[ExI] world’s first brain prosthesis

[Max More]

Rich Strongitharm wrote:
>The world’s first brain prosthesis – an 
>artificial hippocampus – is about to be tested 
>in California. Unlike devices like cochlear 
>implants, which merely stimulate brain activity, 
>this silicon chip implant will perform the same 
>processes as the damaged part of the brain it is replacing.
><http://xenophilius.wordpress.com/2008/07/12/worlds-first-brain-prosthesis-revealed/>http://xenophilius.wordpress.com/2008/07/12/worlds-first-brain-prosthesis-revealed/

It's nice to see this. Ted Berger was one of 
several researchers at the USC Hedco 
Neurosciences department that I interviewed back 
in 1995 for a feature in Extropy #15. The text of 
those issues is not online (yet), but I dug it 
out of my own archive. Here it is:

Ted Berger
Professor of Biomedical Engineering and 
Neurobiology. Hedco Neurosciences and Engineering.
berger at bmsrs.usc.edu

What area of neuroscience do you work in?
I work on the neurobiological basis of memory and 
learning: How the brain stores information, how 
we acquire new associations. Traditionally this 
problem has been approached by recording from 
single cells in the brain and seeing how their 
activity changes during the course of learning. 
One particular part of the brain is essential for 
forming memories­the hippocampus. In many well 
documented cases where patients have suffered 
damage to the hippocampus, we find they still 
retain old memories but lose the ability to lay 
down new memories. This doesn’t affect learning 
of abilities, only learning of fact-based 
information and associations. People have tried 
to find out what kinds of neural representations 
exist, what does that activity correlate with, 
and then how does that change. The problem is 
there are five to ten million neurons in the 
hippocampus. So how do you learn how a system 
like that works by looking at the individual 
elements? There are too many cells. It would be 
like going into a computer and looking at the 
voltage at a point on the chip and then trying to 
figure out how the computer does its job. We just can’t do that.

I did that kind of work for 5 or 6 years and 
pushed it as far as possible. It isn’t enough to 
understand the processes at the system level and 
how cell activity relates to the memory process 
itself. What’s needed is two things: You really 
need a mathematical model of individual elements 
and the whole system, so you can take the data 
about individual neurons and try to relate that 
to some structure. Secondly, you’ve got to have 
the kind of technology that will allow you to 
record from many neurons at the same time, and to 
be able to mimic the computational 
characteristics of the brain system when it’s 
fully operational. You can describe it as what 
seems to be a series of parallel circuits. The 
hippocampus seems to function as a parallel 
processor. Parallel processors are not the kind 
of computers that we have on the desktop, so the 
computational basis for this is not easily available.

So I moved slowly from the area of neurobiology 
into the areas of engineering and mathematics and 
begin to collaborate with engineers who had 
developed modeling methods that were particularly 
good for capturing the dynamic properties of 
single cells and the collective dynamics of 
neural networks. I’ve also begun to collaborate 
with other engineers who are capable of designing 
computer chips that are used as a series of 
detectors, and we use those as electrodes to 
implant them into the brain to record many 
different neurons simultaneously so we can get 
the same population activity, the same population 
dynamics that these brain cells exhibit.

These are analog devices in the sense that you 
use conductive points on the chip as a basis for 
recording analog signals from the brain and then 
take those off the chip and analyze them in a 
computer. Assuming we continue to be successful 
in being able to record the activity of many 
cells simultaneously, then there’s the issue of 
how do you take that information then mimic the 
computational characteristics of some part of the 
brain? So we’ve been working with some other 
colleagues to develop analog VLSI chips that have 
the characteristics of the brain cells that we’ve 
studied. We study a single cell and model the 
properties of that cell, then construct a circuit 
on the analog VLSI chip that will mimic the 
properties of that cell. And we’ve constructed 
the circuits for many cells and put them all onto 
one analog VLSI chip. Now we have a chip which 
essentially has the same characteristics the 
small population of neurons that we’ve looked at.

