REDUCTIONISM AND COMPLEXITY:CONTINUUM OR DICHOTOMY? DON MIKULECKY PROFESSOR EMERITUS OF PHYSIOLOGY...
-
Upload
joy-bishop -
Category
Documents
-
view
213 -
download
0
Transcript of REDUCTIONISM AND COMPLEXITY:CONTINUUM OR DICHOTOMY? DON MIKULECKY PROFESSOR EMERITUS OF PHYSIOLOGY...
REDUCTIONISM AND COMPLEXITY:CONTINUUM OR
DICHOTOMY?
DON MIKULECKY
PROFESSOR EMERITUS OF PHYSIOLOGY AND SENIOR FELLOW IN THE CENTER FOR THE STUDY
OF BIOLOGICAL COMPLEXITY-VCU
http://www.people.vcu.edu/~mikuleck/
ONE OF THE MAIN FUNCTIONS OF REDUCTIONISM IN SOCIETY
IF THE SYSTEM IS CORRUPT THEN HOW CAN A PERSON WHO WANTS NOT TO PARTICIPATE IN CORRUPTION BE A PARTICIPANT?
HE MUST REDUCE THE SYSTEM TO UNRELATED ENDEAVORS SO THAT HE CAN ESCAPE RECOGNIZING HIS PARTICIPATION IN THE CORRUPT WHOLE
COMPLEXITY
REQUIRES A CIRCLE OF IDEAS AND METHODS THAT DEPART RADICALLY FROM THOSE TAKEN AS AXIOMATIC FOR THE PAST 300 YEARS
OUR CURRENT SYSTEMS THEORY, INCLUDING ALL THAT IS TAKEN FROM PHYSICS OR PHYSICAL SCIENCE, DEALS EXCLUSIVELY WITH SIMPLE SYSTEMS OR MECHANISMS
COMPLEX AND SIMPLE SYSTEMS ARE DISJOINT CATEGORIES
COMPLEXITY VS COMPLICATION
Von NEUMAN THOUGHT THAT A CRITICAL LEVEL OF “SYSTEM SIZE” WOULD “TRIGGER” THE ONSET OF “COMPLEXITY” (REALLY COMPLICATION)
COMPLEXITY IS MORE A FUNCTION OF SYSTEM QUALITIES RATHER THAN SIZE
COMPLEXITY RESULTS FROM BIFURCATIONS -NOT IN THE DYNAMICS, BUT IN THE DESCRIPTION!
THUS COMPLEX SYSTEMS REQUIRE THAT THEY BE ENCODED INTO MORE THAN ONE FORMAL SYSTEM IN ORDER TO BE MORE COMPLETELY UNDERSTOOD
SOME OF MY GIANTS:
AHARON KATZIR-KATCHALSKY (died in terrorist massacre in Lod Airport 1972)
LEONARDO PEUSNER (alive and well in Argentina)
ROBERT ROSEN (died December 29, 1998)
SOME REFERENCES
FOR A BIBLIOGRAPHY OF ROSEN’S WORK: http://views.vcu.edu/complex/
Pusner, Leonardo: Two books on network thermodynamics
My book: Application of network thermodynamics to problems in biomedical engineering, NYU Press, 1993
Recent work:
New review:The Circle That Never Ends: Can Complexity Be Made Simple? In Complexity in Chemistry, Biology, and Ecology Bonchev, Danail D.; Rouvray, Dennis (Eds.) 2005
New Book: Into the Cool: Energy Flow, Thermodynamics and Life by: Eric D. Schneider and Dorion Sagan, University of Chicago Press, 2005
THE MODELING RELATION: THE ESSENCE OF SCIENCE ALLOWS US TO ASSIGN MEANING TO THE
WORLD AROUND US STANDS FOR OUR THINKING PROCESS CAUSALITY IN THE NATURAL SYSTEM IS DEALT
WITH THROUGH IMPLICATION IN A FORMAL SYSTEM
THERE IS AN ENCODING OF THE NATURAL SYSTEM INTO THE FORMAL SYSTEM AND A DECODING BACK
WHEN IT ALL HANGS TOGETHER WE HAVE A MODEL
THE MODELING RELATION: A MODEL OF HOW WE MAKE MODELS, A SCIENCE OF FRAMING
NATURAL SYSTEM
FORMAL SYSTEM
NATURAL SYSTEM
FORMAL SYSTEM
ENCODING
DECODING
CAUSALEVENT
MANIPULATION
WE HAVE A USEFUL MODEL WHEN
ARE SATISFACTORY WAYS OF “UNDERSTANDING”THE CHANGE IN THE WORLD “OUT THERE”
THE MODELING RELATION: A MODEL OF HOW WE MAKE MODELS
NATURAL SYSTEM
FORMAL SYSTEM
NATURAL SYSTEM
FORMAL SYSTEM
ENCODING
DECODING
CAUSALEVENT
IMPLICATION
MORE ON THE MODELING RELATION
THE FORMAL SYSTEM DOES NOT INCLUDE INFORMATION ABOUT ENCODING AND/OR DECODING
THEREFORE MODELING WILL ALWAYS BE AN ART ONLY IN THE NEWTONIAN PARADIGM DOES THE FORMAL
SYSTEM BECOME THE NATURAL SYSTEM (ENCODING AND DECODING ARE AUTOMATIC) AND ALL THAT IS LEFT TO DO IS TO MEASURE THINGS
WHY IS “OBJECTIVITY” A MYTH? (OR: WHY IS SCIENCE A BELIEF STRUCTURE)
THE FORMAL SYSTEM DOES NOT AND CAN NOT TELL US HOW TO ENCODE AND DECODE. (MODELING IS AN ART!)
