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User:WillowW/Action potential flotsam

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More flotsam edit

The action potential itself does not cross between neurons; rather, the arrival of an action potential stimulates the release of neurotransmitters from the axonal terminal, the synaptic knob. These neurotransmitters bind to ligand-gated ion channels in the postsynaptic (usually dendritic) membrane, stimulating postsynaptic potentials, excitatory and inhibitory, that may depolarize the postsynaptic axon hillock enough to provoke a new action potential.[1] This integration of dendritic signals and its translation into a temporal code of action potentials at the axon hillock is a key mechanism of neural computing.[2]

Nernst potential edit

If the conductivities g are constant and there are no outside influences, the flow of ions causes the membrane voltage Vm to converge to an equilibrium voltage, E, at which no net current flows. At this voltage, the currents due to difusion and those These two driving forces can be described mathematically. A system at equilibrium contains no net current; the electric field and diffusion work in opposite directions, so that the current due to the electric field exactly cancels the current due to the concentration gradient. When the two concentrations are separated by a membrane, this equilibrium is described by the Nernst equation, where the equilibrium voltage equals the equilibrium electric field integrated over the thickness of the membrane. At room temperature, roughly 59 millivolts (mV) are required for every ten-fold ratio of concentrations; for illustration, a hundred-fold ratio of concentrations can be held in equilibrium by 118 mV (2 powers of ten = 2×59 mV), whereas a thousand-fold concentration ratio would require 177 mV (3 powers of ten = 3×59 mV). The equilibrium voltages for different ions need not be the same, if their concentration gradients differ; this fact is exploited by the neuron to make action potentials.

Ion concentration differences edit

The ionic strength of the solvent inside and outside the neuron is roughly the same, being roughly 100 mM. However, the concentration of a particular ion inside the cell need not be the same as the concentration of the same ion outside the cell. For example, the concentration of potassium ions K+ within the neuron is roughly 20-fold larger than its counterpart outside the cell, whereas the sodium concentration outside the cell is roughly 9-fold larger than that within the neuron.[3][4] Similar discrepancies are observed for other ions, such as calcium, chloride and magnesium.[4]

More on ion channels edit

generally allows only potassium through, and not sodium, despite the fact that the two ions differ only slightly in their radius.[note 1]

Most ions in solution are covered in one or more hydration shells of water molecules, which could further obscure the differences in their radii. Insight into the mechanism of this specificity has come from atomic-resolution crystal structures of ion channels. The water molecules of the hydration shell are stripped off and replaced by four well-ordered carbonyl oxygen atoms of the protein, which mimic the waters. This substitution is favored by entropy, since it allows the formerly bound water molecules to move more freely. Since the carbonyl oxygens are held at a relatively precise distance, ions of different radii will not bind as well, or will clash with them.

Physiology edit

In principle, molecules can diffuse laterally within the cell membrane, but the distribution of ionic channels on the cell membrane seems to be well regulated. For example, a very high density of ion channels is found at the nodes of Ranvier, and in general, voltage sensitive channels are not allowed to diffuse into the dendrites.

Careful studies of the human genome have revealed that there are multiple forms of many channels, which allows for a very fine regulation of the channel's behavior. For example, one version of a channel might be used in the brain, whereas another might be used in a motor neuron.[5]

Channelopathies edit

Mutations in channels that result in disease are known as channelopathies.[6] Such channelopathies have been linked to diseases such as some forms of epilepsy, episodic ataxias, migraines, pathological pain, hyperekplexia, myotonia and periodic paralysis.[7]

useful references edit

Ashcroft FM (2006). "From molecule to malady". Nature. 440 (7083): 440–447. doi:10.1038/nature04707.

Edelstein SJ, Changeux JP (1998). "Allosteric transitions of the acetylcholine receptor". Advances in Protein Chemistry. Advances in Protein Chemistry. 51: 121–184. doi:10.1016/S0065-3233(08)60652-X. ISBN 9780120342518.

Gouaux E, MacKinnon R (2005). "Principles of selective ion transport in channels and pumps". Science. 310 (5753): 1461–1465. doi:10.1126/science.1113666.

