The reliable integration of an ever-changing multitude of environmental inputs is fundamental for learning, memory, and behaviour. Our research aims to understand how information from the world is represented, integrated, and transformed within neuronal networks to uncover key principles of computation underlying memory formation in a state-dependent manner, including during learning, consolidation, and sleep. To achieve this, we combine state-of-the-art circuit neuroscience tools such as opto- and pharmacogenetics with single- and two-photon imaging, miniaturized microscopy for deep-brain recordings, light-sheet microscopy, and advanced AI-driven analysis to reveal frameworks of neuronal coding and plasticity. Our work furthermore focusses on mechanisms of structural plasticity including changes in axonal function, with the common goal of elucidating how these processes support memory formation and recall in the healthy brain, and how they break down in the context of disease.