Category: Stream of consciousness


Last year it was announced that quantum vibrations had been found in microtubules. Microtubules are a hollow structure in the cytoplasm of neurons, the cell substance between the cell membrane and the nucleus. This is extraordinary as such quantum effects are thought to require very cold temperatures and biological systems have been considered to be far to warm for such thing to occur. Further to this, the finding gives some support to a controversial quantum theory of consciousness by Sir Roger Penrose and Stuart Hameroff that is some 20 years old. You can read about it here.

So what does this all imply? I decided to read over Penrose’s books ’The Emperors New Mind’ and ’Shadows of the Mind’ to find out.

Neurons are the basic functional units in the brain. The conventional view is that they transmit information using electrical signals called action potentials. A neuron has a membrane that serves as a barrier to separate the inside and outside of the cell. The membrane voltage of a neuron is dictated by the difference in electrical potential inside and outside of the cell. Neurons are electrically charged by membrane ion channels that pump ions, which have different electrical charges, across their membranes. Neurons are constantly exchanging ions with the extracellular surroundings in this way. In doing so they can not only maintain resting potential, but also propagate action potentials by depolarising the membrane beyond a critical threshold. Action potentials are transmitted between neurons allowing them to communicate.

This functionality can be encoded in an algorithm, which means that the conventional biological model of the brain can be simulated on a computer. In his books Roger Penrose critiques Artificial Intelligence research by claiming that human understanding is essentially non-algorithmic and therefore non-computational. The argument is derived from the Church-Turing Thesis and Godel’s Incompleteness Theorem, which are considered (by Penrose and others but not all) equivalent to each other.

Penrose’s argument goes something like this: There is an algorithm for deciding if a mathematical proposition is true. This algorithm must be consistent otherwise the decision about the proposition cannot be known correctly. However, according to Church-Turing and Godel the algorithm, if it is consistent, cannot by definition be applied to itself to discover if it is consistent/true. The implication for AI is that either we can not know if something is really true or the method used to ascertain truth cannot be known or validated as correct. Penrose believes that out ability to know mathematical and indeed all truths is unassailable, because such truths particularly mathematical ones are ideal. In turn he suggests that we know our understanding is correct and therefore we know something that cannot be known algorithmically.

This leaves us in a number of positions. Either (A) our understanding is algorithmic but we can never understand how it works, (B) our method of understanding is algorithmic but not consistent, or (C) our understanding is non-algorithmic and therefore requires more than our current conventional biological understanding of the brain. Regarding (A) I believe it is possible to develop complex computational systems for which, due to their innate complexity, the detail of their workings cannot be fully known. However, we are still able to use them to solve problems. Liquid-State Machines are a good example of such methodology currently being employed. Hence, I don’t think it is necessary to fully understand our method of deriving understanding in order to create AI. Regarding (B) I think Penrose’s attachment to the ideality of mathematical truths, i.e. their timeless and absolute truth, makes him feel that the ability to grasp this is somehow special and unassailable. I would regard this as a fallacy. A large part of what brains do is statistical pattern recognition. Our ability to understand fuzzy concepts such as a ‘chair’ may be a similar mechanism to that which is used to understand non-fuzzy things like mathematical truths. The reason the latter is so much more precise is not due to the cognitive systems applied to them but due to the thing itself being so much more precise. Hence, I doubt that our understanding is consistent in a Church-Turing/Godel sense. It is just that we do a damn good job when the subject matter is amenable.

Whilst I think what I have argued for (A) and (B) may discount Penrose’s cognitive requirement for (C), I don’t think that it should all be discarded just yet. Penrose argues that quantum mechanisms are non-algorithmic and super-computational and therefore may if tapped into provide a mechanism for understanding. Although I don’t feel this is necessary, I would agree with Penrose’s critique of strong AI that suggests that consciousness emerges from algorithmic complexity alone. Algorithms can be implemented in many mediums, even using cogs and pulleys. It does seem ridiculous that a system of cogs and pulleys if complex enough would become conscious. Therefore, one may conclude that algorithmic complexity alone is not enough. I would suggest that such complexity if instantiated in a particular medium (e.g. biological brains) give rise to consciousness. However, our current understanding of biology and classical physics does not encompass anything that can explain the phenomena of consciousness. Perhaps an interaction between complex biological systems and quantum mechanics, with all its strange phenomena such as entanglement, may open the door to our understanding of consciousness.

The visionary inventor, technologist, and futurist Ray Kurzweil now works at Google. He is heading a research team trying to crack artificial general intelligence seemingly by building a model of the neocortex. Google offers him resources to do this which are unmatched. Kurzweil recently gave a talk at Google I/O about his thoughts on the matter which you can watch here.

Rays talk doen’t give away much about the tech he is developing so I thought I’d buy his most recent book How To Create A Mind and see how he intends to achieve his goal. Ray did early and ground breaking work in text and speech recognition and the technologies he developed are used these days in things such as Apples SIRI. Rays states in his book that the neocortex is a vast hierarchical pattern recognition system and I don’t think anyone would contradict this. Further to this he sites communication with Henry Markham whos work has shown that there are repeated patterns of connectivity in the brain with assemblies of 12 or so neurons connected in a Lego like way. These assemblies are presumed to be individual pattern recognisers, and a hierarchical system of these would support hierarchies of feature detectors leading all the way to abstract concepts. However, I find the implicit belief that all the brain does is pattern recognition rather naive. Questions such as: how does pattern recognition relate to thought processes, behaviour or creativity? are not even approached.

