The dynamics of the two different components of thermodynamically miscible polymer blends can have very different temperature dependences ("thermorheologically complex") in some cases, while in others the two components behave more I in agreement with intuition and have similar temperature dependences. The presence of spatial concentration variations over very local length scales (typically nanometers in size) caused by a combination of thermodynamic factors and chain connectivity effects is one explanation for thermorheological complexity. While several theories have been presented to rationalize this rich variety of rheological behavior, there remain lingering questions of the relative importance of system thermodynamics and chain connectivity effects in determining concentration variations over such small spatial domains. We critically investigate these issues using lattice Monte Carlo simulations on model binary blends. Our simulations show that the distribution of concentrations encountered within a specified control volume is indeed Gaussian with widths that are in excellent agreement with the predictions of mean-field theory. However, these distributions are centered at compositions that are significantly enriched due to chain connectivity effects. These results provide an excellent basis for the development of microscopic theories for the dynamics of polymer blends.