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Translation by AB – June 19, 2021
The belief that nothing changes comes either from poor eyesight or bad faith. The first one corrects itself, the second one fights.
Friedrich Nietzsche – Fragments posthumes
Some projects of the great “vassals” of our technological regime (think of Elon Musk) aim at exploiting our brain, under the pretext that it would be an information processing machine that could be integrated into the natural digital environment like a common device. So, we are all prepared to believe that the brain is a computer. Some researchers and thinkers challenge this approach, but without yet being able to propose an alternative. So, while waiting for the “objectivizing” action of a hypothetical “science of organisms”, what can we say and possibly set against perspective of the “brain-as-a-computer”?
Preamble about the technological regime
The technological regime determines our economic and political systems but it is almost never the target of those who despise these systems. Why such an anomaly? Perhaps, like the Purloined Letter by Edgar Poe, is the fact so ordinary that it is no longer seen? Or has the technological system become so complex that only experts can understand it? However, the technological regime seems to have an immune system that employs several tactics.
First of all, it produces ignorance like the cephalopod produces ink. This fact is studied by “agnotology”1 :
There is a sociology of ignorance, a politics of ignorance; it has a history and a geography – and above all it has powerful origins and allies. The making of ignorance has played an important role in the success of many industries; because ignorance is power.
Next, people have an objective stake in the progress driven by the technological regime in the remedies it offers, particularly in the areas of health, energy, safety or environment. At the same time, it must be acknowledged that major technical research is led mainly with private funds and therefore has very little societal accountability.
The technological regime thus conditions us radically while remaining immune to any criticism: it is obvious like the air we breathe, it popularises without mediatizing, it can produce ignorance, it proposes remedies and finally it delivers its own ethics. It should be clarified that “it” refers to the technological regime as “it” naturally produces these effects without being gifted with any intentionality. The technological regime is not a subject that plots but a set of institutions, public and private, procedures, practices, types of political and economic organization determined by a dominant technique and persevering in existence, like any organization, by the doxic “fumes” that we have just sketched.
We accept as truth the “brain-as-a-computer-idea”, thanks in part to the rhetoric that accompanies the works of “artificial intelligence”, we believe we know what the “brain” means and more or less how it works, we trust the researchers who claim to develop “responsible” thinking by themselves, as well as the companies that offer us products guaranteed by certifying bodies (Elon Musk’s Neuralink is awaiting approval from the Food and Drug Administration – we do not doubt the result), and finally we assent the “brain-as-a-computer-idea” because our brain can then be repaired, cured and even improved.
But the tricky brain is at the same time the last explorable – and therefore destructible – “continent” of our earthly vessel. It therefore deserves our greatest attention.
As the essayist Georges Zarkadakis reminded us in his book “In Our Own Image”, the brain has always been considered as producing “thought” according to the principles of the technological regime in place: hydraulics in the 3rd century B.C. produced a hydraulic model of the brain, the gears of automata from the 15th century onwards gave rise to a mechanical model of the brain, electricity and chemistry in the 17th century gave rise to an electrochemical model, communications in the 18th century gave rise to a telegraphic model, and finally information theory in the 20th century gave rise to a computational model of the brain.
Our current belief system therefore fosters this evidence: the brain is a computer. The French neuroscientist Stanislas Dehaene thus states things like: “our children are supercomputers”, “I think a good teacher is a teacher who has a good mental model of the children’s brain” – incidentally inspiring new pedagogical approaches for the French National Education – or “we are endowed with a brain machine that surpasses computers” to conclude sharply: “we are our brain“. Who does that surprise today? Computational and cognitivist rhetoric has become sadly evident, accustomed as we are to using and depending on smart, connected, intelligent, autonomous artefacts … and which computational principle seems to be universally applicable.
In a very good article, the psychologist Robert Epstein explains that he proposed to prestigious neuroscientists to try to account for human behavior without using the information processing metaphor2:
They couldn’t do it, and when I politely raised the issue in subsequent email communications, they still had nothing to offer months later. They saw the problem. They didn’t dismiss the challenge as trivial. But they couldn’t offer an alternative. In other words, the IP metaphor is ‘sticky’. It encumbers our thinking with language and ideas that are so powerful we have trouble thinking around them.
The technological regime thus escapes any questioning by its self-evident character, sustained by set of cultural conventions and a lexicon, in short by a belief system.
Popularization: the “Blob” example
Any external entity conceived as individualized tends, by empathy, to be conceived in the mode of a living being.
