Brain Chip to Restore Functioning from Damage

The ReNaChip project is developing electronic biomimetic technology that could serve to replace damaged or missing brain tissue. This is basically neuromorphic engineering that seeks to mimic how neurons function. In the future this may be useful for people who have had injuries due to stroke or other illnesses. There are numerous obstacles to getting this tech off the ground. Having the microchip interface properly with the surrounding neural tissue is one issue that could be difficult to circumvent. It is also unclear if some of the models used actually represent specific regions of the mind accurately enough for this to work properly.

This page gives an overview of this undertaking;

The objective of this project is to develop a full biohybrid rehabilitation and substitution methodology; replacing the aged cerebellar brain circuit with a biomimetic chip bidirectionally interfaced to the inputs and outputs of the system. Information processing will interface with the cerebellum to actuate a normal, real-time functional behavioural recovery, providing a proof-of-concept test for the functional rehabilitation of more complex neuronal systems.

More information can be found at this page.

Experiments are carried out with two different types of stimuli; a tone which serves a conditioned stimulus producing no naïve response and an aversive puff to the eye (unconditioned stimulus) resulting in a naïve eyeblink response. The tone always precedes the airpuff in the course of the experiment.

A recent article about it is here.

The project aims include making a computer model of a well-defined brain pathway as proof of concept for the replacement of more complex brain circuits. Implementation of this model in a microchip will be used to create a biohybrid in which a lost behaviour is restored

This abstract discusses about interfacing with neuronal cells.

One of the major goals of the ReNaChip research program was to develop implantable electrodes with a very small size sensing pads. In this talk we will describe the process related issues of such electrodes and their principle of operation.

The researcher Ed Boyden has recently called for the creation of an "exocortex" to augment human abilities. It seems conceivable that a device implanted on top of the head could be used to increase intelligence or other traits. The exocortex would have to communicate with actual brain cells in some fashion. Perhaps this could be done using optogenetics or ultrasound pulses. Neither are approved for human disorders yet. Optogenetics would be more invasive but it is also much more selective in its ability to activate neuron subpopulations. I've been somewhat skeptical about whether it would actually get an FDA nod any time soon, however. Ultrasonic neuromodulation does not currently have the same targeting accuracy, but it would not require a person's skull to be breached. A sophisticated exocortex could potentially allow a two way communication between the external apparatus and the mind. The contraption could essentially scale up the amount of neurons in your brain by an artificial means. Most likely it would be used to improved the disabled first, with other applications being more speculative possibilities.

Page of a researcher who is working on the ReNaChip project.

An older article about Renachip is here.

Artificial Brain

I found a blog that has some more information about the DARPA SYNAPSE project. The SYNAPSE project seeks to create a neuromorphic artificial brain. That blog also has a bunch of older posts that specifically relate to this project. Will this actually lead to anything? I suppose it's always possible, but I guess I'm fairly skeptical that it will accomplish much.

SyNAPSE is a complex, multi-faceted project, but traces its roots to two fundamental problems. First, traditional algorithms perform poorly in the complex, real-world environments that biological agents thrive. Biological computation, in contrast, is highly distributed and deeply data-intensive. Second, traditional microprocessors are extremely inefficient at executing highly distributed, data-intensive algorithms. SyNAPSE seeks both to advance the state-of-the-art in biological algorithms and to develop a new generation of nanotechnology necessary for the efficient implementation of those algorithms.

Another blog also has some information that pertains to neuromorphic electronics.

“Neuromorphic engineering takes inspiration from the signal processing structures found in the brain and physical attributes of animals to design new computers and robots capable of the amazing sensorimotor feats seen in nature. From neurons to behavior, the low-power, robust, real-time, and adaptive nature of biological systems serves as a proof-of-concept of the unique implementation developed by evolution. These principles have been applied to software models of sensory processing, VLSI implementations of neural circuits, and robot design.”

Also I found this interesting paper called "Framework and implications of virtual neurorobotics" (PDF) that discusses about using virtual reality environments to further the development of neuromorphic electronics.

