I know that **the conditional distribution of two gaussian is gaussian**. But in the following statement how does the Θ captures the conditional distributions?

And what do they mean by the term ***"captures"*** here?

> Let's suppose X is a random variable such that  X
> = ( X1 , X2 , . . . , Xp ) has a multivariate Gaussian distribution with mean-vector 0 (for convenience ) and covariance Σ , then Θ
> =Σ<sup>−1</sup> captures the conditional distributions of each X<sub>j</sub> given the rest.