Darwinophilia
... Atom=>... Molecule =>… => ... Cell ... =>… Self…
Darwin Inspired Investigations
Darwinophilia
... Atom=>... Molecule =>… => ... Cell ... =>… Self…
Darwin Inspired Investigations
Preface
This essay is a loosely connected set of “sketches for friends” in the spirit of Darwin.
I would like to think that some of these sketches will evolve further.
The intent is to try to understand the core of Darwin’s thought.
What is it that separates him from his contemporaries?
What did he give us that still is with us?
When we read him, it is not important that some of the “modern” lingo is absent; the logical substrate does not change much (if at all).
Darwin is to Biology what Newton is to Physics.
Newton gave us the laws of motion and,
Darwin gave us a new way of reasoning about evolution.
It is this new way of reasoning which will be our main focus.
This essay is a loosely connected set of “sketches for friends” in the spirit of Darwin.
I would like to think that some of these sketches will evolve further.
The intent is to try to understand the core of Darwin’s thought.
What is it that separates him from his contemporaries?
What did he give us that still is with us?
When we read him, it is not important that some of the “modern” lingo is absent; the logical substrate does not change much (if at all).
Darwin is to Biology what Newton is to Physics.
Newton gave us the laws of motion and,
Darwin gave us a new way of reasoning about evolution.
It is this new way of reasoning which will be our main focus.
Ruben Juarez.
St, John’s College, Santa Fe,
Spring Term 2022.
Introduction
State of Science in the XIX Century.
Bye-bye Aristotle…
The Big and Small.
Sizing the monster
What Cells teach us about Higher Organisms
Tractatus Logico-cytologicus
Form, Information, Transformation
In the realm of the senses
From motion to emotion
If it moves….
State of Science in the XIX Century.
Bye-bye Aristotle…
The Big and Small.
Sizing the monster
What Cells teach us about Higher Organisms
Tractatus Logico-cytologicus
Form, Information, Transformation
In the realm of the senses
From motion to emotion
If it moves….
Introduction
In “The descent of man” Darwin presents us with compelling evidence for the existence of various mechanisms underlying the process of evolution.
He does not go deep as to their ultimate nature, but presents fruitful conjectures based on data, observations, and information from other scientists.
When he talks about inheritance, he already implies the existence of what we moderns call genetic material or genome.
He subscribes to the mechanism of pangenesis and is aware of the existence of cells, - cellular theory was being developed for a few years already.
“According to this hypothesis, every unit or cell of the body throws off gemmules or underdeveloped atoms which are transmitted to the offspring of both sexes and are multiplied by self-division. They may remain underdeveloped during the early years of life or during successive generations….“ [1]
The gemmules posited by him were akin to repositories of instructions to reproduce or act upon internal processes and procure interaction with the outside world.
At a higher level, Darwin describes beautiful examples of self-organization and social behavior in ant groups that appear as complex as those in higher animals.
If for a moment we assume that a group of humans can be very proficient with the same tasks that ants so admirably master; we would say that we would have the makings of –at a minimum-, a well-managed society.
Before we jump to conclusions, we need to understand that there is much more than that involved in the game of evolution.
One lesson we can learn from the ants is that of the persistence of good algorithms over time. For these algorithms, to persist, they need to contain instructions for their replication, propagation, protection, adaptation, etc.
Social insects are much older than we are.
Their core behavior persists along the inheritance chain of life on earth.
The term inheritance chain does not refer to any species in particular, but to life in all its forms.
We moderns know that all life as we know it is DNA based.
The fact that we do not know any exceptions, is proof of common origins and common mechanisms.
When reading Darwin’s description of the social behavior of ants, several questions arise about the nature of knowledge, cognition, consciousness and instinct.
Darwin gives us beautiful examples of instinctive behaviors in many species, but the nature of instinct is left out of the discussion,
It was only in 1859, In the “ The Origin of Species” that the term became better defined even as the science to answer foundational questions was still in its early stages of development.
Some of those questions are:
How does instinct originate?
Where is it stored?
How is it stored?
How is it transmitted?
How is it retrieved and activated?
when?
These questions were not being addressed at the time, because there was not enough data and knowledge to treat them other than in a general and -and somewhat- vague form. This treatment was not detrimental to a coherent theory of evolution. At the time, those questions were secondary to the most pressing ones about life as a whole.
It was the realization that living organisms are complex dynamic systems that somehow needs to be explained in terms of their embodiment and evolution.
To properly frame Darwin’s contributions, we need to survey the state of science at the time of his writings.
What did we know about life sciences? physics? chemistry? physiology?
What was our progress in the understanding of the big and small?
This question is particularly relevant as we will talk about behaviors which persist at all scales.
What where the methods of science?
This question does not come a minute too soon.
Before the nineteenth century, science was maturing by shedding old paradigms and debunking old “systems”.
As chemistry matured, biology became the new frontier.
A cell as a unit of stable and self-regulated behavior consistent with that of higher levels of organization, gives us a perfect place to start thinking in terms of complex systems, and more importantly, at the time of Darwin’s work, cellular theory was taking shape.
It was as if we had the right ingredients and the right mix of scientists to produce modern biology.
[1] Descent of Man, P.264, l 12. Penguin Classics
In “The descent of man” Darwin presents us with compelling evidence for the existence of various mechanisms underlying the process of evolution.
He does not go deep as to their ultimate nature, but presents fruitful conjectures based on data, observations, and information from other scientists.
When he talks about inheritance, he already implies the existence of what we moderns call genetic material or genome.
He subscribes to the mechanism of pangenesis and is aware of the existence of cells, - cellular theory was being developed for a few years already.
“According to this hypothesis, every unit or cell of the body throws off gemmules or underdeveloped atoms which are transmitted to the offspring of both sexes and are multiplied by self-division. They may remain underdeveloped during the early years of life or during successive generations….“ [1]
The gemmules posited by him were akin to repositories of instructions to reproduce or act upon internal processes and procure interaction with the outside world.
At a higher level, Darwin describes beautiful examples of self-organization and social behavior in ant groups that appear as complex as those in higher animals.
If for a moment we assume that a group of humans can be very proficient with the same tasks that ants so admirably master; we would say that we would have the makings of –at a minimum-, a well-managed society.
Before we jump to conclusions, we need to understand that there is much more than that involved in the game of evolution.
One lesson we can learn from the ants is that of the persistence of good algorithms over time. For these algorithms, to persist, they need to contain instructions for their replication, propagation, protection, adaptation, etc.
Social insects are much older than we are.
Their core behavior persists along the inheritance chain of life on earth.
The term inheritance chain does not refer to any species in particular, but to life in all its forms.
We moderns know that all life as we know it is DNA based.
The fact that we do not know any exceptions, is proof of common origins and common mechanisms.
When reading Darwin’s description of the social behavior of ants, several questions arise about the nature of knowledge, cognition, consciousness and instinct.
Darwin gives us beautiful examples of instinctive behaviors in many species, but the nature of instinct is left out of the discussion,
It was only in 1859, In the “ The Origin of Species” that the term became better defined even as the science to answer foundational questions was still in its early stages of development.
Some of those questions are:
How does instinct originate?
Where is it stored?
How is it stored?
How is it transmitted?
How is it retrieved and activated?
when?
These questions were not being addressed at the time, because there was not enough data and knowledge to treat them other than in a general and -and somewhat- vague form. This treatment was not detrimental to a coherent theory of evolution. At the time, those questions were secondary to the most pressing ones about life as a whole.
It was the realization that living organisms are complex dynamic systems that somehow needs to be explained in terms of their embodiment and evolution.
To properly frame Darwin’s contributions, we need to survey the state of science at the time of his writings.
What did we know about life sciences? physics? chemistry? physiology?
What was our progress in the understanding of the big and small?
This question is particularly relevant as we will talk about behaviors which persist at all scales.
What where the methods of science?
This question does not come a minute too soon.
Before the nineteenth century, science was maturing by shedding old paradigms and debunking old “systems”.
As chemistry matured, biology became the new frontier.
A cell as a unit of stable and self-regulated behavior consistent with that of higher levels of organization, gives us a perfect place to start thinking in terms of complex systems, and more importantly, at the time of Darwin’s work, cellular theory was taking shape.
It was as if we had the right ingredients and the right mix of scientists to produce modern biology.
[1] Descent of Man, P.264, l 12. Penguin Classics
State of science in the XIX century
Biology
Darwin wrote Origin of Species in 1859.
In it he acknowledges the evolution of ideas from Lamarck, Wallace, and many other scientists.
In 1809 Lamarck posited the first coherent theory of evolution.
However, imperfect it was, it fueled a line of enquiry -Epigenetics- which continues to this day. The poor reception of this aspect of Lamarck’s work may have resulted from his allegiance to alchemy even as Lavoisier and others were making solid advances in the nascent field of chemistry.
He also posited that lower organisms resulted from spontaneous generation.[1]
Chemistry was being born in earnest after the big advances of the eighteenth century...
Dalton, Lavoisier, Avogadro, Priestley, Joseph Black, and many other scientists had separated themselves from Alchemy and produced spectacular advances which could be explained quantitatively as well as in terms of specific properties of all the elements that were being discovered while alchemy was being relegated to the past.
We cannot over-emphasize the importance of the birth of chemistry.
