hodgkin-huxley model

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    HodgkinHodgkin--Huxley ModelHuxley Model

    andand

    FitzHughFitzHugh--NagumoNagumo ModelModel

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    Nervous SystemNervous System

    Signals are propagated from nerve cell to nerveSignals are propagated from nerve cell to nerve

    cell (cell (neuronneuron) via electro) via electro--chemical mechanismschemical mechanisms ~100 billion neurons in a person~100 billion neurons in a person

    Hodgkin and Huxley experimented on squids andHodgkin and Huxley experimented on squids and

    discovered how the signal is produced within thediscovered how the signal is produced within theneuronneuron

    H.H.--H. model was published inH. model was published in Jour. ofJour. ofPhysiologyPhysiology

    (1952)(1952) H.H.--H. were awarded 1963 Nobel PrizeH. were awarded 1963 Nobel Prize

    FitzHughFitzHugh--NagumoNagumo model is a simplificationmodel is a simplification

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    NeuronNeuron

    C. George Boeree: www.ship.edu/~cgboeree/

    http://www.ship.edu/~cgboeree/http://www.ship.edu/~cgboeree/
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    Action PotentialAction Potential

    10 msec

    mV

    _ 30

    -70

    V

    _ 0

    Axon membrane

    potentialdifference

    V = VV = ViiVVee

    When the axon isexcited,VV spikesbecause sodium

    Na+Na+ andpotassium K+K+ions flow throughthe membrane.

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    Nernst Potential

    VVNaNa ,VVKKandVVrr

    Ion flow due toelectrical signal

    Traveling wave

    C. George Boeree: www.ship.edu/~cgboeree/

    http://www.ship.edu/~cgboeree/http://www.ship.edu/~cgboeree/
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    Circuit Model for Axon MembraneCircuit Model for Axon Membrane

    Since the membrane separates charge, it is modeled asa capacitor with capacitance CC. Ion channels areresistors.

    1/R = g =1/R = g = conductance

    Na+K+

    ggNagK

    C

    inside

    +

    cell

    NaVK rVV

    outside

    r

    +

    axon

    axon

    inside

    outside

    membraneCl

    iiCC = C= C dV/dtdV/dt

    iiNaNa == ggNaNa (V(VVVNaNa))

    iiKK== ggKK (V(VVVKK))

    iirr == ggrr (V(VVVrr))

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    Circuit EquationsCircuit Equations

    Since the sum of the currents is 0, it follows thatSince the sum of the currents is 0, it follows that

    aprrNa

    IVVgVVgVVgdtdVC KKNa += )()()(

    where IIapap is applied current. If ion conductances areconstants then group constants to obtain 1st order, linear eq

    apIVVgdt

    dVC += *)(

    Solving gives gIVtV ap /*)( +

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    Variable ConductanceVariable Conductance

    0

    2

    4

    6

    8

    10

    g_K

    1 2 3 4 5

    msec

    0

    2

    4

    6

    8

    10

    12

    14

    g_Na

    1 2 3 4 5

    msec

    g

    Experiments showed thatExperiments showed that ggNaNa andand ggKK varied with time and V.varied with time and V.After stimulus, Na responds much more rapidly than K .After stimulus, Na responds much more rapidly than K .

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    HodgkinHodgkin--Huxley SystemHuxley System

    Four state variables are used:Four state variables are used:

    v(tv(t)=)=V(t)V(t)--VVeqeq is membrane potential,is membrane potential,m(tm(t) is Na activation,) is Na activation,

    n(tn(t) is K activation and) is K activation and

    h(th(t) is Na inactivation.) is Na inactivation.

    In terms of these variables ggKK=ggKKnn44 and ggNaNa==ggNaNamm

    33hh.The resting potentialVVeqeq--70mV70mV. Voltage clampexperiments determined ggKKand nn as functions oftt and

    hence the parameter dependences on vv in thedifferential eq. for n(tn(t).). Likewise for m(tm(t)) and h(th(t).).

