Information transmission delays in the brain are generated by the physical properties of axons, including their length and diameter. These delays have a range of a few milliseconds and can thus be observed in bioelectric recordings such as electroencephalography and magnetoencephalography (MEG). In this work, we present a novel algorithm to estimate axon diameters from diffusion MRI and MEG. This approach identifies information flow between cortical regions using a model where transmission delays are parameters. The delays which maximize information transfer are identified and, using streamline length obtained through tractography, are then converted to axon diameters. We present results obtained on four subjects of the Human Connectome Project.