The old model of substance was shattered.
Earth, water air and fire were not elemental anymore.
Bye-bye Aristotle, welcome Mr. Lavoisier and friends.
In the XIX century advances in physics and electromagnetism were added to the mix, and -crucially -, the fabric of vitalism was pierced by the synthesis of organic molecules from non-organic compounds.[2]
The best way to describe the state of chemistry in the XIX century is by quoting D’Arcy Thompson in the opening salvo of his magnum opus “On Growth and Form”[3]
“Of the chemistry of his day and generation, Kant declared that it was a science, but not science – eine Wissenschaft, aber nicht Wissenschaft – for that the criterion of true science, lay in its relation to mathematics”
This line of thought was natural in view of the spectacular developments in mathematics, which incessantly permeated science and technology.
Calculus was king. “Laplace’s demon” was a very compelling metaphor for absolute determinism. Euler, Gauss, Abel, Galois, and many others were advancing all the mathematical disciplines while Babbage was advancing “computing devices” well beyond those of Pascal, Napier and Leibniz.
The dream of a mathematical backbone to all forms of knowledge is old, but the XIX century was bringing it within reach.
In physics, the role of mathematics as the main tool for explanations, was accepted truth.
When Boyle separated chemistry from alchemy in the seventeenth century, it became clear that chemistry was next in line.
Thewas also clear that physics was going to be central to the development of chemistry just as the nascent field of biology was going to need chemistry, physics, and mathematics.
These dependencies were complicated by the fact that progress was uneven by necessity. Some of the explanations needed by biology were not yet available from other fields and had to be given as “black boxes” whose behavior was deemed sufficient for the “greater picture”.
The existence of genetic material was accepted and used as part of the ongoing discussions even as its ultimate nature was going to be elucidated much later.
Boyle’s law[4] launched the study of thermodynamics as it applied to any gas independent of its composition.
As the relationships between volume, temperature and pressure were studied, and resulted in the “laws of thermodynamics”, it was clear that chemistry was connected to them.
New elements were being discovered, the idea of molecules[5] began to emerge along with the notion of quantity of substance and chemical bonds.
Further progress brought stoichiometry[6], analysis, synthesis, electrochemistry[7] and -crucially important- organic synthesis[8].
In 1879 Mendeleyev[9] presented his periodic table establishing a solid foundation on which modern chemistry still rests.
This momentous event happened only two years before Darwin’s “The Descent of Man” was published.
The idea of evolution was in the air and chemistry was not immune to it.
The periodic table[10] offered a vision of atomic evolution. It ordered the elements in groups and, whenever they were absent in the ordering scheme, they were predicted.
[1] Richard W. Burkhardt https://www.britannica.com/biography/Jean-Baptiste-Lamarck
[2] Urea was synthesized by Wohler from non-organic molecules in 1828. https://www.britannica.com/biography/Friedrich-Wohler
[3] D’Arcy Wentworth Thompson. “On Growth and Form” P.1. Dover Publications Inc. First published in 1917 and revised by the author in 1942
[4] https://www.britannica.com/science/Boyles-law
[5] https://www.britannica.com/science/molecule
[6] https://www.britannica.com/science/stoichiometry
[7] https://www.britannica.com/science/electrochemistry
[8] https://www.britannica.com/biography/Friedrich-Wohler
[9] https://www.chemistryworld.com/features/the-father-of-the-periodic-table/3009828.article
[10] https://pubchem.ncbi.nlm.nih.gov/periodic-table/
Biology
Darwin wrote Origin of Species in 1859.
In it he acknowledges the evolution of ideas from Lamarck, Wallace, and many other scientists.
In 1809 Lamarck posited the first coherent theory of evolution.
However, imperfect it was, it fueled a line of enquiry -Epigenetics- which continues to this day. The poor reception of this aspect of Lamarck’s work may have resulted from his allegiance to alchemy even as Lavoisier and others were making solid advances in the nascent field of chemistry.
He also posited that lower organisms resulted from spontaneous generation.[1]
Chemistry was being born in earnest after the big advances of the eighteenth century...
Dalton, Lavoisier, Avogadro, Priestley, Joseph Black, and many other scientists had separated themselves from Alchemy and produced spectacular advances which could be explained quantitatively as well as in terms of specific properties of all the elements that were being discovered while alchemy was being relegated to the past.
We cannot over-emphasize the importance of the birth of chemistry.
The old model of substance was shattered.
Earth, water air and fire were not elemental anymore.
Bye-bye Aristotle, welcome Mr. Lavoisier and friends.
In the XIX century advances in physics and electromagnetism were added to the mix, and -crucially -, the fabric of vitalism was pierced by the synthesis of organic molecules from non-organic compounds.[2]
The best way to describe the state of chemistry in the XIX century is by quoting D’Arcy Thompson in the opening salvo of his magnum opus “On Growth and Form”[3]
“Of the chemistry of his day and generation, Kant declared that it was a science, but not science – eine Wissenschaft, aber nicht Wissenschaft – for that the criterion of true science, lay in its relation to mathematics”
This line of thought was natural in view of the spectacular developments in mathematics, which incessantly permeated science and technology.
Calculus was king. “Laplace’s demon” was a very compelling metaphor for absolute determinism. Euler, Gauss, Abel, Galois, and many others were advancing all the mathematical disciplines while Babbage was advancing “computing devices” well beyond those of Pascal, Napier and Leibniz.
The dream of a mathematical backbone to all forms of knowledge is old, but the XIX century was bringing it within reach.
In physics, the role of mathematics as the main tool for explanations, was accepted truth.
When Boyle separated chemistry from alchemy in the seventeenth century, it became clear that chemistry was next in line.
Thewas also clear that physics was going to be central to the development of chemistry just as the nascent field of biology was going to need chemistry, physics, and mathematics.
These dependencies were complicated by the fact that progress was uneven by necessity. Some of the explanations needed by biology were not yet available from other fields and had to be given as “black boxes” whose behavior was deemed sufficient for the “greater picture”.
The existence of genetic material was accepted and used as part of the ongoing discussions even as its ultimate nature was going to be elucidated much later.
Boyle’s law[4] launched the study of thermodynamics as it applied to any gas independent of its composition.
As the relationships between volume, temperature and pressure were studied, and resulted in the “laws of thermodynamics”, it was clear that chemistry was connected to them.
New elements were being discovered, the idea of molecules[5] began to emerge along with the notion of quantity of substance and chemical bonds.
Further progress brought stoichiometry[6], analysis, synthesis, electrochemistry[7] and -crucially important- organic synthesis[8].
In 1879 Mendeleyev[9] presented his periodic table establishing a solid foundation on which modern chemistry still rests.
This momentous event happened only two years before Darwin’s “The Descent of Man” was published.
The idea of evolution was in the air and chemistry was not immune to it.
The periodic table[10] offered a vision of atomic evolution. It ordered the elements in groups and, whenever they were absent in the ordering scheme, they were predicted.
[1] Richard W. Burkhardt https://www.britannica.com/biography/Jean-Baptiste-Lamarck
[2] Urea was synthesized by Wohler from non-organic molecules in 1828. https://www.britannica.com/biography/Friedrich-Wohler
[3] D’Arcy Wentworth Thompson. “On Growth and Form” P.1. Dover Publications Inc. First published in 1917 and revised by the author in 1942
[4] https://www.britannica.com/science/Boyles-law
[5] https://www.britannica.com/science/molecule
[6] https://www.britannica.com/science/stoichiometry
[7] https://www.britannica.com/science/electrochemistry
[8] https://www.britannica.com/biography/Friedrich-Wohler
[9] https://www.chemistryworld.com/features/the-father-of-the-periodic-table/3009828.article
[10] https://pubchem.ncbi.nlm.nih.gov/periodic-table/
Physiology.
“… Je dis à dessein autopsie physiologique parce qu'il n'y a que celles-là qui soient réellement instructives C'est la disparition des propriétés physiologiques qui explique la mort et non pas les altérations anatomiques.” [1]
"... I say physiological autopsy on purpose because only these are really instructive. It is the disappearance of physiological properties that explains death, not anatomical alterations."
Claude Bernard
The advances in chemistry led to an immediate connection to life.
Physiology as the interface between chemistry and life.
In 1856 Carl F.W Ludwig[2] was the first to keep organs alive in vitro.
A sub-system of a living organism was being isolated for the first time.
This milestone proved the importance of the chemical and physical conditions on an individual organ.
In 1865 Claude Bernard published his book “INTRODUCTION À L'ÉTUDE DE LA MÉDECINE EXPÉRIMENTALE” where we can appreciate his enormous contributions to the field of physiology. As one of the founders of experimental medicine, he made important discoveries. The idea of milieu interieur as the processes that maintain life and regulate growth, was perhaps his most important. This process was later renamed” Homeostasis” by Walter Cannon and is central to the modern study of biology.
Herman von Helmholtz “Described body heat and energy, nerve conduction, and the physiology of the eye. “[3] In doing this, he launches the study of energy relations of an organism, and signal processing.
Darwin was very much aware of the work of Helmholtz as he refers to him several times.
[1] Bernard, Claude. Introduction à l'étude de la médecine expérimentale (p. 155). Kindle Edition.
