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Journal of Experimental Psychology:
Learning, Memory, and Cognition
2006, Vol. 32, No. 2, 399 – 415
Copyright 2006 by the American Psychological Association
0278-7393/06/$12.00 DOI: 10.1037/0278-7393.32.2.399
A Study of Relative-Position Priming With Superset Primes
Eva Van Assche
Jonathan Grainger
Ghent University
Centre National de la Recherche Scientifique and
University of Provence
Four lexical decision experiments are reported that use the masked priming paradigm to study the role of letter
position information in orthographic processing. In Experiments 1 and 2, superset primes, formed by repetition
of 1 or 2 letters of the target (e.g., jusstice–JUSTICE) or by insertion of 1 or 2 unrelated letters (e.g.,
juastice–JUSTICE), generated significant priming compared with unrelated primes and did not differ significantly from an identity priming condition. In Experiment 3, identity primes generated significantly faster
responses than subset primes formed by removal of 2 letters from the target (e.g., jutie–JUSTICE), and subset
primes generated faster responses than substitution primes formed by substitution of 2 letters of the target with
unrelated letters (e.g., jumlice–JUSTICE). In Experiment 4, insertion of 3 unrelated letters continued to
generate facilitation relative to unrelated primes but significantly less so than the identity prime condition. The
authors discuss the implications of these results for letter-position coding schemes.
Keywords: reading, word recognition, orthographic processing, letter position
and target (relative-position priming) or the order of shared letters
(transposed-letter priming). The present study extends prior work
investigating relative-position priming. We first summarize the empirical results in this area before examining the consequences for
models of letter-position coding and the main predictions of these
models concerning the experiments to be presented in this study.
One of the most fundamental questions about orthographic processing, how letter position information is represented and processed
during visual word recognition, has attracted increasingly more attention from researchers in recent years (e.g., Davis, 1999; Davis &
Bowers, 2004; Grainger & van Heuven, 2003; Grainger & Whitney,
2004; Perea & Lupker, 2003; Peressotti & Grainger, 1999; Schoonbaert & Grainger, 2004; Whitney, 2001). The growing empirical
evidence has allowed theorists to reject standard accounts of letterposition coding, as implemented in the classic models of visual word
recognition (Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001; McClelland & Rumelhart, 1981; Seidenberg & McClelland, 1989), and
to propose some new coding schemes as viable alternatives (Davis,
1999; Dehaene, Cohen, Sigman, & Vinckier, 2005; Grainger & van
Heuven, 2003; Perea, Gómez, & Ratcliff, 2003; Whitney, 2001). The
present work provides a further investigation of this important issue,
using a novel form of orthographic priming called superset priming.
Two main sources of evidence have been decisive in shaping
current theories of letter-position coding. This evidence has been
obtained with the masked priming paradigm and manipulations involving the relative versus absolute position of letters shared by prime
Relative-Position Priming
In prior experiments investigating relative-position priming,
primes were composed of a subset of the target word’s letters that
preserved the relative position of letters in prime and target. Thus,
for a given target word APRICOT, the prime stimulus arict is
formed of a subset of the target’s letters in the correct order, but
not in the correct absolute, length-dependent position. Humphreys,
Evett, and Quinlan (1990) used a four-field masking procedure in
which primes and targets were briefly presented one after the
other. Before the prime and after the target, two masks were
displayed, and participants had to recognize the target word presented in uppercase letters (primes were in lowercase letters).
Percentage of correct target word identification was measured as a
function of the type of prime stimulus. Robust priming compared
with an unrelated prime condition was obtained when the relative
position of letters was respected across prime and target. Thus, for
example, in Experiment 4 of Humphreys et al., the prime 1245
generated significant priming for five-letter target words compared
with a cross-position condition (1425), an outer-letter only condition (1dd5), and an inner-letter only condition (d24d).1
Peressotti and Grainger (1999) replicated the relative-position
priming effects observed by Humphreys et al. (1990) using the
Eva Van Assche, Department of Psychology, Ghent University, Ghent,
Belgium; Jonathan Grainger, Centre National de la Recherche Scientifique,
and Laboratoire de Psychologie Cognitive, Marseille, France, Université de
Provence, Marseilles, France.
Eva Van Assche is currently a research assistant for the National Fund for
Scientific Research, Flanders, Belgium, and performed this work during an
Erasmus exchange between Ghent University and the University of Provence.
