How to find all the "spiking times" for a single neuron out of several neurons from a Spiking Neural Network?

Description of problem

If I generate a Spiking Neural Network(SNN) which consists of multiple neurons ,from BRIAN2 simulator I can easily find the “spike times” and corresponding neuron indexes.**Out of several neurons if I wish to get all the spike times for a particular neuron, how can I find it apart from manual observation of the result? **.Because for small SNN network I can manually collect all the spiking time information for a particular neuron, but say for a network consists 5000 neuron if I want to know all the spiking times of a single neuron (say," neuron 2001") ,manual calculation is very difficult.

Minimal code to reproduce problem

from brian2 import *
%matplotlib inline
eqs = ‘’’
dv/dt = (1-v)/tau : 1
G = NeuronGroup(8,eqs,threshold=‘v>vt’,reset=‘v=0.0’,method=‘euler’)
G.v=[0.1 ,0.3,0.4,0.5,0.6,0.7,0.8,0.9]

What you have aready tried

with the above code if I add following two lines

it shows the “first spike time” for neuron 5,but how to get rest of the spiking times for neuron 5?
Expected output (if relevant)

Actual output (if relevant)

Full traceback of error (if relevant)

To access all the spike times for a neuron with a certain index, you can use numpy’s boolean indexing functionality. E.g. to get all the spike times for the neuron for index 5, you can use R.t[R.i == 5]. If you need to do this for all/many of the neurons, a more efficient method is to use the SpikeMonitor's spike_trains() method. It will return you a dictionary of spike times per neuron, which you can then access to get all the spike times for a certain neuron:

spike_times = R.spike_trains()
print(spike_times[5])  # spike times for neuron with index 5

A lot of thanks sir. I have understood.