Long SB, Campbell EB, MacKinnon R (2005). "Crystal structure of a mammalian voltage-dependent Shaker family K+ channel". Science. 309 (5736): 897–902. doi:10.1126/science.1116269.{{cite journal}}: CS1 maint: multiple names: authors list (link)

Long SB, Campbell EB, MacKinnon R (2005). "Voltage sensor of Kv1.2: structural basis of electromechanical couplingl". Science. 309 (5736): 903–908. doi:10.1126/science.1116270.{{cite journal}}: CS1 maint: multiple names: authors list (link)

Miyazawa A, Fujiyoshi Y, Unwin N (2003). "Structure and gating mechanism of the acetylcholine receptor pore". Nature. 423 (6943): 949–955. doi:10.1038/nature01748.{{cite journal}}: CS1 maint: multiple names: authors list (link)

Shi N, Ye S, Alam A, Chen L, Jiang Y (2006). "Atomic structure of a Na+- and K+-conducting channel". Nature. 440: 427–429.{{cite journal}}: CS1 maint: multiple names: authors list (link)

Tombola F, Pathak MM, Isacoff EY (2006). "How does voltage open an ion channel?". Annu. Rev. Cell Dev. 22: 23–52.{{cite journal}}: CS1 maint: multiple names: authors list (link)

Table of channelopathies edit

Na+ SCN1A voltage-gated neuron generalized epilepsy with febrile seizures
Na+ SCN4A voltage-gated muscle hyperkalemic periodic paralysis; paramyotonia congenita
Na+ SCN5A voltage-gated heart long QT syndrome 3
Ca2+ CACNA1A voltage-gated neuron familial hemiplegic migraine
Ca2+ CACNA1F voltage-gated retina congenital stationary night blindness
K+ KCNQ2 voltage-gated neuron benign familial neomatal convulsions
K+ KCNQ4 voltage-gated neuron dominant deafness



acetylcholine receptor CHRNA1 congenital myasthenic syndrome

hormone secretion under control of excitable cells

“distal” end = axonal termini = voltage-gated Ca2+ channels

Na+ channels selective (>100:1) high flux 10^7 ions/sec

Lithium edit

The lithium cation (Li+) resembles sodium and potassium, but is significantly smaller; it can replace sodium in an action potential, but is not normally present in significant concentrations in the body. Lithium is sometimes used as a mood stabilizing drug, but its mechanism is not well understood and seems unrelated to its similarity to the sodium ion.[8]

Neural networks edit

Main articles: Biological neural network and Artificial neural network

The nervous systems of animals are characterized by an enormous diversity of neurons, presumably each specialized for its function, and by its high degree of interconnection. Nevertheless, there are a few examples in nature of small biological neural networks that function quasi-indepedently with minimal outside input. Central pattern generators, such as the escape swimming reflex of the mollusc Tritonia diomedea, as are an example of this. When touched by a predatory starfish, Tritonia initiates a fast twitching of 2-20 dorsal and ventral flexions, which is controlled by a small core of roughly 15 neurons.[9] Small central pattern generators have been modeled using equations similar to those used in the Hodgkin-Huxley equations.

The central pattern generators are small and relatively simple circuits that do not exhibit the learning and categorization powers observed in larger, more sophisticated neural circuits. To model such circuits, researchers often simplify the model of the individual neuron. For example, in perceptron-type models, the complex temporal pattern of action potentials carried by an axon may be modeled by the average frequency of the spikes; and the complex excitatory and inhibitory relationships of the dendritic inputs may be replaced by a weighted sum of the incoming axonal signals. Despite their simplifications, such artificial neural networks have learned to carry out complex categorization problems by generalizing from training examples.[10]

Experimental methods edit

Model neurons edit

 
The giant axons of Loligo vulgaris were crucial for scientists to understand the action potential.

Much of the early work on neurophysiology used the giant axons of the squid genus Loligo.[11] These axons are so large in diameter (roughly 1 mm, roughly 100-fold larger than a typical neuron) that they can be seen with the naked eye, making them easy to extract and manipulate.[12] These giant neurons are used by the squid to escape predators by contracting the squid's mantle to make a jet of water through its hyponome; they have evolved to be so large because they provide high conduction speeds, as described above.

