Why does pain hurt?

All life is suffering.

This is the grounding principle of Buddhism that still amazes me to this day as it was taught more than two thousand years ago by a man with no access to physics, mathematics, neuroscience or any of the other rational commodities we comfortably enjoy today. He hypothesised that suffering was a force that permeated all life and designed a careful path of mental training which aimed at overcoming this condition. Counterintuitively it did not involve the cessation of pain.

   This question has puzzled me since an early age. Why does pain hurt? We know what pain is. It's a collection of signals sent from the so-called nocireceptors to the central nervous system and then to the brain. It can be triggered by a strong mechanical stimulation, by high heat or by the potassium release of bursted cells. It travels on known chemistries through known pathways across the nervous system, riding up along the spinal cord, up to the brain stem through the thalamus into the cortex where it blossoms like a beautiful question mark:  why  does  it  hurt?  Why does pain hurt? Why does this dull, unrecognisably grey exchange in the nervous system hurt so damn much?

   To find the answer we don't need to dive so deep to where it's pitch dark. We all know what suffering is. It's something we avoid. And pain is not the problem. You can pinch yourself and though you feel a subtle pain you can go on. The real problem is suffering, of which pain is a common cause. Suffering is what keeps your hand away from the fire.

   If we are to view ourselves as mechanical beings then suffering is what will prevent us in the future from doing something. It's a simple observation: if I hit my nose with a hammer and I feel pain and pain makes me suffer, I won't do it again. After the experience, like the nose, the system just isn't the same. It has become dynamically impossible for the system to spontaneously pick up a hammer and hit itself. If you don't believe my word, try it yourself, I trust my odds.

The motion of a system towards a new dynamical state is called learning. The formation of and motion away from a repulsive state is called suffering. The formation of and motion towards an attractive state is called pleasure.

   Of course, impossible is such a strong word and an inaccurate one for that matter. The system could very well find a way around it after sometime. The system could also perpetuate its suffering by suppressing the wrong reaction to a painful stimulus thereby hopping on a spiral of hurt. Which is worsened if additionally a smart part of the system reacts positively to it and a dumb part of the system reacts negatively, which results in an obsessive behaviour, with one end of the mind being drawn to an action which causes the suffering of another. The system could also overreact, blocking far more than is required, which is called a trauma. This also explains why you can learn to not suffer from pain, by familiarising yourself with the feeling and ceasing to react negatively to it. And even pleasure, instead of suffering, can arise out pain, if pain's dynamical role is to encourage the system to react more often in a destructive way, which is termed masochism.

  These definitions of suffering and pleasure are applicable to any system. In fact, they are familiar experiences to any adaptive system. In the next post we'll deal with a very simple and completely unrealistic one: Marjorie.

The me and the tree

The ones among us that are vegetarians quite often hear the observation:

"Plants can also feel, you know?"

Putting aside how obvious that is, it is worth considering what actually distinguishes us from plants. We look at ourselves as independent, discrete beings, separated from our surroundings with which we interact. Then we look at a tree and that is what we tend to see as well: a discrete being, with its definite separation from it's environment. We then compare these two discrete units -- the "me" and the "tree" -- and see 'obvious' differences, and the absence of a central nervous system is not the least of them. No one denies the complexity of the interactions between the cells in a plant, akin to the complexity we see in our own skin and other organs. But certainly this is not a match to the complexity of our brains and the whole nervous system!

But we are now starting to know better. Remember the simple model akin to a neural network. I say 'akin', of course, because it is not necessarily composed by neurones. Look back at the tree. It might seem to be a simple being when compared to ourselves, but they tend to live in large societies we usually call forests. And we are not talking about "autistic" individuals, living their own life without caring (or knowing) about their neighbours. They communicate with each other. Widening the scope of our analysis to this community we can see all sort of amazing dynamics. For instance: trees infested with bugs will signal the surrounding trees the event so that they can prepare, excreting chemicals that dissuade the same sort of insect attacks. They might even communicate with predatory insects to ask for protection from herbivores [1]. Furthermore, we are coming across with several ways of communicating [2]. We now know that the use of an intricate subterranean system of fungi to communicate chemical signals is fairly common. The roots themselves are obvious ways of communicating underground messages. And, as it has been known for a while now, chemicals can be emitted to the air and picked up by nearby trees, conveying messages as well. The dynamics of these systems are not that different from the dynamics of a nervous system, though with different temporal and spacial scales (we will come back to this in a later post).

We thus might have been letting the trees block our view of the forest. We just need to look to the right scale -- the forest, including other beings that interact with the trees -- and realize that we are not that different.

We leave you with an exercise. Observe the world today and consider: what other systems, subsets of the world around us, show this wonderful dynamic behaviour? Are you part of it? What would it (He? She?) think of you?

[1] http://www.wired.com/wiredscience/2013/12/secret-language-of-plants
[2] http://www.bbc.co.uk/news/science-environment-22462855

Paradox Powered

Some might have missed the point of the previous post, because it's a subtle one. The initial statements we made were based on the assumption that there is an underlying physical world which is fundamental and true. Then we added that all observers are phenomena within this physical world and whose relative reality is necessarily bounded, even though the underlying reality remains true.

