Excellent question. Intfire1 is an artificial spiking cell with sufficiently simple dynamics that its future behavior is analytically predictable from its present state. Consequently there is no need for numerical integration, and no need to update its state variables at each time step. The only time computation must be done is when it receives a new event, and this is handled by the NET_RECEIVE block.*shyam_u2 wrote:In the spikeout.mod file, what is the use of Break point block and the conductance variable g. I dont see a similar thing in Intfire1 class neuron.
Why is what value clamped at 100?shyam_u2 wrote:But why it is clamped at 100 ?
What value are you modifying?when i modify its value to some other number
What did you expect would change?it doesn't produce any change.
The COBA cell, however, is a "conductance based" model, i.e. its synaptic inputs actually produce conductance changes, generating currents that are integrated by membrane capacitance
g can only affect firing rate when it is nonzero. Spike duration is fixed by the event delivery system, so g can't affect that. g equals grefrac during the relative refractory interval, but if g is much larger than all other conductances it will tend to shunt any currents they generate. Try reducing g to 1 or 0.1 and see what hapens.shyam_u2 wrote:I understand the role of g (in spikeout.mod). But What should be the ideal value of g ?
When i change the value of g from 100 to 10 it doesnt have any effect on firing rate.
The assignement statement in the BREAKPOINT block insures that SpikeOut's i is calculated at each time step.The COBA cell, however, is a "conductance based" model, i.e. its synaptic inputs actually produce conductance changes, generating currents that are integrated by membrane capacitance
Does that mean current is not computed at each time step ?
What in my earlier reply led you to infer otherwise?
Here's some more info about BREAKPOINTshyam_u2 wrote:Before u said that the BREAKPOINT block computes current at each time step, i thought that i was done so by default.
Good question. SpikeOut's INITIAL block launches a self event with flag == 3 that returns at t==0. This causes execution of a WATCH statement which causes the mechanism to monitor local v continuously throughout the simulation, so that when v crosses the specified threshold (thresh) a self event with flag 1 will be launched that returns immediately. This in turn results in execution of the code insidehow is the NET_RECEIVE block getting activated here ?
Somewhere in the source code for that model entry in ModelDB there is doubtless a pair of assignment statements that specifies the threshold and vrefrac values.In the appendix it is mentioned that threshold for the cell is -50 mV and vrefrac = -60 mv. But in the spikeout.mod file(in modelDB) i see a different threshold value and vrefrac. Yet the model(in modelDB) runs with the value as mentioned in the appendix. Why is that so
I should also mention that the hoc name of a GLOBAL parameter has the general form
regardless of whether the mechanism is a density mechanism or a point process
What does it mean to say that "another spike arrives as input"? Do you mean "what if an event is deliverd to a synaptic mechanism attached to a cell that has the SpikeOut mechanism attached to it"?shyam_u2 wrote:What will happen if another spike arrives as input when the neuron is in refractory state ?
I don't know anything about your model cell--how big it is, what other mechanisms have been inserted into your model cell, or what values you have assigned to the parameters of the SpikeOut mechanism you are using in your model cell. SpikeOut is a very simple and robust mechanism--if membrane potential rises above its threshold, SpikeOut's conductance g increases to the value specified by the parameter grefrac. As long as grefrac is much larger than any other conductance in the model, v will quickly reset to vrefrac. If vrefrac < thresh, the cell's membrane potential will be subthreshold at the end of the refractory period, so the cell will be able to fire again. If your model cell has a very large surface area, or has one or more density mechanisms with depolarized reversal potentials and high channel densities, it may be necessary to increase SpikeOut's grefrac to ensure that the model cell's v is pulled below threshold.the membrane potential of my neuron increases and reaches saturation thereby stoping it to spike
SpikeOut is not intended to be a target of a NetCon. Examine the original model's source code and you'll see that SpikeOut is used as a spike source, never as a target.But what happens when the next spike arrives ?
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