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Synaptic plasticity can produce and enhance direction selectivity (Carver et al, 2008)
Accession: 116901
" ... We propose a parsimonious model of motion processing that generates direction selective responses using short-term synaptic depression and can reproduce salient features of direction selectivity found in a population of neurons in the midbrain of the weakly electric fish Eigenmannia virescens. The model achieves direction selectivity with an elementary Reichardt motion detector: information from spatially separated receptive fields converges onto a neuron via dynamically different pathways. In the model, these differences arise from convergence of information through distinct synapses that either exhibit or do not exhibit short-term synaptic depression—short-term depression produces phase-advances relative to nondepressing synapses. ..."
Reference: Carver S, Roth E, Cowan NJ, Fortune ES (2008) Synaptic plasticity can produce and enhance direction selectivity. PLoS Comput Biol 4:e32 [PubMed]
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type:  Network;
Brain Region(s)/Organism:  
Cell Type(s):   Electric fish midbrain torus semicircularis neuron;
Channel(s):   
Gap Junctions:  
Receptor(s):  
Gene(s):  
Transmitter(s):  
Simulation Environment:  MATLAB;
Model Concept(s):  Oscillations; Depression; Direction Selectivity;
Implementer(s):  Carver, Sean [sean.carver at jhu.edu];
\
carver
model
params
plots
stimuli
util
README.html
fig2B.jpg
startup.m
                            
README file for CODE to accompany Carver, et al., PLoS Computational Biology

Steps to plot Figure 2:

1. Start Matlab in CARVER directory.  Matlab calls startup.m, setting path.
2. Type "genallplots" to plot Figure 2.

This generates the two subpanels, for example figure 2 B looks like:

figure 2 B

Examples running model (after startup.m is called automatically or manually)

out = dirsel;  % default parameters, sine grating stimulus, preferred direction
out = dirsel(afferents(20,30));  % 20 depressing, 30 nondepressing afferents
out = dirsel(nonpref); % sine-grating stimulus, non-preffered direction
out = dirsel(pulse); % pulse stimulus, preferred direction
out = dirsel(nonpulse); % pulse stimulus, non-preferred direction

Note that parameters can be combined in any order:

out = dirsel(pulse, afferents(10,30));
out = dirsel(afferents(40,25), nonpulse);

Also note that any parameter defined before the "replace" statement in
dirsel.m can be changed on command line when dirsel is called: 

Eg:
out = dirsel('tau_D',100,'tau_S',2000);
out = dirsel('d',0.5,'s',0.98,afferents(20,30),nonpulse);

To view a list of model parameters with default values: execute "type dirsel".

To plot results of any of above simulations:

plot(out.time,out.V) % plots membrane potential (V_infty)
plot(out.time,out.D) % plots state variable D
plot(out.time,out.S) % plots state variable S
plot(out.time,out.F) % plots firing rate F;
P = extracellplot(out.time,find(out.AP)); plot(P{:}) % plots action potentials

To plot an image of the stimulus pass imageflag = 1, e.g.

img = dirsel(pulse,'imageflag',1); image(img)
img = dirsel(nonpref,'imageflag',1); image(img)


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