Continuing our story, we can see that all life and mindfulness
is anchored by meaningful information. There must be a frozen global
scale that carries the “long-lived marks”, the
system’s ideas or memories, that are its source of
organisation – its boundary constraints.
We are well use to thinking of DNA as a memory molecule. Strands of DNA may be wrapped up inside cells but they are still global in the sense that they persist longer, and are spread out over more terrain, than the individual organisms they may be found within. A set of genes may seem localised, but a genome is a global property of a species and even whole biological phyla. Humans and apes share some 96% of their genome. Even chickens share some 60% - which should not be a surprise as we all have the same basic body plan with limbs, blood vessels, a backbone, skin and organs like livers, kidneys and guts.
So genes encode a recipe to make a body. Over billions of years, they learn to make the kinds of bodies that are likely to be successful. Each new generation – assembled with just a smidgen of variation to explore a slightly wider range of evolutionary possibilities – is like a fresh prediction about what should work. The genome works on an anticipatory basis. This prediction is then tested by Darwinian selection. Out of the heat of competition comes learning. The fittest survive and the genome is left slightly better prepared for its next round of predictions, completing the cycle of adaptation.
But DNA is only one of the forms of semiotic information that sustain life. Boundaries such as the membrane of a cell, the skin of the body, or the lining of the gut, are also informational. They are not passive barriers but cognitive structures that need to be able to distinguish between self and non-self. A cell membrane has receptor-controlled pores and other structures that can recognise what substances to let in and which to shove out. The gut and skin exhibit the same kind of discrimination on a larger scale.
This general dependence on information is important as it shows that consciousness and brains emerged from something. Bodies already needed multiple levels of cognition and control. So the evolution of nervous systems was just a further step.
Indeed, it was not even a very big step. A nerve cell (which we call a neuron in the brain) is simply an exaggerated version of an ordinary cell. All cells have the ability to secrete and respond to chemical messages. All cells also have a natural electrical potential drop across their membranes. Because they must maintain the right ionic balance – a salty interior – cells need to be able to pump out positively-charged atoms like sodium, which then leaves their insides slightly negative in charge.
So the basic machinery of chemical signalling was in place. And the membrane already had electrical properties. All that remained was to give the cells a shape – to stretch them out to make an input-output pathway.
In other words to dichotomise them into context~event, ground~figure (noting here a reversal of the usual local first~global second convention of organic logic as the “input” is the global constraint and the “output” is the locally constructive act).
the dichotomistic neuron
The dichotomistic logic of a neuron is clear in its layout. At
a neuron has a bush of dendrites, the synapse-studded tendrils that
receive input signals. At the other end, a neuron is stretched into the
long output arm of the axon. Input charges flow up the dendrites and
accumulate on the cell body. With thousands and sometimes hundreds of
thousands of synaptic inputs, it is clear that a neuron is a contextual
device. It is listening in to the rest of the brain on a global scale.
But then once enough charge has gathered to exceed the neuron’s threshold, it fires. A spike – a rolling wave of membrane depolarisation – speeds down the axon towards its destination. So the actions of a neuron could not be more contrastingly particular or specific – the figure marking a ground, the event that stands out from a context. Input is global and output is local.
So physically the difference between neurons and ordinary cells is quite slight. But in terms of a capacity to represent meaningful information – a dichotomised response to the world - the differences are immense.
As said, all cells traffic in chemical messages. There are even specialist clumps of cells – glands – that use hormone messages to control body-wide growth and reproductive cycles. But the delivery of such messages is somewhat haphazard. The signals have to diffuse through tissues, or be borne along by blood vessels, to reach their targets. The meaning of a hormone message is also genetically-fixed. It is an evolved lock and key response.
Neurons on the other hand can deliver a message point-to-point, anywhere in the body, almost instantly. Thickly insulated motor nerves conduct their signals at several hundred kilometres per hour. The messages themselves are coded in flexible patterns of spikes. A neuron can be conveying information about sights or sounds, tastes or motions, urges or frustrations. The spikes look just the same, the meaning lies in the fleeting patterns of connection being formed.