René Thom – Esquisse d’une sémiophysique
The “blob”, a nickname of Physarum polycephalum, is a fascinating creature: neither animal, nor plant, nor mushroom, it is a unicellular being which develops in the undergrowth of temperate zones and which can reach several meters of diameter3. Consisting of a single cell, the blob has no differentiated organ (such as eyes, mouth, digestive system, legs, etc.) nor therefore any brain. And yet it moves, crawling at the speed of a few centimeters per hour, and it “eats” with appetite yeasts, as well as fungi and other bacteria. To obtain its “favorite” food or simply to ensure its survival, it is able to “develop complex strategies”, to “learn” and even to “pass on its learning” (as says Audrey Dussutour of the French CNRS). The lexicon is running at full speed.
All these wonders are achieved only by the scatterbrained body of this plasmode with such a particular dynamic. Its movement is in fact caused by a back and forth movement of the protoplasmic current within the network of vessels that it projects in search of food. It leaves a mucus in its path which “protects it against desiccation but also has a repulsive role which prevents it from exploring the same track twice”4. With this, we know just enough to briefly explain these so-called “complex strategies”.
It can “solve problems”. We place a blob (or several because the blobs can merge) in a maze whose entrance and exit are filled with food. The blob spreads slowly in all the corners of the labyrinth (we remind you that its mucus allows it to “know” where it has already been), and it obviously ends up reaching the entrance on one side, the exit on the other, and feasting. Then its structure gradually simplifies. A network of vessels remains which connects the entrance and the exit by the shortest path. Thus, the blob seems to be able to “solve problems”5, “think without a brain”6, etc. But food simply acts as an attractive pole which potential is diffused in the vascular network. It is mathematically representable without resorting to solving thought. In the same way, a ball dropped on an inclined plane will “find on its own” the line of greatest slope; A soap film will “solve a complex equation” by forming the minimum surface connecting any contour, etc. Nature is thus made of shapes that “solve” our equations and our problems without a single brain (to say the least, since these equations are one of our representations of the world). Physarum polycephalum is even an excellent railway engineer. Oatmeal flakes are placed on a map representing the main cities around Tokyo; the blob ends up absorbing them all and by forming a network of vessels strangely resembling the railway network optimized by Japanese engineers… What a strange experience.
It can “learn” and “pass on its learning”. What is it about? The blob hates salt like its own mucus. When salt is placed on a bridge leading to its “favorite food”, gradually – the experiment lasts several days – the blob overcomes its repulsion and crosses the salt bridge. The experience is repeated and each time the blob crosses the salt more quickly: it is “learning” says the popularizer7, it is “habituation” says the researcher more cautiously. Better still, a blob that has “learned” can pass an its indifference to salt to a “naive” blob (!), via a vessel that is established between them. The so-called naive blob then crosses the salt bridge as if it had learned to do so on its own. But how is it possible to “learn” and “pass on learning” without a “brain”? What information did these two blobs exchange? What did they say to each other? Obviously not much: the researchers simply realized that the salt concentration of the blob progressively increases during the famous “learning” process8. By ingesting salt, the blob is in a way minimizing a difference with its immediate environment and the naive blob has simply received a good dose of salt from its fellow blob.
We have become accustomed (like the salty blob …) to the lexicon of our technological regime and now think only in its terms, like the neuroscientists challenged by Robert Epstein. The very simple example of Physarum polycephalum should make us careful when it comes to our own brain. Perhaps we should also look for metaphors based on rolling balls, soap films, potentials and minima … and disengage any concept from information and communication theories. But it is not that simple.
To the metaphor of the “brain-computer”, Robert Epstein opposes this principle that we probe in the course of our explorations (The Mirrors of the “I”, etc.):
We are organisms, not computers.
This principle is demanding because the concept of “organism” is complex. An organism has an internal organization relative to an environment that it partially “ingests” (materially and symbolically) in order to fit into it. This nesting modifies it at the same time as its environment. Francisco Varela (Francisco Varela the Heterodox) had translated this dynamic relationship by the expression “structural coupling”.
Robert Epstein presents an example that helps us to better understand the difference between the informational approach and dynamic coupling. It is the movement of the baseball player who must catch a ball:
The IP perspective requires the player to formulate an estimate of various initial conditions of the ball’s flight – the force of the impact, the angle of the trajectory, that kind of thing – then to create and analyse an internal model of the path along which the ball will likely move, then to use that model to guide and adjust motor movements continuously in time in order to intercept the ball.
