Help Privacy Policy Disclaimer
  Advanced SearchBrowse




Journal Article

Learning hierarchical sequence representations across human cortex and hippocampus


Melloni,  Lucia
Department of Neuroscience, Max Planck Institute for Empirical Aesthetics, Max Planck Society;
Department of Neurology, New York University School of Medicine;
New York University Comprehensive Epilepsy Center;

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)

(Publisher version), 839KB

Supplementary Material (public)
There is no public supplementary material available

Henin, S., Turk-Browne, N. B., Friedman, D., Liu, A., Dugan, P., Flinker, A., et al. (2021). Learning hierarchical sequence representations across human cortex and hippocampus. Science Advances, 7(8): eabc4530. doi:10.1126/sciadv.abc4530.

Cite as: https://hdl.handle.net/21.11116/0000-0008-3561-F
Sensory input arrives in continuous sequences that humans experience as segmented units, e.g., words and events. The brain’s ability to discover regularities is called statistical learning. Structure can be represented at multiple levels, including transitional probabilities, ordinal position, and identity of units. To investigate sequence encoding in cortex and hippocampus, we recorded from intracranial electrodes in human subjects as they were exposed to auditory and visual sequences containing temporal regularities. We find neural tracking of regularities within minutes, with characteristic profiles across brain areas. Early processing tracked lower-level features (e.g., syllables) and learned units (e.g., words), while later processing tracked only learned units. Learning rapidly shaped neural representations, with a gradient of complexity from early brain areas encoding transitional probability, to associative regions and hippocampus encoding ordinal position and identity of units. These findings indicate the existence of multiple, parallel computational systems for sequence learning across hierarchically organized cortico-hippocampal circuits.