Retinal ganglion cells responses and activity (Tsai et al 2012, Guo et al 2016)

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Accession:260653
From the abstracts: "Retinal ganglion cells (RGCs), which survive in large numbers following neurodegenerative diseases, could be stimulated with extracellular electric pulses to elicit artificial percepts. How do the RGCs respond to electrical stimulation at the sub-cellular level under different stimulus configurations, and how does this influence the whole-cell response? At the population level, why have experiments yielded conflicting evidence regarding the extent of passing axon activation? We addressed these questions through simulations of morphologically and biophysically detailed computational RGC models on high performance computing clusters. We conducted the analyses on both large-field RGCs and small-field midget RGCs. ...", "... In this study, an existing RGC ionic model was extended by including a hyperpolarization activated non-selective cationic current as well as a T-type calcium current identified in recent experimental findings. Biophysically-defined model parameters were simultaneously optimized against multiple experimental recordings from ON and OFF RGCs. ...
References:
1 . Guo T, Tsai D, Morley JW, Suaning GJ, Kameneva T, Lovell NH, Dokos S (2016) Electrical activity of ON and OFF retinal ganglion cells: a modelling study. J Neural Eng 13:025005 [PubMed]
2 . Tsai D, Chen S, Protti DA, Morley JW, Suaning GJ, Lovell NH (2012) Responses of retinal ganglion cells to extracellular electrical stimulation, from single cell to population: model-based analysis. PLoS One 7:e53357 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Synapse; Extracellular;
Brain Region(s)/Organism: Retina;
Cell Type(s): Retina ganglion GLU cell;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Oscillations; Activity Patterns; Development;
Implementer(s): Tsai, David [d.tsai at unsw.edu.au];
Search NeuronDB for information about:  Retina ganglion GLU cell;
function [E Ec] = potential(elecRad, stimX, stimY, stimZ, x, y, z)
% Calculates the voltage potential at position (x, y, z) for a disk electrode
% of radius `elecRad' positioned at location (stimX, stimY, stimZ). All inputs 
% are in um. 
%
% NOTE: THE FOLLOWING PROCEDURE IS INCORRECT. EDGE EFFECT IS FOR CURRENT, NOT 
% VOLTAGE.
% Besides the constant voltage model of the electrode, we also add a correction 
% factor, which scales up with electrode radius, to correct for the electrode
% field non-uniformity. The result is an envelop around the edge of the 
% electrode with stronger voltage field than otherwise. The magnitude is 
% dependent on the electrode time constant, which is tau = delta*pi*a / 4k, 
% where a is the electrode radius (cf. Behrend08). Currently this is calibrated 
% for 0.1 ms pulses.
% END INCORRTECT STUFF
% 
% Returns results in (`E') and with edge-effect correction in (`Ec').
% standard voltage field waaveform, as in Greenberg99


r = sqrt( (x-stimX).^2 + (y-stimY).^2 );
geo = (2*elecRad) ./ ...
    ( sqrt((r-elecRad).^2+(z-stimZ).^2) + sqrt((r+elecRad).^2+(z-stimZ).^2) );

% gaussian correction ring for edge-effect
a = elecRad*0.0001;  % amplitude of edge effect
b = elecRad*0.45;    % peak point of edge effect
c = elecRad*0.20;    % width of edge effect
edgeCor = 1 + a * exp( -((r-b).^2 / (2*c^2)) );

% without and with correction
E = 2 ./ pi * (asin(geo));
Ec = 2 ./ pi * (asin(geo) * edgeCor) - a;


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