This computational perspective indeed requires a sequence of operations since a) reality must be translated by the brain into information, b) the brain calculates what to do with this information, c) it transmits its results to the body. But nothing like this is necessary for the player to catch the ball:
That is all well and good if we functioned as computers do, but McBeath and his colleagues gave a simpler account: to catch the ball, the player simply needs to keep moving in a way that keeps the ball in a constant visual relationship with respect to home plate and the surrounding scenery (technically, in a ‘linear optical trajectory’). This might sound complicated, but it is actually incredibly simple, and completely free of computations, representations and algorithms.
Thus, the body remains in a dynamic relationship, in accordance with its internal organization, with its environment. Thus, the brainless blob moves and stretches without calculating anything, simply animated and deformed by potential differences. It acts, like us, according to its own mode of coupling. The brain undeniably participates in this mode, like the rest of our body, but in a way that remains to be understood.
The technological system, the basis of the technological regime, produces solutions to problems that it often creates itself (Jacques Ellul and the Technological System). Considerable resources can be committed in exchange for the promise of their resolution. The European Human Brain Project launched in 2013, with a budget of 1 billion euros over ten years, promises to simulate the entire human brain in silico and to revolutionize the treatment of degenerative brain diseases such as Alzheimer’s. The ambition of this project, like that of its American counterpart BRAIN Initiative9 launched in April 2013 by President Obama, is to “understand the brain”. But what does “understand the brain” mean? And more importantly, to do what? Let’s start with this second question that leads to the structure of Stanislas Dehaene’s arguments:
With a deeper understanding of how our brains work, we will understand ourselves differently, treat illness more effectively, educate our children more effectively, be more insightful in law and management, better understand those whose brains have been shaped by other circumstances.
Since “we are our brain”, it is logical that its understanding should lead to improving ourselves, individually and collectively, and thus to building a more “efficient” and better controlled society. This old theme is no longer reserved for science fiction alone. From now on, scientists and “vassals” of the technological regime believe in the possibility of success. Public and private organizations are investing billions of euros in these projects, which are undisputedly intended to cure us.
Now let’s go back to the first question. For neuroscience, “understanding the brain” means explaining how our tens of billions of neurons interact to produce our “behavior”. After more than a century of observations, we already know a lot about the brain, its structure and its principles. It seems natural that sooner or later we will be able to causally explain a behavior from a state of this complex structure, or even to induce this same behavior by reproducing this same state. But there are many objections to this design. Here are two that seem important to us.
First, we must agree on what “behavior” means. If we are talking about the physical manifestations of our body (movements, sounds…), we must admit that there are organic causal links between brain activity and, for example, muscle activity. In this respect, the brain is a simple organ in an organism, like the heart or the liver. But behavior must also, according to neuroscientists, include all internal and sophisticated cognitive processes such as emotions, judgments, intelligence, consciousness… It is no longer a question of physical causality, accessible to the classical methods of science, but of a pseudo-causality internal to our systems of representation. It is thus a question of identifying which electrochemical activity of the neurons provokes the “consciousness”, underlies the “memory”, or establishes the “depression”… that is to say leads the researcher to select, in a pre-existing language, the word that best describes the observed behavior.
Methodologically, it would be roughly equivalent to observing someone “dancing” and inferring that he/she is “happy”. What is “true” in one cultural context may be “false” or even meaningless in another. Dancing may be equated with possession in another context where the very concept of happiness does not exist or is broken down into a myriad of nuances unknown to us. The same is true for the “dance” of neurons, which can be interpreted in a language that is totally inadequate in a given context or for a given individual. Our language, which is the only one capable of selecting a “behavior”, is a convention that could be said to be based on our millennial ignorance of brain mechanics: it has no chance of being suitable for scientifically describing a behavior associated with a chemical or electrical state of the brain.