THE FORMAL SYSTEM DOES NOT AND CAN NOT TELL US WHEN THE MODEL WORKS, THAT IS A JUDGEMENT CALL EVEN IF OTHER FORMALISMS ARE ENLISTED TO HELP (FOR EXAMPLE: STATISTICS)
MODELS EXIST IN A CONTEXT: A FRAME
WHY WHAT “TRADITIONAL SCIENCE” DID TO THE MODELING RELATION MADE THE PRESENT SITUATION INEVITABLE:
WE ARE TOO AFRAID OF “BELIEFS” (SCEPTICISM IS “IN”)
WE DEVELOPED THE MYTH OF “OBJECTIVITY”
WHAT IS “FRAMING THE QUESTION”?
Based on the work of George Lakoff Cognitive Linguistics Frames are the mental structures that shape
the way we see the world Facts, data, models, etc. only have meaning
in a context Leads us to a scientific application of framing:
Rosen’s theory of complexity
Framing the question
Don’t think of an elephant Impossibility of avoiding the frame In science the dominant frame is reductionism
and the associated mechanical thinking The dominant modern manifestations include
molecular biology and nonlinear dynamics
WHY ARE THERE SO MANY DEFINITIONS OF COMPLEXITY?
SCIENTISTS FOCUS ON THE FORMAL DESCRIPTION RATHER THAN THE REAL WORLD
THE REAL WORLD IS COMPLEX FORMAL SYSTEMS COME IN VARYING
SHADES AND DEGREES OF COMPLICATION
Reductionism has framed complexity theory
Rather than change methods we have the changed names for what we do
The consequences are significant It is impossible for you to believe what is being taught in
this lecture and to then simply add it to your repertoire The reason is that in order to see the world in a new way
you have to step out of the traditional frame and into a new one. Once done, you can never go back. The ability to reframe a question is the basis for change and broadening of ideas.
WHAT “TRADITIONAL SCIENCE” DID TO FRAME THE MODELING RELATION
NATURAL SYSTEM
FORMAL SYSTEM
NATURAL SYSTEM
FORMAL SYSTEM
CAUSALEVENT
MANIPULATION
WHAT “TRADITIONAL SCIENCE” DID TO FRAME THE MODELING RELATION
NATURAL SYSTEM
FORMAL SYSTEM
NATURAL SYSTEM
FORMAL SYSTEM
MANIPULATION
WHY WHAT “TRADITIONAL SCIENCE” DID TO THE MODELING RELATION MADE THE PRESENT SITUATION INEVITABLE:
WE MORE OR LESS FORGOT THAT THERE WAS AN ENCODING AND DECODING
WHY WHAT “TRADITIONAL SCIENCE” DID TO THE MODELING RELATION MADE THE PRESENT SITUATION INEVITABLE: IT
FRAMED THE QUESTIN
THE “REAL WORLD” REQUIRES MORE THAN ONE “FORMAL SYSTEM” TO MODEL IT (THERE IS NO “UNIVERSAL MODEL”)
Syntax vs Semantics
The map is not the territory An equation is just an equation without
interpretation This means we use formalisms in a context This context dependence also exists in nature This is one reason why there can never be a
largest model
Context dependence necessarily introduces circularity
A process happens in a context The process usually changes that context If the context changes the process usually
changes as a result. Living systems are replete with examples
of this
CAN WE GET RID OF SELF-REFERENCE, THAT IS, CIRCULARITY?
IT HAS BEEN TRIED IT FAILED THE ALTERNATIVE IS TO “GO AROUND”
IT – THAT IS TO IGNORE CASES WHERE IT POPS UP
WHAT IF IT IS VERY COMMON?
