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⁻¹ captures the conditional distributions of each X_j given the rest.