Neural Correlates of Indirect Semantic Priming: An ERP Study Donna A. Kreher1, Phillip J. Holcomb1 - PowerPoint PPT Presentation

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Neural Correlates of Indirect Semantic Priming: An ERP Study Donna A. Kreher1, Phillip J. Holcomb1

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Title: Neural Correlates of Indirect Semantic Priming: An ERP Study Donna A. Kreher1, Phillip J. Holcomb1


1
Neural Correlates of Indirect Semantic Priming
An ERP StudyDonna A. Kreher1, Phillip J.
Holcomb1 Gina R. Kuperberg1,2Tufts University,
Medford, MA1 Massachusetts General Hospital,
Charlestown, MA2
Figure 3b Experiment 1 Ratings
Figure 3c
Figure 3a Experiment 1 Direct, indirect and
unrelated targets
  • Introduction
  • Direct semantic priming (e.g., tiger--stripes)
    can be explained by both automatic and
    controlled/strategic processes
  • Indirect or mediated semantic priming (e.g.,
    lion--(tiger)--stripes) is best explained by
    automatic spreading activation theories 3
  • Currently, evidence for an N400 effect in
    indirect semantic priming is mixed 1,4
  • The Present Study
  • We systematically varied the associative
    distance of word pairs and task explicitness
    across two experiments
  • If spreading activation theory is correct, we
    predict
  • Indirect targets will elicit N400s in between
    those of direct and unrelated targets
  • 2) Indirect targets will show a significant N400
    effect regardless of task explicitness
  • Results
  • Experiment 1 Relatedness Ratings
  • Priming effects
  • A robust N400 effect was found for both direct
    and indirect targets (Figure 3a)
  • N400s to direct targets were significantly
    smaller than N400s to indirect or unrelated
    targets
  • N400s to indirect targets were significantly
    smaller than N400s to unrelated targets
  • Effects of relatedness judgments
  • Higher ratings of relatedness were also
    associated with significantly smaller N400s
    (Figure 3b)
  • Are priming and ratings effects dissociable?
  • No ratings X priming interaction was found for
    the N400 time window
  • Participants did not become aware of the three
    types of semantic relationships or develop
    strategies accordingly (Figure 3c)

2
  • Experiment 2 Semantic Categorization
  • Smaller but still significant N400 effects were
    found for both direct and indirect targets
    (Figure 4)
  • Direct targets elicited significantly smaller
    N400s than indirect and unrelated targets
  • Indirect targets elicited significantly smaller
    N400s than unrelated targets
  • Methods
  • Experiment 1 Relatedness Ratings Task
  • 18 participants (9 female, mean age 19.83
    years)
  • right-handed native speakers of English
  • normal or corrected-to normal vision
  • Participants were instructed to rate the
    relatedness of word pairs on a 1-7 scale
  • 210 trials
  • 70 directly related word pairs (tiger-stripes)
  • 70 indirectly related word pairs (lion-stripes)
  • 70 unrelated word pairs (soft-stripes)
  • Experiment 2 Semantic Categorization Task
  • 15 participants (10 female, mean age 20.07
    years)
  • right-handed native speakers of English
  • normal or corrected-to normal vision
  • Participants were instructed to press a button
    to all food words

Figure 4 Experiment 2 Direct, indirect and
unrelated targets
  • Discussion
  • A reliable N400 effect was found for indirectly
    related word pairs
  • As predicted, this N400 was halfway between that
    of direct and unrelated targets, even when
    participants were asked to make relatedness
    judgments
  • Although more robust in an explicit task, this
    N400 effect was still significant in a task that
    biased toward more automatic processing
  • Taken together, these results provide further
    evidence for automatic spreading activation
    theories
  • However, N400 amplitude was also modulated by
    participants relatedness judgments, confirming
    that the N400 component is also sensitive to
    controlled or strategic processing, and is not a
    pure index of automatic processes 2

Figure 2 Typical Trials
Figure 1 Electrode Montage
References 1. Chwilla, D.J. Kolk, H.J.H.
(2000). Mediated priming in the lexical decision
task Evidence from event-related potentials and
reaction time. Journal of Memory and Language,
42, ,314-341. 2. Holcomb, P.J. (1988). Automatic
and attentional processing An event-related
brain potential analysis of semantic priming.
Brain and Language, 35, 66-85. 3. McNamara, T.P.
Altarriba, J. (1988). Depth of spreading
activation revisited Semantic mediated priming
occurs in lexical decisions. Journal of Memory
and Language, 27, 545-559. 4. Weisbrod, M.,
Kiefer, M., Winkler, S., Maier, S., Hill, H.,
Roesch-Ely, D. Spitzer, M. (1999).
Electrophysiological correlates of direct versus
indirect priming in normal volunteers. Cognitive
Brain Research, 8, 289-298.
Experiment 1 Relatedness Ratings
Experiment 2 Semantic Categorization
This research was supported by grants from NICHD
(HD25889 and HD43251) to Phillip J. Holcomb, and
by grants from NIMH (K23 MH02034) and NARSAD
(with the Sidney Baer Trust) to Gina R. Kuperberg
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