Equivalence of Gradient Fields and Exact Differentials on a Non-Simply Connected Region

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I've recently been taking 18.02sc Multivariable Calculus on MIT OpenCourseWare, which states the following in one of their course notes:

$$M \hat i + N \hat j = \nabla f \implies M dx + N dy \text{ is exact}$$

This makes sense to me, as:

$$ \nabla f = M \hat i + N \hat j \implies M = f_x \text{ and } N = f_y \implies M dx + N dy = f_x \ dx + f_y \ dy = df$$

Later, however, in a video, it was stated that the above was only true within simply connected regions. Does the above argument work in non-simply connected regions? Or is there simply something I'm missing in my argument?

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After doing further research throughout the readings of 18.02 and 18.02sc, I've found that the above is indeed true in a non-simply connected region. The nuance I was missing was almost notational, in a sense - much like how $ \int_C \vec F \cdot d \vec r = \int_C M dx + N dy$ takes a dot product and carries it into a differential, $ \int_C \nabla f \cdot d \vec r = \int_C \ f_x \ dx + f_y \ dy$ appears to take $\nabla f$ and "split it apart."

As such, the difference between $\nabla f = f_x \ \vec i + f_y \ \vec j$ and $df = f_x \ dx + f_y \ dy$ is almost merely notational, as the two appear to be equivalent everywhere - the latter the differential analogue for the former.