Transcript Document 7591976

11
Apr
2007
J. A. Scott Kelso
What’s it about?
TCN is about a
scientific grounding of
yin ~ yang relationships
in coordination
dynamics, the science of
coordination, which has
revealed a new principle
of brain function
The MIT Press, 2006
Outline
1. Contraries and the squiggle ( ~ ) of the complementary
nature
From contraries to “Contraria sunt complementa”
2. Complexity science and the complementary nature
3. Coordination Dynamics and the complementary nature
a) Functional information ~ self-organization; “agency”
b) Information: what it is, what it does, where it comes from
c) How is the brain coordinated? Metastability: A “new principle” of
brain coordination; integration ~ segregation
4. What it all means for the way you look at things
a) The natural ~ artificial divide
b) Using your “squiggle sense”
Contraries are ubiquitous
“All things come into being by the
conflict of opposites.”
- Heraclitus (540-480 B.C.)
“Without contraries no progression.
Attraction and repulsion, reason and
energy, love and hate are necessary to
human existence.”
- William Blake (1807-1873)
It is really quite a deep issue,
this inquiry as to why the human mind
has always divided itself in opposition
to others
--J. Krishnamurti (1895-1986)
“Understanding” seems more subtle
alive~dying
awake~asleep
change~persistence
discrete~continuous
nature~nurture
genotype~phenotype
central~peripheral
feedback~feedforward
closed loop~open loop
cognitive~motor
computational~dynamical
time~space
wave~particle
order~chaos
top down~ bottom up
create~annihilate
organism~environment
body~mind
conscious~unconscious
reductionism~holism
self~other
arousal~awareness
health~illness
cure~prevention
individual~collective
integration~segregation
competition~cooperation
.
.
.
‘Contraria Sunt Complementa’
“If you hold opposites
together in your mind, you
will suspend your normal
thinking process and allow
an intelligence beyond
rational thought to create a
new form.”
-Niels Bohr (1885-1962)
?
The ‘Squiggle’ : A Novel Syntax for Complementary Pairs
CP: ca1~ca2
CP = complementary pair
ca = complementary aspect
~ = the “squiggle” (tilde) character
The Squiggle (~) is NOT a bridge:
• It doesn’t stand for a separate piece, link, bridge, or glue
“holding” complementary aspects together or mediating between
them.
• A way to write and think about complementary aspects in a way
that emphasizes their inextricably mutual and dynamic nature.
• The squiggle highlights
complementary pair.
the
complementary
nature
of
a
Can you link the role that Complexity
Science plays in The Complementary
Nature and Coordination Dynamics?
Myron Flickner, April 3, 2007
“I do not see any way to avoid the problem of
coordination and still understand the physical
basis of life” (H. Pattee, 1976)
• Biological coordination as a problem of spatiotemporal
order : how components relate in an ordered fashion to
produce a recognizable function?
• Seen on many levels, in many different kinds of systems.
• Are there general laws or principles that enable
understanding?
• What language/ vocabulary might be used to express
them?
Coordination Dynamics - The Science of Coordination
•A
conceptual
framework
for
understanding how the parts and
processes of living things come
together and break apart
• Describes, explains and predicts
how patterns of behavior form,
adapt, persist and change in
natural systems
• Coordination on multiple levels of
description
• Addresses coordination within a
part of a system, between different
parts of a system, and between
different kinds of systems
•Informationally
coupled
organizing systems
The MIT Press,
1995/97
self-
Emergence and Self-Organization in Nature*
1.
In complex (open) systems, patterns arise spontaneously in a
self-organized fashion.
No ghost in the machine!
Compositional complexity—very many components
Nonlinear interactions
2.
Emerging patterns characterized by a few coordination variables,
also called ‘order parameters’
3.
External or internal ‘control parameters’ lead the system through
different patterns but don’t prescribe them
4.
