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 ....

Brain Storms - 4 - Requirements of a target model

The human brain consists of a very large number of interconnected neurons and is capable of handling a large number of sophisticated concepts. Animals (by which I include the great apes and possibly all vertebrates) have brains made up of similar neurons and can take actions which relate to their memories of the environment in which they live. As the earlier posting, The Black Hole in Brain Research, suggests little is known about the way in which changes at the neuron level use these memories to work their way through to the resulting complex decisions leading to actions.

One way of trying to find out what is happening is to try and build a model of the likely processes and memory structures and find out what the model can do, and how far it fits with observations. This post aims to outline one possible approach to modelling the relevant thought processes and some of the observations which a successful model will need to explain.

We know enough about the brain to know that we need a large number of processors each of which is linked to a memory which can store a pattern, with communication links between processors.. The simplest action would be that a processor receives a signal over a link from another processor, compares the signal with its memory, and depending whether there is a match sends a signal to another processor. This can be considered as a single neuron acting as a logic gate.

The aim is to see how far we can model different aspects of brain activity by expanding this simple model in a way that will support complex decisions and actions. In the subsequent postings I will be looking at how research on an unconventional computer language, called CODIL, carried out some years ago, provides a good starting point for such an approach. However the work done so far falls far short of a complete brain model and it is appropriate to list some of the “goals” which will need to be addresses so that that areas where the model needs to be improved can be identified.

1. The model must start – like a new-born baby – knowing nothing and be able to boot-strap itself up to a fully working system.
2. A built in learning mechanism is essential
3. There must be a mechanism to recognise patterns
4. The pattern matching process may sometimes be exact, but will sometimes need to be “fuzzy” especially in early learning stages.
5. There must be some way of organising patterns into categories and events.
6. Information relating to time and distance need to be handled on a relative way.
7. At any one time there needs to be a focus of activity (around short term memory?) but some processes will be “subconscious”
8. Counting (beyond 1, 2, many) and formal mathematics and logic will only be relevant as tasks which the model can learn to do.
9. There will need to be some housekeeping activities – including forgetting!
10. The model should be capable of evolving from simple models.

Human language raises some interesting points. The brain's neural net working in parallel while speech is a sequential process. If information is to be transferred from one human to another by speech there has to be conversion processes (parallel > serial > parallel), introducing syntax. An important question is whether there is any need for special facilities in the brain to carry out this translation type task. The model will need to be able to support different cultures and languages and people with very different skills or political/religious views.

There is one factor that needed to allowed for in discussing any model. This is recursion. I have not defined a “pattern” or how it is represented – but in discussing examples it will be useful to be able to say that a particular pattern identifies a concept equivalent to the English word “Elephant”. However, in the same way that the word “Elephant” can be broken down into individual letters the pattern may also be able to be broken down into separate sub-patterns. For this reason I will use the term “Node” to represent a processor/pattern combination without needing to ask whether it is based on a single neuron, or a linked network of neurons, where the pattern is actually defined by links.  

Brain Storms - 3 - Evolutionary factors starting on the African Plains

Image the plains of Africa three or four million years ago – populated by a range of medium to large sized mammals which (for verbal convenience) we will describe in terms of modern species. There will be herds of antelope and zebras grazing on the ground plants, and animals such as giraffe who can eat foliage from high in the trees. Other herbivores will include elephant and rhinoceros. Wart hogs will have a more varied diet, and there would be the carnivores and carrion feeders such as lions and hyaenas. All have basically the same body plan, biochemistry, and genetic coding mechanisms – which have been modified by evolutionary pressures in different ways in different species. It is reasonable to assume – at least in a brain storm such as this – that the basic body plan includes the processes that allow the brain to store and process information.

Brain Storms - 1 - Introduction

I am trapped in a box. You are trapped in a box, In fact we are all trapped in many different physical, social and mental boxes which in one way or another control the way we look at the world.

And because of we are trapped in mental boxes it is hard to think objectively of human thought and how it evolved because we are not impartial observers. But let us try – so why not join me in this series of brain storming posts about the brain.

But before we do I must declare an interest – by describing the box that I am in. I am in my 70s, and having taken early retirement over 20 years ago I abandoned all direct contact with university research, apart from regularly reading the New Scientist. Recently I decided to catch up online with any recent developments relevant to the discarded research project and what I found suggests that this long forgotten research is actually relevant to some of the obstacles in understanding how the mind works and how it might have evolved. This set my brain spinning, and, as my resources are strictly limited to the web and a desk-top computer (not even a University library reading card at present) I decided to launch this blog.

Whether you decide to join in will depend on whether you are interested in brain storming approaches to how we think – but will also depend on the boxes you are trapped in. For instance your own thought processes may be trapped by a box which means that you automatically assess the quality of research by its status - and automatically assume that the only good ideas come from young researchers, in  prestigious institutions, with plenty of funding. If so you may care to ask yourself if someone in a less favourable situation could get a controversial idea accepted you may find my post Why is Blue Sky research so difficult of particular interest.

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The approach behind these brain storms will be to start by trying to stand back and get an overview of the issue, using Occam’s Razor to discard as much detail as possible. I will try to keep each issue short and any comments, points of information,, etc., which readers can add will be very welcome – and may well influence the way the Brain storms develop. The goal is to explore novel models for the way that the brain supports a wide range of mental activities.

The starting point of the Storms will be to look at The Black Hole in Brain Research and then Human Evolution and the Brain.