EI conductance based balanced network with exponential synapses

Dear All,

I tried to simulate an EI network using almost the same parameters as provided in @neuromatchacademy (W3D1) in the tutorial part but unfortunately, the network doesn’t generate natural rhythms. Here are all the parameters I used via NEST simulator:

"NE”, ”1000” #number of E neurons
"NI”, ”250” #number of I neurons
"CI”, ”25” #number of I connections
"CE”, ”100” #number of E connections
"tauMem”,”10.0” #membrane time constant
"J_ex”, 6 #excitatory connection weight
"J_in”, -36 #inhibitory connection weight
"p_rate”, 10 #poisson rate
"delay”, 2.5 #synaptic delay
"tau_syn_ex”,2 #synaptic decay time of E neurons
"tau_syn_in”,5 #synaptic decay time of I neurons
"V_th”, -55
"g_L”, 10
"V_init”, -65
"E_e”, 0
"E_I”, -80
"E_L”, -75
"tref”, 2

And this is the raster plot of 1000 ms of simulation:

Notes: I tried to play with the parameters but I still get the same results. One of the ways that I could get realistic results was setting:
"tau_syn_ex”, 0.3 #synaptic decay time of E neurons
"tau_syn_in”, 0.5 #synaptic decay time of I neurons

But these parameters are not even close to biological parameters of neuron so I cannot use them really.

Can anyone tell me what’s that I’m doing it wrong, please?

Nosratullah Mohammadi

Hi Nosratullah Mohammadi,

Which model do you use for representing each neuron?
The behavior of the network do not only depends on the “connections” between each neuron model.
What do you expect as a “realistic result”?