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Bursting Neurons Lecture 10

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Bower and Beeman, 1998, The Book of Genesis, second edition, TELOS, ISBN: 0-387-94938-0 ... Koch, 2004, Biophysics of Computation, OUP. ... – PowerPoint PPT presentation

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Title: Bursting Neurons Lecture 10


1
Bursting Neurons(Lecture 10)
  • Harry R. Erwin, PhD
  • COMM2E
  • University of Sunderland

2
Resources
  • Bower and Beeman, 1998, The Book of Genesis,
    second edition, TELOS, ISBN 0-387-94938-0
  • Rieke et al, 1999, Spikes Exploring the Neural
    Code, Bradford Books.
  • Shepherd, G., ed., 2004, The Synaptic
    Organization of the Brain, 5th edition, Oxford
    University Press.
  • Nicholls et al.
  • Kandel et al.
  • Koch, 2004, Biophysics of Computation, OUP.
  • Koch and Segev, 1998, Methods in Neuronal
    Modelling, 2nd edition, MIT Press.
  • Churchland and Sejnowski, 1994, The Computational
    Brain, Bradford Books.

3
The Platonic neuron
  • Consists of a soma, one or more dendrites, and an
    axon
  • Any of these elements may be missing
  • You can also have binary neurons where a dendrite
    is axon-like. These can signal bi- or
    unidirectionally

Apical Dendrite
Soma
Basal Dendrite
Axon and Axon Collateral
4
More complex biologically relevant neurons
  • Characterised by wide variation in firing
    patterns
  • Often make use of active conductances in the
    dendritic tree, which serve to amplify PSPs
    generated there and send them over longer
    electrotonic distances.
  • Many different ion channel types
  • The HH model found in the squid is particularly
    simple, serving to conduct regular neural
    impulses rapidly.

5
Physiological behaviour of the neuron
  • Determined by the types of conductances found in
    its membranes and its topological structure.
  • These experiments will address how periodic
    bursts of action potentials can be generated.
  • This behaviour is found in molluscan pacemaker
    neurons and in the CA3 pyramidal neurons of the
    mammalian hippocampus.

6
Molluscan neurons
  • R3 beater neuron
  • R15 regular burster
  • L10 irregular burster
  • (from Kandel via Bower and Beeman)

7
Periodicity
  • Often entirely endogenous to a neuron, persisting
    when the soma is isolated. These are termed
    pacemakers, responsible for controlling highly
    regular behaviour that is only moderately
    regulated.
  • Other neurons generate a periodic signal in
    response to inputconditional bursters.
  • In the cortex, dopamine and GABA seem to be able
    to turn this on and off.

8
Control of periodicity
  • Uses channels qualitatively similar to the Na
    and K channels in the HH model.
  • Shape and firing patterns influenced by other
    channels and their interactions.
  • Conductances for Ca and Cl- exist.
  • Activation and inactivation is more complex than
    for the HH model.
  • Voltage and ligand-sensitive channels are also
    important.
  • Finally, time constants vary greatly

9
Dance of the ions
10
Ionic conductances
  • Nominal resting potential of -40 mV
  • Reaches 0 mV during the action potential
  • The model molluscan neuron includes
  • Fast Na currents
  • Delayed K currents
  • High-threshold Ca currents
  • Slow inward B-current (Na/Ca)
  • Calcium dependent K C-current
  • Transient K A-current

11
Details
  • Fast Na currents, associated with AP generation.
    Do not inactivate for hyperpolarisation.
  • Delayed K currents, associated with APs and
    repolarisation. Delayed rectifier current.
  • High-threshold Ca currents, activated by APs.
    These channels trigger transmitter release.
  • Slow inward B-current (Na/Ca). Produces a
    sustained depolarisation. Burst current.
    Creates the burst region.
  • Calcium dependent K C-current. Produces a slow
    hyperpolarisation and an inward Ca current.
    Ends the burst. In mammals shifted lower (and
    called the T-current).
  • Transient K A-current, maintaining
    hyperpolarisation and delaying the next AP in
    pacemaker neurons. Primitive.

12
Adrift in parameter space
  • Experiments are often insufficient to provide all
    the parameters needed.
  • Approach
  • Build a correct compartmental model
  • Add passive membrane properties
  • Incorporate active channels based on experimental
    evidence
  • Search parameter space for solutions, taking
    advantage of the different time scales for
    subsystems.

13
Research opportunities
  • I have been funded by EPSRC for a large-scale
    computational model of the inferior colliculus, a
    part of the auditory system
  • We have opportunities for MSc-level projects
    associated with elements of the modelling.
  • This will involve work similar to that described
    here, and also with exploiting those results in
    robotics and linguistics applications.
  • Interested?
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