[2] https://www.britannica.com/biography/Carl-F-W-Ludwig
[3] https://www.britannica.com/summary/Hermann-von-Helmholtz
Microscopy, cell theory.
Microscopy began in the seventeenth century with Leuwenhoek who discovered microorganisms and disproved spontaneous generation. He and Hooke also observed cells and described them. While his invention made him famous, his discoveries did not have an immediate impact in biology because biology as a science did not exist.
It was until 1839 when Schleiden and Schwann[1] posited that plants and animals are made of cells.
Rudolf Virchow in 1858 published his work “Die Cellularpathologie” [2] where we can appreciate in full the state of the art of cellular theory extant at the time of Darwin’s works.
There is nothing in this book that we would not accept today with -in a few cases- , slight revisions of fundamentals and, of course, of extension. He is also attributed to the idea that all cells arise only from pre-existing cells.
Heady stuff! Ripe to be assimilated into evolutionary thinking.
[1] BIOLOGY AND ITS MAKERS WILLIAM A. LOCY . HENRY HOLT AND COMPANY 1908 P.243
[2] The book used as reference is the fourth edition Berlin, 1871.Verlag von August Hirschwald which is available at https://www.gutenberg.org/files/44921/44921-h/44921-h.htm .
Microscopy began in the seventeenth century with Leuwenhoek who discovered microorganisms and disproved spontaneous generation. He and Hooke also observed cells and described them. While his invention made him famous, his discoveries did not have an immediate impact in biology because biology as a science did not exist.
It was until 1839 when Schleiden and Schwann[1] posited that plants and animals are made of cells.
Rudolf Virchow in 1858 published his work “Die Cellularpathologie” [2] where we can appreciate in full the state of the art of cellular theory extant at the time of Darwin’s works.
There is nothing in this book that we would not accept today with -in a few cases- , slight revisions of fundamentals and, of course, of extension. He is also attributed to the idea that all cells arise only from pre-existing cells.
Heady stuff! Ripe to be assimilated into evolutionary thinking.
[1] BIOLOGY AND ITS MAKERS WILLIAM A. LOCY . HENRY HOLT AND COMPANY 1908 P.243
[2] The book used as reference is the fourth edition Berlin, 1871.Verlag von August Hirschwald which is available at https://www.gutenberg.org/files/44921/44921-h/44921-h.htm .
The big and small
“In the theory with which we have to deal, Absolute Ignorance is the artificer; so that we may enunciate as the fundamental principle of the whole system, that, IN ORDER TO MAKE A PERFECT AND BEAUTIFUL MACHINE, IT IS NOT REQUISITE TO KNOW HOW TO MAKE IT. This proposition will be found on careful examination, to express, in condensed form, the essential purport of the Theory, and to express in a few words all Mr. Darwin’s meaning; who, by a strange inversion of reasoning, seems to think Absolute Ignorance fully qualified to take the place of Absolute Wisdom in all the achievements of creative skill. (Beverley 1868)” .
cited by Dennett, Daniel C. From Bacteria to Bach and Back: The Evolution of Minds . W. W. Norton & Company. Kindle Edition.
The study of the big and small is not only a matter of scale, but of complexity.
What have been called “complex instincts” begin to appear early in organisms which are small and, as we shall see, they persist all the way up the evolutionary tree.
In the study of the small, we will take two separate paths for good reasons.
Ants.Once we grant that ants are as good as any insect to study the basic algorithms of animal behavior, we have a comfortable starting point that may lead us to the exploration of human behaviors.
Choosing ants is easy because Darwin provides us with beautiful examples.
“I may, however, briefly specify a few points. Ants certainly communicate information to each other, and several unite for the same work, or for games of play. They recognize their fellow ants after months of absence and feel sympathy for each other. They build great edifices, keep them clean, close the doors in the evening, and post sentries. They make roads as well as tunnels under rivers, and temporary bridges over them, by clinging together. They collect food for the community, and when an object, too large for entrance, is brought to the nest, they enlarge the door, and afterwards build it up again. They store seeds, of which they prevent germination, and which, if damp, are brought up to the surface to dry. They keep aphides and other insects as milch-cows. They go out to battle in regular bands, and freely sacrifice their lives for the common good. They emigrate according to a preconcerted plan. They capture slaves. They move the eggs of their aphides, as well as their own eggs and cocoons, into warm parts of the nest, in order that they may be quickly hatched; and endless similar facts could be given.”[1]
This set of behavior algorithms may be mapped to many human traits including complex social interactions.
Why do ants and humans have some common sets of instructions?
The short version would include optimal decision-making algorithms.
The long version would couple those with action, perception and awareness algorithms progressing into higher complexity.
A very robust description of these algorithms can be found in the essay “Order through Fluctuation:Self-Organization and Social System” [2] by Ilya Prigogyne.
How do they differ in the way up the evolutionary chain?
The long answer will involve the birth of reflective consciousness at some point early up the evolutionary ladder. This point is hard to establish.
Do the ant’s behaviors indicate the presence of some type of consciousness?
I do not think so.
What is it then that causes the type of complex behavior?
The behaviors described by Darwin are all collective behaviors where the individual ants contribute specific actions for the benefit of the group.
In the section “Social Insects” of Prigogine’s essay, he quotes Wilson: “The survival of an individual is practically impossible outside of the group(Wilson 1971)”[3] .Their observed complexity is the outcome of individual ants responding to signals left by other ants. Their collective behavior (and that of the termites) is described in beautiful -and mathematical- detail by Prigogine.[4]
The few hundred thousand neurons of the ant’s brain are sufficient to process signals and to act on their environment. Their stored programs, have instructions to act using what Dennett calls “Competences without comprehension”
“Darwin’s “strange inversion of reasoning” and Turing’s equally revolutionary inversion were aspects of a single discovery: competence without comprehension. Comprehension, far from being a Godlike talent from which all design must flow, is an emergent effect of systems of uncomprehending competence: natural selection on the one hand, and mindless computation on the other.”[5]
The quotation at the epigraph of this section, explains what “Darwin’s strange inversion of reasoning” is.
What Turing’s strange inversion of reasoning is, Dennett summarized with a beautiful take on Beverley’s objection to Darwin’s theory.
“IN ORDER TO BE A PERFECT AND BEAUTIFUL COMPUTING MACHINE, IT IS NOT REQUISITE TO KNOW WHAT ARITHMETIC IS.” Dennett, Daniel C. From Bacteria to Bach and Back: The Evolution of Minds Kindle Edition.
Turing´s strange inversion of reasoning is important because it rests on the same logical premise that it is possible to acquire “competences without comprehension” Chapter four of Dennett’s book gives a full account of these two “strange inversions”.
Is life an instantiation of a universal Turing machine?
Let’s not get there. (Yet)…
[1] Darwin Descent of Man page 173
[2] Essay by Ilya Prigogine in book Evolution and Consciousness. HUMAN SYSTEMS IN TRANSITION. Edited by Erich Jantsch and Conrad Waddington. Addison Wesley Publishing. 1976
[3] Prigogine. Ibidem
[4] Prigogine. Ibidem.
[5] Dennett, Daniel C. From Bacteria to Bach and Back: The Evolution of Minds . location 1317. Kindle Edition. W. W. Norton & Company
“In the theory with which we have to deal, Absolute Ignorance is the artificer; so that we may enunciate as the fundamental principle of the whole system, that, IN ORDER TO MAKE A PERFECT AND BEAUTIFUL MACHINE, IT IS NOT REQUISITE TO KNOW HOW TO MAKE IT. This proposition will be found on careful examination, to express, in condensed form, the essential purport of the Theory, and to express in a few words all Mr. Darwin’s meaning; who, by a strange inversion of reasoning, seems to think Absolute Ignorance fully qualified to take the place of Absolute Wisdom in all the achievements of creative skill. (Beverley 1868)” .
cited by Dennett, Daniel C. From Bacteria to Bach and Back: The Evolution of Minds . W. W. Norton & Company. Kindle Edition.
The study of the big and small is not only a matter of scale, but of complexity.
What have been called “complex instincts” begin to appear early in organisms which are small and, as we shall see, they persist all the way up the evolutionary tree.
In the study of the small, we will take two separate paths for good reasons.
Ants.Once we grant that ants are as good as any insect to study the basic algorithms of animal behavior, we have a comfortable starting point that may lead us to the exploration of human behaviors.
Choosing ants is easy because Darwin provides us with beautiful examples.
“I may, however, briefly specify a few points. Ants certainly communicate information to each other, and several unite for the same work, or for games of play. They recognize their fellow ants after months of absence and feel sympathy for each other. They build great edifices, keep them clean, close the doors in the evening, and post sentries. They make roads as well as tunnels under rivers, and temporary bridges over them, by clinging together. They collect food for the community, and when an object, too large for entrance, is brought to the nest, they enlarge the door, and afterwards build it up again. They store seeds, of which they prevent germination, and which, if damp, are brought up to the surface to dry. They keep aphides and other insects as milch-cows. They go out to battle in regular bands, and freely sacrifice their lives for the common good. They emigrate according to a preconcerted plan. They capture slaves. They move the eggs of their aphides, as well as their own eggs and cocoons, into warm parts of the nest, in order that they may be quickly hatched; and endless similar facts could be given.”[1]
This set of behavior algorithms may be mapped to many human traits including complex social interactions.
