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settings.py
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settings.py
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###############################################################################
## Setting-up, initial conditions, options ####################################
###############################################################################
def setup():
InputOptions = ['Multitrial', 'Svoboda']
# Multitrial uses PSTH data collected by Aguilar & Castro-Alamancos ("Spatiotemporal Gating of Sensory Inputs in Thalamus during Quiescent and Activated States", J. Neurosci. 2005)
# Svoboda loads spike trains generated by the matlab model, based on whisker recordings (Svoboda dataset) and barreloids' filtering models
Input = {'Option' : 'Multitrial',
'Folder' : 'ReadingData_Aguilar',
'Filename' : 'psth.dat'}
# Input = {'Option' : 'Svoboda',
# 'Folder' : 'InstantiatedModel',
# 'Filename' : 'Test_sim_Svoboda_xxx_Thalamic_Spike_Trains.mat'}
Model = {'Folder' : 'InstantiatedModel',
'PreModel' : 'CMDMs_forNetPyNe1.mat',
'FullModel' : 'CMDMs_forNetPyNe1_ConData.mat'}
Ntrials = 50 # number of trials (different inputs)
Nrepetitions = 5 # repetitions of an unique input condition
ExperimConds = {'Ntrials' : Ntrials,
'Nrepetitions' : Nrepetitions}
vr = -60 # resting potential, also sets the initial condition
v0 = -70
u0 = 0 # recovery variable
dyn_thres = 1 # 0: normal izhikevich model - 1: adaptative threshold (Huang et al, "Adaptive Spike Threshold Enables Robust and Temporally Precise Neuronal Encoding", PLoS Comp. Biol. 2016)
tau_plas = 120.0 # plasticity - STD
fr = 1.00 # Fraction of recurrent connections - Useful for setting-up sims
Settings = {'vr' : vr,
'v0' : v0,
'u0' : u0,
'dyn_thres' : dyn_thres,
'tau_plas' : tau_plas,
'fr' : fr}
return Input, Model, ExperimConds, Settings