ltpi_apply
LTPI_APPLY Spike-timing dependent-plasticity for calculating changes in synaptic weights
WEIGHT = LTPI_APPLY(SPIKETIMES_PRE, SPIKETIMES_POST)
Calculates the change in synaptic weight due to the "veto" long
term potentiation of inhibition rule based on the experimental
data of Maffei et. al 2006 (Nature) and on the equations in
Bourjaily and Miller 2011 (Frontiers in Computational Neuroscience).
For all presynaptic (inhibitory) spikes, we look to see if there
is a postsynaptic spike in the interval [t_pre-tau_minus,
tpre+tau_plus]. If so, there is an inhibitory potentiation:
weight = weight + dIW
WEIGHT is a factor that indicates how the maximumal
conductance is modified.In Song and Abbott (2001), the synaptic
conductance was modified by the following forumla:
G -> G + G_max * WEIGHT
Only spikes that occur at or after the time T0 will be examined for STDP.
By default, T0 is 0. (One could use this to restrict the influence
of STDP to spike pairs where at least one member of the pair occurs
after a particular time.)
Normally, we do not know what additional spikes are coming in the future.
The code assumes that we only know up to time of the latest spike in
the 2 trains. (That is, if an inhibitory spike is the last spike to occur,
and it has no postsynaptic partners, then we do not yet know if it will
generate a potentiation event. One can explicitly set T1 to indicate
the latest time that we have information for (which might be later than
the latest spike time).
The parameters of the synapse can be varied by providing additional
inputs as name, value pairs. The names and values that are default are
shown here. For example,
WEIGHT = LTPI_APPLY(SPIKETIMES_PRE, SPIKETIMES_POST, 'tau_plus',0.050)
Parameter name: | default value
------------------------------|-----------------------------
tau_plus | 0.020 (units are same as spiketimes)
tau_minus | 0.020
dIW | 0.001 (a 1% change)
T0 | 0
T1 | max(spiketimes_pre(end),spiketimes_post(end))