How to build a simple model of something as complex as the brain

In trying to model the human brain's basic mechanisms, and how it's evolution can be explained it is important not to be overwhelmed by some of the numbers involved. One approach, which is adopted in other models of other large problems, is to stop worrying about how big the numbers are and simply to assume the number approaches infinity. You can then assume that building a complete model that tries to reproduce everything that might be happening is impossible, and concentrate on looking for simplifying generalizations.

A Simple Guide to the Relationship between Neurons, Natural Language and CODIL

I have posted the detailed discussion paper Fromthe Neuron to Human Intelligence: Part 1: The “Ideal Brain” Model and my idea is to supplement it with brief notes examining various topics, including any raised by comments. This is the first of those notes

A noun such as Macbeth, or Dagger, or Author is represented in the brain as a somewhat amorphous network of neurons which I have called a memode.

Memodes contain other lower level memodes. Thus Murderer will contain Macbeth and Crippen, while Author will contain Shelly and Shakespeare. People will contain sets such as Murderer and Author and individuals such as Churchill.

A memode may also represent a context where several nouns are associated. An example of a context would be Macbeth; Duncan; Dagger. Another might be Macbeth; Shakespeare.

The ideal brain model connect up the links – so the above two examples can be merged as Macbeth; Duncan; Dagger; Shakespeare.

As Macbeth is a Murderer we can expand the above to the context Murderer  Macbeth; Victim  Duncan; Weapon  Dagger; Author  Shakespeare. While we are only using nouns it is easy to relate this to a natural language statement such as “According to Shakespeare Macbeth used a Dagger to kill Duncan.”

CODIL was a blue sky project to try and provide a fundamentally human friendly information processor for handling a range of non-mathematical tasks. In MicroCODIL (a demonstration version that runs on the BBC Microcomputer and uses colour) the above example would be represented as

1 MURDER = Macbeth,

2   VICTIM = Duncan,

3     WEAPON = Dagger,

4       AUTHOR = Shakespeare.

While the ideal brain model works by making links within a network of neurons, and CODIL works by moving symbols around a digital store, the two processes are equivalent.

The CODIL idea was triggered by research on a very large commercial data processing system, and has been trialed in medium sized poorly structured data bases (medical and historical data), providing online tutorial material for classes in excess of 100, as a schools package for demonstrating a wide range of information processing ideas, and in the area of artificial intelligence. A package called TANTALIZE used CODIL to solve 15 consecutive Tantalizers (now called Enigma) published weekly in the New Scientist.

The parallel between the ideal brain model and CODIL suggests that the ideal brain model could probably support a reasonable level of natural language skills – but more research is required. The bottleneck as far as the basic ideal brain model is concerned relates to the speed of learning – and this issue will be addressed in Part2: Evolution and Language.

From the Neuron to Human Intelligence: Developing an “Ideal Brain” Model

I have just posted a discussion paper: From the Neuron to Human Intelligence: Part 1:The “Ideal Brain” Model which will shortly be followed by Part 2: Evolution and Learning. In these papers I propose a model which suggests how the electrical activities of neurons in the brain may be related, via evolutionary probable pathways to high level activities such as language and intelligence. If the model is even reasonably accurate it could have implications in many different specialist areas where an understanding of how the brain works is relevant.

It is clear that more research is needed to establish the validity of the model and my problem is how to go about both publishing and organising any further research, especially as some of the ideas are counter-intuitive – which can make communicating them difficult. If I was a young academic just starting out on a research career and working in a supportive university there would be some relatively obvious options. However I am 75 years old, my only resource is a personal computer with access to the internet, and I currently have no active contacts with any major academic institution. As a scientist through and through I feel the idea should be followed up, and as an old age pensioner I would be happy to hand the matter over to a younger generation and enjoy retirement.

Bearing in mind my limitations the approach I have taken is to use this blog as the means of stimulating discussion of the issues and disseminating information about the research.