Why do ants and humans have some common sets of instructions?
The short version would include optimal decision-making algorithms.
The long version would couple those with action, perception and awareness algorithms progressing into higher complexity.
A very robust description of these algorithms can be found in the essay “Order through Fluctuation:Self-Organization and Social System” [2] by Ilya Prigogyne.
How do they differ in the way up the evolutionary chain?
The long answer will involve the birth of reflective consciousness at some point early up the evolutionary ladder. This point is hard to establish.
Do the ant’s behaviors indicate the presence of some type of consciousness?
I do not think so.
What is it then that causes the type of complex behavior?
The behaviors described by Darwin are all collective behaviors where the individual ants contribute specific actions for the benefit of the group.
In the section “Social Insects” of Prigogine’s essay, he quotes Wilson: “The survival of an individual is practically impossible outside of the group(Wilson 1971)”[3] .Their observed complexity is the outcome of individual ants responding to signals left by other ants. Their collective behavior (and that of the termites) is described in beautiful -and mathematical- detail by Prigogine.[4]
The few hundred thousand neurons of the ant’s brain are sufficient to process signals and to act on their environment. Their stored programs, have instructions to act using what Dennett calls “Competences without comprehension”
“Darwin’s “strange inversion of reasoning” and Turing’s equally revolutionary inversion were aspects of a single discovery: competence without comprehension. Comprehension, far from being a Godlike talent from which all design must flow, is an emergent effect of systems of uncomprehending competence: natural selection on the one hand, and mindless computation on the other.”[5]
The quotation at the epigraph of this section, explains what “Darwin’s strange inversion of reasoning” is.
What Turing’s strange inversion of reasoning is, Dennett summarized with a beautiful take on Beverley’s objection to Darwin’s theory.
“IN ORDER TO BE A PERFECT AND BEAUTIFUL COMPUTING MACHINE, IT IS NOT REQUISITE TO KNOW WHAT ARITHMETIC IS.” Dennett, Daniel C. From Bacteria to Bach and Back: The Evolution of Minds Kindle Edition.
Turing´s strange inversion of reasoning is important because it rests on the same logical premise that it is possible to acquire “competences without comprehension” Chapter four of Dennett’s book gives a full account of these two “strange inversions”.
Is life an instantiation of a universal Turing machine?
Let’s not get there. (Yet)…
[1] Darwin Descent of Man page 173
[2] Essay by Ilya Prigogine in book Evolution and Consciousness. HUMAN SYSTEMS IN TRANSITION. Edited by Erich Jantsch and Conrad Waddington. Addison Wesley Publishing. 1976
[3] Prigogine. Ibidem
[4] Prigogine. Ibidem.
[5] Dennett, Daniel C. From Bacteria to Bach and Back: The Evolution of Minds . location 1317. Kindle Edition. W. W. Norton & Company
Lizards“…The lizard tracked the fly perfectly and finally caught it with its tongue , thrown out at the precise moment . The collicular neurons plotted the moment - to - moment position of the fly and guided the lizard’s muscles, accordingly , eventually dispatching the tongue when the prey was within reach ….”[1]
Antonio Damasio
When a lizard is patiently waiting for a fly at lunchtime and one enters his field of vision, he becomes aware of it and acts in consequence; He lashes out his sticky tongue with precision and swiftness.
The apparition of the colliculi in Damasio’s description, is particularly relevant to our enquiry.
Every brain above the realm of insects is likely to have it as it plays a vital function in the coordination of signals between the outside world and motor reactions.
It is both, a traffic controller and a dispatcher.
It is layered and, its exterior layer processes mostly visual stimuli while the deeper layers process olfactory-gustatory signals as well as tactile, thermal and acoustic.
Let’s stop for a moment and reflect on what we are saying:
Social insects with their limited brain, process simple signals and acts in concert with others to achieve collective tasks All the admirable traits described by Darwin and many others, describe for the most part collective behavior. The actions of the individual ants as we have seen, are much more restricted.
Having said that, we have in them the beginnings of “competences without comprehension” as described before.
Simple decision-making algorithms go a long way.
Obstacle avoidance, distance management, movement control, etc. are all based on the conjunction of stored “signal-detection” mechanisms with a “motor program” honed by eons of use.
The way in which an individual bee keeps its place in the swarm, a starling in a murmuration, a fish in a school, etc. respond to the same simple algorithms.
Instinctual behaviors are made of such algorithms where sensory maps are formed to respond to changing conditions. These maps are tapped by decision-making algorithms which compare them to other maps in memory and activate motor programs.
As the variety of the input increases, so does the complexity of its processing.
The lizard in our story has already evolved a collicular system layered to process the complex signals needed for survival and propagation.
What does the lizard see before she knows that lunch is served?
Maybe a black dot moving in a certain way. That certain way is stored in a layer of the colliculi and when the pattern-matching algorithms confirm that it is a fly within reach, they activate the appropriate motor programs.
The lizard is accountable mostly to herself so, she cannot rely upon the large stores of food of social insects and needs more complex equipment to survive, hence, the layered colliculi where visual, tactile, special, olfactory signals are integrated and processed in milliseconds.
When Darwin talks about size in animals or humans, he usually does so in reference to the advantage that individuals of the same species or some predators gain with size.
In at least one place in the “Descent of Man”, he refers brain size relative to body size. This particular subject was not central in his theory, but it is worth thinking about it in terms of it.
Let’s consider the insects now and let’s compare them with those of the carboniferous era when a dragonfly could have a wingspan of up to 70 cm. and scorpions of that size were also roaming the earth. It has been suggested that such sizes were the result of an atmosphere much richer in oxygen than our present one[2].
Insects have no lungs and receive their oxygen by one or more orifices (spiracles) which collect oxygen from the air and diffuse it inside their bodies by a branching network of tubular channels (trachea) of decreasing size (not too different in shape as our own system of veins and arteries with a fractal distribution of sizes).
The ants have usually one spiracle while cockroaches have many more. So, the richer the oxygen mix is, more oxygen is available to the internals of the animals.
One important fact, is that a bigger insect, does not necessarily need a much bigger brain than its smaller modern counterpart.
The mechanisms of control, and locomotion are essentially the same and only “few” more neurons would be needed to deal with the extra tissue.
We can say the same about our lizard friend whose brain is more complex even as it is functionality may be more or less equal to that of her saurian relatives.
From this we can surmise that -when it comes to brain-, size matters much less than complexity.
In the chapter on information processing, we will get back to this subject, but for now,
Mr. Damasio leaves us with the tantalizing remark:
“Some of the beginnings of mind are probably to be found here , and the beginnings of self might be found here too “
Yes, the humble lizard may be the missing link…
[1] Antonio Damasio. Self comes to Mind. Kindle edition. Chapter 3 - Making Maps and Making Images > Location 1323
[2] https://www.nationalgeographic.com/science/article/110808-ancient-insects-bugs-giants-oxygen-animals-science
Antonio Damasio
When a lizard is patiently waiting for a fly at lunchtime and one enters his field of vision, he becomes aware of it and acts in consequence; He lashes out his sticky tongue with precision and swiftness.
The apparition of the colliculi in Damasio’s description, is particularly relevant to our enquiry.
Every brain above the realm of insects is likely to have it as it plays a vital function in the coordination of signals between the outside world and motor reactions.
It is both, a traffic controller and a dispatcher.
It is layered and, its exterior layer processes mostly visual stimuli while the deeper layers process olfactory-gustatory signals as well as tactile, thermal and acoustic.
Let’s stop for a moment and reflect on what we are saying:
Social insects with their limited brain, process simple signals and acts in concert with others to achieve collective tasks All the admirable traits described by Darwin and many others, describe for the most part collective behavior. The actions of the individual ants as we have seen, are much more restricted.
Having said that, we have in them the beginnings of “competences without comprehension” as described before.
Simple decision-making algorithms go a long way.
Obstacle avoidance, distance management, movement control, etc. are all based on the conjunction of stored “signal-detection” mechanisms with a “motor program” honed by eons of use.
The way in which an individual bee keeps its place in the swarm, a starling in a murmuration, a fish in a school, etc. respond to the same simple algorithms.
Instinctual behaviors are made of such algorithms where sensory maps are formed to respond to changing conditions. These maps are tapped by decision-making algorithms which compare them to other maps in memory and activate motor programs.
As the variety of the input increases, so does the complexity of its processing.
The lizard in our story has already evolved a collicular system layered to process the complex signals needed for survival and propagation.
What does the lizard see before she knows that lunch is served?
Maybe a black dot moving in a certain way. That certain way is stored in a layer of the colliculi and when the pattern-matching algorithms confirm that it is a fly within reach, they activate the appropriate motor programs.
The lizard is accountable mostly to herself so, she cannot rely upon the large stores of food of social insects and needs more complex equipment to survive, hence, the layered colliculi where visual, tactile, special, olfactory signals are integrated and processed in milliseconds.
When Darwin talks about size in animals or humans, he usually does so in reference to the advantage that individuals of the same species or some predators gain with size.
In at least one place in the “Descent of Man”, he refers brain size relative to body size. This particular subject was not central in his theory, but it is worth thinking about it in terms of it.