Whist his book continues to discuss philosophical matters such as ‘what is the similarity between a computer and a brain?’ ,’do we have free will?’, and ‘what is the notion of identity?’, not only does he only cover old ground here but he also does not in any way relate them to his design thesis. His main and concluding thoughts seem to be with regard to the Law of Accelerating Returns, which states that once something becomes an information technology then it is subject to exponential price/performance enhancement. The problem Ray is faced with is that the mechanics of thought are presently unknown and therefore not as yet an information technology and so are not subject to this law. Unfortunately, Ray has not really suggested much on how we might tackle understanding and emulating the mechanics of thought, or perhaps he does know but Google want him to keep it under wraps.

I have been in Dallas Texas all week at the International Joint Conference on Neural Networks. A major player in President Obama’s Brain Initiative Project gave at talk followed by a Q & A session. So what is this Brain Initiative all about?

Back in April President Obama announced a 100 million dollar funded project in studying the brain, with an extra 90 million a year from private investors. It all started when sometime before a group of nano technologists met up with a group of neuroscientists. After a few days presenting their work to each other, the a nano technologist asked what the neuroscientist would most like to be able to do. The reply was: we would like to be able to record from every neuron in the brain at once. The response from the nano guys was:we can help you with that.

 

Recording from neurons is presently an invasive process of sticking probes into the brain. Back in the day we could only record from one neuron at a time. Now we can record 100-200 simultaneously. There are about 80 billion neurons in the brain. Now there are about 100 thousand neurons in a cortical column. If we want to record from 10 columns thats a million neurons. Now we presently can’t record all the neurons in a column at once because we cant fit that many probes in, there just isn’t enough space. If you use Moores Law to see how the technological growth in our ability record from numerous neurons has advanced and predict into the future, then we will be able to record a million neurons by the year 2100. This is far too long to wait.

The Brain Initiative attempts to develop technologies that will enable us to record from a million neurons within 10-15 years. Not only does it hope to record non intrusively but also aims at being able to stimulate these neurons, and as well as that come up with analysis techniques to understand the complex data.

 

This work will not just advance technology that can also be applied in other areas, but it will help us understand the brain so as to develop AI and cure mental diseases.

 

Present Obama was given a selection of projects to choose to fund and made the choice himself to invest in brain research. A very smart man.

The FET Flagship Programme is a new initiative launched by the European Commission and has awarded one billion euros, over ten years to the Human Brain Project. The leader of the project, Henry Markram, a professor of neuroscience at the Ecole Polytechnique Federale of Lausanne in Switzerland, said earlier this month that it could not be undertaken without this kind of funding.

The project will simulate ‘everything we know about the human brain’ in supercomputers. The human brain has approximately 80 billion neurons each with 10000 synaptic inputs. As I am know doubt you are aware, it is not the number of neurons that will make it work, the key to the brains cognitive power is how they are wired together, and we only know so much about that.

The project website states:

“The brain, with its billions of interconnected neurons, is without any doubt the most complex organ in the body and it will be a long time before we understand all its mysteries. The Human Brain Project proposes a completely new approach. The project is integrating everything we know about the brain into computer models and using these models to simulate the actual working of the brain. Ultimately, it will attempt to simulate the complete human brain. The models built by the project will cover all the different levels of brain organisation – from individual neurons through to the complete cortex. The goal is to bring about a revolution in neuroscience and medicine and to derive new information technologies directly from the architecture of the brain.”

You can read more about the project here.

Hi All,

I havent posted on this blog for almost 2 years. I have been snowed under with the PhD and to be frank couldn’t think about anything else. I am going to try to start posting again. As a sign of good will I have set up a nice new look. Hope you like it 🙂

woo hoo my spiking network simulations are working 🙂

My PhD has finally got under way. Imperial College is not intimidating at all which is a relief. I have been given a desk in a room with other PhD students and have a shiny new and fast PC. The nice man from the computer support groups has set me up with Linux and Windows. I think I shall be using Linux as a preference. I have just spent 11 years as a Windows programmer and am glad not to have to be forced to use a particular OS and that particular OS.

I have signed up for a few personal development courses. The first one is on giving presentations which is something that scares me a lot. Not the course but presenting, doh!  I am prone to collapse into a quivering lump of jelly when put in front of an audience. I have to take seminar groups as part of my PhD so it looks like ill be forced to get over my hang ups. I also found it amusing that there is a networking course, not as in computer networks silly! but networking as in making contacts with people. I am quite socially retarded so this came as a nice surprise and I signed up for it too. All they really need to complete me as a fully rounded person is a course in how to talk to women 🙂

Sorry but the site has been down for a while due to problems with our hosting service. I hope no one was put out too much. What am I talking about?…..no one reads this 🙁

My bag is packed and I have my German phrase book at the ready. Tomorrow morning I am off to Berlin for the 2010 Brain Connectivity Workshop which promises to be facinating. I am most keen to hear Olaf Sporns speak who has done a lot of interesting work on structural motifs and dynamics, and Karl Friston whos free energy theory of the brain is one of the most intriguing things ive read in years. Ill try and post the hightlights through the week.

Bon voyage

Hello,

this blog will go fully live in the autumn of 2010 at which time I shall be commencing my PhD in computational neuroscience. I hope to record the highs and lows of the experience as well as report on any interesting research and news I have encountered in the field. I am very aware that writing a blog and stating opinion will document a learning process and as such my ideas and thoughts will in many cases be in error and in almost all cases change over time. I hope my curious ramblings make for interesting reading. Perhaps if anyone actually reads this they will be kind enough to comment, correct or point out alternative points of view as this will enrich the experience of my journey and help me reach my ultimate goal of trying to understand the spiking neural net inside our heads.

David