At so-called critical points, loss of stability  new patterns;
switching between patterns (fluctuations)
5.
The coordination dynamics may have complex solutions,
including transient and irregular behavior
* 1 – 5 provide a foundation for understanding pattern formation and
change in the brain, cognitive and social sciences
See Kelso (1995) Dynamic Patterns: The Self-Organization of Brain
and Behavior, Cambridge, MA: MIT Press
Elementary Images
• “surface complexity arises out of deep
simplicity” (Gell-Mann)
• “surface simplicity arises out of deep
complexity “(coordination dynamics )
How to reconcile?
Material complexity
Pattern dynamics
Pattern forming instabilities
Behavioral complexity !
J. A. Scott Kelso
Dynamic Patterns and Pattern Dynamics
coupling
patterns
mapping
Intrinsic dynamics
of components
Intrinsic dynamics
of components
coupling
patterns
Remarks
• No level is more or less fundamental than any
other.
• Top-down/bottom-up; higher/lower; macro/micro;
etc. distinctions are not relevant.
• Linkage across levels of observation/description
is by virtue of shared dynamics.
Key Theme…..
Mind, brain, body and behavior
share a common underlying
dynamics—equations of motion
for key pattern variables—
patterns of behavior, patterns of
brain activity, patterns of the
mind…
How are CD and Complexity Science Related?
individual~collective, upward~downward,
elements~pattern, parameters~variables, SOD~?
information in~out, negative~positive feedback,
amplifying~dampening, simple~complex, SOD~ID
1. The complementary nature of both CAS and CD is obvious!
2. Besides information, pictures are conceptually identical. What does CD say about information?
Agents:
“Ants in a colony, neurons in neural
networks or particles in physics—all are
described in terms of rules or laws that
determine their behavior in a larger
context…
We can describe the agent as processing
an input to produce an output…The
interactions of a given agent are then
described in terms of the effects of other
agents on its input state”
Holland, 1998
Complementary nature of coordination dynamics
Self-organization: spontaneous formation of pattern
and pattern change at behavioral and brain levels
(relatively autonomous coordination tendencies or
“intrinsic dynamics”)
Functional information: context-, task-specific,
environmental, intentional, attentional, emotional,
learning, memory, social, cultural, etc. On longer
timescales, selection
INFORMATION in Coordination Dynamics
What it is
What it does
Where it comes from
INFORMATION in Coordination Dynamics
What it is
--functional; context-dependent
-- meaningful and specific to coordinative
states
What could be more significant to an
‘organism’ than information that specifies the
coordinative relation between things?
Strategic 6-Step Approach of Coordination
Dynamics
• Step 0: Choose a level of description (subjective but
informed)
• Step 1: Prune away complications, but don't destroy
essentials
• Step 2: Use qualitative change to identify relevant
coordination variables and control parameters. Why?
At critical points, pattern switching occurs
• Step 3: Map coordination variables onto dynamics
(study stability, change, etc.)—Modeling step
• Step 4: Identify individual components and their
dynamics
• Step 5: Establish relation between levels by deriving
coordination dynamics from the nonlinear coupling
among components
Finger metronome
Relative phase
(deg)
Synchronization: on-the-beat coordination
180
0
Time (s)
Kelso et al., 1990
Syncopation: off-the-beat coordination
Finger metronome
Relative phase
(deg)
Phase transition from syncopation to synchronization
180
0
Time (s)
Kelso et al., 1990
metronome
synchronize
flexion
syncopate
1.2
1.4
1.6
1.8
2.0
2.2
2.4
Metronome frequency (Hz)
2.6
2.8
3.0
Functional organization of the brain
is history- and context-dependent
Jantzen, Steinberg & Kelso,
PNAS, 2004
The same physical task is supported
by different interconnected systems
INFORMATION in Coordination Dynamics
What it does
--couples component elements in task-or
function-specific fashion
--constrains and is constrained by selforganizing tendencies ‘intrinsic dynamics’
