Editorial: Unraveling information encoding and representation in memory formation and learning

Understanding how neural circuits encode and represent information during memory formation and learning remains one of neuroscience’s most fundamental challenges. The brain’s remarkable ability to transform sensory inputs into meaningful representations, store these representations over varying timescales, and retrieve them with precision requires the intricate orchestration of neural activity at multiple levels of organization. This Research Topic brings together diverse perspectives that address these mechanisms through computational, analytical, and empirical approaches. The four contributions to this Research Topic explore critical aspects of information encoding, from the multiscale dynamics that characterize different brain states to the fundamental principles that govern how neural networks maintain stable representations while supporting continuous learning. Together, they illustrate how interdisciplinary approaches—combining information theory, computational modeling, signal processing, and neurophysiology—can illuminate the neural codes underlying memory and cognition.