Parameter dictionary

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Default parameters for Two population STDP network model (TwoPopulationNetworkPlastic)

pars = {}

pars["model_name"] = "TwoPopulationNetworkPlastic"  # Network model name

# network and connectivity parameters
pars["N"] = 12500  # total number of neurons
pars["K"] = 1250  # total number of inputs per neuron from local network
pars["beta"] = 0.8  # fraction of excitatory neurons/inputs

pars["allow_autapses"] = False
pars["allow_multapses"] = True

# neuron parameters

# pars["neuron_model"] = "iaf_psc_alpha"
pars["neuron_model"] = "ignore_and_fire"

pars["E_L"] = 0.0  # resting membrane potential(mV)
pars["C_m"] = 250.0  # membrane capacity (pF)
pars["tau_m"] = 20.0  # membrane time constant (ms)
pars["t_ref"] = 2.0  # duration of refractory period (ms)
pars["theta"] = 20.0  # spike threshold(mV)
pars["V_reset"] = 0.0  # reset potential(mV)

# needed for ignore_and_fire version of the model
pars["ignore_and_fire_pars"] = {}
pars["ignore_and_fire_pars"]["rate_dist"] = [0.5, 1.5]
pars["ignore_and_fire_pars"]["phase_dist"] = [0.01, 1.0]

# stimulus parameters
pars["I_DC"] = 0.0  # (constant) external input current (pA)
pars["eta"] = 1.2  # rate of external Poissonian sources relative to threshold rate

# synapse parameters
pars["J_E"] = 0.5  # EPSP amplitude (mV)
pars["g"] = 10.0  # relative IPSP amplitude (JI=-g*JE)
pars["delay"] = 1.5  # spike transmission delay (ms)
pars["tau_s"] = 2.0  # synaptic time constant (ms)

pars["stdp_alpha"] = 0.1  # relative magnitude of weight update for acausal firing
pars["stdp_lambda"] = 20.0  # magnitude of weight update for causal firing
pars["stdp_mu_plus"] = 0.4  # weight dependence exponent for causal firing
pars["stdp_tau_plus"] = 15.0  # time constant of weight update for causal firing (ms)
pars["stdp_tau_minus"] = 30.0  # time constant of weight update for acausal firing (ms)
pars["stdp_w_0"] = 1.0  # reference weight (pA)

# initial conditions
pars["V_init_min"] = pars["E_L"]  # min of initial membrane potential (mV)
pars["V_init_max"] = pars["theta"]  # min of initial membrane potential (mV)

# data recording
pars["record_spikes"] = False  # if True: set up spike detectors and record spikes
pars["N_rec_spikes"] = "all"  # number of neurons to record spikes from; if "all", spikes from all neurons are recorded

# pars["record_weights"] = False           # True: record weights of plastic synapses
# pars["weight_recording_start_time"] = 0. # start time of weight recording (ms)

# simulation parameters
pars["T"] = 10000.0  # simulation time
pars["dt"] = 2**-3  # simulation resolution (ms)  !!! revise documentation (incl delay)
pars["tics_per_step"] = 2**7  # number of tics per time step (defines resolution of time variables in NEST)
pars["seed"] = 1  # seed for random number generator
pars["n_threads"] = 4  # number of threads for simulation
# (note: varying the number of threads leads to different random-number sequences,
# and, hence, to different results)

pars["print_simulation_progress"] = True  # print network time and realtime factor
pars["nest_verbosity"] = "M_WARNING"  # "M_FATAL", "M_ERROR", "M_WARNING", "M_DEPRECATED", "M_INFO", "M_ALL"

pars["data_path"] = "data"