There are several technologies which seem likely to be transformative in the coming decades. Genetic bioengineering gives us the ability to control the basic machinery of life, including ourselves. Artificial intelligence is a suite of active, learning, information tools. Robotics continues its steady advance, and is increasingly reaching into the micro-scale. The world is becoming more and more digital, based upon information, and our ability to translate that information into physical reality is also increasing.

Finally, we are increasingly able to interface ourselves with this digital technology, through brain machine interfaces, and hybrid biological technology. This is the piece I want to discuss today, because of a recent paper detailing a hybrid biopolymer transistor. This is one of the goals of computer technology going forward – to make biological, or at least biocompatible, computers. The more biocompatible our digital technology, the better we will be able to interface that technology with biology, especially the human brain.

This begins with the transistor, the centerpiece of modern computing technology. A transistor is basically a switch that has two states, which can be used to store binary information (1s and 0s). If the switch in on, current flows through the semiconductor, and that indicates a 1, if it is off, current does not flow, indicating a zero. The switch is also controlled by a gate separated by an insulator. These switches can turn on and off 100 billion times a second. Circuits of these switches are designed to process information – to do the operations that form the basis of computing. (This is an oversimplification, but this is the basic idea.)\

This new hybrid transistor uses silk proteins as the insulator around the gates of the transistor. The innovation is the ability to control these proteins at the nano-scale necessary to make a modern transistor. Using silk proteins rather than an inorganic substance allows the transistor to react to its environment in a way that purely inorganic transistors cannot. For example, the ambient moisture will affect the insulating properties of these proteins, changing the operation of the gates.

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One extremely exciting technology that is in development is the brain-machine interface (BMI). This technology allows for communication between a biological brain and a computer chip. Once perfected, the implications are incredible. Perhaps most exciting is the possibility of  robotic prosthetics that can be controlled with the mind. There are many medical conditions that impair the ability to move, from spinal cord injury to strokes that can literally cause people to be “locked in”. In many conditions the brain is working, but the peripheral nervous system is damaged. With a sufficiently functioning BMI non-functioning limbs or blockages in communication can be bypassed. Amputees could also have fully robotic limbs to replace what’s missing.

From a theoretical perspective, all of the necessary proofs of concept have been done. The brain can learn to control machines, even computers. The brain can map itself to new limbs, and it can incorporate new sensory feedback. With sufficient sensory feedback, control is enhanced, and the sensation that the new artificial limb is part of one’s body can be complete. We can even be made to feel as if we occupy virtual avatars.

Computer hardware and software technology are already powerful enough meet the demands of any such BMI application. Robotics are also functional enough to work, although there is certainly a lot of room for improvement here. All these components are good enough to use right now, and continued incremental advances will just make them better.

The main limiting factor for BMI applications right now is the interface itself – how do we connect the brain to silicon? Scalp surface electrodes are the safest and most convenient. Electrical signals from the brain do make their way through the skull and scalp and can be recorded, but they are greatly attenuated. Only relatively large parts of the brain firing at the same time produce a sufficient signal to produce a detectable wave at the surface. Still, even with this method there are BMI applications, but the discrimination is limited.

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Brain-Machine interface (BMI) technology continues to incrementally but steadily progress, and I do think this is one of the technologies that will transform our future. Studies have already demonstrated that there are no biological or theoretical limitations to such technology – the brain happily communicates with computers and seamlessly incorporates signals to and from them through the existing process of brain plasticity. The real limitation with practical applications of BMI is technological, mostly in designing electrodes that can safely work for a long time.

As I have discussed before, there are numerous approaches. Scalp surface electrodes are safe and easy, but have no resolution because the skull attenuates signals to and from the brain. Brain surface electrodes work much better, but they are invasive and tend to form scar tissue which can limit their lifespan. Microwires are a cutting edge approach, very thin hair-like wires that penetrate the brain, and can have both high resolution and long term safety. There is also the clever approach of putting the electrodes inside blood vessels in the brain. One company, Synchron, has been developing this technology since 2010 and their device, the Stentrode (a portmanteau of stent and electrode), has now completed a preliminary human trial.

