Sparse random connected Balanced Neural Network Network architecture:
reference: Brunel N. Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons. J Comput Neurosci. 2000 May-Jun;8(3):183-208. doi: 10.1023/a:1008925309027. PMID: 10809012.
Balanced Neural Network.py simulats a balanced neural network by Brian simulator.
"""
sim(g, nu_ext_over_nu_thr, sim_time, ax_spikes, ax_rates, rate_tick_step):
g -- relative inhibitory to excitatory synaptic strength
nu_ext_over_nu_thr -- ratio of external stimulus rate to threshold rate
sim_time -- simulation time
ax_spikes -- matplotlib axes to plot spikes on
ax_rates -- matplotlib axes to plot rates on
rate_tick_step -- step size for rate axis ticks
"""
example:
"A": { "g": 3, "nu_ext_over_nu_thr": 2, "t_range": [500, 600], "rate_range": [0, 6000], "rate_tick_step": 1000,
"B": { "g": 2, "nu_ext_over_nu_thr": 4, "t_range": [1000, 1200], "rate_range": [0, 400], "rate_tick_step": 100, },
"D": {
"g": 4.5,
"nu_ext_over_nu_thr": 0.9,
"t_range": [1000, 1200],
"rate_range": [0, 250],
"rate_tick_step": 50,
},
