Untangling complex syste.., p.56

Untangling Complex Systems, page 56

 

Untangling Complex Systems
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  FIGURE 9.21 Schematic structure of a neuron. The grey arrows indicate the flow of information from the

  dendrites up to the synapsis through the axon.

  14 There are neurons whose axon can be 1.5 m long! For example, those connecting our toes with the base of the spine.

  15 Note that in pure water D would be ≈ 100 μm2/s, but the crowded environment of a cell reduces the velocity of diffusion significantly, especially for a macromolecule. Read Box 9.4 of this chapter.

  276

  Untangling Complex Systems

  integrated into the axon hillock. Neurons, like the other cells in our body, are electrically polar-

  ized: they have an electric potential gradient between the exterior and the interior of the cellular

  membrane. This gradient of electric potential is made possible by the presence of proteins within

  the membrane; they work as ionic pumps and channels.

  The information that is integrated into the axon hillock can trigger an electrochemical wave

  that crosses the entire axon quickly without weakening and reaches the bottom part of the neuron

  where there are the synapses. At the synapses, the electrochemical information is transduced back

  in chemical signals, and neurotransmitters are released to the dendrites of other neurons.

  Every excitable portion of the neural membrane has two critical values of electric potential: one is

  the resting potential and the other is the threshold potential. The resting potential represents the value

  that the membrane maintains as long as it is not perturbed; usually, in the axon hillock, it is −70 mV.

  The inputs, which a neuron receives, induce either a hyperpolarization or depolarization of the mem-

  brane. In other words, the inputs either decrease or increase its electric potential. When a sufficiently

  strong excitatory input depolarizes the membrane, and its potential overcomes the threshold value

  (that is ≈ −55 mV in the axon hillock), the neuron triggers an action potential (Figure 9.22). The electric potential of the axon hillock soars quickly, in roughly 1 ms or less, up to reach a positive value, as

  large as +50 mV. Then, it drops to values that are more negative than the resting potential. Finally, it

  recovers its initial state, and the neuron is ready to discharge another action potential.

  The discharge of an action potential involves voltage-gated ion channels and pumps that are

  transmembrane proteins shown schematically in Figure 9.23. We start from the resting state (a)

  with the membrane that is hyperpolarized. If the neuron receives an excitatory input, the membrane

  potential raises because the sodium channels open (see step b in Figure 9.23). The increase of the membrane potential induced by the income of the first sodium ions exerts a positive feedback action.

  In fact, it causes a further opening of the Na+ channels and a stronger depolarization. Overall, this

  autocatalytic action determines a sharp jump of the potential membrane (see part c of Figure 9.23).

  Then, within a fraction of one-thousandth of a second, the sodium channels switch to an inactivated

  state due to the highly positive membrane potential (see part d of Figure 9.23). In the inactivated state, the sodium channels are closed and also refractory to reopening. At the same time, potassium

  channels open. They allow K+ ions to leave the neuron. Such transfer repolarizes the membrane.

  Finally, the ion pumps restore the initial transmembrane gradients of K+ and Na+ ions by exploiting

  energy supplied by the cell. After all, the portion of the axon where all the described events have

  occurred is ready to transmit another action potential (see part e of Figure 9.23). Meanwhile, the transmitted action potential propagates only forwards. The refractory states of the sodium channels prevent the depolarization from spreading backward along the axon. The action potentials

  propagate vectorially towards the synapsis, as genuinely electrochemical waves.

  +50

  V)

  al (m

  tenti

  0

  po

  −55

  −

  Membrane

  70

  0

  1

  2

  3

  4

  Time (ms)

  FIGURE 9.22 Schematic profile of an action potential.

  The Emergence of Order in Space

  277

  K+ Channel

  Na+ Channel

  Ion pump

  Na+

  V) +50

  Na+

  K+

  Out

  Na+ Na+ Na+

  Na+

  ial (m

  Na+

  tentpo 0

  K+

  −55

  −70

  In

  K+

  K+

  K+

  Na+

  Membrane

  (a)

  0

  1

  2

  3

  4

  Resting state

  Time (ms)

  V) +50

  Na+

  K+

  Out

  Na+ Na+ Na+

  Na+

  ial (m

  Na+

  tentpo 0

  K+

  −55

  −70

  In

  K+

  K+

  Membrane

  K+

  Na+

  Na+

  (b)

  0

  1

  2

  3

  4

  Depolarization

  Time (ms)

  V) +50

  Na+

  K+

  Out

  Na+

  ial (m

  Na+

  tentpo 0

  K+

  −55

  −70

  In

  K+

  K+

  Membrane

  K+

  Na+

  Na+

  (c)

  Na+

  Further

  0

  1

  2

  3

  4

  Time (ms)