The idea is to insert electrodes the way a stent would be placed inside a blood vessel to treat a blockage. The advantage here is that the endovascular stent technology already exists. They just had to make the stent out of electrodes, which they did. The huge advantage here is that you can get electrodes inside the skull and next to the brain without opening the skull or doing brain surgery. The brain itself is never penetrated. The electrodes are not as intimate with brain tissue as brain surface or penetrating electrodes, but that’s the tradeoff. The question is – how much efficacy can we get from endovascular electrodes?

Much of the research previously has been done on animals, mostly sheep and pigs. Initially the electrodes were connected directly to an external control device that also provides power. But this requires wires to go through the blood vessel to the outside, which is an infection risk. The latest design, the one studied recently, communicates wirelessly to a control box worn by the subject. The only mention I could find of how the electrodes are powered suggests they are powered wirelessly through this control box. This setup could potentially send and receive signals from the Stentrode.

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A newly published study presents a proof-of-concept for using deep brain stimulation controlled with artificial intelligence (AI) in a closed-loop system to enhance cognitive control, suggesting it might be effective for a number of mental illnesses. That’s a lot to unpack, so let’s go back to the beginning. The most fundamental necessary to understand what is going on here is that your brain is a machine. It’s a really complicated machine, but it’s a machine none-the-less, and we can alter the function of that machine by altering its physical state.

This may seem obvious, but actually people are generally psychologically biased against this view. This may, in fact, be a consequence of brain function itself, which evolved to create a seamless stream of consciousness, an illusion of self unaware of all the subconscious processes that make up brain function. This is why we tend to interpret people’s behavior in terms of personality and conscious choice, when in fact much of our behavior is a consequence of subconscious processes. We are also biased to believe that people can think or will-power their way out of mental illness.

The more we understand about how the brain functions, however, the more it becomes apparent that the brain is just a glitchy machine, and lots can go wrong. Even when functioning within healthy parameters, there are many trade-offs in brain function, with strengths often coming at the price of weaknesses. We need to look out for our own interests, for example, but this comes at the price of anxiety and paranoia. But there are some brain functions that are so basic they are almost universally useful, and impairment of them can cause of host of problems. One such basic brain function is called cognitive control, which is essentially the ability to determine what thoughts and actions will be the focus of your brain’s attention.

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Researchers report a study in which they investigate the potential of a closed loop brain-machine interface (BMI) to treat pain in rats. If this line of research is successful it could lead to a new paradigm in the management of chronic pain.

Chronic pain is a tricky condition to treat because we currently have limited options, all of which are problematic in some way. Acute pain, such as after trauma or surgery, is easier to manage because the treatment course is likely to be limited. This kind of pain is called nociceptive pain, when it is the result of tissue damage. The obvious goal here is to manage the damage by treating the underlying condition, but manage the pain in the meantime until healing can reduce the pain. Another category of pain is terminal pain, such as in some cancer patients. While this has its own challenges, aggressive pain management is also appropriate.

Chronic pain, however, may need to be sustained for years, and this presents serious challenges. This may be due to chronic conditions that cannot be cured, such as arthritis, degenerative changes, and primary pain conditions like migraines. This category also include neuropathic pain, where the pain is due to abnormalities in the nervous system itself, rather than the nervous system properly detecting tissue damage. With neuropathic pain, the pain itself is often the disorder.

The challenges of chronic pain stem from the fact that it is often difficult to find a treatment that is effective. But also, even if a treatment is effective, pain medication itself (analgesics) has risks from long term use. Aspirin-like drugs (NSAIDS) can cause ulcers and kidney damage. Acetaminophen can cause liver damage. Narcotics are addictive and cause tolerance. The best approach to chronic neuropathic pain is what we call neuropathic pain prophylaxis – medications safe and intended to take daily to reduce overall pain. But these medications can have significant side effects, and don’t always work sufficiently. There are also nerve stimulators, which avoid pharmaceutical side effects, but have limited efficacy.

