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Flashcards

Individual Neurons

unknown_girl Cognitive Neural Networks University Inglês 12 flashcards

Individual Neurons

Flashcards do conjunto (12)

  1. 1—Vm= membrane potential
    Dtvm = time constant
    Ee - Vm(t) - net potential
    Ge(t) = fraction of e channel open at time t
    G_i = max conductance if channel fully open
    Vm= membrane potential Dtvm = time constant Ee - Vm(t) - net potential Ge(t) = fraction of e channel open at time t G_i = max conductance...
  2. 2When is Inet 01) If current travelling on all channels are stable - cancel each other out
    2) At resting
  3. 3—El = equilibrium potential for channel l (leak)
    Gl g_l El = leak conductance of overall conductance
    El = equilibrium potential for channel l (leak) Gl g_l El = leak conductance of overall conductance
  4. 4—yj = activation value
    (-) = threshold
    Y - gain parameter (larger - steeper)
    yj = activation value (-) = threshold Y - gain parameter (larger - steeper)
  5. 5What is the membrane potential?The net result is an electric potential difference between inside and outside of the cell
  6. 6What is the equilibrium channel potential?Amount of electrical potential needed to counteract diffusion
  7. 7What does I= G(V)?Equilibrium potential
    I - channel
    G - conductance
    V - voltage
  8. 8What is the difference between ANN vs Point NeuronsANN - a single neuron can have excitatory and inhibitory links and weights can change through learning
    Point neurons - Excitatory or inhibitory - converted to Vm then further function outputs
  9. 9What is the problem with XX1 function?Discrete spiking rates are highly noises and spiking is unpredictable. Change to Noisy XX1 function
  10. 10What does resting mean?Resting is where the neuron will stabilise if there is no external activation for a long period of time
  11. 11What is the refractory period?The suppression of a neuron (below resting) following firing.
  12. 12What is the rate code output function?A reasonable approximation to the output of an emsemble of neurons rather than a single neuron

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Descrição
University Cognitive Neural Networks FlashCards sobre Individual Neurons, criado por unknown_girl em 07-05-2014.
Criado por
unknown_girl · mai 2014
Atualizado
19 fev 2016
Visualizações
11
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