So the invention of neurons raised the game. It made it possible for life to use information in an instant and specific way. The knowing of the world could become immediate. To exploit the excellent properties of neurons, nerve networks and brains were a natural next step.
A single nerve can act as an intelligent pathway. Wired at one end to
pressure sensors, and at the other to muscles, a nerve can do things
like allow a worm to recoil when prodded. But a network of nerves all
talking to each other is much better as a network can come to represent
complex realisations and behaviours.
A network of nerves is best thought of as a memory surface. In brains, every neuron is connected to many neighbours. And the strength of each of these connections is tuned by experience.
The changes may be brief. As with the membrane receptors of a bacterium, the receptors at a synapse may change their shape following a burst of activity so that for a second or so a connection is made more sensitive or less sensitive.
Or the changes can be rather longer lasting. The tip of an individual dendrite may swell to expose new synapses, physically strengthening a connection. Or a neuron might sprout extra dendrites. Or whole new neurons might be brought in to swell the pathway. The number of ways of tuning the connection between two brain cells – of wiring in a memory – runs into the dozens, probably even the hundreds.
The result of all this careful tuning is a neural landscape sculpted by its experiences. A network of nerves starts off in a neutral state, but through memory changes it becomes a surface etched with bumps and hollows. When fresh input flows into this landscape, it is then channelled down well-trodden pathways. It is the shape of the network that does the processing. Although, of course, new inputs, new experiences, will in turn start to carve out new memory paths. The network is learning at the same time as it is making.
The only thing missing from this picture is the need for some form of feedback, some way of closing the loop and telling a particular connection that it is doing a good job and so should strengthen itself.
With a simple nerve pathway, such as the bundle of a few hundred nerve cells that actually controls the recoil reflex of a worm, this feedback comes in the form of genetic learning. The nervous system of a worm is small enough for the genes to specify the placement of each individual cell. So the right pattern of connections can be wired in over many generations. Simply put, those worms that know when to pull their heads in are the ones that will survive to pass on their wiring plans.
But the tale of the brain has been one of increasing speed of such feedback. The cycle of adaptation has spun faster and faster until the connective pattern of brains can be reshaped on the fly.
In a worm, the processing is certainly quick – the signal to recoil flashes across its nervous system in an instant. But the learning is slow, it taking many generations to reshape the genetically-coded pattern of connections. The scale of the adaptive change is still global as it is taking place at the species level.
With large brains however, both processing and memory changes have become almost instant. They have become local and specific to some particular organism. So what was originally a neural landscape being slowly sculpted by experience has become an active process of “in the moment” neural resculpting that causes experience. Awareness is the result of having a mind that is differently shaped from one moment to the next, and thus a mind that can appreciate that it does have a continually adapting view of the world.
the architecture of brains
Right, we have spent quite enough time laying down basic principles.
Let’s dive into the actual anatomy of the human brain.
We will start with the thalamus, a blob of nerves about the size of your fingertip that lies at the centre of the brain and acts as the first major stopping off point for all sensory information as it floods in to be processed. This critical organ divides into about 14 major nuclei. These consist of the lateral geniculate, the medial geniculate, the ventral lateral, the ventral posterolateral, the ventral posteromedial, the….err, I think we have a slight problem here.
The human brain has billions of neurons and trillions of synaptic connections. It only has a few thousand distinct processing areas - lobes, ganglia, nuclei or other gobbets of grey matter large enough to have individual names and known jobs. But this is still far too much complexity for anyone but the ardent student of neuroscience (who of course ought to dig out a copy of Going Inside).
So let’s step back a bit to consider the general evolutionary story of nervous systems and how needs have shaped its overall layout.
Any brain is no more than an elaboration of the nervous system, a complication on the pathway connecting sensation to action. Or to put it more organically, less mechanically, context to event. There is the appreciation of the global situation that leads to the production of some specific thought or behaviour.