The main point is that values such as truth are not universal but relative. We may take them for intrinsic qualities of reality but that only works within a limited scope. Truth is itself an outcome of the interaction of phenomena and we would like in this post to develop this idea a bit further, by bringing out its dynamical qualities.

Let's dive right in. If the truth is the state of a system then a proposition is the external stimulus. The system reacts to the stimulus by going either to the state 'true' or 'false'. If we wish to make a statement about everything then we must also include the state of the system itself in the statement. Such is an example of a complete set:

This statement is true.

albeit not a very enlightening one. The statement connects the outcome of the truth system and of the statement, which in this case are the same entity. It's a complete statement, the same as an equation that describes the dynamics of the system as a whole, like the equations that governed the motion of our magnet-and-detector system. As an equation, it can be solved by finding the true/false trajectory that satisfies it. So if we start by assuming the statement "This statement is true." to be true then the statement tells us the statement is true, which corresponds to a trajectory

where each square represents the truth value of the statement at a given time (flowing from left to right, black means 'true', white means 'false'). If we start by assuming the statement is false then the opposite of being true is false, so the statement is consistently false

Try however, this equation instead:

This statement is false.

If we start with the assumption that the statement is true, then it is false. If however it is true then it must be false. This equation has no stationary solutions. They are:

Both equations can be described in the following way:

Once we realize that paradoxes can be treated as equations with non-stationary solutions then we're pretty much ready to analyse just about anything. A scientific view is a collection of logical statements which are connected somehow, of which some of them are the theory and some of them are the observational evidence. They must form a complete set, so that the equations can be solved. We usually expect the scientific view to be like

which is a stable view. However, it looks more often like

where some problems remain unsolvable. Nevertheless, even a stationary view can be challenged by the results of an experiment

In this case, the system undergoes some turmoil but then returns to a stable configuration with the conclusion that the experiment is wrong. However, this behaviour is also possible

which is called a scientific revolution. The very complex linkage between statements makes the system prone to radical changes, a very common feature of complex systems. Here, the system is pushed out of balance by the new evidence and undergoes a transition phase as it's caught in the basin of attraction of another stable configuration which eventually becomes the next accepted paradigm.

Stationary solutions are common but have a huge lack of adaptability and are therefore selected away by the constant inflow of knowledge. Real theories, like real organisms, include mostly stable statements but also some oscillating ones, persistent loops of logic.

When we include ourselves in the theory we quickly run into such loops. That's why it's so difficult to think about the consciousness as our reasoning inevitably starts to chase after its own tail. But we should not be discouraged by this event: it actually reveals the phenomenological and dynamical nature of reality. It means that, instead of worshipping it like a precious stone, we have to treat our theory like a living organism, with its evolving traits but also its cyclic ones, its beating heart and breathing lungs. We started from the assumption that subjective experience stems from physical phenomena and we found that physical phenomena stem from subjective experience. None is more fundamental, they revolve around each other in a logical gravitation.

On the other hand, string theory and other religious movements perpetually seek additional statements which preserve the stable structure of certain dogmatic ones. This ends up being a neurotic behaviour eventually leading to a messy, energy-consuming organism of very little use, like a fat untouchable king cloistered amongst his own devout guard. Sane views abandon the pretence of universalness.

The strong correspondence principle

It's a long standing question of why reasoning, logic and math are so adequate to describe reality. In fact, seekers of the theory of everything, physics' modern knights of the round table, have in their quest an implicit belief that a fundamental principle underlying all of reality holds the key to derive all possible statements about the universe that are true.

As we've already more than knobheadedly stated, the universe is made of things looking at things. Perception and comprehension happen when a system interacts with a second system and both develop an internal structure as a result of their encounter. And, just as we've shown before, such coupled systems often constraint themselves to a limited set of answers.

One thing we can say about the rational part of our mind is that it is a system which effectively (more likely approximatively) deals with only two states: true or false. This system basically measures how comfortable you are with a particular statement and whether you should act according to it. It has its own rules called logic which have been drawn out for quite some time.

The common scientific view, in close connection with these rules, entertains the idea that there is a fundamental reality which is true and that the human mind, through the practice of thought, can come asymptotically close to it. However, as several people have pointed out in very beautiful ways throughout the history of mathematics, statements can't always be either true or false. Indeed, this statement is false, is a statement which is alternatively true or false. If it is true then it is false, and if it is false then it is true.

This happens because logics, reason and mathematics are dynamical phenomena of our mind. There is a physical system whose dynamics correspond to our thought process which are effectively described by the simple rules of logic. For a single statement, the possible orbits are either continuously true, continuously false, or alternatively true and false. The paradoxical statement above is in fact a logical equation whose solution is a cycle: true, false, true, false, true, false, true... but true is nothing fundamental about the world. It is a state of the system.