WHAT IS COMPLEXITY?
TOO MANY DEFINITIONS, SOME CONFLICTING OFTEN INTERCHANGED WITH “COMPLICATED” HAS A REAL MEANING BUT AFTER THE
QUESTION IS REFRAMED THAT MEANING ITSELF IS COMPLEX(THIS IS
SELF-REFERENTIAL: HOW CAN WE DEFINE “COMPLEX” USING “COMPLEX”?)
ROSEN’S CONCEPT FOR COMPLEXITY: A NEW FRAME
Complexity is the property of a real world system that is manifest in the inability of any one formalism being adequate to capture all its properties. It requires that we find distinctly different ways of interacting with systems. Distinctly different in
the sense that when we make successful models, the formal systems needed to describe each distinct aspect are NOT
derivable from each other
The Mexican sierra [fish] has "XVII-15-IX" spines in the dorsal fin. These can easily be counted ... We could, if we wished, describe the sierra thus: "D. XVII-15-IX; A. II-15-IX," but we could see the fish alive and swimming, feel it plunge against the lines, drag it threshing over the rail, and even finally eat it. And there is no reason why either approach should be inaccurate.
Spine-count description need not suffer because another approach is also used. Perhaps, out of the two approaches we thought there might emerge a picture more complete and even more accurate that either alone could produce. -- John Steinbeck, novelist, with Edward Ricketts, marine biologist (1941)
COMPLEX SYSTEMS VS SIMPLE MECHANISMS
COMPLEX NO LARGEST MODEL WHOLE MORE THAN SUM
OF PARTS CAUSAL RELATIONS RICH
AND INTERTWINED GENERIC ANALYTIC SYNTHETIC NON-FRAGMENTABLE NON-COMPUTABLE REAL WORLD
SIMPLE LARGEST MODEL WHOLE IS SUM OF PARTS
CAUSAL RELATIONS DISTINCT
N0N-GENERIC ANALYTIC = SYNTHETIC FRAGMENTABLE COMPUTABLE FORMAL SYSTEM
An Example of Reframing the question to get an answer : The work of Robert Rosen
What is life?
Why is an organism different from a machine?
ROBERT ROSEN: THE WELL POSED QUESTION AND ITS ANSWER-WHY ARE ORGANISMS DIFFERENT FROM MACHINES?
Rosen used relational ideas to apply category theory to living systems
These were called “Metabolism/Repair” systems oo M-R systems
Causal mappings were diagramed a syntax involving category theory mappings and the semantics were used along with this to apply the causal interpretaion
The result was a clear demonstration that the machine and the organism are disjoint in this context
An organism is closed to efficient cause while a machine is not
AMONG OTHER CONCLUSION THAT CAN BE DRAWN FROM THIS ELEGANT STUDY IS ONE THAT MIGHT SEEM SURPRISING
Since machines are causally impoverished, they lead to an infinite regress of causes.
Descartes led us to use the machine metaphor for organisms
In so doing he made a concept of God necessary Today, “Intelligent Design” is based on this
erroneous Cartesian metaphor: The Machine Metaphor
Real orgainisms are closed causually and escape this fallacy
WHAT IS SCIENCE?
HAS MANY DEFINTIONS SOME OF THESE ARE IN CONFLICT SCIENCE IS A BELIEF STRUCTURE SCIENCE OF METHOD VS SCIENCE OF
CONTENT
WHAT ARE SOME OF THE THINGS THAT MAKE “COMPLEXITY THEORY” NECESSARY? (WHAT HAS “TRADITIONAL SCIENCE” FAILED TO EXPLAIN?)
WHY IS THE WHOLE MORE THAN THE SOME OF THE PARTS?
SELF-REFERENCE AND CIRCULARITY THE LIFE/ORGANISM PROBLEM THE MIND/BODY PROBLEM
CIRCULARITY (SELF-REFERENCE) CAUSES PROBLEMS FOR LOGIC AND SCIENCE
I AM A CORINTHIAN ALL CORINTHIANS ARE LIARS OR “THE STATEMENT ON THE OTHER SIDE
IS FALSE”-ON BOTH SIDES
WHY WHAT “TRADITIONAL SCIENCE” DID TO THE QUESTION MADE THE PRESENT SITUATION INEVITABLE:
THE MACHINE METAPHOR TELLS US TO ASK “HOW?”
REAL WORLD COMPLEXITY TELLS US TO ASK “WHY?”
THE FOUR BECAUSES: WHY A HOUSE?
