The more we probe the brain, the less we understand it

The New Scientist of 19th October has an article "Hidden depths - The vast majority of brain research is now drowning in uncertainty. It is time to build a more complete understanding of the mind" by Ingfei Chen. This queries the foundations of much of the research into scans which attempt to relate what we are thinking with neural activity. The approach seems to be the more and more detail we have the better we can understand - but that is true only if we are asking the right question. Readers of this blog will know I believe that we are already drowning in detail without understanding the neural code. If the neurons use the same code, whatever their detailed task,  you don't need to look at millions - you need to stand back and look for the common features. As a result I have submitted the following letter to the New Scientist, and also posted it as a comment to the article.

Brain research is drowning in uncertainty (Hidden Depths, New Scientist 19^th October) because nearly everyone is looking for a non-existent Philosopher's Stone of Biological Human Intelligence. In reality we have the same unsophisticated neural code as animals but have replaced a degree of critical thinking with a sheep-like “follow my leader” approach to speed learning. Of course this is an advantage as culturally learnt intelligence skills, communicated by language, are very much more powerful than our genetically based animal intelligence. Unfortunately the inherent weaknesses of the comparatively crude biological foundations show through as confirmation bias and the way our memories of past events drift with time. In evolutionary terms our big brain is no more significant than a giraffe's long neck, and we might understand how the brain works better if we were not so “big-headed” as to think our brain is biologically anything special.

From Neural Code to Religion - An Evolutionary Model of the Human Brain

A New Look at the Evolution of the Human Brain

A talk given to the Chiltern Humanists on 10th October, 2013

Copy of slides (pdf)

Illustrated text supporting the slides (pdf)

The following notes outline the arguments which underlie the talk. Most technical information on the model of the neural code used, and the related CODIL research, are available on this blog, and I am happy to answer any questions/comments about more technical aspects of the research.

Evolution of the Human Brain

Chiltern Humanist Meeting

Evolution of the Human Brain

The first of our autumn series of meetings will be held on Tuesday 10 September at Wendover Library.

Chris Reynolds, a retired scientist who has been a member of our group for several years, will take a new look at the evolution of the human brain. This has been researched at a biological level and raises the question of whether there is an inbuilt reason why some people are drawn to religion whilst others are not.

By temperament Chris likes to stand back and get an overview, rather than getting stuck in a narrow specialist area. After taking a doctorate in Chemistry he started working with computers in 1965; he was soon involved in research, and developed a language called CODIL over the following years. As Reader in Computer Science at Brunel University, Uxbridge during the 1970’s, he became involved in a project, funded by the British Library, concerned with interactive publication, which in a very elementary way anticipated the World Wide Web. Later he edited an online professional book review service on the subject of Human-Computer Interaction. In retirement his main interests are genealogy and local history.

His talk promises to be an interesting and different take on evolution.

Humans like to think they are something special - If not actually made by God in his own image, or the centre of the universe, are least we can console ourselves that we are more intelligent than the other animals that inhabit  our planet.

Or can we? No animal needs a brain that is bigger than necessary to survive, and we only have to look at the other mammals that share this planet to see that there are many cases where a species can be characterized by a greatly enlarged organ, whether it is a giraffe with its long neck, an elephant with its greatly extended nose, or the hands of the bat. And what about the changes we see in the whales!

This talk assumes that all mammals have brains that use the same neural code, and that the human brain is no more than a normal animal brain which has been supercharged to give it more processing capacity. It considers the limitations one might expect from a very simple neural code, and asks what the evolutionary pressures would be on the braians of hominids who were faced with the drying out of the African rain forests three million years ago.

The key factor would seem to be the point where cultural knowledge passed between the generations became more important to survival than the basic brain mechanisms on their own. At this point it there was an advantage in have a larger brain and developing faster mechanisms for learning. Better learning means better tools for survival, and one of those tools is language, which will automatically develop from generation to generation. One could get an auto-catalytic situation where the culture we pass on is augmented at a growing rate in each successive generation. 

Unfortunately the basic animal neural code is mathematically not very sophisticated, and while this is not important to other animals the defects become more evident as the human species pushes the code to its limits. While many of the defects can be avoided using language the logical weaknesses, such as confirmation bias, can, and are, exploited by religions and political belief systems. Even scientists will not be immune, as they take part in the rat race for prestige and funds!

