STATISTICAL TERMS

Can you explain the primary difference between using the Generalized Difference Equation and First Difference Method in correcting for serial autocorrelation?  These are methods used in a multiple regression analysis that will compensate for serial autocorrelation (time series data).  I guess my question is a distinction between the two methods.  For example, I think First Difference method uses lagged variables, but I am not sure if the General Difference Method does something different.  I hope this is helpful.