22 Aug
2023
22 Aug
'23
5:05 p.m.
Hi,
No problem. The step current generator isn't showing any effect, because the first
timepoint of the current generator (in ``amplitude_times``) is set to 1000, and you're
also simulating for 1000 ms, so the simulation ends too soon (or the amplitude timepoint
should be set earlier).
As for the spiking behaviour, this is because of the way the NESTML model is formulated.
When the neuron reaches threshold, a spike is emitted, but the membrane potential is not
reset to a large negative value (like E_L), so it stays above threshold and the condition
remains active, triggering more spikes to be emitted. You can add the reset to make this
issue go away. If this reset is undesirable (because it does not match the way your model
should behave), the test that finds the peak in V_m should be improved, for instance by
storing one more "old" version of V_m as the model currently does on line 197.
Hope this helps!
Yours,
Charl
On Tue, Aug 22, 2023, at 15:47, atiye nejadebrahim wrote:
Hello Hans,
This is the scripts with step_current_generator that can't generate spikes:
*import numpy as np*
*import nest*
*import shelve*
*import matplotlib.pyplot as plt*
*nest.Install('hh_motor_neuron_module')*
*neuron=nest.Create('hh_motor_neuron_nestml',1) #{'I_e':1000})*
**
*scg1 = nest.Create("step_current_generator", 1, params={*
* "amplitude_times": [1000],*
* "amplitude_values": [2000],*
*})*
**
*mm1 = nest.Create("multimeter", 1, params={*
* "interval": .1,*
* "start": 0,*
* "stop": 1000,*
* "record_from": ["I"],*
*})*
**
*multimeter = nest.Create("multimeter",
params={'record_from':['V_m'],'interval': .1})*
*spikerecorder = nest.Create("spike_recorder")*
*spike_times = nest.GetStatus(spikerecorder, keys='events')[0]['times']*
**
*nest.Connect(multimeter, neuron)*
*nest.Connect(neuron, spikerecorder)*
*nest.Connect(scg1, neuron)*
*nest.Connect(mm1, scg1)*
**
*sim_time = 1000.0 # Simulation time in milliseconds*
*dt = 0.1 # Simulation time step in milliseconds*
*nest.Simulate(sim_time)*
**
*fig, ax = plt.subplots(nrows=2)*
*ax[0].plot(multimeter.get("events")["times"],
multimeter.get("events")["V_m"])*
*ax[1].plot(mm1.get("events")["times"],
mm1.get("events")["I"])*
*ax[0].scatter(spike_times, np.zeros_like(spike_times), marker="d",
c="orange", alpha=.8, zorder=99)*
*ax[0].set_ylabel("v [mV]")*
*ax[1].set_ylabel("I")*
*ax[-1].set_xlabel("Time [ms]")*
*fig.show()*
*plt.show(block=True)*
**
this is the code with injecting I_e that generates asysnchronous outputs between spikes
and AP:
*import numpy as np*
*import nest*
*import shelve*
*import matplotlib.pyplot as plt*
**
*nest.Install('hh_motor_neuron_module')*
**
*neuron=nest.Create('hh_motor_neuron_nestml',1, {'I_e':2000})*
**
*multimeter = nest.Create("multimeter",
params={'record_from':['V_m'],'interval': .1})*
**
*spikerecorder = nest.Create("spike_recorder")*
**
*spike_times = nest.GetStatus(spikerecorder, keys='events')[0]['times']*
**
*nest.Connect(multimeter, neuron)*
*nest.Connect(neuron, spikerecorder)*
**
*sim_time = 1000.0 # Simulation time in milliseconds*
*dt = 0.1 # Simulation time step in milliseconds*
*nest.Simulate(sim_time)*
**
*dmm = multimeter.get()*
*Vms = dmm["events"]["V_m"]*
*ts = dmm["events"]["times"]*
*plt.figure(1)*
*plt.plot(ts, Vms)*
*events = spikerecorder.get("events")*
the .nestml neuron model is attached. however it is clear in 'hh_psc_alpha'
model, too.
On Tuesday, August 22, 2023 at 03:33:35 PM GMT+2, Hans Ekkehard Plesser
<hans.ekkehard.plesser(a)nmbu.no> wrote:
Hello Atiye,
Please post a script that reproduces the behavior you describe. Without it, it is
impossible to provide good advice.
Best,
Hans Ekkehard
--
Prof. Dr. Hans Ekkehard Plesser
Department of Data Science
Faculty of Science and Technology
Norwegian University of Life Sciences
PO Box 5003, 1432 Aas, Norway
Phone +47 6723 1560
Email hans.ekkehard.plesser(a)nmbu.no
Home http://arken.nmbu.no/~plesser
*From: *atiye nejadebrahim <atiye.nejadebrahim(a)yahoo.com>
*Date: *Tuesday, 22 August 2023 at 14:12
*To: *NEST User Mailing List <users(a)nest-simulator.org>
*Subject: *[NEST Users] asynchronicity between spikes and firing pattern
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Dear All,
I made a HH neuron model and I can get an action potential from it. but it seems there is
a problem in spikes. Action potential shape show one spike, but spike recorder shows
several spikes and there is not any synchronicity between them. can you help me why?
my second question is about spike generation, when I use I_e current for injecting
current to the neuron, I can record spikes, but when I use step current generators, no
spike shows. can you help me why?
Thank you for your consideration.
Best,
Atiyeh
Inline image
Dear All,
I made a HH neuron model and I can get an action potential from it. but it seems there is
a problem in spikes. Action potential shape show one spike, but spike recorder shows
several spikes and there is not any synchronicity between them. can you help me why?
my second question is about spike generation, when I use I_e current for injecting
current to the neuron, I can record spikes, but when I use step current generators, no
spike shows. can you help me why?
Thank you for your consideration.
Best,
Atiyeh
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*Attachments:*
• hh_motor_neuron.nestml
