In applying our theory of associative decorrelation dynamics to visual cortex to compare with the psychophysical experiments on orientation illusions, the linear first-order approximation is used, which is
where it is assumed that the input correlations are small. It is
interesting to notice that the linear first-order approximation leads to
anti-Hebbian feedback connections: 
which is
guarantteed to be stable around 
[7].
Let us to illustrate the consequences of this for a simple two neurons
case. Suppose the 
, that is the original inputs ensemble is
uncorrelated. Now the network is adapted to an input 
, what is the network response to an input 
now?
From equation 17
and
So the response after adaptation is actually rotated from the
``vertical'' of input 
, the angle 
rotated is given by
