As computer scientists like to say, "Garbage in, garbage out:” If the neural connectivity of Blue Brain is wrong, the simulation will be too. But let's not be overly critical. In the future, Markram could always incorporate information from connectomes into Blue Brain. Then wouldn't his simulation become truly realistic?
To answer this question, let's again consider the roundworm C. elegans. Its connectome is already known, unlike that of the neocortex. It may come as a surprise that only small parts of its nervous system have been simulated. These models have been helpful for understanding some simple behaviors, but they are piecemeal efforts. No one has come close to simulating the entire nervous system.
Unfortunately, we lack good models of C. elegans neurons. As I mentioned earlier, most of them don't even spike, so the weighted voting model isn't valid. To model the neurons, we'd have to measure from them, but this turns out to be more difficult for C. elegans than for mouse or even human neurons. We also lack information about C. elegans synapses. The connectome did not even specify whether the synapses were excitatory or inhibitory.
So Blue Brain lacks a connectome, while C. elegans lacks models of neuron types. Both elements are needed to simulate a brain or nervous system. Thus the earlier claim should be revised to say, "You are your connectome plus models of neuron types' (Let's assume that a connectome is defined to specify the type of each neuron.) But the models of neuron types are likely to contain much less information than the connectome, as most scientists agree that there are far fewer neuron types than neurons. In this sense, "You are your connectome" would remain a very good approximation. Furthermore, we assumed above that all neurons of one type behave in the same way in all normal brains, just as all polar bears hunt seals under normal circumstances. If we uploaded multiple people, all the simulations could share the same models of neuron types. The only information unique to a person would be his or her connectome.
It's worth noting that the balance of information content is quite different in C. elegans. Its three hundred neurons have been classified into about one hundred types, which is not that much smaller than the number of neurons. Essentially every neuron (along with its twin on the other side of the body) is its own type. Every neuron may end up requiring its own model, and the total information in these models might exceed that in the connectome. So "You are your connectome" would be a terrible approximation for a worm, even though it might be almost perfect for us.
To put it another way, the C. elegans nervous system is like a machine built from parts that are all unique. The individual workings of the parts are just as important as their organization. The opposite extreme would be a machine built from a single type of part. (You may be old enough to remember old-fashioned Lego sets, which contained only one type of Lego block.) The functionality of such a machine would depend almost entirely on the organization of its parts.
Electronic devices are close to this extreme, as they contain only a few types of parts, like resistors, capacitors, and transistors. That's why a radio's wiring diagram determines so much of its function. The parts list for the human brain is longer, so it will take many years of effort to model every neuron type in the human brain. But the parts list is still far shorter than the total number of parts. That's why the organization of the parts is so important, and why connectomes are more crucial for humans than for worms.
There's one more important aspect of connectomes to include in brain simulations: change. Without it, your uploaded self would not be able to store new memories or learn new skills. Markram and Modha have included reweighting using mathematical models of Hebbian synaptic plasticity. But it's also important to include reconnection, rewiring, and regeneration. In general, our models for the four R's are much less refined than those for electrical signals in neurons. It will be possible to improve them, but it will take many more years of research.
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10 Comments
Add CommentFirst of all, I would like to say that I learned a lot from the article about the current problems of neuronal simulation, thanks a lot!
Reply | Report Abuse | Link to thisHowever, I think it's neccessary to say, that claiming to "simulate a cat's/mouse's brain" is not a philosophical question of what a brain is, but simply not possible, as was pointed out 3 pages later in this same article. Therefore, I would support Markram in his opposition, although I would choose different words.
Apart from that, the article gives the impression, that the only purpose of the "Human Brain Project" is to provide a complete simulation of the human brain. Certainly, that was never the intention but rather to provide a reduced, yet realistic model or am I wrong?
Greetings!
I get the impression from the article that a lot of people believe that, “You are your brain”, and/or “You are your connectome”. Let me explain why I think this is an incorrect assumption.