Let’s consider the insects now and let’s compare them with those of the carboniferous era when a dragonfly could have a wingspan of up to 70 cm. and scorpions of that size were also roaming the earth. It has been suggested that such sizes were the result of an atmosphere much richer in oxygen than our present one[2].
Insects have no lungs and receive their oxygen by one or more orifices (spiracles) which collect oxygen from the air and diffuse it inside their bodies by a branching network of tubular channels (trachea) of decreasing size (not too different in shape as our own system of veins and arteries with a fractal distribution of sizes).
The ants have usually one spiracle while cockroaches have many more. So, the richer the oxygen mix is, more oxygen is available to the internals of the animals.
One important fact, is that a bigger insect, does not necessarily need a much bigger brain than its smaller modern counterpart.
The mechanisms of control, and locomotion are essentially the same and only “few” more neurons would be needed to deal with the extra tissue.
We can say the same about our lizard friend whose brain is more complex even as it is functionality may be more or less equal to that of her saurian relatives.
From this we can surmise that -when it comes to brain-, size matters much less than complexity.
In the chapter on information processing, we will get back to this subject, but for now,
Mr. Damasio leaves us with the tantalizing remark:
“Some of the beginnings of mind are probably to be found here , and the beginnings of self might be found here too “
Yes, the humble lizard may be the missing link…
[1] Antonio Damasio. Self comes to Mind. Kindle edition. Chapter 3 - Making Maps and Making Images > Location 1323
[2] https://www.nationalgeographic.com/science/article/110808-ancient-insects-bugs-giants-oxygen-animals-science
What cells teach us about higher organisms
En ese instante gigantesco, he visto millones de actos deleitables o atroces; ninguno me asombró como el hecho de que todos ocuparan el mismo punto, sin superposición y sin transparencia. Lo que vieron mis ojos fue simultáneo: lo que transcribiré, sucesivo, porque el lenguaje lo es.
El Aleph, Jorge Luis Borges.
In that gigantic instant, I saw millions of delightful or atrocious acts; none astonished me as the fact that they all occupied the same spot, without overlapping and without transparency. What my eyes saw was simultaneous: what I will transcribe, successive, because language is.
El Aleph, Jorge Luis Borges[1].
In the previous part we started our musings in the world of ants and lizards. It made sense to do so because we are talking about evolution.
We cannot start at a molecular level and hope to understand processes which are more complex at a biological level. One of the reasons is that we are aiming to understand emerging qualities of less complex processes and structures.
Life is one of those emerging qualities resulting from dynamic meta-stable molecular processes which became capable of replication and evolution.
As we talked about ants and lizards, we did it without thinking about how is it that they are alive. We did not question their underlying structures. They were just there.
This is a good thing because starting from the beginning, would make it harder for us to see what we are talking about. If we descend a few levels in the organization of life, we can gain new insights.
The cell is the best place to start. All organisms are made of cells.
Cell theory was a very mature science around Darwin’s time, and it was solid enough to have survived intact in its foundations which have not buckled under the weight of new knowledge.
To guide our discussion, I wrote a little “history” of the cell in the form of a Tractatus Logico-Cytologicus[2] (Appendix 1) A casual traversal of it is all we need to appreciate the evolution of cells and their increasing complexity. At one point, we begin to instantiate “in silico” some properties of the nerve cells. The “final” form of this “tractatus” would reveal many more stages of evolution.
The point where we instantiate “in silico” what nature does “in the flesh” marks the place where Darwin meets Turing.
Before we get there, we need to appreciate the unfolding of complexity from the bottom-up.
The bottom-up approach by definition excludes a “master plan” or special creation.
Seminal work on Complex Adaptive Systems (CAS) was made by John H. Holland whose book “Adaptation in Natural and Artificial Systems” “Presented the genetic algorithm as an abstraction of biological evolution and gave a theoretical framework for adaptation under the GA” [3] where -again- Darwin meets Turing.
Other creatures worth noting are the CA’s (Cellular Automaton). They were originally conceived by Stanislav Ulam and John von Neumann and were investigated by a number of other scientists. In recent times, they have been explored by Stephen Wolfram[4] who pointed out the fact that even as they follow very simple -bottom up- rules of production, they are not necessarily related to the mechanisms of natural selection. In chapter eight of his book “A new Kind of Science”, in the section “Fundamental issues in Biology” [5] Mr. Wolfram proceeds to explain how very simple production rules in CA’s, will eventually lead to complexity.
This discovery is very important because provides new explanations for the complexity found in biology Could CA’s one day help us understand the nature of instinct? we do not know.
For now, let´s take a look at the simplest cells.
Prokaryotes are everywhere from times immemorial. They are the most abundant life form on earth. They are also the simplest unicellular organisms. With a single circular strand of DNA in its nucleole they reproduce asexually. Bacteria and Archea are the two types of prokaryotes. Their nucleole floats freely in the cytoplasm as opposed to the DNA in eucaryotes which is membrane bound.
Both type of cells is contained within a membrane which separates them from the outside and holds the cytoplasm and other cellular structures. Both types of cells contain ribosomes which are protein factories. Prokaryotes are ecological agents as they help conditioning soil and are symbionts with all life forms. Eukaryotes are the cells of plants, fungi, animals and unicellular organisms.
Eukaryotes do have organelles to deal with their increased complexity. Many of those organelles have DNA directing their functioning. Mitochondria have prokaryote- type genetic material which may indicate endosymbiotic origin. This is a major step in cellular evolution.
Without going too far into the details of the organization of cells, we can appreciate complex behaviors informed by genetic material.
When we talked about cellular automata, we mentioned that simple rules generate complexity.
If we think of chemical bonds happening under a range of physical conditions, we can have these types of rules and atoms and molecules acting as cellular automata forming complexity in a richer-by-the-day primeval soup. chemical affinities may be the oldest tropisms, but… wait, the term tropism already implies types of movement associated with life….
As we have discussed, cellular automata do not necessarily conform to the principles of natural selection, but that does not exclude them from being a foundational algorithm for evolution. It would be at the very least, good to form a primeval soup and to guide synthesis of increasingly complex molecules.
Once these molecules began replicating, the pace of complexification increased in geometric proportion.
Viruses were at the mercy of the composition of the soup they floated in first, and eventually the cytoplasm of cells became that soup. When cells were formed, it was the membrane that kept the soup (cytoplasm) inside for the DNA to instantiate its algorithms. The cytoplasm contains building blocks and water imported from outside the membrane via osmosis or capillary diffusion. Those building blocks are metabolized by the mitochondria to produce ATP and by the ribosomes to produce proteins.
As the cells evolve more complexity, we can appreciate the development of the milieu interieur in great detail. The findings are not surprising. The milieu interieur of a cell is not very different in functionality from that of higher organisms in their core functions.
At this point it is clear that we can continue to discuss the cells for more clues to our understanding of evolution but let´s have a few remarks before we move onto the next chapter in our initial tour.
We are describing the evolution of cells from primeval soup all the way up to instantiations in silico of some of the algorithms of evolution. This description is always incomplete just as with every tic of a clock, we can generate more Cantor´s dust. The tractatus logico-cytologicus is condemned to have gaps at the same time that, at any state of incompleteness, we can derive new insights by its exploration.
When Darwin meets Turing, it happens first at the behavioral level. The artificial neuron gives raise to the neural networks which in turn beget perceptrons and other machines.
Cellular automata, show us that the bottom-up approach is a realistic path of evolution at the most fundamental level.
At the highest levels of complexity, the perceptron shows that patterns can be stored and processed using random connectivity oriented by feedback and feedforward mechanisms. The discovery of mechanisms which can deal with immensely large number of connections for pattern recognition and motor programs action, is crucial to biology.
The modest ant already has several hundred thousand neurons and, those alone, could not have been properly treated without the perceptron model.
The un-initiated, may profit from a cursory look at entry 5.5 in the tractatus.
[1] El Aleph. By Jorge Luis Borges. Obras completes. P.625. EMECÉ.
[2] Apologies to Mr. Wittgenstein for my shameless poaching of his title and his ordering principle.
[3] AN INTRODUCTION TO GENETIC ALGORITHMS. MELANIE MITCHEL MIT Press 1996.
[4] Stephen Wolfram. “A NEW KIND OF SCIENCE” Wolfram Media Inc. 2002.
[5] Ibidem. P. 383
En ese instante gigantesco, he visto millones de actos deleitables o atroces; ninguno me asombró como el hecho de que todos ocuparan el mismo punto, sin superposición y sin transparencia. Lo que vieron mis ojos fue simultáneo: lo que transcribiré, sucesivo, porque el lenguaje lo es.
El Aleph, Jorge Luis Borges.
In that gigantic instant, I saw millions of delightful or atrocious acts; none astonished me as the fact that they all occupied the same spot, without overlapping and without transparency. What my eyes saw was simultaneous: what I will transcribe, successive, because language is.
El Aleph, Jorge Luis Borges[1].
In the previous part we started our musings in the world of ants and lizards. It made sense to do so because we are talking about evolution.
We cannot start at a molecular level and hope to understand processes which are more complex at a biological level. One of the reasons is that we are aiming to understand emerging qualities of less complex processes and structures.
Life is one of those emerging qualities resulting from dynamic meta-stable molecular processes which became capable of replication and evolution.
