Our laboratory is interested in how the dynamics of neural activity reflects experiences and behavior in changing environments. To this end, we develop theories of how intrinsic dynamical patterns such as sequences can be used for efficient representations of both sensory stimuli and actions and that allow exploration of unknown spaces. We particularly focus on neural representations of space in the hippocampus and the auditory system. Our approaches connect data analytical methods and mathematical modeling over multiple levels: subcellular compartments, neural circuits, interactions of brain areas, and behavior. We believe that unraveling the fundamental building principles of neurobiological information processing is imperative for designing energy-efficient artificial autonomous agents, for understanding evolution of animals in changing environments, and for improving treatments of neurological diseases.