• Intentional
behavior
constrained
by
underlying pattern dynamics; ’intrinsic; selforganized tendencies
• Intentions parameterize the
stabilizing~destabilizing behavior
dynamics
• Identifying pre-existing pattern dynamics
crucial to understanding what can be
changed intentionally and how
• Information expressed in the same space as
pre-existing pattern dynamics
Self-organizing processes are crucial to
understanding at any level of description. WHY?
Offer a way to find relevant coordination
variables in complex systems and their
coordination dynamics—still a huge problem in
many branches of science
Need to know what can be modified, e.g. by
learning, and how modification occurs
Human Skill Learning
x
J.B. Watson, the father of
behaviorism, in his
prebehaviorist period:
“This gives us a key to what all
animals of a particular species
naturally do—i.e., the acts which they
perform without training, tuition, or
social contact with their fellow
animals. It teaches the psychologist,
too, the way to go about the animal’s
education—i.e., gives him a notion of
the problems which the structural
peculiarities of the animal will permit
him to learn…We must know the
avenues through which we may
appeal to him”
- Harper’s (1909)
Behavioral Studies on Learning
1.
Probe to see if an individual “pre-existing behavioral
repertoire” (preferences/tendencies) exists prior to learning.
2.
Based on pre-existing repertoire, set up task to be learned, so
that it does not coincide with 1)
3.
Probe the behavioral repertoire during and after learning to
see if 1) is changed and how.
4.
Check persistence of behavioral repertoire after a time delay
(e.g. 10 days) to assess memory (viewed as the (meta)stability
of coordination states in the brain)
Learning Dynamics
form learning takes is determined by preexisting tendencies ’intrinsic dynamics’
novel information modifies pre-existing
repertoire through cooperative~competitive
mechanisms
Dual paths to learning: nonequilibrium
phase transitions or shifts in parameter
space depending on the relationship
between new information and intrinsic
dynamics
INFORMATION in Coordination Dynamics
What it does
--couples component elements in task-or
function-specific fashion
How A Complementary
Science Informs a
Theory of Thinking
The Sight of Two Brains Talking
360
180
0
-180
-360
10
EYES CLOSED
20
30
time (s)
EYES OPEN
40
50
EYES
CLOSED
60
Neuromarkers for Social Coordination
t=0-20s
t=20-40s
t=40-60s
Tognoli, Lagarde, DeGuzman & Kelso, PNAS, in press
Episodic transitions to a coupled behavior
Behavioral profile
“Social neglect”
Transient phase-locking
Changes in
frequency and phase
Fully synchronized inphase
Fully synchronized antiphase
Fully synchronized with continuation
Neuromarkers of Social coordination: Phi Rhythm
Neuromarkers of Social coordination: Phi Complex
Instructions: move at a comfortable pace. No explicit instructions as to coordination
with other S.
time
f ERS
frequency
Phi increases when
visually coordinated
action occurs.
Alpha and mu decrease
a ERD
Alpha and mu have
higher power when
there is no visual
coupling.
+
m
ERD
Visual coupling
between Ss
Neuromarkers of Social Coordination: Phi Rhythm
INFORMATION in Coordination Dynamics
Where it comes from
--arises in the metastable régime
The ‘Flights~Perchings’ of Brain Activity
What have we got here?
•Coordinated phase-and frequency locked
states; (functional integration; binding;
dynamic linking)
•No coordination (segregation; independence
of neural populations)
•Transitions (a kind of dynamic decisionmaking)
•Partial coordination (transient tendencies to
couple coexist with tendencies of components
to remain independent; high “neural
complexity”)
How to explain? Understand?
Segregation
Integration
Metastability
Escape
time
Dwell
time
Escape
time
Elementary Law of Coordination
f = Dw - a sinf - 2b sin (2f) + Qxt
SYMMETRY
BREAKING
COUPLING
FLUCTUATIONS
Integration
ff
multistability
2
0
Integration ~ Segregation
ff
f
p/2
p
-2
3p/2
transitions
2p
2
0
f
p/2
p
-2
CEVA
ff
3p/2
2p
metastability
2
0
f
p/2
p
-2
SVI
ASA
3p/2
2p