We thank André Vandierendonck for his continuing help in arranging
the Erasmus exchange program. We also thank Colin Davis for providing
us with the match scores of the SOLAR model (http://www
.maccs.mq.edu.au/⬃colin), Walter van Heuven for calculating the match
scores for both versions of the open-bigram model, and Carol Whitney for
providing us with the match scores of the SERIOL model.
Correspondence concerning this article should be addressed to Jonathan
Grainger, Laboratoire de Psychologie Cognitive, Université de Provence,
3 place Victor Hugo, 13331, Marseille, France. E-mail: grainger@
up.univ-mrs.fr
1
We use the following notation to describe prime stimuli in the present
study. Each letter in the target word is given a number, and a prime condition
is described with the numbered letters of the target. A letter not present in the
target is indicated by the letter d (different). For example, a prime 12d45 shares
the first, second, fourth, and fifth letters with the target word. The third letter
is an unrelated letter that is not present in the target word.
399
400
VAN ASSCHE AND GRAINGER
masked priming paradigm of Forster and Davis (1984). Primes shared
four out of six letters with French target words, and the order of letters
was respected across prime and target (e.g., blcn as a prime for
BALCON). These primes significantly facilitated target word recognition compared with an unrelated condition. Peressotti and Grainger
(1999) also tested for priming effects when primes contained letters
from the target word without respecting their relative position. One
condition involved changing the position of the two external letters of
the target, and the other involved changing the two internal letters
(e.g., nlcb and bcln as primes for BALCON). Significant facilitation
relative to an unrelated condition was observed only when prime and
target had the same letters in the same relative position. When the
prime contained the same letters as the target, but in a partially
scrambled order, there were no significant priming effects. Peressotti
and Grainger also showed that inserting filler characters to provide
absolute position information (e.g., b-lc-n) did not lead to significantly
larger priming effects. These results have recently been replicated and
extended by Grainger, Granier, Farioli, Van Assche, and van Heuven
(in press), who again showed significant priming from subset primes
as long as the relative position of letters was respected across prime
and target stimuli. Finally, relative-position priming effects have also
been observed with word primes that are orthographically related to
target words but not the same length (De Moor & Brysbaert, 2000).
In De Moor and Brysbaert’s study, high-frequency primes that were
one letter longer or one letter shorter than the corresponding target
word in Dutch (e.g., boord–BOOR, eeuw–GEEUW) were found to
inhibit target processing compared with unrelated prime words.
However, recent work has shown that minor changes in letter
order (e.g., transposing two adjacent letters; jugde–judge) produce very robust priming effects in the masked priming paradigm (Forster, Davis, Schoknecht, & Carter, 1987; Humphreys
et al., 1990; Perea & Lupker, 2003, 2004; Schoonbaert &
Grainger, 2004). Perea and Lupker (2003, 2004) have shown
that transposed-letter primes facilitate target word recognition
compared with primes in which the two transposed letters are
substituted by two unrelated letters (e.g., jupfe–judge). These
transposed-letter priming effects have so far been reported only
for primes that contain exactly all of the target’s letters. As
shown in the experiments described above, when primes do not
contain all of the target’s letters, then even minor changes in
letter order are very detrimental to priming effects. Although at
first sight contradictory, these two fundamental phenomena,
relative-position priming and transposed-letter priming, likely
reflect the operation of the same basic mechanism: the mechanism used by the human brain to code for letter position during
orthographic processing. Both of these phenomena suggest a
rather coarse-grained, approximate coding of letter position
information in the initial stages of printed word perception.
Several recent accounts of letter position coding provide a
unitary explanation for these two phenomena.
New Approaches to Letter-Position Coding
Standard slot-based coding schemes, such as those implemented
in the interactive-activation and dual route cascaded models (Coltheart et al., 2001; McClelland & Rumelhart, 1981) have been
given increased flexibility through the introduction of probabilistic
coding at each letter position (see Grainger & van Heuven, 2003,
for a review of letter-position coding schemes). In the overlap
model of Perea et al. (2003), a given letter is coded as being at a
given position with a certain probability and at other neighboring
positions with probabilities that vary following a Gaussian distribution. The overlap model provides a natural explanation for
transposed-letter priming effects, as the probability of coding two
adjacent letters in the opposite locations is relatively high in this
model. This approach imposes strong constraints on the limits of
relative-position priming. By increasing the degree of separation of
letters shared by prime and target (i.e., two adjacent letters in the
target become separated in the prime stimulus or vice versa), the
overlap model predicts that relative-position priming should diminish (see Grainger et al., in press, for a more detailed examination of this point). This model has difficulty, for example, in
capturing the effects of subset primes formed by quite extreme
concatenations (e.g., 1469 for a nine-letter target word), as observed by Grainger et al. (in press). We return to a closer examination of effects of letter contiguity after describing the other
models.
