Transcript 0_NeuroOverviewx

Universal laws
and architectures:
Theory and lessons from
brains, bugs, nets, grids,
docs, planes, fire, fashion,
art, turbulence, music, buildings,
cities, earthquakes, bodies, running, throwing,
Synesthesia, spacecraft, statistical mechanics
John Doyle 道陽
Jean-Lou Chameau Professor
Control and Dynamical Systems, EE, & BioE
Ca#1tech
• Neuroscience
+ People care
+Live demos!
1.
2.
3.
4.
experiments
data
theory
universals
8
Fragility
4
p
l0  l
z p2
 ln
z p
1
eye
l0  l  1
Slow
Act
.1
fast slow
delay
vision
  .1s
.05
vision
.2
.5
Length
Slow(meters)
1
Universal
Fast
laws
VOR
Inflexible
Flexible
thin
small
1
Fast
fragile
Survive
robust
10
fragile
too
fragile
Flexible z  p Inflexible
z  p complex
Laws
cheap
Multiply
thick
big
costly
No tradeoff
0
10 -1
10
k
0
10
1
10
expensive
Universal laws
and architectures:
Theory and lessons from
brains, bugs, nets, grids,
docs, planes, fire, fashion,
art, turbulence, music, buildings,
cities, earthquakes, bodies, running, throwing,
Synesthesia, spacecraft, statistical mechanics
Slow
Fast
Flexible
General
Inflexible
Special
Which blue line is longer?
Which blue line is longer?
Which blue line is longer?
Which blue line is longer?
Which blue line is longer?
Slowest
3D +
motion
eye
vision
fast
Act
Slow
color
vision
slow
delay
vision
VOR
Fast
Flexible
Inflexible
See Marge
Livingstone
Stare
at thegood.
intersection
This
is pretty
Layered
Architecture
DNA
New Gene
gene
RNA
Transcription
Other
Control
RNAp
mRNA Amino
Acids
Ribosomes
Translation
Slow
Proteins
Other
HGT
Cheap
Control
DNA repair
Products
Metabolism
Mutation
ATP
DNA
replication
control feedbackSignal transduction
Transcription
Translation
Metabolism
Signal…
Fast
Costly
Inflexible
Flexible
General
Special
vision
Prefrontal
Slow
Fast
Motor Fast Sense
HGT
DNA repair
VOR
Mutation
DNA replication
Apps
Transcription
Reflex
OS
OS
Translation
HW
HW
Metabolism
Dig.
Dig.
Digital
Signal
Lump. Lump. Lump. Lumped
Distrib. Distrib. Distrib. Distrib. Distrib.
Inflexible
Flexible
Special
General
Compute
Comms
Gödel
Shannon
Turing
Von
Neumann
Theory?
Deep, but fragmented,
incoherent, incomplete
Nash
Carnot
Boltzmann
Bode
Heisenberg
Control, OR
Einstein
Physics
Compute
Turing
Delay
and risk
are most
important
Bode
Control, OR
• Worst-case (“risk”)
• Time complexity (delay)
Computation for control
• Off-line design
• On-line implementation
• Learning and adaptation
• Worst-case (“risk”)
• Delay severely degrades
robust performance
Compute
Communicate
Turing
Shannon
Delay and
risk are
most
important
Delay and
risk are
least
important
Carnot
Bode
Control, OR
Boltzmann
Heisenberg
Einstein
Physics
Communicate
• Space complexity
Shannon
• Average case (risk neutral)
• Random ensembles
• Asymptotic (infinite delay)
Dominates
“high
impact
science”
literature
Carnot
Boltzmann
Heisenberg
Einstein
Physics
Compute
Communicate
Turing
Delay and
risk are
most
important
Shannon
New progress!