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I have been tracking the research in brain-machine interface (BMI), specifically with an eye towards studies that claim to interpret brain data. Typically I find that such studies are overhyped, at least in the press release and subsequent reporting. The question I always ask myself is – what exactly are they measuring and interpreting? A new study, using BMI and a form of AI called Generative adversarial neural networks (GANs), claims to read brain data to determine what faces subjects find attractive. What are the researchers doing, and what are they not doing?

The ultimate goal of BMI research (or at least one goal) is to figure out how to interpret brain activity so well that it is essentially mind-reading. For example, you might think of the word “cromulent” and a machine reading the resulting brain activity will be able to interpret it so well that it can generate the word “cromulent”. This would make possible a fully functional digitial-neural interface, like in The Matrix. To be clear – we are no where near this goal.

We have picked some of the low-hanging fruit, which are those areas of the brain that function through some form of somatotopic mapping. Vision is the most obvious example – if you are looking at the letter “F”, neurons in the visual cortex in the literal shape of an “F” will become active. Visual processing is much more complex than this, but at some level there is this bitmap level of representation. The motor and sensory parts of the brain also follow somatotopic mapping (the so-called homonculus for each). There is likely also a map for auditory processing, but more complex and we don’t fully understand it.

The big question is – what are the conceptual maps? Physical maps representing space, images, even sound frequencies, are easy to understand. What are the neural map for words, feelings, or abstract concepts? Related to this is the concept of embodied cognition – that our reasoning derives ultimately from our understanding of the physical world. We use physical metaphors to represent abstract concepts. For example, an argument can be “strong” or “weak”, your boss is hierarchically “above” you, you may have “gone too far” with a wild idea that is a “stretch”. This may just be how languages evolved, but the idea of embodied cognition is that the language represents something deeper about how our brains work. Perhaps even abstract concepts are physically mapped in the brain, anchoring even our abstract thoughts to a physical reality. Perhaps embodied cognition is not absolute, but more of a bridge between the physical and the abstract, or a scaffold on which fully abstract ideas can be cortically mapped. We are a long way from sorting all this out.

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Here is yet another incremental advance in brain-machine interface (BMI) technology – decoding what someone is saying from their brainwaves using a neural network and machine learning. We are still a distance away from using a system like this to allow someone who cannot speak to communicate, but the study nicely illustrates where the technology is. Here is the BBC’s reporting:

Scientists have taken a step forward in their ability to decode what a person is saying just by looking at their brainwaves when they speak.

They trained algorithms to transfer the brain patterns into sentences in real-time and with word error rates as low as 3%.

Previously, these so-called “brain-machine interfaces” have had limited success in decoding neural activity.

Now here are all the caveats from the paper. First, the technology used electrocorticography (ECoG), which is an EEG with brain surface electrodes. So this requires an invasive procedure, and persistent electrodes inside the skull and on top of brain tissue. Also, in order to get the best performance, they used a lot of electrodes – resulting in 256 channels (a channel is a comparison in the electrical activity between two electrodes). They simulated what would happen with fewer electrodes by eliminating many of the channels in the data, down to 64, and found that the error rates were about four times greater. The authors argue this is “still within the usable range” but they consider usable range up to a 20-25% error rate. What this shows is that – yes, more electrodes matter. You need the very fine discrimination of brain activity in order to get good (usable) results.

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Researchers at Yale report (at a meeting – not yet published) that they were able to keep pig brains alive for up to 36 hours after the pigs were decapitated. They acquired the pig head from a slaughterhouse, and experimented on them about 4 hours after death. This research is a long way from an alive “brain in a jar” but it does raise some early ethical questions.