MATERIAL: THE STUFF IT’S MADE OF EFFICIENT: IT NEEDED A BUILDER FORMAL: THERE WAS A BLUEPRINT FINAL: IT HAS A PURPOSE
WHY IS THE WHOLE MORE THAN THE SOME OF THE PARTS?
BECAUSE REDUCING A REAL SYSTEM TO ATOMS AND MOLECULES LOOSES IMPORTANT THINGS THAT MAKE THE SYSTEM WHAT IT IS
BECAUSE THERE IS MORE TO REALITY THAN JUST ATOMS AND MOLECULES (ORGANIZATION, PROCESS, QUALITIES, ETC.)
SELF-REFERENCE AND CIRCULARITY
THE “LAWS” OF NATURE THAT TRADITIONAL SCIENCE TEACHES ARE ARTIFACTS OF A LIMITED MODEL
THE REAL “RULES OF THE GAME” ARE CONTEXT DEPENDENT AND EVER CHANGING- THEY MAKE THE CONTEXT AND THE CONTEXT MAKES THEM (SELF-REFERENCE)
EXAMPLE: THE LIFE/ORGANISM PROBLEM
LIFE IS CONSISTENT WITH THE LAWS OF PHYSICS
PHYSICS DOES NOT PREDICT LIFE LIVING CELLS COME FROM OTHER
LIVING CELLS AN ORGANISM MUST INVOLVE CLOSED
LOOPS OF CAUSALITY LIFE DOES INVOLVE PURPOSE: See Into
the cool
Complexity is inescapable even in reductionism Thermodynamics is an example of how
attempts to remove complexity from reductionist thought can not succeed
The nature of thermodynamic reasoning had resisted this tendency very well and we will look at why this is so
SOME CONSEQUENCES
REDUCTIONISM DID SERIOUS DAMAGE TO THERMODYNAMICS
THERMODYNAMICS IS MORE IN HARMONY WITH TOPOLOGICAL MATHEMATICS THAN IT IS WITH ANALYTICAL MATHEMATICS
THUS TOPOLOGY AND NOT MOLECULAR STATISTICS IS THE FUNDAMENTAL TOOL
EXAMPLES:
CAROTHEODRY’S PROOF OF THE SECOND LAW OF THERMODYNAMICS
THE PROOF OF TELLEGEN’S THEOREM AND THE QUASI-POWER THEOREM
THE PROOF OF “ONSAGER’S” RECIPROCITY THEOREM
THE NATURE OF THERMODYNAMIC REASONING
THERMODYNAMICS IS ABOUT THOSE PROPERTIES OF SYSTEMS WHICH ARE TRUE INDEPENDENT OF MECHANISM
THEREFORE WE CAN NOT LEARN TO DISTINGUISH MECHANISMS BY THERMODYNAMIC REASONING
NETWORKS IN NATURE
NATURE EDITORIAL: VOL 234, DECEMBER 17, 1971, pp380-381
“KATCHALSKY AND HIS COLLEAGUES SHOW, WITH EXAMPLES FROM MEMBRANE SYSTEMS, HOW THE TECHNIQUES DEVELOPED IN ENGINEERING SYSTEMS MIGHT BE APPLIED TO THE EXTREMELY HIGHLY CONNECTED AND INHOMOGENEOUS PATTERNS OF FORCES AND FLUXES WHICH ARE CHARACTERISTIC OF CELL BIOLOGY”
THERMODYNAMICS OF OPEN SYSTEMS THE NATURE OF THERMODYNAMIC
REASONING HOW CAN LIFE FIGHT ENTROPY? WHAT ARE THERMODYNAMIC
NETWORKS?
DISSIPATION AND THE SECOND LAW OF THERMODYNAMICS
ENTROPY MUST INCREASE IN A REAL PROCESS
IN A CLOSED SYSTEM THIS MEANS IT WILL ALWAYS GO TO EQUILIBRIUM
LIVING SYSTEMS ARE CLEARLY “SELF - ORGANIZING SYSTEMS”
HOW DO THEY REMAIN CONSISTENT WITH THIS LAW?