The very simplest nervous systems, like those of a jellyfish, have no centre. They are just a web of nerves which prodded anywhere will spark a muscular contraction. But fairly early on, evolution discovered that it was good for an animal to have a definite head and tail – to have a body plan that expressed an intent, a direction.
This is being a little unfair on the jellyfish, of course, as it may be a ring structure, yet it is still dichotomised into a top and bottom. Contractions push it away from something, and thus towards something else. However, the value of a more strongly dichotomised body plan – the stretched out linear tube of a worm - is dramatic.
segmentation as divide and rule
At this point we should note that the step from jellyfish to worm is
mechanical. A worm is constructed by chaining a sequence of basically
similar body compartments – body segments – in a
line. The first big evolutionary shift was from single celled organisms
to multicellular ones. Individual blobs became the larger blobs of a
slime mould, volvox or jellyfish – creatures with only a
vaguely dichotomised body plan. While the growth of a body was free in
all three dimensions as it is with a blob, it remained hard for
evolution to sculpt particular body parts.
But by constraining growth to a linear sequence, a single dimension, evolution could begin to mechanically construct. It could tack on new segments. And in their relative isolation, each new segment could be tweaked to do slightly different things. A segment could sprout a wing or a leg, a ventricle or a sense organ. Segments could have both functions in common – global ones – and also their own particular or local functions. The global and the local could become more crisply defined, more concretely dichotomised, by a reduction in dimensionality from generalised blob to segmented line.
This is obvious with for example the evolution of a gut – a digestive tube with an input and an output that can process food in a mechanical sequence of stages. Jellyfish have to make do with a simple sac in which digestion is an inefficient “boil in a bag” affair. But a worm can segment the digestion of food, breaking it down into (mechanically) logical steps. It can deconstruct a meal like fallen leaf!
First comes the gizzard that grinds up the leaf into more digestible fragments. Then comes a series of acid baths and enzyme attacks followed by the absorption of nutrients, recovery of fluids and expulsion of waste. Digestion is a crisply particular series of actions.
Of course there is still a deeper organic logic behind the mechanical logic. Each segment is dichotomised in the sense that it is specialised for particular actions – and so is defined equally by all the other actions it is not performing.
A worm is still a fairly uncomplicated critter. So for example, its digestion might be chunked, but its locomotion remains fairly generalised – not a great advance on the pulsating jellyfish or tumbling E. coli. Each segment contributes to a wave-like stretch and pull, bristled skin gripping the soil. But with insects the segments can sprout legs, wings, antennae. Crisp choices can be made about switching between modes of action. The segments that are flapping are definitely not contributing to any walking.
the further evolution of organisation
Sorry for yet another diversion, but we are talking about complexity
here. Life and mind are complex systems because they arise out of
physico-chemical vagueness by a process of dichotomisation to become
increasingly hierarchically organised. And this also means that they
become more mechanically controlled.
Organic logic is about everything happening at once, causality going in all possible directions. It is holistic in that everything is the product of interaction (as well as separation). But then complex systems arise through a steady move towards mechanism – the development of methods of crisp construction and thus crisp control over what exists.
An organism is still organic (naturally!) but it becomes more machine-like in important respects - as we know from genes, cell membranes, neurons, tissues, body segments, organ systems and even systems of communication like human language. The organism can be fabricated because its parts and its whole are so sharply distinct. Indeed, so sharply distinct that minds and bodies, cognition and structure, form and substance, come to seem like dualistically different modes of being. Life can almost be defined in terms of the controlled and the uncontrolled, the computational and the dynamic.
Getting back to the evolution of brains, we can see that the first step was to break up the unoriented blob of cells with its unoriented ring of nerves to create the linear, segmented, body of a worm. A row of segments could become a row of neural specialisms to process a world in more mechanical fashion, de-constructing it as sensation and re-constructing it as anticipations or actions.
With the worm being crisply dichotomised into a head and tail end, it was only natural for all the major sense organs to develop up front near the mouth-parts where the action took place. And then it was only natural to build a brain there as well, elaborating the nervous system at the point where all the information from the various sensory systems could be pooled to form a general picture, and this general picture used to drive the animal’s behaviour.