Context-sensitive coding, such as the wickelgraph scheme used
in Seidenberg and McClelland’s (1989) model, has been given
more flexibility through the introduction of coding for noncontiguous letter sequences. This was first used in the work of Mozer
(1987) and more recently in the work of Whitney (2001) and
Grainger and van Heuven (2003). Grainger and van Heuven coined
the term open bigram to refer to ordered sequences of adjacent and
nonadjacent letters. For example, the word CART would be coded
as the following set of bigrams: CA, CR, CT, AR, AT, and RT.
Grainger and van Heuven’s (2003) open-bigram model and Whitney’s (2001) SERIOL (sequential encoding regulated by inputs to
oscillations within letter units) model differ mainly in terms of the
mechanism used to activate open bigrams. In Whitney’s model,
order information is provided by a beginning-to-end activation
gradient across letter representations that determines the order in
which letter detectors fire. This firing order then determines the set
of open bigrams that are activated and their relative activation
levels. Grainger and van Heuven, on the other hand, assumed a
hierarchical, parallel activation mechanism shown in Figure 1. In
Grainger and van Heuven’s model, a specialized set of letter
detectors, called the alphabetic array, codes the identity of all
letters in a stimulus string in parallel (within the limits of visual
acuity). Each letter detector in the alphabetic array matches visual
feature information extracted from a particular location relative to
eye fixation (along a horizontal meridian for languages like English and French) with 1 out of 26 possible letter identities. At this
level of processing, the system “knows” that a given letter is at a
given location but does not know where this letter is relative to the
other letters in the word. Therefore, this location-dependent processing of letter identities must be transformed into a locationindependent, word-centered orthographic code (e.g., Caramazza &
Hillis, 1990). This is achieved by letter-combination detectors (i.e.,
open-bigram units) that receive activation from appropriately ordered pairs of letters that are activated in the alphabetic array.
Thus, for example, whenever there is a letter A located to the left
of a letter T, the letter-combination detector for A_T will be
activated.
Dehaene et al. (2005) proposed a modified version of Grainger and
van Heuven’s (2003) model in an attempt to provide a stronger and
more neurally plausible hierarchical structure. The crucial difference
with respect to Grainger and van Heuven’s approach is that bigram
detectors operate locally (local combination detectors) in the Dehaene
MASKED SUPERSET PRIMING
401
Figure 1. Grainger and van Heuven’s (2003) model of orthographic processing. Visual features extracted from
a printed word stimulus are fed into a bank of alphabetic character detectors (the alphabetic array). The next level
of processing combines information from different processing slots in the alphabetic array to provide a relative
position code for letter identities. In the unconstrained version of open-bigram coding depicted in this figure, all
ordered pairs of adjacent and nonadjacent letters in the alphabetic array send activation to the appropriate
representations at the relative-position map. These open-bigram representations then control activation at the
level of whole-word orthographic representations (O-words) via bidirectional excitatory connections.
et al. model. It is the overlapping receptive field structure of letter
detectors (similar to Perea et al.’s, 2003, proposal) that provides some
position invariance at the bigram level (and not complete position
invariance, as proposed by Grainger & van Heuven, 2003, and Whitney, 2001). Grainger et al. (2005) referred to this version of bigram
coding as the overlap open-bigram model (because it combines the
principles of the overlap model and the open-bigram model). In this
approach, bigram units code for the presence of two letter identities in
two adjacent slots of the letter detector array, as a function of the
probability that each letter is present at a given slot. These bigram
units will therefore code for adjacent letter combinations, but because
of the overlapping receptive fields of letter detectors, the local bigram
detectors also react, albeit to a lesser extent, to transposed-letter
combinations and noncontiguous letter combinations.
