Modeling dendritic spikes and plasticity (Bono and Clopath 2017)

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Accession:232914
Biophysical model and reduced neuron model with voltage-dependent plasticity.
Reference:
1 . Bono J, Clopath C (2017) Modeling somatic and dendritic spike mediated plasticity at the single neuron and network level. Nat Commun 8:706 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Realistic Network;
Brain Region(s)/Organism:
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: Brian 2; Python;
Model Concept(s): Synaptic Plasticity; STDP; Dendritic Action Potentials;
Implementer(s): Bono, Jacopo [ j.bono13 at imperial.ac.uk];
from __future__ import division
import numpy as np


def  f_create_spiketrain_var2(Rates, timeStep):
    #induce spikes: 
    #   induce Poisson-distributed spikes and regular spikes
    
    train = np.zeros(np.shape(Rates))
    
    # avoid dividing by 0
    Rates[Rates==0] = 0.0000001
    
    ### Poisson-distributed spikes ###
    r = np.divide(np.random.rand(np.size(Rates,axis=0),np.size(Rates,axis=1))*(1000/timeStep),Rates)
    train[r<1] = 1
    
    return train
    
    

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