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A cornerstone in convex analysis is the crucial relationship between functions and their convex conjugate via the Fenchel-Young inequality. In this dual variable setting, the maximal monotonicity of the contact set $ \big\{(x,y) \ \big| \ f(x) + f^*(y) = \langle x,y \rangle \big\}$ is due to the involution $f^{**} = f$ holding for convex lower-semicontinuous functions defined on any Hilbert space. We investigate the validity of the cyclic version of involution and maximal monotonicity for multiple (more than two) convex functions. As a result, we show that when the underlying space is the real line, cyclical involutivity and maximal monotonicity induced by multi-conjugate convex functions continue to hold as for the dual variable case. On the other hand, when the underlying space is multidimensional, we show that the corresponding properties do not hold in general unless a further regularity assumption is imposed. We provide detailed examples that illustrate the significant differences between dual- and multi-conjugate convex functions, as well as between uni- and multi-dimensional underlying spaces.