Reply | Report Abuse | Link to thisIn information systems there is a concept called software, which means that the system has a memory that contains information (like a computer or a cortex). If you don’t know that your system is running a software system, it will seem to behave in utterly inexplicable ways to the hardware experts (biologists) who will attribute the complex behavior to some hardware element that they don’t quite understand (like the connectome). The connectome is a hardware detail, not software.
The brain and mind are separate entities. The human brain is just a computer made of biological hardware. The mind system is a software system being processed by the cortex. That software is stored as weights on the neurons, not somehow embedded in the brain, or in the connectome designs. So neither the brain nor the connectome is “you”. You are the sum of information stored in memory (the learned software system). The Home sapiens version of the software system that develops over someone’s lifespan is what psychologists study. When you are born you have a brain, but no mind, because only a trivial amount of learned information has been accumulated, and it takes years to make a person.
If what I’m saying is true, then uploading a mind is a much easier exercise, because you just need to read out the memory contents, and process the mind software on a more robust computing platform.
The Openworm project is working on the C. Elegans connectome. This document contains the excitatory and inhibitory neurons. The Google docs file is attached. Search for Openworm if the link does not work. https://docs.google.com/spreadsheet/ccc?key=0Avt3mQaA-HaMdHZuZnFuZmI5Q1VRU0VMekZ5d1QyZVE#gid=0
Reply | Report Abuse | Link to thisNot everyone's neurons are going to be identical, methinks. First consider people who have brain damage, and second consider that brains do not all develop identically. How much of development is neurons and how much is connectomes (or something else, if connectomes don't include the 'weights' jsweck was referring to), I do not know.
Reply | Report Abuse | Link to thisSuppose a simulated brain passes the Turing test, how then do we know we've managed to simulate a human brain? I admit, this may be more of a philosophical question than a computational one, but still...
Reply | Report Abuse | Link to thisBut philosophy aside, I've always thought that to be able to properly simulate something, you'd first have to know exactly just what you're trying to simulate. After all, how else are you going to know whether you've succeeded? And these scientists are telling us that they do know how the human brain is wired together and how it functions? They can come up with objective metrics that tell us about succes or failure? I am very impressed.
The problem with seeing it as a "Software" vs. "Hardware" is this: At some level, all software is stored by a physical change in hardware.
Reply | Report Abuse | Link to thisWhether that's transistors set to a particular position or the specific pattern of grooves in a DVD, "software" is not physically, intrinsically independent of hardware like you say it is. Software must change the hardware in order to store and process information.
In this case, the argument is being made that the connectome may be the intrinsic "hardware" marker of "software" on the brain. Like the grooves on a DVD, changing the connectome changes the information stored. By using your analogy, you are born with a brain but without a mind because the connectome is random, and the "software" is random nonsense. As it is refined and becomes non-random you "learn" and your neurons are programmed to interact in certain, specific ways.
You can see the connectome as "software" but at some level the software/hardware dichotomy becomes arbitrary as software is itself encoded on and processed by minute physical changes in hardware.
Yes, software must ultimately be stored in some physical way in a memory system, but the software system is almost completely independent in operation. It is not some high level hardware abstraction; it’s a separate and independent system in memory.
Reply | Report Abuse | Link to thisTo see this, think about battling monsters in a computer game. What exactly is the nature of the monsters? It’s not the billions of randomly flipping logic gates in the computer; it’s a piece of software in independent operation, and there’s nothing random about its operation. All you need to have software is a memory system – the stuff you store in that system is always software. The cortex is primarily a memory system, so it must have a huge software system. When we learn, we are adding to those software data structures.