1. The two papers have been kept comparatively short to make them more readable. If I tried to address every possible research issue that might be relevant it would take me far too long and the texts would become unreadable.
2. Anyone who want to see more examples of how CODIL works, its applications, etc. can look at the many CODIL papers already online. In addition I have other reports (some only in draft form) and actual computer listing of other applications – and these can be posted online if appropriate.
3. If anyone has difficulty in understanding any points, and/or has specific questions – I will be happy to answer them via this blog. In particular if you are doing some brain related research (in the widest sense) send me details (remembering I may have problems with pay walls) and I will happily give you my suggestions. After all a good test of my ideas is whether I can answer your questions convincingly.
4. If there is enough interest I will try and make arrangements to make MicroCODIL software and manuals available to anyone who has access to a BBC Microcomputer. (Because the computer has become something of a cult survival second hand ones are often available.)
5. Should I be able to help an existing university research project by giving a talk, attending a seminar, etc., I am happy to do so. Even if you don't agree with me exposure to controversial ideas can help everyone to start thinking outside the box.
6. If a particular research group wanted to resurrect any of the CODIL programs and applications, or use them as a basis for an “ideal brain” simulation I would be happy to advise.

How the Human Brain works – concept cells, memodes and CODIL

BRAIN 

STORMS 

Number

13

I am really Excited.

I can't wait to tell you about it. 

See Later Follow Up Discussion Papers 

From the Neuron to Human Intelligence: Part 1: The “Ideal Brain” Model Part 2: Evolution and Learning (to appear shortly)

I am currently preparing a talk How Evolution has made us the way we are – and I had a problem. You can't really assess how evolution has affected the development of the human mind unless you have a clear model of how the brain processes and stores information. I have already, in earlier brain storms on this blog pointed to the black hole in brain research where very significant amounts of work is being done round the edge of the problem but where there is no good model of how electrical pulses in the brain are translated into human language or behaviour. I have also discussed at length how work on a highly unconventional language called CODIL (COntext Dependent Information Language) may throw some light on the issue and recently introduced the term memode (memory node - see The Evolution of Intelligence - From Neural Net to Natural Langauge) to try and demonstrate a possible mechanism. However there was still a major gap in the model if it was to serve as an adequate model for understanding how the evolutionary pressures worked.

So What has Happened???

The trigger to filling the gap came from the article “Brain Cells for Grandmother” in this month's Scientific American, by Rodrigo Quian Quiroga, Itzhak Fried and Christof Koch. (see also Concept Cells: the building blocks of declarative memory functions by Rodrigo Quain Quiroga). This research involved monitoring the activity of single neurons in the medial temporal lobe of epileptic patients undergoing assessment prior to surgery. It was observed that a single cell might respond to different pictures of a single individual, while remaining inactive when pictures of other people were shown. In one case a neuron was found which responded to three different pictures of Luke Skywalker, his name (either in writing or spoken) and interestingly to a picture of Yoda, another character in the film Star Wars.

One of the problems I was facing in earlier brain storms was the relationship between the information in the working memory (called the Facts in CODIL) and the main memory which contained the items of information and the links between them. On reading "Brain Cells for Grandmother" the relationship became clear. Information is stored in the links, and the main memory and the working memory are one and the same – the difference is that the working memory is defined by the links which are currently active. I can now tie my model into the neural network in the brain and the change of viewpoint provides throws light on the following aspects of the working and evolution of the human mind..

• The “virtual” information represented when the top neuron in a memode is active is simply the sum of all the subsidiary memodes (recursively) which are linked to the memode. Thus each concept is at the top of a tree of subsidiary concepts. There is no one location where information about a concept is stored.
• The senses trigger bottom up activity in the memodes, the objects  we “see,” “hear,” or “smell” being the highest level memodes activated.
• The CODIL Decision Making algorithm maps onto a process in which active memodes can trigger top-down activity in related but initially non-active memodes. (Basically the brain can decide that if “A” and “B” are active “C” should be active.)
• Consciousness (the information we are actively aware of – and equivalent to the Facts in CODIL) is the sum of the information represented at the time by the top active memodes.
• Learning involves the linking of the top active memodes to generate a new higher level memode. (In fact it looks as if deciding what not to learn and what to forget becomes the critical factor than learning in building memories.)
• If we assume that some decisions are made sequentially - with a series of memodes triggered in a predefined order – the model could support at least a simple spoken (i.e. sequential) language. The experience with CODIL being able to handle significant non-trivial information processing tasks is relevant here. This points to an evolutionary tipping point leading to the explosive growth of both language and other special skills.

For more details read on ....