Other neurons commonly used as model systems include those from the related cuttlefish[13], snails[14] and sea slugs such as Aplysia,[15] octopi, toads[16] and frogs (especially Xenopus laevis[17] and Rana pipiens), bristle worms,[18] crayfish, crabs and lobsters,[19][20] some fish and birds, and mammals such as rabbits, rats[21] and cats.[22] It is important to study neurons from many types of animals, since they may exhibit different properties. For example, the squid axons lack a myelin sheath,[23] and the ion currents generated during their conduction of action potentials are simpler than those of some other types of neurons.[12]

 
Researchers have often used an oscilloscope to follow the rapidly changing voltage of an action potential.

Electrodes and oscilloscopes edit

See also: Electrophysiology, Electrode, and Neurochip

The study of action potentials requires a method for measuring the voltage across the membrane of a neuron. Since a neuron is typically 1–10 microns in diameter, such measurements require extremely small electrodes. A typical electrode is a fine glass tube filled with a conducting solution, which is then connected to an amplifier. The original glass capillary electrodes of Hodgkin and Huxley were roughly 100 microns in diameter and had to be inserted into the open end of a cut axon.[24] A breakthrough came with the work of Ling and Gerard in 1949, who formed micropipette electrodes by melting the middle of glass tubes under extreme tension; once they melted, the two halves separated quickly, drawing the glass to a fine tip.[25] This method for producing electrodes was quickly adopted by other researchers[26][27] and was crucial for the success of the work of Hodgkin and Huxley. Refinements of this method are able to produce electrode tips that are as fine as 100 Å (10 nm).[28] A modern alternative is to record action potentials with a neurochip containing EOSFETs.

The transmembrane voltage of an action potential can be monitored by connecting the electrode to a device such as an oscilloscope.[29] Such devices must be sensitive to microvolts (10−6 volts) and picoamps (10−12 amperes), able to follow the rapidly changing voltages, and must have a very high input impedance, so that the measurement itself does not affect the voltage being measured.[30] A typical input impedance for electrophysiology research might be as high as 100 Megaohms (MΩ).[31] Oftentimes, the data are collected in a Faraday cage, to prevent ambient electric fields from interfering with the sensitive measurements.

Voltage clamping and patch clamping edit

Main articles: Voltage clamp and Patch clamp
 
The voltage-clamp circuit provides just enough current to hold the voltage across the membrane fixed at any chosen value. This allows scientists to study transmembrane ionic currents as a function of transmembrane voltage, without the complication of the capacitative current I = C dV/dt.

Voltage clamping was another technique critical to the successful study of the action potential. As noted above, electrophysiology experiments are quite demanding; the instrumentation must be sensitive and the electrical noise minimal. One important source of noise is the capacitative current C dV/dt that arises from the capacitance of the membrane and the changing voltage. To eliminate this source of noise, and to focus on the currents passing through the membrane itself, Kenneth Cole and others developed the voltage clamp, a negative feedback circuit that supplies whatever current is necessary to keep the transmembrane voltage at any chosen set-point. By systematically changing this set-point and studying the variation in the needed current, Hodgkin and Huxley were able to isolate and monitor the currents passing through the voltage-dependent sodium and potassium channels. From those data, they proposed their mathematical model of the action potential.

 
In patch clamping, the conductance of a single ion channel (shown in red) can be monitored over time, revealing the distinct states of the channel and different types of channels. Earlier work looked at the overall current through the membrane, which is the net effect of many channels.
 
Conductance of a single ion channel monitored by a patch clamp electrode. The channel clearly oscillated between two discrete states, open (high conductance) and closed (low conductance).

The experiments of Hodgkin and Huxley in the 1950's measured the average conductance of the membrane, but could not discern the conductance of individual ion channels. This became possible only in the 1970's with the development of the patch clamp by Erwin Neher and Bert Sakmann, for which they were awarded the Nobel Prize in Physiology or Medicine in 1991. Patch-clamping verified that ionic channels have discrete states of conductance, such open, closed and inactivated. Consistent with statistical mechanics, the channel switches back and forth between these states stochastically; the application of voltages or chemicals can alter the relative probabilities of the channel being in one or another state.