Davis’s (1999) SOLAR (self-organizing lexical acquisition
and recognition) model uses an activation gradient to code for
relative letter position (activation values are highest for letters
at the beginning of the string and lowest for letters at the
end— but note that these activation values do not affect how
well the individual letters are perceived). In the SOLAR model,
the orthographic input layer includes letter units that are position independent and context independent. The relative order of
the letters in a string is coded by the relative activity of the
letter nodes. The activation input for each word detector is
calculated by evaluating the match between two spatial codes:
(a) the spatial code corresponding to the word represented by
this detector and (b) the spatial orthographic code corresponding to the input stimulus. The similarity of these two spatial
codes is a function of the number of shared letters and the extent
to which the order of the shared letters is respected across the
two strings (see Davis, in press, for a detailed presentation of
the SOLAR model and relevant match calculations).
Contiguity Effects
These new accounts of letter position coding (the overlap model;
Grainger and van Heuven’s, 2003, open-bigram model; the SERIOL
model; Dehaene et al.’s, 2005, local-bigram model; and the SOLAR
model) all do very well in accommodating the basic results obtained
with relative-position priming (Grainger et al., in press; Humphreys et
al., 1990; Peressotti & Grainger, 1999) and transposed-letter priming
(Forster et al., 1987; Humphreys et al., 1990; Perea & Lupker, 2003,
2004; Schoonbaert & Grainger, 2004). All these models predict, to
varying degrees, that the level of contiguity of letters shared by prime
and target should influence the magnitude of orthographic priming
effects. In the overlap model (Perea et al., 2003) and Dehaene et al.’s
(2005) local-bigram model, the size of overlapping receptive fields for
letter detectors determines the sensitivity of the model to manipulations of contiguity. In open-bigram coding schemes, contiguity can
influence processing by having bigram activation vary as a function of
the degree of separation of the constituent letters (bigrams formed of
adjacent letters are more strongly activated than bigrams formed of
nonadjacent letters— e.g., Grainger & van Heuven, 2003; Schoonbaert & Grainger, 2004; Whitney, 2001). In the most extreme version
of open-bigram coding, however, contiguity is irrelevant (at least
within the limits of parallel letter identification), and contiguous and
noncontiguous letter combinations are given equal weight (Grainger
et al., in press).2 In the SOLAR model, contiguity is one of the factors
2
In the most general form of open-bigram coding, contiguity can be considered
as a parameter that governs the “coarseness” of orthographic coding. This parameter could change during the process of learning to read (from more fine grained
to more coarse grained) and could be modifiable as a function of online processing
difficulty (depending on stimulus quality, for example).
VAN ASSCHE AND GRAINGER
402
that determines the amount of orthographic similarity across two letter
strings (Davis, 1999, 2006).
Grainger et al. (in press) failed to find conclusive evidence that
level of contiguity influences the size of priming effects obtained
with relative-position subset primes. When the confounding effects
of prime-target phonological overlap were removed (in conditions
in which there was no evidence for an influence of this factor),
then level of contiguity was found not to affect the size of relativeposition priming effects. Thus, for example, completely contiguous prime stimuli (1234 or 6789) were not more effective than
noncontiguous primes (1469) in priming nine-letter target words at
prime exposures of 33 ms. The present study provides a further test
of contiguity effects in relative-position priming.
The Present Study
Primes that respect the relative position of letters in targets
while violating absolute position can be formed in two different
ways: either by the removal of letters from the target (subset
primes) or by the addition of letters to the target (superset primes).
The majority of prior work investigating relative-position priming
(Grainger et al., in press; Humphreys et al., 1990; Peressotti &
Grainger, 1999) has used subset primes. The present study examines contiguity effects in relative-position priming using superset
primes. One advantage of using superset primes is that the level of
orthographic overlap (number of shared letters) can remain high
while the level of contiguity is lowered by inserting unrelated
letters in the prime stimulus.
The results from relative-position priming experiments in which
primes are a subset of the target’s letters demonstrate that subsets
can generate significant activation in the appropriate superset word
representation (Grainger et al., in press; Humphreys et al., in press;
Peressotti & Grainger, 1999). There is also evidence that supersets
can lead to the activation of their embedded subset items (Bowers,
Davis, & Hanley, 2005; De Moor & Brysbaert, 2000). Bowers et
al. (2005) found that semantic categorization times to superset
targets (e.g., is “hatch” a part of the human body?) were affected
by whether an embedded word (e.g., hat embedded in hatch)
belonged to the same response category. This result suggests that
the orthographic and semantic representations of embedded words
are activated during the processing of the superset target. It is
therefore likely that relative-position primes forming a superset of
the target word should generate significant facilitation in target
word processing. The present study tests for such superset priming
with target words embedded as noncontiguous sequences of letters.
