This repository contains scripts to analyze the data on local connectivity (lateral distance from soma < 500 um>) in cat primary visual cortex from
Armen Stepanyants, Judith A. Hirsch, Luis M. Martinez, Zoltán F. Kisvárday, Alex S. Ferecskó, Dmitri B. Chklovskii, Local Potential Connectivity in Cat Primary Visual Cortex, Cerebral Cortex, Volume 18, Issue 1, January 2008, Pages 13–28, https://doi.org/10.1093/cercor/bhm027
Data were privately shared. It should be added into subfolder data
'./data/Cat_Np.mat'
Raw data are a dictionary with following items:
| key | value | shape | comments |
|---|---|---|---|
| Np_int_ee | numpy array | (150, 150, 51) | Expected number of potential synapses Exc -> Exc |
| Np_int_ei | numpy array | (150, 150, 51) | Expected number of potential synapses Exc -> Inh |
| Np_int_ie | numpy array | (150, 150, 51) | Expected number of potential synapses Inh -> Exc |
| Np_int_ii | numpy array | (150, 150, 51) | Expected number of potential synapses Inh -> Inh |
| P_int_ee | numpy array | (150, 150, 51) | Probability of potential connectivity Exc -> Exc |
| P_int_ei | numpy array | (150, 150, 51) | Probability of potential connectivity Exc -> Inh |
| P_int_ie | numpy array | (150, 150, 51) | Probability of potential connectivity Inh -> Exc |
| P_int_ii | numpy array | (150, 150, 51) | Probability of potential connectivity Inh -> Inh |
| roi | numpy array | (1, 5) | |
| roe | numpy array | (1, 5) | |
| htz | numpy array | (1, 5) | borders of layers [um] |
| z_int | numpy array | (1, 150) | depth, 5 -- 1495 um |
| Rxy_int | numpy array | (1, 51) | lateral position, 0 -- 500 um |
For Np_int_XY and P_int_XZ axis are indexing
somatic depth of presynaptic cell (z_pre),
somatic depth of postsynaptic cell (z_post),
relative lateral (horizontal) position (rho).
data are sufficient/insufficient for
Missing data
Np_int_XYhas the same missing data asP_int_XY- for a given combination of
z_preandz_postthere are either data available for all values ofrhoor no values at all. - thus one can check the missing data with a fixed value of
rho - Figs 8, 10, 11, 12 show there are data missing
Layer 1 is omitted from the analysis, since no data for Layer 1 were provided
It can fit following functions:
Jak resim normalizaci???