These chips have the exact characteristics of the 
cells they are learning. Such a chip will allow 
you to predict the activity of the neurons. 
Having developed an analog VLSI chip that 
essentially has on it a small population of 
neurons, that’s essentially equivalent to 
creating a hardware model of a slice through a 
3-dimensional structure. They have so far created 
a population of nine neurons and have designed 
one for 100. We’ve essentially modeled a 2-D 
plane of a 3-D structure. If you want to mimic 
how the whole system works you need to do this in 
three dimensions. So we’re also working with a 
colleague in photonics where they use light 
signals to connect analog VLSI devices. They’ve 
developed a brand new technology that will allow 
you to stack analog VLSI chips together and 
sandwiched in between them is the photonic 
technology for connecting those VLSI chips. We’re 
going to apply this technology to try to create a 
3 dimensional structure which has the same 
properties of at least part of the brain system.

There will be 100 neurons in each of the planes. 
As many of those as we can stack together. Then 
we can have the 3-dimensional characteristics of 
part of the brain system. That allows you to 
study the parallel processing capabilities of a 
brain in a way which you can’t on the kinds of 
computers that you use right now. We know the 
properties of those cells have the same 
properties as parts of the brain. We can begin to 
ask what are the dynamics of this brain system, 
and how is it that a network of this kind can be 
trained to learn something new.

What are your objectives with this research?
There are several objectives to this project. One 
is to understand how brain systems work. What are 
the computational characteristics and 
computational limits of different brain systems? 
We really need to have the three dimensional 
structure of that brain system in a model to be 
able to answer those kinds of questions. There is 
a second objective: We want to create a hardware 
device which will function like the parts of the 
brain. There are three major advantages to a 
hardware device. One is you can incorporate true 
parallel processing. The second is speed: you can 
do very rapid processing. The third is size. So 
the second objective relates to those three advantages.

If we can mimic the computational characteristics 
of the brain at a reduced scale using a hardware 
device then there’s no reason why we can’t begin 
to contemplate replacing parts of the brain that 
are damaged, with computer chips that have the 
same properties and can be connected to the rest 
of the brain through the specially designed 
interface electrodes. We can sense the activity 
within the brain and we can send out signals into 
the brain. These kinds of sensing probes or 
signaling probes could be sandwiched on the end 
of a 3-dimensional structure that could perform 
the same function as the part of the brain that 
we want to replace. The replacement parts would 
be of a similar volume of the parts of the brain they are replacing.

The third major objective is to understand enough 
about how the brain works to be able to build 
devices to solve problems in the real world that 
take advantage of the things the brain does 
really well. One of the things the brain does 
really well is to associate arbitrary kinds of 
objects. There are some real world problems the 
brain is very good at and does better than any 
other kind of device. If we can understand what 
those principles are, then we can build devices 
that will solve problems in the real world. We’ve 
designed a device that could function as a 
wireless duplication receiver based on some of 
the first principles that we’ve understood about 
the hippocampus. That may have an application in cellular phone technology.

How far off do you think any kind of neuroprosthesis will be?
It actually depends on the parts of the brain 
we’re talking about. There may be lower level 
functions­spinal cord functions, motor systems 
that control the limbs­that may be possible 
within ten years. For replacing the kind of 
higher cognitive functions that involve learning 
and memory, that would be more like ten to twenty 
year range. Replacing a damaged point in the 
spinal cord may be possible in ten years. The 
tissue above and below the point of damage is 
functioning normally. If you can sense the 
activity of all the cables that are on the brain 
side, and you can drive the activity of all the 
cables that are on the lower spinal cord side, 
and you have a set of chips which performs the 
correct connection and the correct 
transformational activity from the brain to the spinal cord, then why not?