First the technical stuff, with the caveat that the study is not yet published in the peer-reviewed literature so some details are sparse. We know the researchers experimented on pig heads. The report does not say explicitly whether the brains were completely removed from the skulls or not, but they did have access to the brain itself so it was at least exposed if not removed. They attached a series of pumps to the blood vessels and pumped oxygenated blood through them. They also used drugs to prevent the brains from swelling, and the researchers say these drugs would also prevent some brain cell activity (they are channel blockers).

They used brain-surface EEG to record electrical brain activity and – there was none. The pig brains were flat-line. But when they later dissected the brain tissue there was cellular activity for up to 36 hours.

This is clearly a baby step in the direction of maintaining a living brain outside of a body. Four hours after death is a long time, and there would certainly already be a lot of cellular death by that point. If the goal (and this wasn’t their goal) is to maintain a fully functional extracorporeal brain, then it would need to be hooked up to external blood flow within minutes of death, not hours. You can’t just get pig heads from the slaughterhouse.

But there is no theoretical reason why this would not work. If the brains were kept oxygenated throughout the process, and they were hooked up to an external system that fed oxygenated blood with managed CO2 levels and a supply of glucose (basically normal arterial blood), there is no reason why the cells could not survive for a long time. There are likely to be many technical hurdles here, but as a thought experiment it seems plausible.

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A new study looks at the brains of young adults who suffered a stroke in the language center of their brains as infants. They found that the subjects developed normal language, which just relocated to the mirror-image other side of the brain. This is not surprising, and reflects our evolving understanding of how the brain develops and functions.

For most people language localizes to the left frontal and temporal lobes of the brain. Broca’s area in the frontal lobe is involved in speaking, in the subtle motor output necessary to precisely articulate words. Wernicke’s area is in the temporal lobe and is involved in translating words into ideas and ideas into words. The two areas are connected by the arcuate fasciculous. These are the central language areas. There is also surrounding cortex which is necessary for communication between the language structures and other parts of the brain.

For most people the language area is on the left side of the brain. Meanwhile, the mirror right side of the brain is involved with understanding and producing speech intonation – knowing when someone is asking a question or being sarcastic. The right side is also involved with music and singing.

We also know that brains are plastic, meaning they can change the structure of their connections as necessary. People often use a computer analogy when talking about the brain, but the analogy to digital computers is flawed. Computers are hardware that run software, but brains are neither hardware or software – they are wetware, which is both at the same time. The connection of neurons in the brain is where information is stored and processed, and those connections change as a result of the processing, which alters the memory.

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The link to the article from the BBC Science News page reads, “Therapy “Wakes” Vegetative-State Patient.” The headline of the article was a bit more conservative, “Vegetative-state patient responds to therapy.” Annoying click-bait aside, what is actually going on here?

Like every such case so far, the improvement in neurological function in this patient with severe coma is extremely limited. This is mostly a proof of concept study, and the results are interesting, but the term “wakes,” even is quotations, is not even close to being justified.

Here is the case report: Restoring consciousness with vagus nerve stimulation. Even that title is a bit misleading – they aren’t saying they actually restored consciousness, just that vagus nerve stimulation might be a viable approach to develop. For background, a vegetative state is one in which basic neurological functions, like breathing, having a sleep-wake cycle, and some automatic movements, are retained. However, the conscious part of the cortex does not appear to be working. By definition there is no reaction to the environment.

By contrast a minimally conscious state has, as the name implies, minimal response to the environment. Patients in this state might blink to threat, or turn to a voice, but cannot communicate or participate in their daily activities. There is a continuum of neurological function from this minimal state to fully conscious.

As I have discussed before, researchers are trying to improve out ability to tell how impaired individual people are who clinically appear to be vegetative or minimally conscious. The challenge is that the neurological exam is limited. If the patient cannot follow commands, we have a limited ability to directly test which circuits in the brain are functioning. The patient may be more conscious than they appear to be because they are paralyzed or deaf, for example. Using functional MRI scanning and EEGs have enhanced our ability to assess brain function in these cases. Continue Reading »