How a very young baby sees the world

A new baby's brain is exact
It can see things you can't; that's a fact,
But its brain has to choose
What to keep, what to loose
And the key shapes it needs to extract.

Trying to find out what a very young baby actually sees would seem to be an almost impossible job, but a recent Scientific American article summarizing research by a team led by Jiale Yang of Chuo University, Japan, has produced some interesting results.

Were there significant differences between Neanderthals and us?

Adam Benton, on Evoanth recently posted an interesting article "How similar were Neanderthals and humans?" which looked at the evidence and while there are definite differences it is not clear how significant they are -in deciding why they became extinct and we did not.

I responded:

It might be worth thinking about later encounters – when the Europeans discovered America and Australia. The Europeans came off best because they had the stronger cultural communal knowledge base, which enabled them to build more powerful weapons. It might be a complete accident of history that the discovery of how to make iron happened on one side of the Atlantic rather than the other.

Could we have done better than the Neanderthals because we had a better cultural knowledge base which gave us more advanced technology and allowed us to work together in larger groups, perhaps with some people beginning to take on specialist roles. At the time that language was first appearing the key to having a better cultural knowledge base would be having a more powerful language. Thus it may be that when modern humans first met with Neanderthals we collectively “knew more” – so we came off best – just as Europeans came off better in America and Australia – because they had better technology.

If we look at language as a self-modifying tool there were almost certainly some key “inventions” – such as being able to differentiate between the past, present and future, counting, etc.  Perhaps it was just an accident of history that one of our species, rather than a Neanderthal, made the first key technical advances which allowed language to develop and that Neanderthal brains were just as capable in that respect as our own.

Should we do something about the "happiness problem"?

I always like things which encourage people, including myself, to think outside the establishment box, especially when they relate to how our brains work. In reading recent student posts on the futurelearn course "What is a Mind" I discovered a link to the paper "A proposal to classify happiness as a psychiatric disorder." I hope you enjoy reading it as much as I did.

The brain is really flexible

It says a lot about the adaptability of the brain, and how it can wire itself 
up in unusual circumstances just to watch how these 7 year olds can work
together, and share information. for instance if one watches the TV the
other can also "see" it

The Brains of The Great Apes

Mother Chimp showing infant how to break open nuts

The BBC Iplayer is currently showing a program on the brains of the great apes.The summary says "Chris Packham explores the evolution of the great ape's brain to reveal how different parts have been adapted over time by its anatomy, ingenuity and sociability." In practice it says little about the brain except to say that different aspects, such as the development of the hand, has meant that there has been enlargement of the relevant areas of the brain. However there are some excellent wild like photographs illustrating the advanced features of ape behaviours, and I fouind the discussion about the differences between Bono-boos and Chimpanzees particularly interesting. The section on chimpanzees "teaching" their young to crack open nuts showed, in my opinion, how inefficient the chimp teaching techniques are - as it takes 10 years for the young chimp to develop the skill by simply copying the mother.

The Brain and the Evolution of Human Intelligence (Comments Please)

I am currently drafting a paper on the Evolution of Human Intelligence which will bring together three interacting models, each representing different levels of activity and abstraction. The jumping off model I am calling the “Brainwave Model” which looks at simple decisions at the human short term memory level. Above this is an “Intelligent Pattern Recognition Model” which examines the relevant CODIL research and its relevance to culture, natural language and intelligence – and in effect defined the brain’s “Symbolic Language”. Below the Brainwave Model” there is the “Ideal Brain Model” (early draft to be rewritten) which looks at what the neurons need to be able to do in order to support the two higher models. The paper will continue looking at the evolution of the brain and human intelligence, using the models as a guide, starting with the requirements of a simple animal and looking at how the brain’s power increases as culture evolves.

Draft Section: The "Brainwave Model

The Brainwave Model forms a short term memory bridge which links the complex high level mental activities which we associate with human intelligence, with electrical and chemical activities at the neuron level, and the objects in the real world we are thinking about.  It is best described by a simple example.

Imagine the brain as a sea of interconnected neurons and into this sea we drop pebbles of information. This creates ripples of activity which spread out across the sea, and eventually die away. For instance our eyes see a rabbit and result in a “rabbit” ripple becoming active. This process could well involve many hundreds or thousands of neurons becoming active as the ripple develops and this activity can only pass between neurons which are linked. Each ripple can be considered as an active thought in the short term memory and at this level of modelling we are not interested in the fine detail within a wave of activity.

At the same time the body becomes hungry and a “food” ripple becomes active. The two ripples spread and meet and combine to generate a new brainwave – “rabbit pie”. At the point at which they coalesce there will be a neuron which is linked in such a way that it can be activated by either the “rabbit”, the “food” or “rabbit pie” ripples. What has happened at the thought/concept level could be represented as:

rabbit, food à rabbit pie

We can generalize this to model the human short term memory. At any one time there are a maximum number of ripples (about seven) which can be active at any one time. Each ripple can be given a concept name, which for convenience in this text will be shown in bold brown font. Where two or more ripples intersect there will be a neuron (or a group of neurons) which can be activated by the relevant concept and this can “take a decision” by activating a new ripple.

