Luzin's (N) and randomness reflection

We show that a computable function $f:\mathbb{R}\to \mathbb{R}$ has Luzin’s property (N) if and only if it reflects ${\mathrm{\Pi }}_1^1$-randomnes, if and only if it reflects ${\mathrm{\Delta }}_1^1(\mathcal{O})$-randomness, and if and only if it reflects $\mathcal{O}$-Kurtz randomness, but reflecting Martin-L"of randomness or weak-2-randomness does not suffice. Here a function $f$ is said to reflect a randomness notion $R$ if whenever $f(x)$ is $R$-random, then $x$ is $R$-random as well. If additionally $f$ is known to have bounded variation, then we show $f$ has Luzin’s (N) if and only if it reflects weak-2-randomness, and if and only if it reflects ${\mathrm{\varnothing }}^{\mathrm{\prime }}$-Kurtz randomness. This links classical real analysis with algorithmic randomness.