Associative and categorical priming in a word-picture paradigm: a diffusion model analysis

Area of Science:

• Cognitive Psychology
• Psycholinguistics
• Computational Neuroscience

Background:

• Language cues are processed automatically, influencing subsequent perceptions.
• Understanding how different types of word primes affect cognitive tasks is crucial.
• Semantic priming is a key phenomenon in cognitive science research.

Purpose of the Study:

• To investigate how associative and categorically congruent prime words influence a semantic picture categorization task.
• To differentiate the cognitive processes underlying associative versus categorical priming.
• To apply a hierarchical diffusion model to analyze underlying cognitive mechanisms.

Main Methods:

• Participants categorized target pictures (living/non-living) preceded by manipulated prime words.
• Prime words varied in association and semantic category congruence with target pictures.
• A hierarchical diffusion model was used to analyze response times (RT) and error rates (ER).

Main Results:

• Category congruency significantly affected both RT and ER.
• Associative priming primarily influenced RT, not ER.
• Diffusion model analysis showed associative priming affected non-decision time (visuo-semantic processing head start), while categorical priming affected drift rate (decision-making facilitation).

Conclusions:

• Priming effects in picture classification involve distinct cognitive processes compared to word-word priming.
• Associative and categorical priming differentially impact the speed and accuracy of semantic picture categorization.
• Findings contribute to theoretical models of priming and cognitive processing.