More recently, investigators are focusing on the core assumptions of the brain “algorithm” itself—trying to replicate uniquely “neuromorphic” dynamics such as action potential spiking and synaptic learning. Only now are large-scale neuromorphic models becoming feasible, due to the availability of powerful supercomputers and an expanding supply of parameters derived from research into the brain’s interdependent electrophysiological, metabolomic and genomic networks. Personal computer technology has also led to the acceptance of computer-generated humanoid images, or “avatars”, to represent intelligent actors in virtual realities. In a recent paper, we proposed a method of virtual neurorobotics (VNR) in which the approaches above (social-emotional robotics, neuromorphic brain architectures, and virtual reality projection) are hybridized to rapidly forward-engineer and develop increasingly complex, intrinsically intelligent systems. In this paper, we synthesize our research and related work in the fi eld and provide a framework for VNR, with wider implications for research and practical applications.

I don't see much discussion about the ethics of doing this type of research. I'm not sure if they are attempting to make artificial brains that are conscious or not. Bringing about a conscious AI could have a variety of ethical implications. Most likely, though, progress in this field will be fairly slow. I wouldn't expect much to happen for quite some time, if at all.

FACETS Project

There is another project that is attempting to simulate aspects of the brain via a computer. The FACETS project (short for uh, Fast Analog Computing with Emergent Transient States) has already been ongoing for several years. The FACETS acronym is not as clever as the SYNAPSE project term, if you didn't already notice. It seems like DARPA is better at coming up with witty acronyms.

The FACETS project aims to address the unsolved question of how the brain computes with a concerted action of neuroscientists, computer scientists, engineers and physicists. It combines a substantial fraction of the European groups working in the field into a consortium of 13 groups from Austria, France, Germany, Hungary, Sweden, Switzerland and the UK. Since September 2005 more than 80 scientists join their efforts over a period of 4 years. A project of this dimension has rarely been carried out in the context of brain-science related work in Europe, in particular with such a strong interdisciplinary component.

A recent article has some more good information on the progress of this project.

The goal is to use these models to build a ‘neural computer’ which emulates the brain. The first effort is a network of 300 neurons and half a million synapses on a single chip. The team used analogue electronics to represent the neurons and digital electronics to represent communications between them. It’s a unique combination.

When will people learn? You have to make an acronym with a little pizazz, otherwise no one will care about your project. Maybe that's why the US is always beating the Europeans on this stuff. Some people really need a basic course in memetics 101.

Synthetic Brain

Researchers from the University of Southern California have shown that carbon nanotubes may be used to model the functioning of brain cells (neurons). These researchers are designing a carbon nanotube circuit to model the properties of a real brain cell. So far the scientists have only tested computer simulations to see whether it is theoretically possible and have not actually synthesized a carbon nanotube circuit yet. So this may lead to the creation of better artificial neurons and potentially enable the construction of a synthetic electronic brain. I've mentioned in the recent past about using carbon nanotubes to create brain computer interfaces. In that post, I talked about how carbon nanotubes were able to make a working connection between different neurons. Carbon nanotubes are molecular tube shape structures composed of honeycomb patterns of chemically bonded carbon atoms. They conduct electricity and have already found use in a variety of novel technologies. This ability to conduct electricity allows the carbon nanotubes to serve as a communication junction between two neurons. This new research shows they may have even more versatility and usefulness for brain emulation advancement.

The researchers have shown that portions of a neuron can be modeled electronically using carbon nanotube circuit models and have performed detailed simulations of the circuit models. A single archetypical neuron, including excitatory and inhibitory synapses, has been modeled electronically and simulated. Parker and her co-researcher Chongwu Zhou are in the process of combining these circuit models of neurons to create a functional carbon nanotube circuit model of a small network of neurons. This small network of interconnected neurons will be simulated using the carbon nanotube models. This network demonstrates an interesting neural circuit that detects moving edges in a selected direction.
Source Here

The actual creation of entire synthetic brains may be quite a ways away, if at all. It may be fairly difficult to actually pull off this type of brain emulation. However, this preliminary research is a step in that direction.