Second, how to represent the activity of tens of billions of neurons? This is the main challenge that the American BRAIN initiative or the European Human Brain Project set in 2013. If we comprehend the brain as an information-processing machine, as our technological regime prescribes, then the method must consist of a) making an inventory of its elementary component types (cell types) as one would of an electronic circuit (transistors, diodes, etc.), b) drawing up a map of the connections at all scales, which is called the “connectome”, the equivalent of the genome for the genes. This research requires the collection and analysis of gigantic volumes of data earned on a micrometric scale by real-time observation of brain activity, such as videos of unprecedented definition. If this collection is only a matter of technical power and does not raise any theoretical objection, the analysis on the other hand should be a human task in order to lead to manipulable theories (intelligence consists to a large extent in filtering and then reducing the available signals into simple and efficient “proxies” such as a theory or a language). However, these projects generate such a large amount of information that the analysis and reduction into concepts is no longer humanly feasible. It is then necessary to rely on automatic mathematical reductions and artificial intelligence systems. We are trying to accomplish this somewhat absurd feat of having a digital replica of brain activity as detailed as a real brain, but without much use10:
As the German neuroscientist Olaf Sporns has put it: “Neuroscience still largely lacks organising principles or a theoretical framework for converting brain data into fundamental knowledge and understanding.” Despite the vast number of facts being accumulated, our understanding of the brain appears to be approaching an impasse.
Miming is not explaining.
Of course, European and American projects have their own sections dedicated to ethics. Thus (extract from BRAIN Initiative)11:
Because the brain gives rise to consciousness, our innermost thoughts and our most basic human needs, mechanistic studies of the brain have already resulted in new social and ethical questions. Can research on brain development be used to enhance cognitive development in our schools? Under what circumstances should mechanistic understanding of addiction and other neuropsychiatric disorders be used to judge accountability in our legal system? Can civil litigation involving damages for pain and suffering be informed by objective measurements of central pain states in the brain? Can studies of decision‐making be legitimately used to tailor advertising campaigns and determine which products are more attractive to specific consumer bases?
Let us note the strangeness of these questions supported by the “evidence” that “we are our brain”. If we can measure what we are by co-measuring it to our brain state, then they all fall under a kind of Chinese-style “social credit rating” (China and AI: imperial!). Therefore the only truly ethical question is: should we admit that our behavior is measurable? At the limit, this “zero ethical” question: what should we accept from these researches?
Premises for an inflection
However, Science is moving forward and is already beginning to silently undermine the foundations of the technological regime and its brain-centric doxa. Here are two quick illustrations.
In October 2005, psychiatrist J. Allan Hobson published an article entitled “Sleep is of the brain, by the brain and for the brain”. But this cognitivist vision of sleep is now being challenged12 :
The results suggest that one very fundamental job of sleep — perhaps underlying a network of other effects — is to regulate the ancient biochemical process of oxidation, by which individual electrons are snapped on and off molecules in service to everything from respiration to metabolism. Sleep, the researchers imply, is not solely the province of neuroscience, but something more deeply threaded into the biochemistry that knits together the animal kingdom.
The study of sleep deprivation in flies shows that lethal changes are induced not in their tiny brains but in their intestines. So:
The flies that never sleep and their glowing guts remind us that sleep is profoundly a full-body experience, not merely a function of the mind and brain.
Sleep and sleep deprivation do have effects on the brain, but they are no more brain functions than solving mazes is a skill of blobs. A second research, also very recent and exciting, shows that “fear” and “attention” (our behavioral terms) are very strongly correlated with heart rate13. The brain and the heart work closely together without our being aware of it.
Scientific works are multiplying which show that intelligence, consciousness, emotions… are embodied and far from being localized in the brain. Let’s quote again Robert Epstein:
[…] even if we had the ability to take a snapshot of all of the brain’s 86 billion neurons and then to simulate the state of those neurons in a computer, that vast pattern would mean nothing outside the body of the brain that produced it.
We should not be surprised that the blob does not have a brain and yet manifests “behaviors” that we can only describe as “complex” or “strategic”. It is, like any autonomous being, an organism that interacts directly with its environment and is organized accordingly.
The Brain differently
Everything that follows, a brief response to Epstein’s challenge, is pure speculation (or even poetry…).
Paleontology tells us that the first brain structure appeared in worms 500 million years ago. Worms inaugurate a type of anatomical organization in specialized tissues and organs coming from one of the three embryonic layers: endoderm, mesoderm, ectoderm. Humans develop according to the same principle. Each species “interprets” and develops these embryonic layers according to its own genetic material while following a similar pattern : the endoderm forms the base of the internal organs (walls of the digestive tract – except for the extremities –, glands – liver, pancreas, gall bladder –, respiratory system), the mesoderm that of the skeleton and the musculature and finally the ectoderm, the outermost layer, the skin or the carapace, the teeth, the nose, the ears and … the nervous system.
