersect at millions of different points, where they can form a synapse. This makes communication between individual neurons possible. In a recent article in the journal Proceedings of the National Academy of Sciences, Markram writes that such connections are also developed entirely without external influence. This could indicate a sort of innate knowledge that all people have in common. Markram refers to it as the "Lego blocks" of the brain, noting that each person assembles his own world on the basis of this innate knowledge. _Spiegel

The object of study for the Human Brain Project may be the most complex dynamic system in the universe. The attempt would be impossible without the most sophisticated computing hardware and software available. And one must have more than a mere fistful of Euros to acquire such advanced goodies.

Modeling all of this in a computer is extremely complex. Markram's current model encompasses tens of thousands of neurons. But this isn't nearly enough to come within striking range of the secret of our brain. To do that, scientists will have to assemble countless other partial models, which are to be combined to create a functioning total simulation by 2023.

The supercomputers at the Jülich Research Center near Cologne are expected to play an important role in this process. The brain simulation will require an enormous volume of data, or what scientist Markram calls a "tsunami of data." One of the challenges for scientists working under Thomas Lippert, head of the Jülich Supercomputing Centre, is to figure out how to make the computer process only a certain part of the data at a given time, but without completely losing sight of the rest. They also have to develop an imaging method, such as large, three-dimensional holograms, to depict the massive amounts of data.

All it takes is a look at the work of Jülich neuroscientist Katrin Amunts to understand the sheer volume of information at hand. The team she heads is compiling a detailed atlas of the human brain. To do so, they cut a brain into 8,000 slices and digitized them with a high-performance scanner. The brain model generated in this way consists of cuboids, each measuring 10 by 10 by 20 micrometers, and the size of the data set is three terabytes. Brain atlases with higher resolutions, says Amunts, would probably consist of more than 700 terabytes _Spiegel

The answer to the question posed above is: No, this goal cannot be met within a time frame of ten years. Because the challenge is not merely quantitative -- a matter of compiling the precise assembly of terabytes to create a brain atlas. The goal is to create a dynamic, interactive model of incredible plasticity -- a model which changes itself moment to moment. The "700 terabyte" requirement mentioned above is just the starting point -- the bare beginning -- in the assembly of such a dynamic and ever-changing model.

But the problem is even harder -- much, much harder. The quantitative complexity -- even in dynamic flow -- is nothing when compared to the qualitative complexity, which is nowhere near to being solved by Markram's team.

The project as described in brief above is an excellent starting point. Much can be learned from such an approach. But starting points do not necessarily point directly toward the end that one seeks. Rather, they point somewhere "out there." It is for the questers to continuously adjust their headings -- and often they are forced to adjust their goals.

Good luck to Henry and his team -- with the funding and with the ongoing project. It is an ambitious goal worthy of any scientist.

Double Plus Overhype Ado About Artificial Synapse?

There's a news story replicating on the web right now about a "Functioning Synapse Created Using Carbon Nanotubes," for instance here and here.

....the circuit has not actually been constructed, so the "apparatus" photo there is kind of silly. It just gives the false impression that a synapse model was actually built physically with analog components.

...[ed: all that we have is] an electrical circuit schematic that in turn depends on certain SPICE models of carbon nanotube FETs (which have apparently been available since 2006). So in other words, this circuit is a particular model of a synapse being simulated with a simple circuit. _Science20

Samuel Kenyon points out at the Science20 article linked above, that the "artificial synapse" is only a simulated circuit using the SPICE electronic simulation program. But the overhype is doubly overdone, because even if the researchers had actually built a real, physical circuit that functioned as an "artificial synapse", it would still not put them any closer to actually building an "artificial brain."

PDF Source (via Science20) This overhyped excitement is reminiscent of IBM scientist Dharmendra Modha's claim that he had built a computer that was the equivalent of "a cat's brain." Initially, most science blogs (except Al Fin) accepted Modha's claim at face value. Then when Henry Markram came out publicly to refute the claim, Modha backed off and clarified, and almost everyone agreed in the end, that it was all pretty much ado about nothing.

It is the same thing here, where science and tech blogs initially rush to accept exaggerated claims in press releases. Then, little by little, sceptics step up and insist upon clarifications and qualifications of claims, until the claims are downgraded to the point that eventually no one can remember what the fuss was about.

In the case of "the artificial synapse", it is important to understand why this real world device is not even a synapse, much less a possible ingredient for an artificial brain.

The USC and Stanford researchers have designed a computer model of "an artificial synapse," not an actual artificial synapse. But even if it were a real synapse, would engineers be able to use it to assemble an artificial brain? No. And the reason why one thing does not naturally lead to the next is crucial to an understanding of how real brains work -- real brains being the only working proof of concept of intelligence in the known universe.

Artificial intelligence enthusiasts will rush to say that working brains do not necessarily have to work just like the bio-brains we know now. But then, what is the point of emulating a tiny component of a bio-brain in the first place, if you cannot use it to build a functioning brain, as we understand it? In other words, if your objective is to build a new class of brain, why start with a poor imitation of a low level component of a bio-brain? Why not start with something "better" from the get-go? [By "better", I mean faster, more versatile, etc etc]

Here is the reason: Because artificial intelligence researchers do not have a clue as to how to build an intelligent brain. And so they are practising a subtle form of cargo cult science.