Synthetic brains are a long way from reality, but researchers at the University of Southern California, funded by the National Science Foundation, are taking the first steps to build neurons from carbon nanotubes that emulate human brain function "At this point we still don't know if building a synthetic brain is feasible," said Alice Parker, professor of electrical engineering. "It may take decades to realize anything close to the human brain but emulating pieces of the brain, such as a synthetic vision system or synthetic cochlea that interface successfully with a real brain may be available quite soon, and synthetic parts of the brain's cortex within decades."

Artificial neurons constructed from carbon nanotubes could one day be implanted directly within a person's brain. This could be used to replace missing brain tissue. More sophisticated brain implants may be constructed with this material that would have improved functioning.

Parker believes carbon nanotubes are an ideal material to emulate brain function because their three-dimensional structure allows connectivity in all directions on all planes and because a carbon-based prosthesis is less likely to be rejected by the human body than one made from inorganic materials. But their invasive nature could result in them invading surrounding tissue and prompting lesions and cancers.

Obviously this recent research is similar to the project to construct a neuromorphic chip that the government is undertaking. Neuromorphic engineering seeks to mimic brain functioning on a silicon chip. Carbon nanotube artificial neurons could potentially be used in this manner to create artificially intelligent brains. A neuromorphic chip constructed from carbon nanotubes could be smaller and more efficient than other types of existing electronics. As to whether these artificial neurons could actually replicate the exact functioning of actual neurons is debatable. It will still be a while before we know for sure.

Here is a fairly recent article that discusses more about carbon nanotubes being used as neuron interfaces. This ability to make connections with real neurons could be utilized to seamlessly integrate the artificial neurons into existing brain matter.

The research shows that carbon nanotubes, which, like neurons, are highly electrically conductive, form extremely tight contacts with neuronal cell membranes. Unlike the metal electrodes that are currently used in research and clinical applications, the nanotubes can create shortcuts between the distal and proximal compartments of the neuron, resulting in enhanced neuronal excitability.

It should definitely be interesting to see what happens as the development of this technology matures.

Neuromorphic Brain Emulation

The US government's Defense Advanced Research Projects Agency (DARPA) has given a 4.9 million dollar grant to I.B.M. research and five universities for a new project. They basically want to reverse engineer the brain on a neuromorphic chip. I have mentioned about DARPA doing this in the past. However, then the deal was not yet finalized. You can read about the contract at DARPA's website. At the I.B.M. Almaden Research Center, Dharmendra Modha is now currently the manager of cognitive computing. You can read more information about this project at Modha's blog. Modha’s team has already been trying to reverse engineer the human brain. Modha estimates that by 2018 we will have the capability to simulate the entire human brain in real time on a computer. Modha’s group has already published a paper about simulating a rat brain in real time.

The human cortex has about 22 billion neurons which is roughly a factor of 400 larger than our rat-scale model which has 55 million neurons. We used a BlueGene/L with 92 TF and 8 TB to carry out rat-scale simulations in near real-time [one tenth speed]. So, by naïve extrapolation, one would require at least a machine with a computation capacity of 36.8 PF and a memory capacity of 3.2 PB. Furthermore, assuming that there are 8,000 synapses per neuron, that neurons fire at an average rate of 1 Hz, and that each spike message can be communicated in, say, 66 Bytes. One would need an aggregate communication bandwidth of ~ 2 PBps.

Modha also believes that nanotechnology will enable researchers to develop and replicate at the nano-scale the structure of a real human brain. Modha recently gave a talk at the 2008 singularity summit.

Here's an excerpt from the IBM press release about this new project.