Of course it is important to realise that a concept name, such as rabbit, is not a precisely defined entity as the ripple through the neurons would be different depending on the colour of the rabbit, or whether it was a real rabbit or a rabbit in a children’s story book. It may well be that in some situations the sight of a wild rabbit, or a carcase in a butcher’s shop will trigger the rabbit pie decision, while the sight of a domesticated rabbit, or a picture of Beatrix Potter’s Peter Rabbit will not. At the same time the strength of the food concept will vary depending on how hungry you are. Other minor factors might affect whether you imagine the pie to be topped with short crust or puff pastry – or whether instead you think of rabbit stew. Such differences are an essential features of how the brain works.

The brain is a dynamic learning (and forgetting) system which is not concerned with any externally defined global models. In a relation such as

rabbit, food à rabbit pie

the “meaning” of rabbit is defined only by the ripples active at the time the rabbit pie decision is made. As part of the brain’s learning process the mental activity involved will have a feedback effect which could modify the way the activated neurons are linked – so the meaning of rabbit could be slightly different the next time a similar rabbit is seen in a similar situation.

When we come to the exchange of information between people using natural language we need to agree stable long term concept names for objects, such as rabbits, but our individual brains will associate the concept rabbit with different memories which will develop over time. Later in the paper, when I look at CODIL as a model of brain activity, the same situation arises. CODIL was conceived as a practical working tool which did what its human user wanted – and by default items (the equivalent of concepts) have to be stable – although options were built in to allow CODIL to dynamically alter its behaviour over time.

Before moving on to discuss higher level models of brain activities it is necessary to understand how this simple brainwave model provides a basis for further research. The brain contains billions of neurons, and each neuron has direct (and indirect) links to many other neurons. This would represent a massive array involving tremendous computer power if one tried to look at the problem globally. The wave of activity associated with the current thoughts (concepts) in our short term memory act as an filter on the vast array selecting a minute number of entries – and in some cases none at all. When considering how the brain processes higher level “intelligent” ideas all neurons and links can be ignored apart from the tiny number which are activated in the current context.

Are Humans domesticated Apes?

I like "out of the box" ideas and I really enjoyed the post I like this hypothesis by P.Z. Myers about the effects of domestication on animals. When we domesticate an animal species we select for tameness and this means, in effect, we select animals which have reduced adrenal glands as in such animals their stress levels are reduced, they are generally less fearful, and they are more open to socialization.

There appear to be associated side effects. For instance Mouse, rat, guinea pig, rabbit, dog, cat, fox, mink, ferret, pig, reindeer, sheep, goat, cattle, horse, camel, alpaca, and guanaco all show depigmentation (especially white patches and brown regions). Rabbit, dog, fox, pig, sheep, goat, cattle, and donkey have floppy ears while rat, dog, cat, ferret, camel, alpaca, and guanaco have reduced ears.

He suggests that the common factor is linked to neural crest cells during the early development stage.

Image: fotolia

This would also the fact that domesticated rat, guinea pig, gerbil, rabbit, pig, sheep, goat, cattle, yak, llama, camel, horse, donkey, ferret, cat, dog, and mink have reduced brain sizes compared with their undomesticated relatives.

Myers speculates that is might be the explanation for Neanderthal brains being bigger that ours - in that the difference is due to Homo sapiens being more domesticated!

Of course this is speculation - but the whole article emphasises that evolutionary changes in one feature can have knock on effects elsewhere in the body.

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..

Did the Neanderthals die out because humans had a better culture?

Two recent news items, coupled with earlier reports that Neanderthal children matured faster than human children, could be relevant to Neanderthal intelligence and perhaps to the species becoming extinct.

The paper New insights into differences in brain organization between Neanderthals and anatomically modern humans by Eiluned Pearce, Chris Stringer and R. I. M. Dunbar notes that while the Neanderthal brain size was similar to Homo sapiens, more of the brain was devoted to sight and controlling a larger body.

The paper Barium distributions in teeth reveal early-life dietary transitions in primates by Christine Austin et al examined a Neanderthal tooth as estimated that breast feeding in Neanderthals may have only continued for about 14 months compared with 30 months in human non-industrial societies.

Why is Albert Perry's DNA so interesting?

Many people researching their family history are interested in finding as much as possible about the paternal line – and have resorted to DNA testing of the Y chromosome, which passes from father to son, and which is not found in women. Because small copying errors occur between one generation and the next it is possible to find out how closely related and two men are. Fossil evidence suggests that modern man came into existence about 200,000 years ago and that all living men shared a common “Adam” ancestor somewhere between 60 and 140,000 years ago.

That is until Albert Perry's DNA was sent for testing by a relative – and the laboratory carrying out the genealogical tests on his DNA were puzzled – as it didn't fit. Further investigation suggested that his Y chromosome was so different to yours or mine that the “Human” paternal ancestor we shared with Albert lived about 340,000 years ago – over 100,000 years before the beginnings of the modern human species.

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.