As we talked about ants and lizards, we did it without thinking about how is it that they are alive. We did not question their underlying structures. They were just there.
This is a good thing because starting from the beginning, would make it harder for us to see what we are talking about. If we descend a few levels in the organization of life, we can gain new insights.
The cell is the best place to start. All organisms are made of cells.
Cell theory was a very mature science around Darwin’s time, and it was solid enough to have survived intact in its foundations which have not buckled under the weight of new knowledge.
To guide our discussion, I wrote a little “history” of the cell in the form of a Tractatus Logico-Cytologicus[2] (Appendix 1) A casual traversal of it is all we need to appreciate the evolution of cells and their increasing complexity. At one point, we begin to instantiate “in silico” some properties of the nerve cells. The “final” form of this “tractatus” would reveal many more stages of evolution.
The point where we instantiate “in silico” what nature does “in the flesh” marks the place where Darwin meets Turing.
Before we get there, we need to appreciate the unfolding of complexity from the bottom-up.
The bottom-up approach by definition excludes a “master plan” or special creation.
Seminal work on Complex Adaptive Systems (CAS) was made by John H. Holland whose book “Adaptation in Natural and Artificial Systems” “Presented the genetic algorithm as an abstraction of biological evolution and gave a theoretical framework for adaptation under the GA” [3] where -again- Darwin meets Turing.
Other creatures worth noting are the CA’s (Cellular Automaton). They were originally conceived by Stanislav Ulam and John von Neumann and were investigated by a number of other scientists. In recent times, they have been explored by Stephen Wolfram[4] who pointed out the fact that even as they follow very simple -bottom up- rules of production, they are not necessarily related to the mechanisms of natural selection. In chapter eight of his book “A new Kind of Science”, in the section “Fundamental issues in Biology” [5] Mr. Wolfram proceeds to explain how very simple production rules in CA’s, will eventually lead to complexity.
This discovery is very important because provides new explanations for the complexity found in biology Could CA’s one day help us understand the nature of instinct? we do not know.
For now, let´s take a look at the simplest cells.
Prokaryotes are everywhere from times immemorial. They are the most abundant life form on earth. They are also the simplest unicellular organisms. With a single circular strand of DNA in its nucleole they reproduce asexually. Bacteria and Archea are the two types of prokaryotes. Their nucleole floats freely in the cytoplasm as opposed to the DNA in eucaryotes which is membrane bound.
Both type of cells is contained within a membrane which separates them from the outside and holds the cytoplasm and other cellular structures. Both types of cells contain ribosomes which are protein factories. Prokaryotes are ecological agents as they help conditioning soil and are symbionts with all life forms. Eukaryotes are the cells of plants, fungi, animals and unicellular organisms.
Eukaryotes do have organelles to deal with their increased complexity. Many of those organelles have DNA directing their functioning. Mitochondria have prokaryote- type genetic material which may indicate endosymbiotic origin. This is a major step in cellular evolution.
Without going too far into the details of the organization of cells, we can appreciate complex behaviors informed by genetic material.
When we talked about cellular automata, we mentioned that simple rules generate complexity.
If we think of chemical bonds happening under a range of physical conditions, we can have these types of rules and atoms and molecules acting as cellular automata forming complexity in a richer-by-the-day primeval soup. chemical affinities may be the oldest tropisms, but… wait, the term tropism already implies types of movement associated with life….
As we have discussed, cellular automata do not necessarily conform to the principles of natural selection, but that does not exclude them from being a foundational algorithm for evolution. It would be at the very least, good to form a primeval soup and to guide synthesis of increasingly complex molecules.
Once these molecules began replicating, the pace of complexification increased in geometric proportion.
Viruses were at the mercy of the composition of the soup they floated in first, and eventually the cytoplasm of cells became that soup. When cells were formed, it was the membrane that kept the soup (cytoplasm) inside for the DNA to instantiate its algorithms. The cytoplasm contains building blocks and water imported from outside the membrane via osmosis or capillary diffusion. Those building blocks are metabolized by the mitochondria to produce ATP and by the ribosomes to produce proteins.
As the cells evolve more complexity, we can appreciate the development of the milieu interieur in great detail. The findings are not surprising. The milieu interieur of a cell is not very different in functionality from that of higher organisms in their core functions.
At this point it is clear that we can continue to discuss the cells for more clues to our understanding of evolution but let´s have a few remarks before we move onto the next chapter in our initial tour.
We are describing the evolution of cells from primeval soup all the way up to instantiations in silico of some of the algorithms of evolution. This description is always incomplete just as with every tic of a clock, we can generate more Cantor´s dust. The tractatus logico-cytologicus is condemned to have gaps at the same time that, at any state of incompleteness, we can derive new insights by its exploration.
When Darwin meets Turing, it happens first at the behavioral level. The artificial neuron gives raise to the neural networks which in turn beget perceptrons and other machines.
Cellular automata, show us that the bottom-up approach is a realistic path of evolution at the most fundamental level.
At the highest levels of complexity, the perceptron shows that patterns can be stored and processed using random connectivity oriented by feedback and feedforward mechanisms. The discovery of mechanisms which can deal with immensely large number of connections for pattern recognition and motor programs action, is crucial to biology.
The modest ant already has several hundred thousand neurons and, those alone, could not have been properly treated without the perceptron model.
The un-initiated, may profit from a cursory look at entry 5.5 in the tractatus.
[1] El Aleph. By Jorge Luis Borges. Obras completes. P.625. EMECÉ.
[2] Apologies to Mr. Wittgenstein for my shameless poaching of his title and his ordering principle.
[3] AN INTRODUCTION TO GENETIC ALGORITHMS. MELANIE MITCHEL MIT Press 1996.
[4] Stephen Wolfram. “A NEW KIND OF SCIENCE” Wolfram Media Inc. 2002.
[5] Ibidem. P. 383
Form, information, transformation
“( information). C'est, à côté de l'espace, du temps et du mouvement, une autre forme fondamentale de l'existence de la matière — c'est la qualité de l'évolution,
. “ Jiri Zeman.[1]
"(information). It is next to space, time and movement, another fundamental form of the existence of matter: it is the quality of evolution.”.
Jiri Zeman.
Form, information and transformation are central to Biology.
Form begins at the elementary particle level.
When a molecule is formed, it is formed by bonds at certain angles which are determined by their atomic structure.
Form not only as shape, but also as result of an informational process.
The word information comes from Latin Informare. “To put something into a form, or aspect, to form, to create, but also to represent, create an idea or a notion... [2].”
In the epigraph of this section, Jiri Zeman describes Information as a quality of evolution.
The genotype contains information which is expressed in the phenotype as well as information to guide the milieu interieur.
Much of the information processing happens at the nervous system in a complex web of processing involving sensory organs, effector organs, muscles, internal data stores, chemical processes, etc.
Let’s return to our lizard friend to visualize basic information processing.
[1] “Cahiers de Royaumont. Le concept d’information dans la science contemporaine.” Les éditions de minuit/gauthier-villars. París. P 285 Jiri Zeman
[2] “Le mot latin informare, dont est surgi le mot l'information, signifie mettre en forme, donner une forme ou un aspect, former, créer, mais aussi représenter, présenter, créer
une idée ou une notion. “ Ibidem Jiri Zeman
“( information). C'est, à côté de l'espace, du temps et du mouvement, une autre forme fondamentale de l'existence de la matière — c'est la qualité de l'évolution,
. “ Jiri Zeman.[1]
"(information). It is next to space, time and movement, another fundamental form of the existence of matter: it is the quality of evolution.”.
Jiri Zeman.
Form, information and transformation are central to Biology.
Form begins at the elementary particle level.
When a molecule is formed, it is formed by bonds at certain angles which are determined by their atomic structure.
Form not only as shape, but also as result of an informational process.
The word information comes from Latin Informare. “To put something into a form, or aspect, to form, to create, but also to represent, create an idea or a notion... [2].”
In the epigraph of this section, Jiri Zeman describes Information as a quality of evolution.
The genotype contains information which is expressed in the phenotype as well as information to guide the milieu interieur.
Much of the information processing happens at the nervous system in a complex web of processing involving sensory organs, effector organs, muscles, internal data stores, chemical processes, etc.
Let’s return to our lizard friend to visualize basic information processing.
[1] “Cahiers de Royaumont. Le concept d’information dans la science contemporaine.” Les éditions de minuit/gauthier-villars. París. P 285 Jiri Zeman
[2] “Le mot latin informare, dont est surgi le mot l'information, signifie mettre en forme, donner une forme ou un aspect, former, créer, mais aussi représenter, présenter, créer
une idée ou une notion. “ Ibidem Jiri Zeman
Perception, Signalization.
Our lizard is endowed with sensory organs to perceive light, movement, taste, sound, etc.
The sensory organs transduce signals into electrical or chemical patterns.
Invariant Frames, Long Term Store, Motor Program,
Unconscious Reflex, Unconscious Processes and more
Lower part of a model by Helmar Frank. Page 193
Kybernetische Grundlagen der Pädagogik. Urban-Taschenbücher, Kohlhammer
The signals received by the sensory organs of our lizard are optical, auditory, olfactory, thermal, …
This model is for human information processing, but by trimming the input/output is applicable to our green friend.
Before we get to lunch time, let’s consider our capabilities.
