In this study, we investigated the cognitive processing stages underlying associative recognition using MEG. Over the last four decades, a model of associative recognition has been developed in the ACT-R cognitive architecture. This model was first exclusively based on behavior, but was later evaluated and improved based on fMRI and EEG data. Unfortunately, the limited spatial resolution of EEG and the limited temporal resolution of fMRI have made it difficult to fully understand the spatiotemporal dynamics of associative recognition. We therefore conducted an associative recognition experiment with MEG, which combines excellent temporal resolution with reasonable spatial resolution. To analyze the data, we applied non-parametric cluster analyses and a multivariate classifier. This resulted in a detailed spatio-temporal model of associative recognition. After the visual encoding of the stimuli in occipital regions, three separable memory processes took place: a familiarity process (temporal cortex), a recollection process (temporal cortex and supramarginal gyrus), and a representational process (dorsolateral prefrontal cortex). A late decision process (superior parietal cortex) then acted upon the recollected information represented in the prefrontal cortex, culminating in a late response process (motor cortex). We conclude that existing theories of associative recognition, including the ACT-R model, should be adapted to include these processes.