In the present study, superset primes contain all of a target’s
letters in the correct order, plus one or more irrelevant letters (e.g.,
gardsen is a superset prime for the target GARDEN). In Experiments 1 and 2, we compare the effects of superset primes formed
by repeating a letter in the target word either adjacent to the
repeated letter or nonadjacent (repeat and repeat– displace priming
conditions, respectively), with superset primes formed by inserting
a letter that is not present in the target word (insert priming
condition). Experiment 3 tests for subset priming, in which letters
are removed from the target (remove priming condition), and
substitution priming, in which target letters are replaced by unrelated letters (substitute priming condition), using the same set of
targets as tested in Experiments 1 and 2. Finally, Experiment 4
tests for superset priming with primes formed by inserting three
unrelated letters in target words. Table 1 gives an overview of the
prime conditions tested in the present study.
As noted above, all recent models of letter position coding,
except for an unconstrained version of open-bigram coding
(Grainger et al., in press), predict graded effects of contiguity. That
is, priming effects should gradually diminish as level of contiguity
decreases. The predictions of four coding schemes are provided in
Table 2. These are the unconstrained open-bigram scheme and the
overlap open-bigram model described in Grainger et al.’s (in press)
study,3 the SERIOL model (Whitney, 2001), and the SOLAR
model (Davis, 2005). Each of these models can generate precise
predictions for priming effects expressed in terms of how well the
orthographic representation of the prime stimulus matches that of
the target stimulus. Match values in each model vary as a function
of the number of letters shared by prime and target (not the number
of unrelated letters) and the relative positions of these shared
letters in prime and target stimuli. They are independent of letter
identity and therefore do not reflect the operation of additional
mechanisms tied to specific letter identities (this is the realm of
full-blown simulations run on implemented versions of the different models and is beyond the scope of the present study). Higher
match values predict larger priming effects. Unrelated primes have
a match value of 0, and identity primes have a match value of 1.
Within a given priming condition, the match values are identical
across different items.
As can be seen in Table 2, all models except for the unconstrained open-bigram scheme of Grainger et al. (in press) predict
graded effects of letter insertion in superset priming. The overlap
open-bigram model, the SERIOL model, and the SOLAR model
all predict that increasing the number of inserted letters will
gradually lower the amount of priming. We tested this by comparing effects of number of inserted letters across Experiments 1,
2, and 4. The unconstrained open-bigram model makes the strong
prediction that superset priming should be as strong as identity
priming (match value ⫽ 1). Finally, concerning the different types
of superset primes, only the overlap open-bigram model and the
SERIOL model predict that letter repetition should be less damaging than letter insertion and that immediate repetition should be
less damaging than a displaced repetition. Both the SOLAR model
and the unconstrained open-bigram model predict no influence of
this factor, with equivalent priming effects across the repeat,
repeat– displace, and insert conditions. Experiment 1 provides an
initial test of these predictions with superset primes containing one
letter more than the corresponding target, either as a directly
repeated letter, a displaced repetition, or the insertion of a letter
that is not present in the target.
Experiment 1
Method
Participants. Forty psychology students at the University of Provence
participated in the experiment in return for course credit. They all reported
being native speakers of French with normal or corrected-to-normal vision.
Stimuli and design. Sixty French seven-letter words were selected as
critical targets in a masked priming lexical decision experiment. Their
3
We expected Grainger et al.’s (in press) implementation of the overlap
open-bigram scheme to generate predictions similar to Dehaene et al.’s
(2005) local bigram scheme.