The reason all computers exist is to solve problems. But you can only solve the simplest computational problems with logic gates or neurons – there is no way you can solve the big stuff, unless you create a memory system with those components. Then you simply move informational versions of the problem elements into memory, compute a bit, and the problem has the potential to be solved. So that having a memory system is the key to solve all big problems. In the computer world the only reason the hardware exists is to serve as the basis for the software system, and that software system is the one that solves all of the significant problems of the system. When the software is active the hardware people see random behavior, because they are not in control of the system.
I don't see how to avoid the idea that every neuron is actually unique, even if they also fall into subtypes. A single neuron fires when a person sees a picture of a particular person, and not when the person sees other people. Those neurons must be unique just by the memories stored in/by them.
Reply | Report Abuse | Link to thisSuppose you try to simulate a computer that has no information stored in it? What would such a computer do? Maybe you can have fun watching the various connections light up randomly, but you aren't actually simulating a computer. You aren't simulating any actual thought process or transmission of information.
It seems a bit like making a map of every road, highway, driveway and building in a country, and then simulating traffic patterns on them. Does that tell you anything about what is happening inside the houses, what the people think, or what the decisions of the government will be? Suppose you add all the phones, internet, cable networks, etc., and simulating electrical signals on them. Does that tell you what the people think or talk about? No, you have to model the components that remember and process memories and make decisions and then send that information out through the various forms of communication. Those components would be the people.
What I am saying is that until you know how neurons store, process and transmit information, and actually include the information itself in the simulation, you can't simulate a nervous system.
RE: Beware of pseudoscientific pretensions in Brain-reductionist cognitions! (Continued from above)
Reply | Report Abuse | Link to thisFrom a practical science and philosophy perspective today: Reductionism -- or specifically Physico-reductionism -- has its roots in our innate analytical thinking and inductive reasoning of physical facts and observations on Nature -- the Physical World -- since the primeval epistemological claims of the several pre and post-Socratic philosophers: Among whom, Thales (624-546 BCE) being the first who proclaimed that all entities come from water; and then, Anaximenes (circa 6th century BCE) who assumed that all things are composed of air; and centuries later, Epicurius (341-270 BCE) who intuited that all entities are made of atoms; and of course, of no lesser significant in his imagination, Aristarchus (circa 3rd century BCE) who was the first to pronounce that the sun is the center of the universe, and that the earth moves around the sun -- almost 2 millennia before Astronomy was first established as a Science (Physical Science) by Galileo Galilei (1564-1642) during the Renaissance in Europe and beyond!
Fast forward to the 21st century: The latest antithetical (or anti-theism) reductionist-cosmologist pretension, is one that has been recently expressed by Stephen Hawking: in which he boldly declares that our Cosmos (or Universe) is created by Time and that Time is created by the Big Bang; and therefore, no theological imaginations or inspirations shall be necessary in his field of Physico-reductionist cosmology* and in which, Hawking has in fact (unknowingly and utterly) negated his own fundamental epistemological inquiry and reductionist speculation: What has had caused the Big Bang -- if there was indeed a Big Bang (nor God) at all!? Thus, Hawking should have had not irrelevantly or immaterially raised nor hackled Theology in his field of universally Physico-epistemological inquiry at all! -- [*See my comment on Physico-reductionism in cosmology today here: http://www.scientificamerican.com/article.cfm?id=the-consolation-of-philos&posted=1&posted=1&posted=1#comment-110 -- "The Consolation of Philosophy -- RE: Physico-reductionism at its Best: When in a miraculous shebang Nothing became Everything in our Dynamic Universe! -- Or, could physico-reductionists (including evolutionary sophists and neo-Darwinists alike) be able to self-examine and heal themselves of their socio-reductionist-bias (or hubris) syndrome!?" (ScientificAmericanUSA; May 5)] (To be continued below)
I think these people simply don't get it how tremendously complex nature is. The naive belief that funding a super supercomputer feeding it with several complicate rules won't work. It will not meet the expectations, as it was the case with the human genome project. It would be much better to use that money for several smaller researches than throwing it into another disappointing mammouth project.
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