Varying coupling


0

0
Varying intrinsic
differences

Segregation; uncoupled
Integration; Coupled
2p
relative phase, f
relative phase, f
3p/2
p
p
p/2



2
3


time


time



2
3





time
p
p
p
relative phase, f
3p
relative phase, f
Coordination Variable
2p
3p
2p
2p
p
p


2
3

time






2
3

time
Segregation ~ Integration




Phase evolution as a function of increasing coupling
Fixed asymetry: dw = 2
Increasing coupling: a = 0 – 2.2, in 0.01 steps
Relative phase dynamics:
df
 w  a sin f  b sin 2f   (t )
dt
Phase evolution as a function of
increasing component differences
Fixed coupling: a = 1.95
Frequency difference: dw = 1.5 - 3, in 0.01 steps
Relative phase dynamics:
df
 w  a sin f  b sin 2f   (t )
dt
CD entails and explains “metastability”
“Metastability is an entirely new conception of brain
functioning where the individual parts of the brain
exhibit tendencies to function autonomously at the
same time as they exhibit tendencies for
coordinated activity (Kelso, 1991; 1995; Kaplan,
1998; Friston, 2000)”
Fingelkurts & Fingelkurts, Int. J. Neurosci., 2004
"Poetry is more a threshold than a path,
one constantly approached and
constantly departed from, at which
reader and writer undergo in their
different ways the experience of being at
the same time summoned and released.“
- Seamus Heaney (1939-)
Why is brain metastable?
•Can visit everywhere in the relevant state
space of the coordination dynamics yet still
exhibit preferences~dispositions
•Slightest input can kick it into meaningful
coordination states, thereby creating (and
destroying) information
Brain~mind
stability
loss
transition
brain areas
metastable
stable
stable
dwell
time
phase
Relative
Coordination between
stable
escape
time
metastable régime
creates~destroys
Two CP~CD strategies
The complementary pair
CP~CD says:
• coordination dynamics entails complementary pairs, as
well as their interpretation (this has been found)
• complementary pairs entail coordination dynamics. (this
has been found within coordination dynamics
These realizations and findings immediately lend themselves to
some tangible strategies to employ the philosophy~science
CP~CD:
To study the complementary pairs of coordination dynamics
in order to aid and advance the science of coordination
dynamics.
To use the concepts, methods and tools of coordination
dynamics to understand complementary pairs wherever
they are found.
Current CP of CD Base Set
attraction~repulsion
between~within
bifurcation~path
birth~death
bistability~monostability
bottom-up~top-down
boundary~domain
context-dependent~independent
control parameter~coordination variable
convergence~divergence
cooperation~competition
correlative inference~pop. inference
coupling~components
creation~annihilation of FI
deterministic~stochastic
discrete~continuous
dwell~escape
dynamic patterns~pattern dynamics
emergentism~reductionism
fluctuations~states
FI~SODS
gradual~abrupt
homogeneous~heterogeneous
individual~collective
integration~segregation
information~intrinsic dynamics
learning~memory
linear~nonlinear
local~global
macro~micro
metastability~FI
multifunctionality~func. equivalence
multistability~metastability
organism~environment
part~whole
perception~action
persistence~change
planning~execution
preferences~exploration
qualitative~quantitative
reaction~anticipation
recruitment~annihilation
reduction~construction
SODS~ID
simplicity~complexity
source~sink
space~time
stability~instability
stabilization~destabilization
stable~unstable
states~tendencies
structure~function
symbolic~dynamic
symmetry~dynamics
symmetry~broken symmetry
togetherness~apartness
vertical~horizontal
within~between
Human ~ Machine Interaction
At a generic level:
HMI = sensorimotor task
Advances in basic science as well as technology have allowed
HMI exploration along the following lines:
 Machine as a behavioral clamp – parameter space of
interaction can be explored quickly
 HMI as continuous perception-action coupling
process that induces self-organized pattern formation
 If machine is cloaked with biologically relevant
features, HMI may be explored for use as surrogate
to study social interaction
Human ~ Machine Interface
Idea: Replace a partner with a virtual one that exhibits some biologically
relevant features such as embodiment, interactivity, and variability. Interactivity
from the artificial stimulus can be implemented via HKB coupling. To get
variability, one may exploit asymmetry as well as introduce parametric noise.
Embodied stimulus + Biological motion
Can be disembodied
through image
transformation
Interactivity
Variability
Others
x  ( Ax 2  Bx 2   ) x  w 2 x  ( x  X h )(   ( x  X h )2 )
e.g. Generic DOT
or real HAND
x , x
Simulated social HKB
response from
computer
X h , X h
Human input
HKB System Diagram
Parameter Board

HKB

Parameters
can be
changed on
the fly.

w
A
B
Flat Panel
Personal Computer
f
g
Finger Movement
Goniometer
x
x
Oscilloscope
Avoidance
Behavior
experiment
 Stimulus is oscillator-animated image of human finger
 Oscillator seeks anti-phase relation with subject
 Subject task – synchronize in phase with stimulus
Oscillator equation of motion
x  ( Ax 2  Bx 2   ) x  w 2 x  ( x  f )(   ( x  g ) 2 )
Conditions
(1) Experimental: Bi-directional
coupling
(2) Control 1: Oscillator coupling
removed, subject sees stimulus
(3) Control 2: Oscillator coupled,
screen occluded
Subjects maintain in-phase relation
Relative Phase Distributions
Oscillator cannot maintain anti-phase relation
Fully coupled system exhibits range
of behaviors showing strategies adapted
subjects depending on the oscillator
behavior
Using Your Squiggle Sense…
Why Do it?
• To more deeply understand what is going on -- yourself and the world you
live in
• To more deeply understand squiggles of interest (teacher~student,
parent~child, friend ~ enemy, genes ~ environment, learning~forgetting)
• To frame a subject and level of interest appropriately for coordination
dynamic theory~experiments, e.g. promotor~repressor, buying ~ selling)
• To gain novel insights into a specific subject of interest in which a
complementary pair is found via that complementary pair and its associated
coordination dynamics
What You Do:
• Choose subject, field, level of interest
• Choose your squiggles (consult your squiggle dictionary?)
• Study their coordination dynamics
And Remember…
• When anyone says “this is the way”, think squiggle!
• When you get trapped in a single mode, think squiggle!
• When it seems like it’s either/or, think squiggle! YOUR BRAIN CAN DO IT
Theory/Analysis
~
Experiments
H.Haken
K.J. Jantzen
A. Fuchs
F. Steinberg
V. Jirsa
O. Oullier
G. DeGuzman
J. Lagarde
E. Tognoli
Further Reading
http://thecomplementarynature.com
http://www.ccs.fau.edu/section_links/HBBLv2/