Understanding associative vs. abstract pictorial relations: An ERP study

Leemor Zucker*, Liad Mudrik

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

One of the most remarkable human abilities is extracting relations between objects, words or ideas – a process that underlies perception, learning and reasoning. Yet, perhaps due to its complexity, surprisingly little is known about the neural basis of this fundamental ability. Here, we examined EEG waveforms evoked by different types of relations, conveyed by pairs of images. Subjects were presented with the pairs, that were either associatively related, abstractly related or unrelated, and judged if they were related or not. Evidence for a gradual modulation of the amplitude of the N400 and late negativity was found, such that unrelated pairs elicited the most negative amplitude, followed by abstractly-related pairs and lastly associatively-related ones. However, this was confined to first encounter with the pairs, and a different, more dichotomous pattern was observed when the pairs were viewed for the second time. Then, no difference was found between associatively and abstractly related pairs, while both differed from unrelated pairs. Notably, when the pairs were sequentially presented, this pattern was found mostly in right electrodes, while it appeared both in left and right sites during simultaneous presentation of the pairs. This suggests that while two different mechanisms may be involved in generating predictions about an upcoming related/unrelated stimulus, online processing of associative and abstract semantic relations might be mediated by a single mechanism. Our results further support claims that the N400 component indexes multiple cognitive processes that overlap in time, yet not necessarily in neural generators.

Original languageEnglish
Article number107127
JournalNeuropsychologia
Volume133
DOIs
StatePublished - Oct 2019

Keywords

  • Expectations mechanisms
  • Late negativity
  • N400
  • Object processing
  • Relational processing
  • Semantic integration

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