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The role of the super and subordinate hierarchical relationships in word priming
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Poster A27 in Poster Session A, Tuesday, October 24, 10:15 am - 12:00 pm CEST, Espace Vieux-Port
Beck N.I. Hardy1, Dwight J. Kravitz1,2; 1The George Washington University, 2National Science Foundation
As we read, text we have already read primes semantic networks resulting in predictions of upcoming words, making reading more efficient. This process is so automatic that in garden-path sentences participants experience a surprisal effect when the conclusion of the sentence violates those predictions. Current cognitive theories propose semantic similarity primarily drives priming within the semantic network. However, linguistic theories propose a number of other features that define semantics such as frequency, structure, word type, specificity, and hierarchical relationships. In the current study, we sought to explore the impact of hierarchical relationships on language processing and priming. Utilizing a lexical decisions paradigm, we quantified the asymmetry in priming when the same pair of superordinate and subordinate words reverse which is the prime or probe. On each trial, participants were asked to judge whether a briefly presented (500ms) stimulus was a real or pseudoword. Pseudowords were constructed to precisely match the real words in letter frequency and position. Unbeknownst to the participants, the 144 total trials were arranged into a set of counterbalanced pairs, such that real and pseudowords, and superordinate and subordinate words followed each other equally often. Stimuli were tightly controlled for frequency, string length, and semantic similarity between pairs. If the cognitive science model of spreading activation predicted by semantic similarity is accurate, the Superordinate-Subordinate and Subordinate-Superordinate conditions should be equal as the exact same words occur in both conditions. However, linguistic models would predict that the Subordinate-Superordinate condition should be faster as subordinate category members contain specific features with more information, leading to higher likelihood of priming the superordinate category head. Contrary to both of these theories the strongest priming was observed in the Superordinate-Subordinate condition. Thus, neither theory accurately predicted the outcome, as hierarchy directly affected priming but in the opposite direction from the linguistic prediction. One possible explanation is that the superordinate word led to greater priming by virtue of simultaneously priming a number of near semantic neighbors to the subordinate word, which in turn supported the subordinate word. This explanation combines the influence of both semantic relatedness and hierarchy via a mechanism well situated in the known properties of the neural substrate. In essence, the structure of language itself introduces a hierarchical effect without the need for a specific representation of that hierarchy. Understanding these dynamics has the potential to advance our knowledge of the neural mechanisms underlying language processing and contribute to the development of more comprehensive models.
Topic Areas: Meaning: Lexical Semantics,