The French mathematician René Thom tried to make an inventory, with his theory of “catastrophes”, of the different possible natural shapes, their unfolding and their trajectories. In particular, he applied his work to the living shapes, morphogenesis and embryonic development that we have just outlined. Thus, the nervous system is a shape that appeared from the ectoderm, the sheet destined to form the edge or envelope of the organism, both the “carapace” (or “shell”) against predators and the interface of exchange with the environment (ingestion, expulsion). René Thom then makes this striking observation, the starting point of our answer14:
The vertebrate has taken the risk of giving up this Maginot line, the exoskeleton; it has replaced it with a carapace of virtual pain.
The brain is thus placed at the edge of the organism and participates in its “carapace”, that is to say, in its protection as a prey: reflex movements of the newborn, then progressive elaboration of strategies of bodily movements and, above all, of anticipation by replay of these strategies (conscious thought). The nervous system is not an inert exoskeleton – an armor – but an “active” exoskeleton, therefore plastic, and which participates in the singular history of the organism that it “shelters”. The brain thus takes the “shape” of the body’s experiences, just as the shell keeps track of shocks and contacts, and it “tells” the body what to do in each particular situation according to its “scars”, which makes the French philosopher Bernard Andrieu say, echoing Robert Epstein15:
The brain has a singular flesh for each human body.
We can thus re-present the brain as something other than a computer manipulating information, data, rules, algorithms, symbols, lexicons, etc. or than a “brain machine” that stores, retrieves and processes. The brain can be seen as the active “shell” of a single body. An organism does not pre-exist an environment and does not come equipped with a machine that calculates its adaptation. The organism fits into a determined environment16 and its brain-shell is at the interface of this permanent fitting, the traces of which it preserves and replays (which requires a constant activity of the brain – 2% of the human body’s weight but 20% of its total energy consumption). The brain “resists” during this fitting, giving the body a “solidity” that completes that of the passive endoskeleton. The brain would thus be an edge with physical properties, not a digital processing center. It remains to be understood why and how nature has selected this biological structure, of this dimension, to implement these properties.
It is thus from a “physics” of animate matter that we could borrow tomorrow’s metaphors, a “science of organisms” that could inaugurate a new biocompatible technological regime.
1. ↑ Mathias Girel / Journal du CNRS – May 5, 2014 – L’invention la plus dangereuse de l’histoire
2. ↑ Robert Epstein / Eon – 18 mai 2016 – The empty brain
3. ↑ Audrey Dussutour / CNRS – December 21, 2016 – Le « blob » : capable d’apprendre… et de transmettre ses apprentissages
4. ↑ Wikipédia – Physarum polycephalum
5. ↑ Alex Horton / Washington Post – October 17, 2019 – The ‘blob,’ a brainless mystery organism that can solve mazes, makes its public debut
6. ↑ Pallavi Prasad / The Swaddle – October 21, 2019 – Meet ‘The Blob,’ the Slime Mold That Can Think Without a Brain, Eat Without a Mouth
7. ↑ CNRS national press release – December 21, 2016 – Le « blob » : capable d’apprendre… et de transmettre ses apprentissages
8. ↑ Nathalie Mayer / Futura Sciences – April 28, 2019 – Le blob mémorise sans cerveau en absorbant des substances
9. ↑ The BRAIN Initiative
10. ↑ Matthew Cobb / The Guardian – February 27, 2020 – Why your brain is not a computer
11. ↑ The BRAIN Initiative – June 5, 2014 – BRAIN 2025, A scientific vision
12. ↑ Veronique Greenwood / Quanta Magazine – June 4, 2020 – Why Sleep Deprivation Kills
13. ↑ Jordana Cepelewicz / Quanta Magazine – July 6, 2020 – How Your Heart Influences What You Perceive and Fear
14. ↑ René Thom – 1988 – Esquisse d’une sémiophysique
15. ↑ Bernard Andrieu / Dans Revue internationale de philosophie 2002/4 (n° 222), pages 557 à 582 – Le corps pensant
16. ↑ « L’organisme n’est pas quelque chose qui existe d’abord pour soi et qui s’adapte ensuite. C’est l’inverse : l’organisme s’emboîte chaque fois dans un milieu déterminé » (“The organism is not something that first exists for itself and then adapts. It is the opposite: the organism fits each time in a determined environment“) – Heidegger / nrf – 1929 – Les concepts fondamentaux de la métaphysique, monde, finitude, solitude