  Na+

  Na+

  depolarization

  K+

  Na+

  V)

  K+

  +50

  K+

  Out

  Na+

  Na+

  ial (m

  tent

  Na+

  po

  0

  −55

  K+

  −70

  In

  K+

  Membrane

  Na+

  (d)

  Na+

  0

  1

  2

  3

  4

  Na+ Na+

  Repolarization

  Time (ms)

  Na+

  V) +50

  Na+

  K+

  Na+

  Out

  Na+ Na+

  Na+

  ial (m

  Na+

  tentpo 0

  K+

  −55

  −70

  In

  K+

  K+

  K+

  Membrane

  Na+

  (e)

  0

  1

  2

  3

  4

  Restoring the resting potential

  Time (ms)

  FIGURE 9.23 Schematic description of five relevant steps in the discharge of an action potential: resting

  state (a); depolarization (b); further depolarization (c); repolarization (d), and restoring the resting potential (e).

  When the action potential reaches the synapsis, voltage-gated Ca + 2 channels open and calcium

  ions enter the axon terminals. Ca + 2 entry causes neurotransmitter-containing synaptic vesicles to

  move to the plasma membrane, fuse with it and release their content according to the process of

  exocytosis. The neurotransmitter diffuses and binds to ligand-gated ion channels of the dendrites of

  other neurons, exerting either an inhibitory or an excitatory action.

  278

  Untangling Complex Systems

  Our understanding of how voltage-gated ion channels give rise to propagating action potentials is

  primarily due to the physiologists Alan Hodgkin and Andrew Huxley. They were the first to record

  the potential difference across the membrane of a squid giant axon by inserting a fine capillary

  electrode in it. It was the year 1939. The Second World War began only a few weeks after their first

  experiments were published in Nature (Hodgkin and Huxley 1939). Therefore, they were forced

  to quit their research. After the war, Hodgkin and Huxley could restart their fruitful collaboration

  that culminated with the publication of their mathematical model of the action potential in 1952

  (Hodgkin and Huxley 1952). The electrical behavior of the axon membrane may be described by the

  electrical circuit represented in Figure 9.24. Current flows through the membrane either by charging the membrane capacity ( I

  (

  ))

  C = CM dE dt

  or by movement of ions through resistances that are in

  parallel with the capacity. The ionic current consists of three contributions: sodium ( I ), potassium

  Na

  ( I ) and leakage ( I ) current, the latter being due to other ions, such as chloride anions. Each term of K

  L

  the ionic current is given by Ohm’s law:

  1

  I

  (

  )

  Na =

  E − ENa

  [9.48]

  RNa

  1

  I

  (

  )

  K =

  E − EK

  [9.49]

  RK

  1

  I

  (

  )

  L =

  E − EL

  [9.50]

  RL

  In the equations [9.48 through 9.50], E is membrane potential, whereas E , E , and E are the equi-Na

  K

  L

  librium potentials for sodium, potassium, and leakage ions, respectively. The terms (1 /R ), (1 /R )

  Na

  K

  and (1 /R ) are the sodium, potassium and leakage ions conductances.

  L

  The sodium and potassium conductances are time- and membrane potential-dependent. In

  fact, depolarization causes a temporary rise in sodium conductance, whereas repolarization

  determines an increase in potassium conductance but also a decrease in sodium conductance.

  If we refer all the potentials to the absolute value of the membrane resting potential Er, and

  we fix V = E − Er, VNa = ENa − Er, VK = EK − Er, VL = EL − Er, the equation that gives the total membrane current I is:

  Extracellular

  I

  INa

  IK

  IL

  RNa

  RK

  RL

  CM

  E

  −

  +

  +

  −

  +

  −

  ENa

  EK

  EL

  Intracellular

  FIGURE 9.24 Electrical circuit proposed by Hodgkin and Huxley as a model to explain the formation of

  action potentials in axons.

  The Emergence of Order in Space

  279

  dV

  1

  1

  1

  I = C

  (

  )

  (

  )

  (

  )

  M

  +

  V − VNa +

  V − VK +

  V − VL

  [9.51]

  dt

  RNa

  RK

  RL

  After defining the best non-linear analytic functions for (1 /R ) and (1 /R ) by fitting experimental

  Na

  K

  data of potassium and sodium conductances, Hodgkin and Huxley succeeded in reproducing the

  shape of an action potential. For the description of how an action potential propagates through an

  axon, we must consider the concatenation of circuits like that of Figure 9.24. If we indicate with r the spatial coordinate that represents the principal axis of the cylindrical axon, perpendicular to the

  membrane, the current flowing along r is

  1

  ∂ V

  2

  I =

  [9.52]

