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Older adults often experience substantial declines in navigational abilities. At present, however, the functional and neurophysiological mechanisms that cause such navigational deficits are poorly understood. To address this important question, we conducted two studies where we 1) characterized age-related deficits in learning a photorealistic virtual environment, by measuring how healthy older and younger adults retrieved its spatial layout across several learning blocks, and 2) investigated the underlying neural mechanisms for these deficits using fMRI and DCM PEB. Moreover, we developed a Bayesian implementation of a state-space model that enabled us to precisely estimate hidden learning states, because behavioral performance is noisy and may not accurately reflect the subject-specific learning state. The findings of these studies are reported in: Diersch, N., Valdes-Herrera, J. P., Tempelmann, C., & Wolbers, T. (2021). Increased hippocampal excitability and altered learning dynamics mediate cognitive mapping deficits in human aging. *The Journal of Neuroscience*, JN-RM-0528-20, DOI: Here, we provide the source data files for the main results figures of the paper. We additionally provide a key resources table listing all the software that we used. The Stan code of the Bayesian state-space model can be found in Figure 2-1 of the Extended Data. If you have questions, do not hesitate to contact