After the talk I will be posting the slides used and background notes on this blog..

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.

Looking for the "Neural Code"

Going through an older section of my email inbox I found a Scientific American link to John Hogan's blog post Do Big New Brain Projects make sense when we don't even know the “Neural Code” in which he wrote:

Neuroscientists have faith that the brain operates according to a “neural code,” rules or algorithms that transform physiological neural processes into perceptions, memories, emotions, decisions and other components of cognition. So far, however, the neural code remains elusive, to put it mildly

The neural code is often likened to the machine code that underpins the operating system of a digital computer. According to this analogy, neurons serve as switches, or transistors, absorbing and emitting electrochemical pulses, called action potentials or “spikes,” which resemble the basic units of information in digital computers.

I prepared the following, perhaps too lengthy, comment but when I came to post it I got a message that the page had been moved - and all attempts to find it resulted in irrelevant pages on the Scientific American web site. So I am posting my response below:

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I would argue that the problem with modern brain research is an inability to see the wood for the trees. Of course if you look in detail at the brain things get very complex. But such complexity is common in science. The key idea underlying evolution is very simple – but when you look at individual cases in detail there can be enormous complexity. The same applied in medieval times when the movements of the known heavenly bodies appeared to be very complex – until it was realised that things became much simpler if you calculated the motions of the planets using the sun, rather than the earth, as a key reference point.

The problem with the human brain is that, as John Hogan says, we don't know the “Neural Code” and virtually everyone is looking at the problem in ever greater detail – apparently on the assumption that the harder you look at the fine detail the more certain you are to find out the shape of the wood!

I have been trying to stand back and get an overview and have come up with an “ideal brain” model which in some ways parallels the “ideal gas” model in physics. All neurons (like all gas molecules) are identical – and the dynamic links between neurons are like the dynamic collisions between gas particles. Using such a simple model it is possible to “grow” a brain that can remember and use more and more complex concepts – with the complexity of the most advanced concepts it can handle depending of the brain's capacity and time for learning. The model explains consciousness and can predict detailed observations about the brain - for instance the so-called “mirror cells” in the brain turn out to be nothing special as the observations simply reflect the way that all neurons work in the “ideal brain”. In addition it is possible to ask how human “intelligence” might evolve and this approach predicts a major tipping point (rather than some major genetic “improvement”) which produces and “explosion” of “new ideas” when “cultural intelligence” becomes a more effective tool than the innate biological “intelligence” of the “ideal brain” model.

The problem with the model, and possibly the reason why it appears not to have been explored before is that to a “culturally matured” mind (and all people accessing this text on the internet will be culturally mature) the model involves several counter intuitive steps.

1. The model assumes that at the genetic level the only significant difference in the processing mechanisms between our brains and most animals relates to supercharging effects (more capacity, more links, more effective blood supply, etc.), and that if there is a difference the model actually suggests a reason why we might be genetically less intelligent that some other animals! Before you shout me down over this “outrageous claim” I should point out that the model suggests why culturally supported intelligence is infinitely more effective than the genetic intelligence foundation on its own.
2. You have to forget everything you have learnt about computers and algorithms. The definition of a stored program computer model requires there to be a pre-defined model of the task to be performed. The “ideal brain” model starts by knowing nothing about anything and has no idea what kinds of tasks it will be required to carry out. Virtually all it does is store and compare patterns without having any idea what those patterns represent. Once you start looking in great detail at how specific name tasks are processed you have taken your eye off the ball - as you are asking about what the brain can learn to do - and not what the underlying task independent mechanism is.
3. Everyone knows there can't be a simple model of a Neural Code – because with so many people are looking someone would have found it if it existed - so there is no point in looking ...
4. My research has “reject” stamped in all the standard “Winner of the Science Rat Race” boxes. I make no secret that I am 75, am not currently associated with any established research group, and the only facilities I have are a P.C. in a back bedroom, access to the internet, and access to some old research notes on a long abandoned blue sky project which was trying to design a human friendly white box computer to replace the standard human hostile black box computer everyone takes for granted.

If you are interested I hope to have a detailed description of the “ideal brain” model on my blog later this month.