Neural Network Input: -1 To 1?

General data mining books talk about NN taking inputs which are between -1 and 1. Even Jamie's book says that's what it generally receives. I don't think this is a requirement for the Microsoft algorithm, but I wanted to ask if it was a best practice. If you're feeding it something like home values where 99% of homes are under $1 million you can use some normalization trick so that mansions don't skew the data. But if your data doesn't need such normalization, is there any need to normalize it to the -1 to 1 range?



Also, is the Microsoft algorithm sensitive to the relative size of different inputs? For instance, if InputA is home size (500-50,000 square feet) and InputB is months unoccupied (0-24 months), does that cause the Microsoft NN to weigh home size more heavily?