The necessity of the hippocampus for statistical learning

Natalie V. Covington, Sarah Brown-Schmidt, Melissa C. Duff

Research output: Contribution to journalArticlepeer-review

53 Scopus citations


Converging evidence points to a role for the hippocampus in statistical learning, but open questions about its necessity remain. Evidence for necessity comes from Schapiro and colleagues who report that a single patient with damage to hippocampus and broader medial temporal lobe cortex was unable to discriminate new from old sequences in several statistical learning tasks. The aim of the current study was to replicate these methods in a larger group of patients who have either damage localized to hippocampus or broader medial temporal lobe damage, to ascertain the necessity of the hippocampus in statistical learning. Patients with hippocampal damage consistently showed less learning overall compared with healthy comparison participants, consistent with an emerging consensus for hippocampal contributions to statistical learning. Interestingly, lesion size did not reliably predict performance. However, patients with hippocampal damage were not uniformly at chance and demonstrated above-chance performance in some task variants. These results suggest that hippocampus is necessary for statistical learning levels achieved by most healthy comparison participants but significant hippocampal pathology alone does not abolish such learning.

Original languageEnglish (US)
Pages (from-to)680-697
Number of pages18
JournalJournal of cognitive neuroscience
Issue number5
StatePublished - May 1 2018
Externally publishedYes

Bibliographical note

Funding Information:
This work was supported by NIDCD grant R01 DC011755 to M. C. D. and S. B. S. We thank Sharice Clough for her help during data collection. We thank Anna Schapiro and the Turk-Browne laboratory for their willingness to share experimental materials and for valuable discussion.

Publisher Copyright:
© 2018 Massachusetts Institute of Technology.


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