Computation is the transformation of inputs into outputs through logical operations such as AND, OR, and NOT. This literature review compares models of computation at different physiological resolutions, whole brain networks, multi-cell circuits, individual synapses and individual molecular interactions and discusses if these models might be useful for bridging between functional neuroimaging with molecular models of disease. While resolution in functional neuroimaging such as EEG, MEG, PET, and fMRI is of groups of neurons pharmacotherapy alters the brain at a molecular level. Bridging this resolution gap presents many difficulties for modellers and wider connectome projects. Sufficiently detailed models can quickly outstrip computational capacity while not including sufficient detail leads to models lacking physiological validity. This is particularly problematic when connectome projects overpromise in their capacity to understand brain disorders without basis in valid physiological models. Examples of computation at network and molecular levels suggests a lack of consensus about what resolution the brain performs computations and how these computations interact. This interaction should be a goal for further research, especially given its role in linking functional neuroimaging diagnostics and pharmacological treatments in neurology.