Delay and
risk are
least
important
Bode
Control, OR
Physics
.2 m
2 s/m
1
Axon
size and
speed
C
delay
sec/m
.1
20 m
Aα
.01
.008 s/m
.1
.01
1
1
diam(m) 10
area
100
1
C
delay
sec/m
.1
Aγ
Aδ
Aβ
.01
.1
.01
1
1
Aα
diam(m) 10
area
100
Axon size and speed
unmyelinated
1
delay
sec/m
.1
myelinated
.01
.1
.01
1
1
diam(m) 10
area
100
.1 m
1
delay
sec/m
10 m
.1
myelinated
myelin
1 m
.01
.1
.01
1
1
diam(m) 10
area
 m
2
100
Why such extreme diversity in delay and size?
Other
myelinated
1
delay
sec/m
Retinal
ganglion
axons?
.1
Why no
diversity
in VOR?
VOR
.01
.1
.01
1
1
diam(m) 10
area
100
Fractal wrongness
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•
•
•
Wrongness everywhere, every scale, “truthiness”
Involving anything “complex”…
Wild success: religion, politics, consumerism, …
Debates focused away from real issues…
• Even if erased, sustainability challenges remain
• Hopeless if it persists
• I’ll set aside all of this for now, and “zoom in” on the
world of PhD research/academic scientists
• BTW, excellent case study in infectious hijacking
This paper aims to bridge progress in neuroscience involving
sophisticated quantitative analysis of behavior, including the use
of robust control, with other relevant conceptual and theoretical
frameworks from systems engineering, systems biology, and
mathematics.
Trivial
examples
Doyle, Csete, Proc Nat Acad Sci USA, JULY 25 2011
“New sciences” of
“complexity” and
“networks”?
Science as
• Pure fashion
• Ideology
• Political
• Evangelical
• Nontech trumps tech
worse
• Edge of chaos
• Self-organized criticality
• Scale-free “networks”
• Creation “science”
• Intelligent design
• Financial engineering
• Risk management
• “Merchants of doubt”
•…
Complex systems?
Fragile
Even small
amounts can
create
bewildering
complexity
•
•
•
•
•
•
•
•
•
•
Scale
Dynamics
Nonlinearity
Nonequlibrium
Open
Feedback
Adaptation
Intractability
Emergence
…
Complex systems?
Robust
•
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•
•
•
•
•
•
•
•
Scale
Dynamics
Nonlinearity
Nonequlibrium
Open
Feedback
Adaptation
Intractability
Emergence
…
Fragile
•
•
•
•
•
•
•
•
•
•
Scale
Dynamics
Nonlinearity
Nonequlibrium
Open
Feedback
Adaptation
Intractability
Emergence
…
Complex systems?
Robust complexity
•
•
•
•
•
•
•
•
•
•
Scale
Dynamics
Nonlinearity
Nonequlibrium
Open
Feedback
Adaptation
Intractability
Emergence
…
•
•
•
•
•
•
•
Resources
Controlled
Organized
Structured
Extreme
Architected
…
• These words have lost much of
their original meaning, and have
become essentially meaningless
synonyms
• e.g. nonlinear ≠ not linear
• Can we recover these words?
• Idea: make up a new word to
mean “I’m confused but don’t
want to say that”
• Then hopefully we can take
these words back (e.g. nonlinear =
not linear)
Fragile
complexity
•
•
•
•
•
•
•
•
•
•
Scale
Dynamics
Nonlinearity
Nonequlibrium
Open
Feedback
Adaptation
Intractability
Emergence
…
New words
Emergulent
Emergulence
at the edge of
chaocritiplexity
Fragile
complexity
•
•
•
•
•
•
•
•
•
•
Scale
Dynamics
Nonlinearity
Nonequlibrium
Open
Feedback
Adaptation
Intractability
Emergence
…
Things we won’t get to
Attention/Awareness
(Graziano)
Compassion
Consciousness
Free will
Me vs We
Us vs Them
Things we won’t get to
Things we
won’t get to
Good/Evil
Things we
won’t get to
Things we won’t get to