If we look more closely at the primitive vertebrate brain - the ancestral brain of animals like fish, reptiles, birds and mammals that have backbones – we can see even this developed according to the segmented linear plan. It began as a simple neural tube, a spinal cord, which then swelled to form a series of bulges at one end.
The forebrain dealt with olfaction – the sense of smell - and the kinds of behaviours that go with smell, such as eating and mating (pheromone scent messages being important to many vertebrates). The midbrain then dealt with vision and other distance senses such as hearing. Finally the bulge of the brainstem made general decisions about arousal levels and motor activity, being well-positioned to turn the body’s thermostat up or down, depending on the demands of the moment.
Thus the vertebrate brain had a rough division of labour from the start. Olfaction, vision and body control were strung out like beads on a chain. Yet each of these primitive bulges was also intimately connected. Nerve signals flowed back and forth to knit their activity together. So the smell of food would cause the eyes to search and the arousal centre to call the body to readiness. There remained a generally connected, jelly-fish logic to the vertebrate brain. Tug any corner of the nervous system and the rest would jangle in a co-ordinated network of response.
As the vertebrate brain grew larger, both the number of divisions and the counter-balancing mechanisms of integration became more complex. What had initially been simple bulges broke up into hundreds of sub-modules, each sharing aspects of the tasks. So with vision, for example, the brain broke up into areas dealing separately with colour, motion, location, shape and perspective. Human brains ended up with 30 or more such stages. With more neurons to throw at the job, the processing of visual experience became divided into an ever increasing number of parts.
It was all very mechanical – a collection of processing modules. And yet to keep all this activity properly integrated, the cross talk between the many brain areas had to increase in turn. Which is why nearly half the human brain has come to be white matter –trunk cabling that allows all the islands of grey matter to stay continuously in touch which each other’s activities. Some neuroscientists estimate that for every one neuron crunching input, another nine are needed to tell the rest of the brain about it.
So a division of labour and the integration of this labour were dichotomous trends in the elaboration of the vertebrate brain. Differentiation~integration or separation~mixing. The story of large brains is about their complex anatomy, but also about their simple drive for unity.
There are a couple of further trends that characterise the evolution of large vertebrate brains (though birds and mammals followed somewhat different paths). One is encephalisation – the ballooning of the very first spinal cord bulge, the forebrain, to create the cerebral hemispheres. The cortex, the wrinkled surface of these paired lobes, offered a virgin terrain. And this space was colonised by vision, hearing, motor co-ordination and other tasks that had originally been lower brain activities.
The reason for this forward shift of the faculties had a lot to do with a second trend - a change from a hardwired nervous system, built to a strict genetic template, to a nervous system that was plastic, being shaped largely by experiences and memories.
As said, genes can code for the individual placement of neurons in small brains. But once faced with brains of billions of cells, they have to construct in a more general way. They can specify roughly where a block of cells – the raw neural materials – should be placed. Then the job of wiring up the cells has to be left to experience. The right connections must be learnt through trial and error. That old dichotomy of nature~nurture or evolution~development.
It seems that evolution found the forebrain to be most pliable lobe, being the least involved in critical functions like the control of the heartbeat or breathing. It was simple just to inflate the forebrain to several thousand times its original size, then let vision and other functions remap themselves onto its generous, unmarked surface. So the genes did as much as they could to specify the detailed structure of the vertebrate brain, then did as much as they could to make it receptive to the further lessons that life could teach.
Is a baby conscious when it is born? This will sound a strange question
to any parent. But it is a serious one for neuroscientists.
A human baby is born with hardly any connections in its cortex, its higher brain, just a mass of unwired cells. The lower brain is well developed at birth and is capable of producing a variety of instinctive behaviours such as suckling, crying, recoiling, even tracking objects with the eyes. But the higher brain is blank of the memories and experiences with which to make rich sense of the world.
