Modeling dendritic spikes and plasticity (Bono and Clopath 2017)

 Download zip file 
Help downloading and running models
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_Inpt_x(Pre_spikes,input_x,Neuron_par,timeStep):
#Calculate evolution of spike trace (inputs)

    #######################
    # Parameters
    #######################
    x_tau = Neuron_par[8] #timeconstant for spiketrace
    x_reset = Neuron_par[9]/x_tau # reset value for spiketrace    
    
    ##############
    # x_trace
    ##############         
    
    ### x (spike trace) ###
    input_x = input_x - (timeStep/x_tau)*input_x + Pre_spikes*x_reset
    
    return input_x
    
    

Loading data, please wait...