Optical methods edit

Most neurons are not visible with the naked eye, being typically 10 microns in diameter. Therefore, most neurophysiological experiments on individual neurons are done under a microscope, with the electrodes being maneuvered using micromanipulators. Since the neuron is under a microscope, it made sense to develop optical methods to monitor ionic events within the cell; optical methods may also cause a smaller perturbation of the neuron being studied, compared with inserting an electrode. The first optical method used the jellyfish protein aequorin to monitor the release of free calcium ions,[32] such as those released by the action potential when it reaches the synaptic knob. Dyes that change their fluorescence or absorbance were developed in the early 1970's to monitor action potentials,[33] and have been improved ever since.[34]

Terminology checklist edit

  • nerve
  • tracts, fiber tracts, nuclei
  • neuroglia, glia cells, amacrine cells
  • neuron, nerve cell
  • membrane
  • some, cell body
  • "projecting from the soma": dendrites, dendritic tree,
  • axon, axon hillock
  • synapse, synaptic cleft, pre/postsynaptic, synaptic vesicle
  • action potential (voltage change) part of nerve impulse
  • membrane potential, resting potential, hyperpolarization, depolarization
  • stimulus
  • active response, passive response
  • threshold, all-or-none
  • latency, strength-latency curve
  • absolute/relative refractory period
  • frequency coding?
  • accommodation
  • passive spread, electrotonic spread
  • myelinated axon, modes of Ranvier
  • postsynaptic potential (PSP)
  • chemically excitable, electrically excitable
  • graded response, temporal/spatial summation
  • slow potentials in the dendrites
  • presynaptic inhibition
  • inhibitory equilibrium potential
  • tonic neurons vs. phasic neurons
  • adaptation
  • generator potential
  • transduction, sensory organs/neurons
  • membrane current, membrane permeability
  • sodium pump
  • conductance
  • diffusion
  • membrane capacitance, membrane time constant
  • sodium/potassium equilibrium potential
  • sodium inactivation
  • neurotransmitter persistence, quantization
  • equivalent circuits, flux equation
  • cable equation, space constant, time constant
  • space clamp, voltage clamp (time clamp)

