Humans experience sensory input continuously as segmented units of words and events. The ability of the brain to discover regularities is known as statistical learning. This concept can be represented at multiple levels including transitional probabilities and the identity of units. In a new report now published on Science Advances, Simon Henin and a team of scientists at the New York University School of Medicine, Yale University and the Max Planck Institute in the U.S. and Germany recorded sequence encoding in the cortex and hippocampus of human subjects exposed to auditory and visual sequences with temporal (time-based) regularities. Using early processing, they tracked lower-level features such as syllables and learned units including words, while later processing could only track learning units. The findings showed the existence of multiple parallel computational systems in humans to assist learning across organized cortico-hippocampal units.