c. excitable media - utkweb.eecs.utk.edu/~bmaclenn/classes/420-594-f08/handouts/... ·...
TRANSCRIPT
![Page 1: C. Excitable Media - UTKweb.eecs.utk.edu/~bmaclenn/Classes/420-594-F08/handouts/... · 2008-09-10 · 9/9/08 46 NetLogo Simulation of Streaming Aggregation 1. chemical diffuses 2](https://reader033.vdocuments.mx/reader033/viewer/2022042321/5f0ba82f7e708231d431946c/html5/thumbnails/1.jpg)
9/9/08 1
C.
Excitable Media
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9/9/08 2
Examples of Excitable Media
• Slime mold amoebas
• Cardiac tissue (& other muscle tissue)
• Cortical tissue
• Certain chemical systems (e.g., BZ reaction)
• Hodgepodge machine
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Characteristics ofExcitable Media
• Local spread of excitation– for signal propagation
• Refractory period– for unidirectional propagation
• Decay of signal– avoid saturation of medium
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Behavior of Excitable Media
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Stimulation
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Relay (Spreading Excitation)
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Continued Spreading
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Recovery
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Restimulation
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Typical Equations forExcitable Medium
(ignoring diffusion)
• Excitation variable:
• Recovery variable:
˙ u = f (u,v)
˙ v = g(u,v)
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Nullclines
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Local Linearization
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Fixed Points & Eigenvalues
stablefixed point
unstablefixed point
saddle point
real parts ofeigenvaluesare negative
real parts ofeigenvaluesare positive
one positive real &one negative real
eigenvalue
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FitzHugh-Nagumo Model
• A simplified model of action potentialgeneration in neurons
• The neuronal membrane is an excitablemedium
• B is the input bias:
˙ u = uu3
3v + B
˙ v = (b0 + b1u v)
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NetLogo Simulation of
Excitable Medium
in 2D Phase Space
(EM-Phase-Plane.nlogo)
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Elevated Thresholds DuringRecovery
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Type II Model
• Soft threshold with critical regime
• Bias can destabilize fixed point
fig. < Gerstner & Kistler
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Poincaré-Bendixson Theorem
˙ u = 0
˙ v = 0
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Type I Model
˙ u = 0
˙ v = 0stable manifold
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Type I Model (Elevated Bias)˙ u = 0
˙ v = 0
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Type I Model (Elevated Bias 2)˙ u = 0
˙ v = 0
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Type I vs. Type II
• Continuous vs. threshold behavior of frequency
• Slow-spiking vs. fast-spiking neurons
fig. < Gerstner & Kistler
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Modified Martiel & GoldbeterModel for Dicty Signalling
Variables (functions of x, y, t):
= intracellular concentration
of cAMP
= extracellular concentration
of cAMP
= fraction of receptors in active state
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Equations
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Positive Feedback Loop
• Extracellular cAMP increases( increases)
• Rate of synthesis of intracellular cAMPincreases( increases)
• Intracellular cAMP increases( increases)
• Rate of secretion of cAMP increases• ( Extracellular cAMP increases)
See Equations
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Negative Feedback Loop• Extracellular cAMP increases
( increases)
• cAMP receptors desensitize(f1 increases, f2 decreases, decreases)
• Rate of synthesis of intracellular cAMPdecreases( decreases)
• Intracellular cAMP decreases( decreases)
• Rate of secretion of cAMP decreases• Extracellular cAMP decreases
( decreases)See Equations
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Dynamics of Model• Unperturbed
cAMP concentration reaches steady state• Small perturbation in extracellular cAMP
returns to steady state• Perturbation > threshold
large transient in cAMP, then return to steady state
• Or oscillation (depending on modelparameters)
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Circular & Spiral WavesObserved in:
• Slime mold aggregation
• Chemical systems (e.g., BZ reaction)
• Neural tissue
• Retina of the eye
• Heart muscle
• Intracellular calcium flows
• Mitochondrial activity in oocytes
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Cause ofConcentric Circular Waves
• Excitability is not enough
• But at certain developmental stages, cellscan operate as pacemakers
• When stimulated by cAMP, they beginemitting regular pulses of cAMP
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Spiral Waves
• Persistence & propagation of spiral wavesexplained analytically (Tyson & Murray,1989)
• Rotate around a small core of of non-excitable cells
• Propagate at higher frequency than circular• Therefore they dominate circular in
collisions• But how do the spirals form initially?
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Some Explanationsof Spiral Formation
• “the origin of spiral waves remains obscure”(1997)
• Traveling wave meets obstacle and isbroken
• Desynchronization of cells in theirdevelopmental path
• Random pulse behind advancing wave front
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Step 0: Passing Wave Front
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Step 1: Random Excitation
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Step 2: Beginning of Spiral
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Step 3
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Step 4
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Step 5
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Step 6: Rejoining & Reinitiation
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Step 7: Beginning of New Spiral
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Step 8
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Formation of Double Spiral
from Pálsson & Cox (1996)
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NetLogo SimulationOf Spiral Formation
• Amoebas are immobile at timescale of wavemovement
• A fraction of patches are inert (grey)• A fraction of patches has initial
concentration of cAMP• At each time step:
– chemical diffuses– each patch responds to local concentration
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Response of Patch
if patch is not refractory (brown) then
if local chemical > threshold thenset refractory period
produce pulse of chemical (red)
elsedecrement refractory period
degrade chemical in local area
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Demonstration of NetLogoSimulation of Spiral Formation
Run SlimeSpiral.nlogo
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Observations• Excitable media can support circular and spiral
waves• Spiral formation can be triggered in a variety of
ways• All seem to involve inhomogeneities (broken
symmetries):– in space– in time– in activity
• Amplification of random fluctuations• Circles & spirals are to be expected
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NetLogo Simulation ofStreaming Aggregation
1. chemical diffuses2. if cell is refractory (yellow)3. then chemical degrades4. else (it’s excitable, colored white)
1. if chemical > movement threshold thentake step up chemical gradient
2. else if chemical > relay threshold thenproduce more chemical (red)become refractory
3. else wait
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Demonstration of NetLogoSimulation of Streaming
Run SlimeStream.nlogo
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Demonstration of NetLogoSimulation of Aggregation
(Spiral & Streaming Phases)
Run SlimeAggregation.nlogo