It's okay. We all understand that rents and utilities must be paid, the price of gasoline is high, everything costs money. Academics must publish or perish, and getting research grants to build "artificial synapses" does sound kind of sexy. Anything to keep the lights on, right?

But all the same, it is important to understand that brains are not the plural of "synapse." It is time to stop pretending that one has made progress toward AI, when nothing of the sort has happened.

More: It is important to understand that the bulk of the exaggeration comes from press releases and media coverage. Here is the actual conclusion from the research study referred to:

A carbon nanotube synapse typical of cortical synapses has been designed and simulated using SPICE. While the simulations were successful, the design of a single typical synapse is only a small step along the path to a synthetic cortex. The variations in synapses, including inhibitory synapses, will be the focus of future research. Predicting the interconnection capabilities of nanotube circuits is also important in understanding the future prospects for a synthetic cortex. _PDFeve.usc.eduPDF

Unfortunately, as computer modelers try to more realistically model the events in the brain at cellular and molecular levels, computing power and computing time demands explode out of control very rapidly. More, the researchers above do not seem to understand the key facts of brain function upon which conscious intelligence is balanced: time-dependent high level cross-brain synchronisation (via evolved white matter pathways) of evolved multiple modular (grey matter) brain centers from brain stem to neocortex, dancing alongside sensory input, jostled by memory, under the changing lights of emotion, and swept up in hormonal tides and chaotic flows of molecules...

More complex than one imagines? More complex than one can possibly imagine. The job is simply too hard for intelligent design. Only evolution will do. We need to get better at intelligently designing evolution. ;-)

Micro-Electronic Brain Implant Supervises Brain Re-Wiring

When the human brain is damaged from trauma, stroke, infection, or tumour etc., the damaged tissue does not re-grow itself spontaneously. Instead, the person must learn to compensate for the loss of function. Some brain plasticity may occur, as undamaged parts of the brain take responsibility for some of the functions which the destroyed parts previously carried out. But damaged brain does not heal.

Researchers at Case Western Reserve University intend to change that, by using implanted electronics devices which can help teach the brain how to re-wire itself to allow disconnected parts of the brain to become connected -- and functional -- again.

Pedram Mohseni, a professor of electrical engineering and computer science at Case Western Reserve University, and Randolph J. Nudo, a professor of molecular and integrative physiology at Kansas University Medical Center, believe repeated communications between distant neurons in the weeks after injury may spark long-reaching axons to form and connect.

Their work is inspired by the traumatic brain injuries suffered by ground troops in Afghanistan and Iraq.

...Mohseni has been building a multichannel microelectronic device to bypass the gap left by injury. The device, which he calls a brain-machine-brain interface, includes a microchip on a circuit board smaller than a quarter. The microchip amplifies signals, called neural action potentials, produced by the neurons in one part of the brain and uses an algorithm to separate these signals – brain spike activity - from noise and other artifacts. Upon spike discrimination, the microchip sends a current pulse to stimulate neurons in another part of the brain, artificially connecting the two brain regions.

...During the next four years, they expect to understand the ability to rewire the brain in a rat model and to determine whether the technology is safe enough to test in non-human primates. If tests show the treatment is successful in helping recovery from traumatic brain injury, the researchers foresee the possibility of using the approach in patients 10 years from now. _Eurekalert

Here is an abstract of a paper published by Mohseni in an IEEE publication from 2008:

This paper reports on the design, implementation, and performance characterization of a high-output-impedance current microstimulator fabricated using the TSMC 0.35 mum 2P/4M n-well CMOS process as part of a fully integrated neural implant for reshaping long-range intracortical connectivity patterns in an injured brain. It can deliver a maximum current of 94.5 muA to the target cortical tissue with current efficiency of 86% and voltage compliance of 4.7 V with a 5-V power supply. The stimulus current can be programmed via a 6-bit DAC with an accuracy better than 0.47 LSB. Stimulator functionality is also verified with in vitro experiments in saline using a silicon microelectrode with iridium oxide (IrO) stimulation sites. _IEEEXplore

The technology for such interventions is in the early stages. The researchers are also working on devices which can be used for a broad range of neurological and psychiatric conditions, and in conjunction with neurosurgery and standard post-surgical rehabilitation.

Eventually such devices will probably be implanted into a damaged area of brain, along with an artificial matrix seeded with a person's own stem cells and growth factors. The devices will be wired to "bridge" from healthy brain on one side of the lesion to healthy brain on other sides of the lesion (corresponding to interrupted pathways). The electronic signals will not only help guide a re-wiring of the brain, but they should also guide the re-growth of new replacement brain tissue of specific replacement types.

Anyone who has read the science fiction novel "Old Man's War" by John Scalzi, should recognise some of the intent behind the early stage, rudimentary devices being developed at Case Western -- and to see where the technology may be heading.

More on a related topic from Brian Wang