IBM and its collaborators have been awarded $4.9 million in funding from the Defense Advanced Research Projects Agency (DARPA) for the first phase of DARPA’s Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE) initiative. IBM’s proposal, “Cognitive Computing via Synaptronics and Supercomputing (C2S2),” outlines groundbreaking research over the next nine months in areas including synaptronics, material science, neuromorphic circuitry, supercomputing simulations and virtual environments. Initial research will focus on demonstrating nanoscale, low power synapse-like devices and on uncovering the functional microcircuits of the brain. The long-term mission of C2S2 is to demonstrate low-power, compact cognitive computers that approach mammalian-scale intelligence.

Its still too early to say how much this research will actually accomplish. I suspect we may be able to simulate some of the processes of the brain relatively well. However, I think it may be fairly difficult to get that brain to be conscious. If we do successfully replicate consciousness it brings up all sorts of ethical issues, like how ethical is it to make a conscious human brain replica?

There are a variety of ways of going about creating a brain. This could include computer brain simulations (see here and here), neuromorphic chips or even possibly using stem cells to synthesize whole brain tissue. I think eventually we will be able to replicate a brain fairly well. If not on a computer or neuromorphic chip, then definitely using actual neurons possibly created from stem cells. Sufficiently advanced nanotechnology should allow the precise placement of neurons, dendrites and synapses. With sophisticated brain imaging techniques, this could allow scientists to create an exact replica of someone's brain.

Here's a video about the project.

Neuromorphic Electronics

I previously mentioned about the synapse program which is DARPA's attempt at creating a neuromorphic brain. A neuromorphic brain is basically a computer chip that is designed to replicate the functioning of a real brain. According to the wired defense blog they want to make it at a cats level of intelligence. The government wants to replicate a cat's cortex in a chip.

The follow-on phases of the project will create a technology that functions like the brain of a cat, which comprises 10^8 neurons and 10^12 synapses,"

Why a cat and not a rat? I have absolutely no clue, but I guess they have to start somewhere. I thought it might be easier to attempt to replicate an insect level of intelligence, but our government is somewhat more ambitious than that. There is no mention of creating a human level intelligence yet, but that would be the next logical progression. It probably won't end up getting that far, though.

You can read more about this new project at this website. (Never mind, The press release has actually been retracted, apparently the deal has not been finalized yet, so the company HRL may not be doing this). The press release is mysteriously dissapearing from every website, so I won't link to it. One could say, though, that the cat is out of the bag. Basically, there really isn't much new info that hasn't already been discussed. What will this actually accomplish? The chip could end up being a million dollar paper weight. Maybe I'm a little pessimistic, but it would be interesting if they got it to act in a similar manner to a real brain.

I'll admit, though, I really don't understand too much about this type of technology. Ray Kurzweil had an interesting comment in his book The Singularity is Near about creating an artificial brain that seemed appropriate (pg 177-178).

Modeling human-brain functionality on a nonlinearity-by-nonlinearity and synapse-by-synapse basis is generally not necessary.

He goes on to say;

Preserving the exact shape of every dendrite and the precise squiggle of every interneuronal connection is generally not necessary. We can understand the principles of operation of extensive regions of the brain by examining their dynamics at the appropriate level of detail.

Basically he is saying that we have (or will soon have) detailed enough maps of the brain to start to replicate it's functioning either in a computer or on a chip. We don't need to perfectly model every receptor protein or atom in a neuron (or even synapse?) to get a decent representation of the brain.

Kurzweil really is quite a creative genius and a very interesting futurist, but he does get a heck of a lot of stuff wrong in his predictions. So I'm not so sure that he is necessarily correct. He does give a pretty good argument, though, that this is possible. However there is a lot we don't know about the brain. For one thing, there is the 3-Dimensional arrangement of neurons in specific brain areas and how those regions interact with each other. The interaction of these regions according to the laws of physics is not fully understood even if you know the firing patterns of the underlying neurons and region activation. It is unclear if you can condense that function down to a presumably smaller (or perhaps larger) chip while retaining the essence of those complex interactions, without also replicating the underlying physics, chemistry or any other "level" inherent to this world. Maybe it is possible to drastically simplify things and still get a working model. However, I still have my doubts that this will be possible.