How do inorganic chips connect to biological neurons?
There has been a lot of research identifying the 
kinds of conditions that will allow neurons to 
attach to the electronic current sensing part of 
the chip. Under the right conditions cells will 
attach to the metal surface and stay attached. 
Whenever the cell exhibits electrical activity 
then the underlying circuit will detect that 
activity and transmit it elsewhere. Or, in just 
the reverse way, you could actually supply 
current to the chip and that can drive the 
activity within the cell. So there’s a way of interfacing neurons and chips.

The additional problem is how to get the neurons 
that are interfaced with the chips to connect 
with the rest of the brain directly. That’s a 
problem where there are a lot of unknowns. But we 
do know two essential principles: One is, nerve 
cells connect themselves up together. There are 
growth factors and a lot of other things that 
guide the connections from one neuron to another. 
They may not find the right pairs, but they do 
find each other. Secondly, it turns out that 
during development these connections are formed 
between cells that are active simultaneously. It 
involves part of the same process that’s used in 
the brain of the adult animal to store 
information. The strengths of connection between 
neurons in the hippocampus and in other parts of 
the brain changes as a function of activity. If 
two cells are active at the same time then the 
synaptic connection between them is strengthened. 
There are other conditions under which those 
connections can weaken. We now understand a great 
deal about the principles for how connections 
between neurons are strengthened, and it’s 
primarily on the basis of activity. So if a cell 
has been grown to the surface of a chip and we 
put this chip into the brain, and we want to 
connect up correctly the cells that are on the 
interface one of the ways to do that is to drive 
the activity of the cells. We can control that 
and as a result control in part how these cells 
wire themselves up to the rest of the brain. 
Although that will be a very difficult problem we 
can see the beginnings of how to approach the problem.

How does this approach differ from things like 
NetTalk (a neural network for recognizing speech)?
Our objective is to create a hardware model of 
the function of the hippocampus. It’s situated in 
a part of the brain where after the rest of the 
sensory systems break down the incoming signal, 
determine what the features are and integrate all 
those features that identify a face­it’s that 
information that goes into the hippocampus. All 
the feature analysis has been completed. That 
information is processed in some way, along with, 
for example, the auditory sounds that the 
creature made, so that the features (which have 
already been identified as a face) and the 
auditory signals which identify how your name 
sounds, those two things get fed into the 
hippocampus and they’re associated in some way 
and then sent back to the cortical regions that 
do the sensory analysis, and they’re stored 
there. This signal transformation process and the 
association process is done in some way that 
allows this human to learn this new information 
and to insert it into long term memory without 
disrupting all the other long term memories. The 
associations formed by the hippocampus allow each 
of our databases to be updated without destroying 
the existing databases and make retrieval of that 
data optimal. It’s that function that we’re 
trying to emulate. Not just learning new 
information or identifying speech patterns, but 
how to take that new item that’s learned and 
insert it into a database so that it has the 
correct associations with all the other things the person has learned.

This is a unique effort. People with very 
different backgrounds have agreed to work 
together. I’m one of five people. Without the 
different backgrounds the problems couldn’t be 
solved. The Hedco Neurosciences program is 
unique. The purpose is to get neurobiologists, 
biologists, computer scientists, engineers, 
psychologists, all in the same building. All the 
members of the team are willing to be members of 
a team. It turns out that there are an awful lot 
of problems that we have with the neurobiology 
that there are already solutions for in the field 
of engineering. We  just don’t know about them. 
So breaking down the disciplinary areas is extremely important.

How long will it be until we have a real 
artificial brain of human level intelligence?
What’s most important in answering that question 
is that in the last couple of years we have 
reached a point both in understanding the 
neurobiology of the brain and understanding the 
fundamental principles of engineering and 
computer science where we can entertain that 
question, where’s it’s actually reasonable to ask 
how long do you think it will be. Just five or 
ten years ago, that would be seen as a science 
fiction question. But now it is feasible to start 
thinking about things like that, just as its 
feasible to start taking about replacing parts of 
the brain. I don’t have the faintest idea. I 
could say 50 years from now. I don’t think it’s 
unreasonable to think in those terms.

