Code to calc. spike-trig. ave (STA) conduct. from Vm (Pospischil et al. 2007, Rudolph et al. 2007)

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Accession:116086
PYTHON code to calculate spike-triggered average (STA) conductances from intracellular recordings, according to the method published by Pospischil et al., J Neurophysiol, 2007. The method consists of a maximum likelihood estimate of the conductance STA, from the voltage STA (which is calculated from the data). The method was tested using models and dynamic-clamp experiments; for details, see the original publication (Pospischil et al., 2007). The first application of this method to experimental data was from intracellular recordings in awake cat cerebral cortex (Rudolph et al., 2007).
References:
1 . Pospischil M, Piwkowska Z, Rudolph M, Bal T, Destexhe A (2007) Calculating event-triggered average synaptic conductances from the membrane potential. J Neurophysiol 97:2544-52 [PubMed]
2 . Rudolph M, Pospischil M, Timofeev I, Destexhe A (2007) Inhibition determines membrane potential dynamics and controls action potential generation in awake and sleeping cat cortex. J Neurosci 27:5280-90 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Synapse;
Brain Region(s)/Organism:
Cell Type(s): Abstract integrate-and-fire leaky neuron;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: Python;
Model Concept(s): Methods; Sleep; Activity Patterns;
Implementer(s): Destexhe, Alain [Destexhe at iaf.cnrs-gif.fr]; Pospischil, Martin ;
/
demo_STA
readme.txt
ge_sta.txt
gi_sta.txt
header.py
main.py
methods.py
vm_sta.txt
                            
###################################################################
#  STA analysis                                                   #
#                                                                 #
#  based on the publication                                       #
#                                                                 #
#  Martin Pospischil, Zuzanna Piwkowska, Michelle Rudolph,        #
#  Thierry Bal and Alain Destexhe "Calculating Event-Triggered    # 
#  Average Synaptic Conductances From the Membrane Potential",    #
#  J Neurophysiol 97:2544-2552, 2007.                             #
#                                                                 #
###################################################################

This application performs a conductance analysis of spike-triggered 
average voltage traces. A file containing this voltage STA is 
loaded, and a short adjustable interval before the spike is removed 
from the trace. If necessary, the voltage STA can be smoothed in 
order to minimise the effect of recording noise. All parameters are 
provided by the file 'header.py', the call 'python main.py' from 
the system prompt starts the analysis. The time courses of the 
excitatory and inhibitory STAs are then written to the files 
'ge_sta.txt' and 'gi_sta.txt', respectively. In order for this to 
work, the python scripting language along with the packages 
'Numeric' and 'pylab' need to be installed.

Modifications need only be done to the 'header.py'-file. The 
adjustable parameters contained therein are as follows:

vmFile      -   file containing the voltage STA in a single column
dt          -   time step (inverse of sampling frequency) in ms
t_cut       -   length of interval before spike in ms that is       
                removed from the analysis
n_smooth    -   SD in timesteps of the Gaussian filter that is used 
                for smoothing
Iext        -   current level in nA
ge          -   mean of exc. conductance distribution in uS
gi          -   mean of inh. conductance distribution in uS
se          -   standard deviation (SD) of exc. conductance 
                distribution in uS
si          -   SD of inh. conductance distribution in uS
gl          -   leak conductance in uS
vl          -   leak reversal potential in mV
cap         -   capacitance in nF
te          -   correlation time constant of excitation in ms
ti          -   correlation time constant of inhibition in ms
ve          -   reversal potential of excitation in mV
vi          -   reversal potential of inhibition in mV

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