ModelDB: Reverse-time correlation analysis for idealized orientation tuning dynamics (Kovacic et al. 2008)

Reverse-time correlation analysis for idealized orientation tuning dynamics (Kovacic et al. 2008)

Accession: 117514

"A theoretical analysis is presented of a reverse-time correlation method used in experimentally investigating orientation tuning dynamics of neurons in the primary visual cortex. An exact mathematical characterization of the method is developed, and its connection with the Volterra–Wiener nonlinear systems theory is described. Various mathematical consequences and possible physiological implications of this analysis are illustrated using exactly solvable idealized models of orientation tuning."
Reference: Kovacic G, Tao L, Cai D, Shelley MJ (2008) Theoretical analysis of reverse-time correlation for idealized orientation tuning dynamics. J Comput Neurosci 25:401-38 [PubMed]

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Model Information (Click on a link to find other models with that property)

Model Type:
Brain Region(s)/Organism:	Neocortex;
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment:	MATLAB;
Model Concept(s):	Methods;
Implementer(s):	Kovacic, Gregor [kovacg at rpi.edu];

Model files

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This the readme for models associated with the publication

Kovacic G, Tao L, Cai D, Shelley MJ (2008) Theoretical analysis of
reverse-time correlation for idealized orientation tuning dynamics.
J Comput Neurosci 25:401-38 

These model files were supplied by Dr Kovacic.

Matlab routines are included that I used to compute the RTC function (Fig. 3,
Fig. 8 left), the scaled and superimposed time- slices of the RTC
function (Fig. 8 right), and the parameter dependence of the location
and size of the maxima and minima associated with the "Mexican hat"
shapes.  The codes for the maxima and minima are very raw, and
unfortunately I don't have the time to rerun them and document them
better.  I'm also appending some data that I obtained for the paper.

Example run:

By starting matlab and typing rtcfnpub after cd'ing to the Plot_Tuning_Curve
directory results in the figures similar to Fig 3 from the paper:

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