Like the magnet detector, a result of true or false doesn't tell us anything about reality. As Trinity put it, "The Matrix can't tell you who you are." It can't tell you what things are either. The results of reasoning only express the result of the interaction of the logic thinker and the object. Existence happens at the edge of real things.

And this is why mathematics has always come through. The rational part of our brain is an adaptive system where logic structures form until a stable structure is found. That's why theories evolve as discovery proceeds and, just like with living organisms competing for survival, massive extinctions can also happen. They're called scientific revolutions.

The same way the auditory cortex adapts to recognise new sounds, the logic centres design new theories as a result of their own environmental constraints. This whole theory of ours is the outcome of our rational interaction with the world. But then so are the physical phenomena that underlie our conscious thought. Which has led us to formulate the strong correspondence principle:

Every phenomenon has an experience associated with it and every experience has a phenomenon associated with it. Phenomena and experience are themselves an experience and a phenomenon. They are indistinguishable.

Whereas in the weak correspondence principle we assume the tangible existence of a physical phenomenological world which expresses itself through subjective experiences, this updated statement acknowledges the fact that the depiction of reality in terms of physical phenomena is itself an outcome of the dynamics of these physical phenomena. It means we can either think of the world in physical terms or in mental terms; they are the same.
The reason why so many people disagree about the nature of the world is because the whole system is so complex that many realities (stable configurations that result from the universe's interactions) are possible. We know many systems in our mind, such as the emotional mind, think very differently from the rational mind. Yet they also evolve, reach a conclusion then evolve again.

Looking at logics from a phenomenological point of view makes it pervious to generalisation. How common is our logic? Does it emerge often in complex systems? We will come back to this point later.

The living knitworks of nature

If everything is conscious and experiencing the world, the real question is whether their experience somehow relates to ours. So what are the fundamental aspects of ours? A bit of introspection will reveal that we experience all of existence in webs of concepts. What a car is to us is a hub of many impressions: it induces an image of a four-wheeled machine from the sound "car", it produces the sound "car" from the image of a four-wheeled machine, it can make us hesitate before we cross the road or pull us to a storefront when it's bright shiny new in a dealership. The thought of it is generated from the sight of a wheel, of a tire, of a leathered seat or of a metallic paint job. What the car is, really, is a certain behaviour of our mind, or rather even, a connector between two successive mental states.
But where does this dynamic nature come from? It turns out that the artificial neural network, a mathematical toy simpler than its biological counterparts, is enough to help us understand. An artificial neural network, simply put, is a web of nodes that stimulate each other, where a specific node activates if enough other nodes stimulate it. It won't necessarily take every other node's contribution equally but might be more susceptible to certain stimuli. Thus, an artificial neural network is uniquely described by which nodes are linked to which nodes and how much each link weights in the activation of another node. Something like this:

So consider this simple network that connects the activity at many end points to the activity at another end. It doesn't really matter how (for now) but let's say the network relaxes to a specific configuration, meaning that the weight of each link, thanks to some dynamical mechanism, reaches a stable value. Imagine each input end reacts to the ink of a black-and-white painting. Then the whole system answers a yes-or-no question about the image. The first two nodes will react to two different features of the image and the final node will react to a specific combination of these two features. For example, it might activate only if the image contains both features (the weight of each is not enough) or if it contains at least one of them (both weights are high). These familiar rules of logic emerge from the simplicity of the two-noded system.

In larger networks it becomes entirely hopeless to figure out accurately what each node does. One can however use a vast array of inputs, collect those which activate a given node and build from it an average over the set of inputs which the cell is sensitive to. That will tell us roughly which specific feature a specific node is encoding. This technique is one of the basic tools of neuroscience used to figure out the role of each neurone in our experience.
According to our own introspective conclusions, a web of connected features is commonly called a concept. Any active web-like structure will share this general trait of our subjective experience. It will perceive the world in connected happenings, every one of them bringing about the next. It doesn't even matter what mechanism brought it to its present configuration, whether it is according to our human opinion or to an environmental constraint a smart one or a dumb one: for as long as the universe lets it be the way it is, it will experience according to the concepts encoded in its network.

Fortunately, the universe is full of such systems, which means we won't run short of acquaintances to make too soon. Trees in a forest, chemicals in a cell, commercial exchanges across the atlantic are all examples of such connected webs which experience concepts like we do. The everywhere-presence of rich subjective experiences reminds us how our own is a naturally occurring phenomenon. The only reason the world appears to be far more complex where we stand is because most of the things our own networks react to are human-related. The same way I can’t tell the difference between two brutal death metal songs where others hear entirely different “melodies”, we humans can’t see order, reason, intent and sophistication in most of the world's phenomena, even though we try very hard with science, spirituality, art and other amazing human endeavours. Every creative action we take is an additional attempt to relate to some new feature of the universe, by creating a new structure in our own network that reacts to it. This cognitive movement is a very common one in nature. In fact, all it needs is interaction, and there’s plenty of that to go around.