Vanderbilt University.
J Cogn Neurosci. 2018 May;30(5):680-697. doi: 10.1162/jocn_a_01228. Epub 2018 Jan 8.
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.
越来越多的证据表明海马体在统计学习中起作用,但关于其必要性的问题仍未解决。必要性的证据来自 Schapiro 及其同事的报告,他们指出,一名海马体和更广泛的内侧颞叶皮层受损的单一患者无法在几个统计学习任务中区分新序列和旧序列。本研究的目的是在具有海马体或更广泛的内侧颞叶损伤的更大患者群体中复制这些方法,以确定海马体在统计学习中的必要性。与健康对照组参与者相比,海马体损伤患者的整体学习效果始终较差,这与海马体对统计学习的贡献的新兴共识一致。有趣的是,损伤大小并不能可靠地预测表现。然而,海马体损伤患者并非完全处于随机水平,在某些任务变体中表现出高于随机水平的性能。这些结果表明,海马体对于大多数健康对照组参与者达到的统计学习水平是必要的,但仅存在显著的海马体病理学并不会消除这种学习。