Spiking Neuron Models:
Single Neurons Populations Plasticity
Wulfram Gerstner Werner Kistler Cambridge University Press
Computational and Mathematical Modeling of Neural Systems
Peter Dayan L. F. Abbott MIT Press (parameters taken from here)
Hodgkin A. L. and Huxley A. F.
A Quantitative Description of Membrane Current
and Its Application to Conduction and Excitation in Nerve
Journal of Physiology 117 500-544 (1952)
hh_psc_alpha is an implementation of a spiking neuron using the Hodkin-Huxley formalism.
(1) Post-syaptic currents
Incoming spike events induce a post-synaptic change of current modelled
by an alpha function. The alpha function is normalised such that an event of
weight 1.0 results in a peak current of 1 pA.
(2) Spike Detection
Spike detection is done by a combined threshold-and-local-maximum search: if there
is a local maximum above a certain threshold of the membrane potential it is considered a spike.
The following parameters can be set in the status dictionary.
V_m double - Membrane potential in mV
E_L double - Resting membrane potential in mV.
g_L double - Leak conductance in nS.
C_m double - Capacity of the membrane in pF.
tau_ex double - Rise time of the excitatory synaptic alpha function in ms.
tau_in double - Rise time of the inhibitory synaptic alpha function in ms.
E_Na double - Sodium reversal potential in mV.
g_Na double - Sodium peak conductance in nS.
E_K double - Potassium reversal potential in mV.
g_K double - Potassium peak conductance in nS.
Act_m double - Activation variable m
Act_h double - Activation variable h
Inact_n double - Inactivation variable n
I_e double - Constant external input current in pA.
better spike detection
initial wavelet/spike at simulation onset