There are basic mechanisms for avoidance or attraction.
At a basic level, avoidance of pain or seeking nourishment can be reduced to a simple reflex where no reflective processes are involved.
In the case of immediate and present danger like stepping on a coal, the thermal sensors inform the avoidance mechanisms to act immediately. No time for reflexional cycles.
Perceived danger has a more complex mechanism.
The fact that we use the word perceived, implies that there has been some processing made before decisions are taken.
Patterns of diverse signals form maps which are matched with maps in deep memory as invariant frames.
The optical system probably sees only a dot moving in a certain way while the auditory system identifies the buzzing.
The optical and acoustical patterns are transmitted to the colliculi for map-matching and dispatching of instructions to the motor programs.
A bright light triggers avoidance mechanisms such as closing of the eyelids and in many cases, tight contractions of the muscles around the eye. Of all those actions, few trigger immediate reactions invoking cellular-level actions, but most involve local-system actions. The closing of the eyelids needs not to be processed beyond the immediate sphere of action of the system involved.
Let’s stop for a moment to process what we just said.
Before the fly enters the picture, there are many actions which are performed by pure reflex with no intervention of any conscious processes.
They are processed locally.
This later assertion implies a minimal unit of information processing at the Intercellular level.
In the Tractatus Logico-cytologicus(TLC) the artificial neuron appears related to the biological one.
This relatedness is limited to connectivity patterns and signal processing, but it is powerful enough to be stoking the fires of machine learning to the present day.
We can see that at the level of perception, we have the so called “Invariant Frames” connected to long term storage at the same time that they are available to the Motor Program in order to act upon the environment.
Invariant frames are those information maps that do not need much additional data to be part of a larger frame. Their existence, simplify the processing of signals.
The lizard patiently waits in the grass not too far from a source of flies identified by smell of location, buzzing sounds, sun/shade patterns, etc. combinations of those are stored as invariant frames because buzzing, olfactory, … signals come only within certain ranges and combinations.
The invariant frames by being processed at once, allow for focus on other stimuli (the fly).
The other aspect of invariant frames is that they inform the motor programs to prepare and act.
These motor programs have evolved from time immemorial in concert with the sensory programs. Their wiring and the action-patterns have co-evolved plastic to their environment.
From the example given above, we can easily surmise that.
The sensory organs are not passive receivers of data any more than the brain would be a mere data storage unit.
Evolution is an active process.
It is in this basic level where one day, we may locate the beginning of the self…
Our lizard is endowed with sensory organs to perceive light, movement, taste, sound, etc.
The sensory organs transduce signals into electrical or chemical patterns.
Invariant Frames, Long Term Store, Motor Program,
Unconscious Reflex, Unconscious Processes and more
Lower part of a model by Helmar Frank. Page 193
Kybernetische Grundlagen der Pädagogik. Urban-Taschenbücher, Kohlhammer
The signals received by the sensory organs of our lizard are optical, auditory, olfactory, thermal, …
This model is for human information processing, but by trimming the input/output is applicable to our green friend.
Before we get to lunch time, let’s consider our capabilities.
There are basic mechanisms for avoidance or attraction.
At a basic level, avoidance of pain or seeking nourishment can be reduced to a simple reflex where no reflective processes are involved.
In the case of immediate and present danger like stepping on a coal, the thermal sensors inform the avoidance mechanisms to act immediately. No time for reflexional cycles.
Perceived danger has a more complex mechanism.
The fact that we use the word perceived, implies that there has been some processing made before decisions are taken.
Patterns of diverse signals form maps which are matched with maps in deep memory as invariant frames.
The optical system probably sees only a dot moving in a certain way while the auditory system identifies the buzzing.
The optical and acoustical patterns are transmitted to the colliculi for map-matching and dispatching of instructions to the motor programs.
A bright light triggers avoidance mechanisms such as closing of the eyelids and in many cases, tight contractions of the muscles around the eye. Of all those actions, few trigger immediate reactions invoking cellular-level actions, but most involve local-system actions. The closing of the eyelids needs not to be processed beyond the immediate sphere of action of the system involved.
Let’s stop for a moment to process what we just said.
Before the fly enters the picture, there are many actions which are performed by pure reflex with no intervention of any conscious processes.
They are processed locally.
This later assertion implies a minimal unit of information processing at the Intercellular level.
In the Tractatus Logico-cytologicus(TLC) the artificial neuron appears related to the biological one.
This relatedness is limited to connectivity patterns and signal processing, but it is powerful enough to be stoking the fires of machine learning to the present day.
We can see that at the level of perception, we have the so called “Invariant Frames” connected to long term storage at the same time that they are available to the Motor Program in order to act upon the environment.
Invariant frames are those information maps that do not need much additional data to be part of a larger frame. Their existence, simplify the processing of signals.
The lizard patiently waits in the grass not too far from a source of flies identified by smell of location, buzzing sounds, sun/shade patterns, etc. combinations of those are stored as invariant frames because buzzing, olfactory, … signals come only within certain ranges and combinations.
The invariant frames by being processed at once, allow for focus on other stimuli (the fly).
The other aspect of invariant frames is that they inform the motor programs to prepare and act.
These motor programs have evolved from time immemorial in concert with the sensory programs. Their wiring and the action-patterns have co-evolved plastic to their environment.
From the example given above, we can easily surmise that.
The sensory organs are not passive receivers of data any more than the brain would be a mere data storage unit.
Evolution is an active process.
It is in this basic level where one day, we may locate the beginning of the self…
From motion to emotion
What movement is has been described since times immemorial, but at the end of the day, it comes to a vector in space-time.
For something to move, it needs to exist first. This obvious fact is complicated by the fact that the something itself somehow may have resulted from movement of some ancestors.
By ancestor we mean that the entity in question resulted from simpler building blocks.
If we subscribe to the theory that there was some sort of big bang where in the first instants there was only a very intense and fast moving primeval high-energy plasma which eventually cooled down at the same time that more complex material structures were being created, we need to appeal to a complexifying force which accretes elements, molecules, … life.
What movement is has been described since times immemorial, but at the end of the day, it comes to a vector in space-time.
For something to move, it needs to exist first. This obvious fact is complicated by the fact that the something itself somehow may have resulted from movement of some ancestors.
By ancestor we mean that the entity in question resulted from simpler building blocks.
If we subscribe to the theory that there was some sort of big bang where in the first instants there was only a very intense and fast moving primeval high-energy plasma which eventually cooled down at the same time that more complex material structures were being created, we need to appeal to a complexifying force which accretes elements, molecules, … life.
Conclusions (for now)
In this sketches we tried to offer a broad vision about Darwin’s influence in science in general and more important, what his real contribution has been to civilization in general.
To say that he contributed greatly to the idea of evolution in its modern form, would be a fair statement, but that would not compare in importance to his theories.
The idea of “The strange inversion of reasoning” brilliantly described by Dennett, may be his -everlasting- contribution.
This strange inversion of reasoning usurps from the gods the role of “creation”.
The bridge to “the strange inversion of reasoning” by Turing and, the fact that, -as we speak-, evolution is being recreated “in silico” , attests the power of Darwin’s thoughts.
In this paper I used references and models spanning from the immediate present back to Darwin and before.
The model of Helmar Frank is from 1976 and Damasio’s remarks are contemporary. Damasio explains in exquisite detail the processing of information in the brain in his book “Self comes to Mind” ,, his explanations are coherent with Frank’s purely cybernetic model. In both descriptions, evolution is the engine.
In the last (for now) chapter, we did not go beyond the lizard’s brain, but we get the idea that arrival to the whole human brain is not only possible, but within reach…
When we explore the “in silico” section of the tractatus logico-cytologicus and look at the perceptron, we realize that the state of the art of machine learning (pompously called Artificial Intelligence) is using only the most basic algorithms of evolution to produce the great results it already does. To reach human level intelligence will require more work, but it will happen (??).
Another consequence of Darwinian thought is that the logic we instantiate in silico, is now part of our ecosystem.
By turns, we are symbionts, predators and maybe prey to our own creations…
Appendix 1 Tractatus Logico-Cytologicus
This tractatus is to be forever in flux. Whichever path you take, there is always more to explore.
From the “Inorganic” to thriving organisms to organisms in silico.
0,01
Pre-biotic molecules. Amino acids and other molecules formed a “primeval soup” where more complex molecules eventually “learned” to replicate
….
0.02
Viruses are the first “modern” form of life. To reproduce, it needs a host environment. Either a “primeval soup” or a host cell…
……………………..
1.0
The cells of an organism are the totality of the organism.
1.1
They are totality as a whole, but also individually
1.2
As a whole, they constitute the embodiment of a genotype
1.3
Individually, they are the expression of the genotype at a given locus
1.4
Individually, they carry in their nucleus the whole instruction set for the entire organism. The exception are the blood cells.
2.0
A cell is not only a building brick of an organism, but an actor in its evolution
2.1
A cell is a dynamic system in its own right even if it is part of a larger system.
2.11.0
Cells are prokaryotes or eukaryotes
2.11.1
Prokaryotes are smaller and contain linear single DNA strands in a nucleotide
2.11.11
Prokaryotes are the most abundant life form on earth.
