There is an exercise in a textbook by Durret. Find $E(B_{1}^2B_{2}B_{3})$, where $B_{i}$ is Brownian motion. I try to use the definition $E(B_{s}B_{t})=s\wedge t$ and $B_{t}$ has independent increments. I have got that
$$E(B_{1}^2B_{2}B_{3})=E\big(B_{1}^2(B_{2}-B_{1})(B_{3}-B_{2})\big)+E((B_{1}^2(B_{2}-B_{1})^2)+E(B_{1}^3(B_{2}-B_{1}))+E(B_{1}^3(B_{3}-B_{1}))+E(B_{1}^4).$$
But I am not sure that $E(B_{1}^4)=1$ and I have no idea about $B_{t}^2$ still standard normal Gaussian distribution. And if it is true, the answer is 1, since
$$E\big(B_{1}^2(B_{2}-B_{1})(B_{3}-B_{2})\big)=0$$ $$E((B_{1}^2(B_{2}-B_{1})^2)=0$$ $$E(B_{1}^3(B_{2}-B_{1}))=0$$ $$E(B_{1}^3(B_{3}-B_{1}))=0$$
$\begin{aligned}\begin{aligned}B_{1}^{2}\end{aligned} B_{2}B_{3} & =B_{1}^{2}B_{2}\left(B_{3}-B_{2}\right)+B_{1}^{2}B_{2}^{2}\\ & =B_{1}^{2}\left(B_{2}-B_{1}+B_{1}\right)\left(B_{3}-B_{2}\right)+B_{1}^{2}\left(B_{2}-B_{1}+B_{1}\right)^{2}\\ & =B_{1}^{2}\left(B_{2}-B_{1}\right)\left(B_{3}-B_{2}\right)+B_{1}^{3}\left(B_{3}-B_{2}\right)+B_{1}^{2}\left(B_{2}-B_{1}\right)^{2}+2B_{1}^{3}\left(B_{2}-B_{1}\right)+B_{1}^{4} \end{aligned} $
Then by linearity of expectation, independence and the fact that every $B_{t}$ has mean $0$ we find:
$\mathsf{E}\begin{aligned}B_{1}^{2}\end{aligned} B_{2}B_{3}=\mathsf{E}B_{1}^{2}\mathsf{E}\left(B_{2}-B_{1}\right)^{2}+\mathsf{E}B_{1}^{4}=1+3=4$
To find the equality $\mathsf{E}B_{1}^{4}=3$ see the answer of harmonicuser or have a look at the moments of normal distribution on wikipedia.