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    HodgkinHodgkin--Huxley SystemHuxley System

    IVvgVvngVvhmgdt

    dvC aprrKNa

    KNa

    += )()()( 43

    mvmvdt

    dmmm )()1)(( =

    nvnvdt

    dnnn )()1)(( =

    hvhvdt

    dhhh )()1)(( =

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    FastFast--Slow DynamicsSlow Dynamics

    m(t)

    n(t)

    h(t)

    10msec

    mm(v(v) dm/) dm/dtdt == mm(v(v)) m.m.

    mm(v(v) is much smaller than) is much smaller than

    nn(v(v) and) and hh(v(v). An increase). An increase

    in v results in an increase inin v results in an increase in

    mm(v(v)) and a large dm/and a large dm/dtdt..Hence Na activates moreHence Na activates more

    rapidly than K in responserapidly than K in response

    to a change in v.to a change in v.

    v, m are on a fast time scale and n, h are slow.v, m are on a fast time scale and n, h are slow.

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    FitzHughFitzHugh--NagumoNagumo SystemSystem

    Iwvfdt

    dv+=

    )( wvdt

    dw

    5.0=and

    IIrepresents applied current, is small and f(vf(v)) is a cubic nonlinearity.Observe that in the ((v,wv,w)) phase plane

    which is small unless the solution is near f(v)f(v)--w+w+II=0=0. Thus the slowmanifoldis the cubic w=w=f(v)+f(v)+IIwhichwhich is the nullclineof the fast variable

    vv. And ww is the slow variable with nullclinew=2vw=2v.

    Iwvf

    wv

    dv

    dw

    +

    =

    )(

    )5.0(

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    Take f(vf(v)=v(1)=v(1--v)(vv)(v--a)a) .

    Stable rest state

    vv

    w

    I=0I=0 Stable oscillation I=0.2I=0.2

    w

    vv

    R fR f

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    ReferencesReferences1.1. C.G.C.G. BoereeBoeree,, The NeuronThe Neuron,, www.ship.edu/~cgboeree/.

    2.2. R.R. FitzHughFitzHugh, Mathematical models of excitation and, Mathematical models of excitation andpropagation in nerve, In: Biological Engineering, Ed: H.P.propagation in nerve, In: Biological Engineering, Ed: H.P.SchwanSchwan, McGraw, McGraw--Hill, New York, 1969.Hill, New York, 1969.

    3.3. L. EdelsteinL. Edelstein--KesketKesket, Mathematical Models in Biology, Random, Mathematical Models in Biology, RandomHouse, New York, 1988.House, New York, 1988.

    4.4. A.L. Hodgkin, A.F. Huxley and B. Katz,A.L. Hodgkin, A.F. Huxley and B. Katz, J. PhysiologyJ. Physiology116116, 424, 424--448,1952.448,1952.

    5.5. A.L. Hodgkin and A.F. Huxley,A.L. Hodgkin and A.F. Huxley, J.J. PhysiolPhysiol.. 116,116, 449449--566, 1952.566, 1952.6.6. F.C.F.C. HoppensteadtHoppensteadt and C.S.and C.S. PeskinPeskin,, Modeling and Simulation inModeling and Simulation in

    Medicine and the Life SciencesMedicine and the Life Sciences, 2nd ed, Springer, 2nd ed, Springer--VerlagVerlag, New, NewYork, 2002.York, 2002.

    7.7. J. Keener and J.J. Keener and J. SneydSneyd,, Mathematical PhysiologyMathematical Physiology, Springer, Springer--VerlagVerlag, New York, 1998., New York, 1998.

    8.8. J.J. RinzelRinzel,, Bull. Math. BiologyBull. Math. Biology5252, 5, 5--23, 1990.23, 1990.

    9.9. E.K.E.K.YeargersYeargers, R.W., R.W. ShonkwilerShonkwiler and J.V. Herod, Anand J.V. Herod, An IntroductionIntroductionto the Mathematics of Biology: with Computer Algebra Modelsto the Mathematics of Biology: with Computer Algebra Models,,BirkhauserBirkhauser, Boston, 1996., Boston, 1996.