The human brain is a bit like an ice-cream cone both in its physical shape and its development. There is a firm crusty base. The genes have learnt over millions of years of vertebrate evolution how to wire up the brainstem and many of the mid-brain structures to handle basic jobs like breathing and swallowing, or even walking, pouncing and copulating. So the lower brain provides a narrow but solid foundation of the most essential input~output pathways (and for a simple animal like a frog or snake, it can handle just about everything that needs to be handled).
But mammals, and especially the monkeys and apes, have expanded the forebrain enormously. The cerebral hemispheres now sit perched atop the crusty cone of the lower brain like big soft scoops of ice-cream. And as said, they are also produced quite differently. Being much too big to be hardwired, the genes have to throw up a generalised mass of neurons, then allow life to lick it into shape.
Thus the answer to the question about a baby being born conscious is that it probably enjoys only a reptilian level of awareness – and a somewhat dazed reptile at that! Or we could say that its consciousness is vague and awaits the development of more crisply formed ideas and impressions.
The process of building the higher brain actually starts in the womb. The womb may seem a watery twilight world, but a foetus can still squirm about enough to begin to educate its motor circuits. It also has a chance to touch, taste and hear. So apart from vision, some learning is possible in the months before birth.
However it is only after birth that the higher brain really starts to get going. The cortex neurons enter a phase of rampant growth, sprouting a profusion of dendrites and axons. In the first few years of its life, a baby’s brain is forming nearly two million new synaptic connections each second. Yet this growth is rather random, connections being made willy-nilly. The connections are also immature, not yet having white matter sheathing to insulate them. So instead of nerve signals zipping about at hundreds of kilometres per hour, they are creeping along at nearer walking pace.
But then comes the second phase of the cortex’s development. By about six months, a baby’s brain has made about twice as many connections as it actually needs. The next step is to start pruning these thickets. In fact, the synapses compete against each other to find which is the best placed for the job of processing the world. The ones that are lucky enough to be in the right position to do useful work will survive. But inactive synapses wither. As a result, neural connections start to disappear at the rate of a quarter million each second. From this pruning, the original mish-mash of wiring is slimmed down to a set of cortical pathways that actually work.
For the baby, the effect must be rather like tuning into a distant radio station. Scientists have recorded from the brains of infants staring at a pattern of simple black bars. In the first few weeks of life, this pattern always provoked a broad crackle of activity from many neurons. Because of the promiscuous maze of interconnections along the pathway bringing information from the eyes, plenty of neurons felt they were vaguely seeing something. But they were not being specific. A grid with thicker or thinner lines also evoked much the same broad wash of activity. So mentally the baby must have experienced a rather indistinct state – a sense of general “grid-ness” if anything at all.
A few weeks later, however, the boundary-detecting areas of the visual cortex had begun to tune into the world. The maze of connections had been pruned to give more precise responses. Only particular cells fired in response to lines of particular size. So now the baby would start to have the same sense as an adult of seeing thin bars and fat bars as clearly different kinds of experience. Out of a grey crackle of static, the brain gradually homes in on a crisp signal. It tunes into a sharp experience of life.
The infant brain builds itself up like this in a series of stages. First it tunes into the simple aspects of the world. It gets used to comprehending shapes, colours and motions. It learns about simple motor activity too – how it can use the information about what it senses to control its actions. A baby’s first discoveries are about how to grip objects and bring them to its mouth (or fling them across the room). Then each newly acquired set of sensory and motor skills becomes the platform for yet more complex skills. So once it can see shapes and colours clearly, a child is ready to notice the differences between cats and dogs, or family and strangers. Simple ideas pave the way for more complex ideas.
Steadily the higher brain bulks up with memories and habits. Its circuits come to represent the astounding variety of things that every human child knows how to do. It can speak, think rationally, make predictions, empathise, show self-control. Out of very general beginnings – a formless scoop of grey matter – emerges a set of finely-honed pathways that have learnt to deal with the world in precise ways. The brain becomes an organ that can do many things. The problem then is to get it to do the one right thing that best fits each passing moment. And this again is a matter of adaptation. But now adaptation that must take place within a split second.