2.11.12
……
2.12.0
Archea and Bacteria are prokaryotes
2.12.1
Archea are prokaryotes which are found in many extreme environments. They may be the most resistant forms of life.
2.12.11
…
2.12.2
Bacteria are ecological agents and symbionts, essential to the evolution of higher forms of life.
3.0
Eukaryotes are the cells of complex organisms. From plants to humans
3.0.1
They evolved from prokaryotes and share structural forms.
3.0.11
Their replication is DNA-based
3.0.12
…
3.1
The primary distinction between these two types of organisms is that eukaryotic cells have a membrane-bound nucleus and prokaryotic cells do not. The nucleus is where eukaryotes store their genetic information.
2.3
The membrane is the boundary with other cells or the “outside world”
2.4
A membrane is shaped in accordance with the specialized functions of the cell and may have specialized extensions such as dendrites, axons, cilia, etc.
3.0
An individual cell has its own milieu interieur. If the cell is part of an organism, it interacts with the milieu interieur of the organism, if self-standing (bacteria and other unicellular organisms), the interactions happen with whatever is outside.
Mitochondria are ATP factories and have DNA to instruct its metabolism in concert with the nuclear DNA containing information about the entire organism
The mitochondrial DNA takes care of the cell´s internal energy management while the nuclear DNA “takes notes” and corrects deviations…
4.0
Neurons are cells of the nervous system.
The nervous system is the control and action center of an organism
Neurons interconnect to create networks of memories and actions.
By Egm4313.s12 (Prof. Loc Vu-Quoc) - Own work, CC BY-SA 4.0, ttps://commons.wikimedia.org/w/index.php?curid=72801384
…
5.0
Artificial Neurons. Logical circuits mimicking neural connections.
5.01
“A Logical Calculus of the ideas Immanent in Nervous Activities” by Warren McCulloch and Walter Pitts in 1943, explains it.
5.02
Figure 1. The neuron ci is always marked with the numeral i upon the body of the cell, and the corresponding action is denoted by “N” with is subscript, as in the text: (a) N*(t) .=.N,(t- 1); (b) N,(t).s.N,(t-l)vN,(t-1); (c) N3(t).s.N1(t-1).N2(t-1); (d) N3(t).= N,(t-l).-N,(t-1); (e) N,(t):=:N,(t-l).v.N,(t-3).-N,(t-2); N&).=.N2(t-2).N2(t-1); (f) N4(t):3: --N,(t-l).N,(t-l)vN,(t-l).v.N,(t-1). N,(t-l).N,(t-1) NJt):=: -N,(t-2).N,(t-2)vN,(t-2).v.N,(t-2). N,(t-2).N,(t-2); (g) N,(t).=.NN,(t-2).-N,(t-3); (h) N,(t).=.N,(t-l).N,(t-2); (i) N,(t):=:Nz(t-l).v.N,(t-l).(Ex)t-1 .N,(x).N,(x).
5,03
THE HOMEOSTAT by Ashby, is a physical instantiation of a milieu interieur.
Ross Ashby.
Design for a Brain. Science Paperbacks. Chapman and Hall.
P.102.
5.5
Schematic of a Perceptron
Brains, Machines and Mathematics. P42
Michael A. Arbib
MaGraw Hill.
5.51
The perceptron is a neural network primarily used for pattern recognition. It is an algorithm invented by Rosenblatt, which resembles closely the way actual neural systems work.
One of the most important attributes of this model is the possibility of being able to recognize patterns using random connections between different layers of the perceptron. This is a very important aspect of our understanding because in actual living systems, the number of connections is enormous and the ability of pattern formation/recognition using quasi-random connectivity is crucial. It opens the door to very large-scale transactions which is exactly what life is all about. We can think of the colliculi as multi-layered perceptrons in charge of controlling all the reflex actions oriented by maps stored in the deepest recesses of our memory banks.
Modern perceptrons are multi-layered and have multiple feedback and feedforward loops.
The perceptron presented here has a “retina of sensory units” which reacts to stimuli. The cells receiving light will elicit responses distinct from those which do not. The associator units receive inputs with charges proportional to the sensors activity and send patterns to the response units which in turn activate many processes.
This tractatus is to be forever in flux. Whichever path you take, there is always more to explore.
From the “Inorganic” to thriving organisms to organisms in silico.
0,01
Pre-biotic molecules. Amino acids and other molecules formed a “primeval soup” where more complex molecules eventually “learned” to replicate
….
0.02
Viruses are the first “modern” form of life. To reproduce, it needs a host environment. Either a “primeval soup” or a host cell…
……………………..
1.0
The cells of an organism are the totality of the organism.
1.1
They are totality as a whole, but also individually
1.2
As a whole, they constitute the embodiment of a genotype
1.3
Individually, they are the expression of the genotype at a given locus
1.4
Individually, they carry in their nucleus the whole instruction set for the entire organism. The exception are the blood cells.
2.0
A cell is not only a building brick of an organism, but an actor in its evolution
2.1
A cell is a dynamic system in its own right even if it is part of a larger system.
2.11.0
Cells are prokaryotes or eukaryotes
2.11.1
Prokaryotes are smaller and contain linear single DNA strands in a nucleotide
2.11.11
Prokaryotes are the most abundant life form on earth.
2.11.12
……
2.12.0
Archea and Bacteria are prokaryotes
2.12.1
Archea are prokaryotes which are found in many extreme environments. They may be the most resistant forms of life.
2.12.11
…
2.12.2
Bacteria are ecological agents and symbionts, essential to the evolution of higher forms of life.
3.0
Eukaryotes are the cells of complex organisms. From plants to humans
3.0.1
They evolved from prokaryotes and share structural forms.
3.0.11
Their replication is DNA-based
3.0.12
…
3.1
The primary distinction between these two types of organisms is that eukaryotic cells have a membrane-bound nucleus and prokaryotic cells do not. The nucleus is where eukaryotes store their genetic information.
2.3
The membrane is the boundary with other cells or the “outside world”
2.4
A membrane is shaped in accordance with the specialized functions of the cell and may have specialized extensions such as dendrites, axons, cilia, etc.
3.0
An individual cell has its own milieu interieur. If the cell is part of an organism, it interacts with the milieu interieur of the organism, if self-standing (bacteria and other unicellular organisms), the interactions happen with whatever is outside.
Mitochondria are ATP factories and have DNA to instruct its metabolism in concert with the nuclear DNA containing information about the entire organism
The mitochondrial DNA takes care of the cell´s internal energy management while the nuclear DNA “takes notes” and corrects deviations…
4.0
Neurons are cells of the nervous system.
The nervous system is the control and action center of an organism
Neurons interconnect to create networks of memories and actions.
By Egm4313.s12 (Prof. Loc Vu-Quoc) - Own work, CC BY-SA 4.0, ttps://commons.wikimedia.org/w/index.php?curid=72801384
…
5.0
Artificial Neurons. Logical circuits mimicking neural connections.
5.01
“A Logical Calculus of the ideas Immanent in Nervous Activities” by Warren McCulloch and Walter Pitts in 1943, explains it.
5.02
Figure 1. The neuron ci is always marked with the numeral i upon the body of the cell, and the corresponding action is denoted by “N” with is subscript, as in the text: (a) N*(t) .=.N,(t- 1); (b) N,(t).s.N,(t-l)vN,(t-1); (c) N3(t).s.N1(t-1).N2(t-1); (d) N3(t).= N,(t-l).-N,(t-1); (e) N,(t):=:N,(t-l).v.N,(t-3).-N,(t-2); N&).=.N2(t-2).N2(t-1); (f) N4(t):3: --N,(t-l).N,(t-l)vN,(t-l).v.N,(t-1). N,(t-l).N,(t-1) NJt):=: -N,(t-2).N,(t-2)vN,(t-2).v.N,(t-2). N,(t-2).N,(t-2); (g) N,(t).=.NN,(t-2).-N,(t-3); (h) N,(t).=.N,(t-l).N,(t-2); (i) N,(t):=:Nz(t-l).v.N,(t-l).(Ex)t-1 .N,(x).N,(x).
5,03
THE HOMEOSTAT by Ashby, is a physical instantiation of a milieu interieur.
Ross Ashby.
Design for a Brain. Science Paperbacks. Chapman and Hall.
P.102.
5.5
Schematic of a Perceptron
Brains, Machines and Mathematics. P42
Michael A. Arbib
MaGraw Hill.
5.51
The perceptron is a neural network primarily used for pattern recognition. It is an algorithm invented by Rosenblatt, which resembles closely the way actual neural systems work.
One of the most important attributes of this model is the possibility of being able to recognize patterns using random connections between different layers of the perceptron. This is a very important aspect of our understanding because in actual living systems, the number of connections is enormous and the ability of pattern formation/recognition using quasi-random connectivity is crucial. It opens the door to very large-scale transactions which is exactly what life is all about. We can think of the colliculi as multi-layered perceptrons in charge of controlling all the reflex actions oriented by maps stored in the deepest recesses of our memory banks.
Modern perceptrons are multi-layered and have multiple feedback and feedforward loops.
The perceptron presented here has a “retina of sensory units” which reacts to stimuli. The cells receiving light will elicit responses distinct from those which do not. The associator units receive inputs with charges proportional to the sensors activity and send patterns to the response units which in turn activate many processes.