Although previous studies point to qualitative similarities between working memory (WM) and attention, the degree to which these two constructs rely on shared neural mechanisms remains unknown. Focusing on one such potentially shared mechanism, we tested the hypothesis that selecting an item within WM utilizes similar neural mechanisms as selecting a visible item via a shift of attention. We used fMRI and machine learning to decode both the selection among items visually available and the selection among items stored in WM in human subjects (both sexes). Patterns of activity in visual, parietal, and to a lesser extent frontal cortex predicted the locations of the selected items. Critically, these patterns were strikingly interchangeable; classifiers trained on data during attentional selection predicted selection from WM, and classifiers trained on data during selection from memory predicted attentional selection. Using models of voxel receptive fields, we visualized topographic population activity that re...