HOW CAN LIFE FIGHT ENTROPY? DISSIPATION AND THE SECOND LAW OF
THERMODYNAMICS PHENOMENOLOGICAL DESCRIPTION OF
A SYTEM COUPLED PROCESSES STATIONARY STATES AWAY FROM
EQUILIBRIUM
PHENOMENOLOGICAL DESCRIPTION OF A SYTEM WE CHOSE TO LOOK AT FLOWS
“THROUGH” A STRUCTURE AND DIFFERENCES “ACROSS” THAT STRUCTURE (DRIVING FORCES)
EXAMPLES ARE DIFFUSION, BULK FLOW, CURRENT FLOW
A GENERALISATION FOR ALL LINEAR FLOW PROCESSES
FLOW = CONDUCTANCE x FORCE
FORCE = RESISTANCE x FLOW
CONDUCTANCE = 1/RESISTANCE
STATIONARY STATES AWAY FROM EQUILIBRIUM
AND THE SECOND LAW OF THERMODYNAMICS
T Ds/dt = J1 X1 +J2 X2 > 0 EITHER TERM CAN BE NEGATIVE IF THE
OTHER IS POSITIVE AND OF GREATER MAGNITUDE
THUS COUPLING BETWEEN SYSTEMS ALLOWS THE GROWTH AND DEVELOPMENT OF SYSTEMS AS LONG AS THEY ARE OPEN!
STATIONARY STATES AWAY FROM EQUILIBRIUM LIKE A CIRCUIT REQUIRE A CONSTANT SOURCE OF
ENERGY SEEM TO BE TIME INDEPENDENT HAS A FLOW GOING THROUGH IT SYSTEM WILL GO TO EQUILIBRIUM IF
ISLOATED
HOMEOSTASIS IS LIKE A STEADY STATE AWAY FROM EQUILIBRIUM
INLET VALVE
OUTLETVALVE
PUMP
ORIFICE CONNECTING TANKS
RESERVOIR
THE RESTING CELL
High potassium Low Sodium Na/K ATPase pump Resting potential about 90 - 120
mV Osmotically balanced (constant
volume)
WHAT ARE THERMODYNAMIC NETWORKS? ELECTRICAL NETWORKS ARE
THERMODYNAMIC MOST DYNAMIC PHYSIOLOGICAL
PROCESSES ARE ANALOGS OF ELECTRICAL PROCESSES
COUPLED PROCESSES HAVE A NATURAL REPRESENTATION AS MULTI-PORT NETWORKS
ELECTRICAL NETWORKS ARE THERMODYNAMIC RESISTANCE IS ENERGY DISSIPATION
(TURNING “GOOD” ENERGY TO HEAT IRREVERSIBLY - LIKE FRICTION)
CAPACITANCE IS ENERGY WHICH IS STORED WITHOUT DISSIPATION
INDUCTANCE IS ANOTHER FORM OF STORAGE
A SUMMARY OF ALL LINEAR FLOW PROCESSES
PROCESS FLOW FORCE CONSTANT
DIFFUSION Jn /t
C=C1-C2 P
BULK FLOW Q p=p1-p2 LP
CURRENT
v/t
IV=V1-V2 G
REACTION KINETICS AND THERMODYNAMIC NETWORKS
START WITH KINETIC DESRIPTION OF DYNAMICS
ENCODE AS A NETWORK TWO POSSIBLE KINDS OF ENCODINGS
AND THE REFERENCE STATE
EXAMPLE: ATP SYNTHESIS IN MITOCHONDRIA
EH+ <--------> [EH+]
E <-------------> [E]
EMEMBRANE
S
P
H+ [H+]
THE SAME KINETIC SYSTEM HAS AT LEAST TWO NETWORK REPRESENTATIONS, BOTH VALID
ONE CAPTURES THE UNCONSTRAINED BEHAVIOR OF THE SYSTEM AND IS GENERALLY NON-LINEAR
THE OTHER IS ONLY VALID WHEN THE SYSTEM IS CONSTRAINED (IN A REFERENCE STATE) AND IS THE USUAL THERMODYNAMIC DESRIPTION OF A COUPLED SYSTEM
SOME PUBLISHED NETWORK MODELS OF PHYSIOLOGICAL SYSTEMS
SR (BRIGGS,FEHER) GLOMERULUS (OKEN) ADIPOCYTE
GLUCOSE TRANSPORT AND METABOLISM (MAY)
FROG SKIN MODEL (HUF)
TOAD BLADDER (MINZ)
KIDNEY (FIDELMAN,WATTLINGTON)
FOLATE METABOLISM (GOLDMAN, WHITE)
ATP SYNTHETASE (CAPLAN, PIETROBON, AZZONE)
CONCLUSIONS
THE REAL WORLD IS COMPLEX THE WORLD OF “SIMPLE MECHANISMS” IS A
SURROGATE WORLD CREATED BY TRADITIONAL SCIENCE
WE ARE AT A CROSSROADS: A NEW WORLDVIEW IS NEEDED
THERE WILL ALWAYS BE RISK ASSOCIATED WITH ATTEMPTS TO PROGRESS
YOUR CRYSTAL BALL MAY BE AS GOOD AS MINE OR BETTER