Neocortical catastrophic interference in healthy and amnesic adults: A paradoxical matter of time

Maayan Merhav, Avi Karni, Asaf Gilboa

Research output: Contribution to journalArticlepeer-review


The human cortex can accommodate overlapping semantic information, such as synonyms, homonyms, or overlapping concepts. However, neuronal models of cortical networks predict Catastrophic Interference in conditions of overlapping information, obliterating old associations and sometimes preventing formation of new ones. It has been proposed that Catastrophic Interference in declarative memory is never observed in biological systems because of hippocampal pattern separation of competing associations. Here, we tested neocortical Catastrophic Interference during acquisition of overlapping associations through Fast Mapping; an incidental, exclusion based learning mechanism, that can support hippocampal-independent learning. Young adults acquired picture-label associations, either through explicit encoding or through Fast Mapping and were tested after 24 h. Overlapping/competing associations were presented either minutes (Early), or 22 h (Delayed) after learning. Catastrophic Interference was evident only following Fast Mapping, and only in the Delayed competition. In a follow-up experiment, Medial Temporal Lobe (MTL) amnesic patients demonstrated retroactive Catastrophic Interference after the Early competition, despite normal memory for noninterfered Fast Mapping associations. Thus, following Fast Mapping, a biological system demonstrated susceptibility to Catastrophic Interference, as predicted by the neuronal-model. Early retroactive Interference, however, can be prevented by MTL integrity.

Original languageEnglish
Pages (from-to)1653-1662
Number of pages10
Issue number12
StatePublished - 1 Dec 2014

Bibliographical note

Publisher Copyright:
© 2014 Wiley Periodicals, Inc.


  • A-B, A-C paired-associates
  • Fast mapping
  • Hippocampus
  • Semantic memory
  • The Complementary Learning System

ASJC Scopus subject areas

  • Cognitive Neuroscience


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