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Hence we are only correlating inputs with each other, thus, the name of this rule: Input correlation learning (ICO, Porr and Wörgötter 2006).
To simulate highly correlated input, we used 2,000 independent spike trains, resulting in an input correlation of 1,000/2,000 = 0.5 (i.e. any two neurons share on average 1,000 × 0.5 = 500 common input spike trains).
The necessity of taking the input correlation into account is illustrated.
Input: Correlation matrix defined in (14), where,, the maximum number of iterations, channel statistics and for the SD-MSTR case.
Limits where level-crossing cross-correlations have been previously calculated are the weak and strong input correlation limit [3].
In this study, we examine how the organization of primary auditory cortex (A1) is altered by tones designed to decrease the average input correlation across the frequency map.
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(b) Comparing the (L(c)) vs. the (tilde{L}( f(c))) functions for the DG and LNL models, respectively (here input correlations (lambda=0.17) for DG model).
There are a number of studies that explored theoretically the case of weakly correlated neurons and employed perturbation methods to relate output spike train correlations to input correlations [46 52].
To introduce input correlations, we followed the same method as Lindén et al. (2011).
In the case of correlation based developmental models [ 35], the statistical structure of input correlations provides a mechanism for spontaneously breaking some underlying symmetry of the neuronal receptive fields leading to the emergence of feature selectivity.
As described below, quantitative anatomical measurements of RBC-A17 connectivity allowed us to relate the measured input correlations to nearby A17 amacrines to the strength of CSS in RBC output.
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