References edit

  1. ^ Bullock, Orkand, and Grinnell, pp. 177–202.
  2. ^ Bullock, Orkand, and Grinnell, pp. 203–240.
  3. ^ Steinbach HB, Spiegelman S (1943). "The sodium and potassium balance in squid nerve axoplasm". J. Cell. Comp. Physiol. 22 (2): 187–196. doi:10.1002/jcp.1030220209.
  4. ^ a b Hodgkin AL (1951). "The ionic basis of electrical activity in nerve and muscle". Biol. Rev. 26 (4): 339–409. doi:10.1111/j.1469-185X.1951.tb01204.x.
  5. ^ Herz JM, Thomsen WJ, Yarbrough GG (1997). "Molecular approaches to receptors as targets for drug discovery". J. Recept. Signal Transduct. Res. 17 (5): 671–776. doi:10.3109/10799899709044284. PMID 9292776.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  6. ^ Lehmann-Horn F, Jurkat-Rott K (1999). "Voltage-gated ion channels and hereditary disease". Physiol. Rev. 79: 1317–1372.
    Ashcroft FM (1999). Ion Channels and Disease: Channelopathies. London: Academic Press. ISBN 978-0120653102.
  7. ^ Goldin A. "Neuronal Channels and Receptors". In SG Waxman (ed.). Molecular Neurology. Burlington MA: Elsevier Academic Press. pp. 53–56. ISBN 978-0-12-369509-3.
  8. ^ Harwood AJ, Agam G (2003). "Search for a common mechanism of mood stabilizers". Biochem. Pharmacol. 66 (2): 179–89. doi:10.1016/S0006-2952(03)00187-4. PMID 12826261.
  9. ^ Getting PA (1983). "Neural control of swimming in Tritonia". In A Roberts, BL Roberts (ed.). Neural origin of Rhythmic Movements. London: Cambridge University Press. pp. pp. 89–128. {{cite book}}: |pages= has extra text (help)
  10. ^ McCulloch WS (1988). Embodiments of Mind. Cambridge MA: The MIT Press. pp. pp. 19–39, 46–66, 72–141. ISBN 0-262-63114-8. {{cite book}}: |pages= has extra text (help)
    Neurocomputing:Foundations of Research. Cambridge, MA: The MIT Press. pp. 15–41. ISBN 0-262-01097-6. {{cite book}}: Unknown parameter |editors= ignored (|editor= suggested) (help)
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  12. ^ a b Meunier C, Segev I (2002). "Playing the devil's advocate: is the Hodgkin-Huxley model useful?". Trends Neurosci. 25 (11): 558–63. doi:10.1016/S0166-2236(02)02278-6. PMID 12392930.
  13. ^ Arvanitaki A (1939). "Recherches sur la réponse oscillatoire locale de l'axone géant isolé de Sepia". Arch. Int. Physiol. 49 (2): 209–56. doi:10.3109/13813453909150823.
  14. ^ Meves H (1966). "Das Aktionspotential der Riesennervenzellen der Weinbergschnecke Helix pomantia". Pflüger's Arch. Ges. Physiol. 289: R10.
  15. ^ Junge D, Moore GP (1966). "Interspike-interval fluctuations in Aplysia pacemaker neurons". Biophysical Journal. 6 (4): 411–34. doi:10.1016/S0006-3495(66)86667-5. PMC 1367959. PMID 19210968.
  16. ^ Araki T, Otani T (1959). "Accommodation and local response in motoneurons of toads' spinal cord". Japan J. Physiol. 9: 69–83. doi:10.2170/jjphysiol.9.69.
  17. ^ Frankenhaeuser, B (1960). "Quantitative description of sodium currents in myelinated nerve fibres of Xenopus laevis". J. Physiol. 151: 491–501. PMC 1363279. PMID 13824558. {{cite journal}}: Unknown parameter |name= ignored (help)
  18. ^ Begenisich T (1975). "Magnitude and location of surface charges on Myxicola giant axons". J. Gen. Physiol. 66 (1): 47–65. doi:10.1085/jgp.66.1.47. PMC 2226185. PMID 1159402.
  19. ^ Julian FJ, Moore JW, Goldman DE (1962). "Membrane potentials of the lobster giant axon obtained by use of the sucrose-gap technique" (PDF). J. Gen. Physiol. 45 (6): 1195–1216. doi:10.1085/jgp.45.6.1195. PMC 2195233. PMID 14452759.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  20. ^ Julian FJ, Moore JW, Goldman DE (1962). "Current-voltage relations in the lobster giant axon membrane under voltage clamp conditions" (PDF). J. Gen. Physiol. 45 (6): 1217–38. doi:10.1085/jgp.45.6.1217. PMC 2195240. PMID 14452758.{{cite journal}}: CS1 maint: multiple names: authors list (link)
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  28. ^ Snell FM (1969). "Some Electrical Properties of Fine-Tipped Pipette Microelectrodes". In M. Lavallée, OF Schanne, NC Hébert (ed.). Glass Microelectrodes. New York: John Wiley and Sons. LCCN 689252. {{cite book}}: Check |lccn= value (help)CS1 maint: multiple names: editors list (link)
  29. ^ Brown PB, Maxfield BW, Moraff H (1973). Electronics for Neurobiologists. Cambridge, MA: The MIT Press. ISBN 978-0262020947.{{cite book}}: CS1 maint: multiple names: authors list (link)
  30. ^ Kettenmann H, Grantyn R (1992). Practical Electrophysiological Methods. New York: Wiley. ISBN 978-0471562009.
  31. ^ Junge, p. 2.
  32. ^ Llinás R, Blinks JR, Nicholson C (1972). "Calcium transients in presynaptic terminal of squid giant synapse: detection with aequorin". Science. 176 (4039): 1127–1129. doi:10.1126/science.176.4039.1127.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  33. ^ Ross WN, Salzberg BM, Cohen LB, Davila HV (1974). "A large change in dye absorption during the action potential". Biophysical Journal. 14 (12): 983–986. doi:10.1016/S0006-3495(74)85963-1.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  34. ^ Grynkiewicz G, Poenie M, Tsien RY (1985). "A new generation of Ca2+ indicators with greatly improved fluorescence properties". J. Biol. Chem. 260: 3440–3450.{{cite journal}}: CS1 maint: multiple names: authors list (link)


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