Much of the population is uneasy with the idea of 
replacing parts of the brain. They believe that 
there’s something up here that’s outside physics 
and chemistry. If we replace parts of the brain 
with things we’ve built, then aren’t we just a 
machine of some kind? How do feel about that and 
how do you think people ought to feel about it? 
Should we be losing a sense of being special, or 
should we just realize that we’re the most magnificent machines around?
To understand how the brain works and to approach 
the problem of understanding cognitive behavior 
scientifically it’s imperative to treat the brain 
as a kind of machine, that this system can be 
reduced to a set of parts and they have relations 
to one another. When those relations are allowed 
to exist there’s a dynamic that unfolds that 
explains the global behavior of the system. When 
you’re trying to explain the complex thought 
processes that we engage in, when you have many 
elements and the dynamics of those elements are 
complex, it becomes a much harder problem. But 
nonetheless, the essential tenet of the 
scientific approach is that everything can be 
treated as a machine and broken down into its component parts.

People will become more comfortable with 
that­with the consequences of that approach, such 
as with the consequence of putting computers into 
the brain. Once they experience the benefits
 
Everyone has a problem with their mother having 
Alzheimer’s disease or their child having 
epilepsy. Any solution is a good solution to such 
problems. We not talking about changing the 
entire function of the individual but simply 
replacing the part that used to be there, 
replacing the function that used to be there. 
Then I think a lot of that resistance will melt away.

What if we do start talking about altering and 
enhancing our capabilities? Without having to sit 
down out a computer, what if I can work out 
complex equations and trajectories, what if I can 
do all those things in my head? What if I can 
work out complex strategies and patterns that 
would normally have to do on a very powerful 
computer ­ do you think people will be more upset about those?
Yes, I think there are going to be great social 
debates over whether we should enhance the 
capabilities of the brain, and do anything other 
than replace non-functioning parts of the brain. 
As soon as the work began to move towards 
enhancing function of the brain I think that 
would cause a great deal of social debate. 
Personally I think it would be extremely 
interesting to find out how much we could enhance 
human brain function. I think it should be tried. 
Now we’re talking way downstream, but if we can 
replace brain function, well why not try to find 
out how well we can enhance brain function. I 
think it would be incredibly interesting to try. 
I would love to be able to remember things that I 
forget. How many times has it been that you 
wished you were in a certain cognitive or 
emotional state, and you can’t be in that state. 
It would be an incredible advantage to be able to have that choice.

What do you think of the idea of uploading the 
contents of a brain into a computer?
I think it’s far more likely that these 
technological developments will allow the 
uploading into the brain of information from the 
computer. If we can understand how it is that 
certain signals input into a system, how that 
neural representation is transformed and how it’s 
associated with other representations, then it 
seems to me that we should be able to upload into 
a human the correct series of input signals at 
the right places at the right times; we’ll be 
able to build into the memory banks new 
associations that we haven’t in fact experienced. 
That’s because we’ve identified a very discrete 
part of the brain that’s important for laying 
down new memories. But we don’t know where the 
memories are stored. We think we know. We think 
they’re stored in the neocortex­phylogenetically 
the newest part of the brain. But exactly where 
and how it’s stored no one really has much idea.

Do you personally look forward to having some 
neurons replaced, some functions augmented?
I would love to. That would be extremely 
interesting to me. It’s a challenge in sense of 
being an entirely different dimension of testing 
how well you’ve understood the system. Replacing 
functions is one thing, but when you’re trying to 
enhance brain function, that’s potentially 
different problem. We might not know how to 
change properties of the brain so you enhance the 
functions you wanted without disrupting other 
functions. That’s a very hard problem and a very interesting one.

So it takes another 100 years or 150 years, would 
you want to stick around for that?
Oh, you better believe it! Without a doubt. I’d love to.


-------------------------------------
Max More, Ph.D.
Strategic Philosopher
Extropy Institute Founder
www.maxmore.com
max at maxmore.com
-------------------------------------