Before revision:  Here we show that maximizing likelihood over both response functions and noise functions is equivalent to simply identifying maximally informative response functions -- ones that maximize the mutual information I[ R;M ] between predicted responses and corresponding measurements .
After revision:  Here we show that maximizing likelihood over both response functions and noise functions is equivalent to simply identifying maximally informative response functions -- ones that maximize the mutual information I[ R;M ] between observed measurements and predicted representations .