  2

  2π ( R

  )

  out + Rin

  r

  ∂

  where R and R are the external and internal resistances of the axon.16 If we consider an axon out

  in

  surrounded by a large amount of conducting fluid, R is negligible compared with the resistance

  out

  of the axoplasm (that is the cytoplasm within the axon of a neuron), i.e., R . If we indicate with a

  in

  the radius of the axoplasm and with ρ its resistivity, the final equation describing the propagation

  in

  of an action potential is

  a ∂ V

  2

  V

  1

  1

  1

  =

  ∂

  C

  (

  )

  (

  )

  (

  )

  M

  +

  V − VNa +

  V − VK +

  V − VL

  [9.53]

  2

  2

  ρ in r

  ∂

  t

  ∂

  RNa

  RK

  RL

  Equation [9.53] can be rearranged in the following form:

  ∂ V

  2

  =

  a

  ∂ V + f V()

  [9.54]

  ∂ t

  2 C

  2

  ρ in M ∂ r

  9.7.2 The fisher-kolmogorov eQuaTion

  Equation [9.54] is formally equivalent to the equation that describes a traveling wave. If you remem-

  ber equations [9.42 and 9.43], it is evident that the traveling waves of a chemical concentration x that

  diffuses and reacts, are expressed by

  16 It is important to notice that, so far, we have learned and modeled how electrochemical signals propagate within an axon of small diameter. In large diameter axons, the propagation of electrochemical signals is assisted by the myelin sheath.

  The myelin sheath is made of cells wrapping the axon with concentric layers of their cell membranes. Such layers are

  made of lipids. Therefore, they are not conductive. In a myelinated neuron, the portions of the axon not covered are called nodes of Ranvier (see Figure in this note). The layer of insulation generated by the myelin coat avoids current leakage from the axon by blocking the movement of ions through the axon membrane. As a result, action potentials propagate

  faster in a myelinated axon rather than an unmyelinated one.

  Nodes of ranvier

  Myelinated axon

  Unmyelinated axon

  280

  Untangling Complex Systems

  ∂ x

  2

  = ∂ x

  D

  + f ( x)

  [9.55]

  ∂ t

  ∂ r 2

  where D is the diffusion coefficient, and f ( x) represents the kinetic law. The simplest case of a kinetic law that generates propagating chemical waves involves an autocatalytic reaction of the type:

  X S

  ka

  +  →

   2 X

  [9.56]

  The net reaction is S → X. S is the reacting substrate and X is the autocatalytic species. If we have S distributed homogeneously in our system, the addition of a small amount of X at one point can

  trigger the autocatalytic reaction, like a burning fire. Then, the autocatalysis coupled with diffusion

  makes the rest, and chemical waves spread throughout the system. If the initial concentration of S

  is s 0 and that of X is negligible, the mass balance allows us to write s 0 = s + x. Therefore, equation

  [9.55] becomes

  ∂ x

  2

  = ∂ x

  D

  + kax

  [9.57]

  2

  ( s 0 − x)

  ∂ t

  ∂ r

  where k is the kinetic constant of the autocatalytic reaction. We may rewrite equation [9.57] in

  a

  terms of the dimensionless variable ξ = x/ s 0 and obtain

  ∂ξ

  ξ

  2

  = ∂

  D

  + k ξ

  a

  1

  ( − ξ )

  [9.58]

  ∂ t

  ∂ r 2

  Equation [9.58] was proposed by the British statistician and mathematical biologist Ronald Fisher

  (1937) for describing the spatial spread of an advantageous mutant gene through a population of

  interbreeding organisms in a linear habitat, such as a shoreline. He wrote a partial differential equa-

  tion like [9.58], where ξ represents the frequency of the advantageous mutant gene X at the expense

  of the allelomorph S occupying the same locus;17 k represents the rate of mutation and D is the coef-a

  ficient of diffusion of the advantageous gene. Fisher showed that waves of stationary shape advance

  through the population with speeds

  v ≥ 2 kaD

  [9.59]

  The same result was achieved by the Russian mathematician Andrey Kolmogorov and his co-

  workers, exactly in the same year (Kolmogorov et al. 1937). This is the reason why equation [9.58]

  is now known as Fisher-Kolmogorov equation. 18 It is surprising that the result [9.59] was anticipated

  17 In genetics, allelomorphs (or shortly, alleles) are alternative forms of a gene that can occupy the same locus on a particular chromosome and control the same character.

  18 A detailed mathematical treatment of the Fisher-Kolmogorov equation that does not have an analytical solution can be found in chapter 13 of the book “Mathematical Biology I” by Murray (2002), and in the feature article by Scott and Showalter (1992) published in the Journal of Physical Chemistry. In the latter, the authors deal not only with a quadratic but also a cubic autocatalytic process. A representation of propagation of chemical waves according to the Fisher-Kolmogorov equation is shown in the Figure of this note.

 

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