MASKED SUPERSET PRIMING
403
Table 1
Summary of the Prime Conditions Tested in Experiments 1– 4
Experiment
Repeat
1a
1b
Repeat–displace
12334567
12345567
2a
2b
12534567
12345367
Insert
12d34567
12345d67
Unrelated/identity
dddddddd
1234567
Repeat
Repeat–displace
Insert
Unrelated/identity
123334567
123455567
125534567
123453367
12dd34567
12345dd67
ddddddddd
1234567
Substitute–group
Substitute–disperse
Remove
Unrelated/identity
3a
3b
12dd567
123dd67
12d45d7
1d34d67
12457
13467
4
Insert–group
Insert–disperse
12ddd34567
123ddd4567
1234ddd567
12345ddd67
12d3d4d567
123d4d5d67
Identity
1234567
ddddddd
1234567
Unrelated
dddddddddd
Note. The numbers refer to the position of a given prime letter in the target word. The letter d refers to the presence of a different letter at a given position
in the prime and target.
mean printed frequency was 15 per million and ranged from 1 to 133 (New,
Pallier, Ferrand, & Matos, 2001). The words were nouns, adjectives, or
verbs in infinitive form. Sixty pronounceable, orthographically regular
nonwords were selected that were all seven letters long. None of the words
or nonwords contained a repeated letter. These 120 items formed the
targets. For all of these targets, three related types of eight-letter nonword
primes were constructed: (a) a related prime, which was formed by repetition of the third or fifth letter of the target (repeat condition; e.g., jusstice
or justiice as a prime for JUSTICE); (b) a related prime, in which the third
or fifth letter also appeared in the sixth or third letter position, respectively
(repeat– displace condition; e.g., justisce or juistice as a prime for JUSTICE); and (c) a related prime, in which a different letter was inserted in
Table 2
Match Values for the Unconstrained Open-Bigram (UOB)
Model, the Overlap Open-Bigram (OOB) Model, the SERIOL
Model, and the SOLAR Model for the Conditions Tested in the
Present Experiments
Experiment and
condition
UOB
OOB
SERIOL
SOLAR
Repeat
Repeat–displace
Insert
1.00
1.00
1.00
0.96
0.90
0.87
1.12
0.91
0.89
0.94
0.94
0.94
Repeat
Repeat–displace
Insert
1.00
1.00
1.00
0.95
0.82
0.79
1.14
0.84
0.81
0.80
0.80
0.80
Substitute
Remove
0.48
0.48
0.39
0.44
0.48
0.53
0.71
0.60
Insert–disperse
Insert–group
1.00
1.00
0.67
0.78
0.73
0.77
0.63
0.67
1
2
3
4
Note. SERIOL ⫽ sequential coding regulated by inputs to oscillations
within letter units; SOLAR ⫽ self-organizing lexical acquisition and
recognition.
the third or sixth position (insert condition; e.g., juastice or justimce as a
prime for JUSTICE). In addition to the three related conditions, there was
an unrelated prime condition, in which the prime had no letters in common
with the target (e.g., benpalqo–JUSTICE), and an identity prime condition,
in which prime and target were identical (e.g., justice–JUSTICE). The
unrelated primes had the same consonant–vowel structure as one of the
related primes (equally distributed across the three possibilities). The word
targets and corresponding prime stimuli are given in Appendix A. Prime
type (repeat vs. repeat– displace vs. insert vs. unrelated vs. identity) was
crossed with position of insertion, thus generating eight priming conditions, which were tested in two subexperiments. Each subexperiment tested
the 120 targets in the four prime conditions as described in Table 1.
Prime–target pairing was counterbalanced using a Latin square design.
Participants ran both experiments, and the order of experiments was
counterbalanced over the group of participants.
Procedure. Each trial consisted of four stimuli presented one after the
other at the center of a computer screen. The first was a row of 10 hash
marks (##########), which served as a forward mask, and was presented
for 500 ms together with two vertical lines positioned above and below the
center of the mask, serving as a fixation mark. Second, the prime was
displayed on the screen for 50 ms and was followed immediately by a
backward mask for 16 ms. The target was presented immediately after the
backward mask and remained on the screen until participant’s response or
for a maximum duration of 4,000 ms. The intertrial interval was 667 ms.
Presentation of the visual stimuli and recording of the response times (RTs)
were controlled by DMDX and TimeDX software Version 3.0 (Forster &
Forster, 2003) on a PC. All stimuli were presented in Arial font as white
characters on a black background. Primes and targets were of different
sizes in order to minimize physical overlap: Arial 16 for primes and Arial
12 for targets. For the masks, the same font size as for the primes was used.
The presentation of all trials was randomized, with a different order for
each participant. Participants were instructed to focus on the center of the
row of hash marks when they appeared (indicated by the two vertical lines)
and to decide whether the following string of letters was a French word or
not. Participants were instructed to make this decision as quickly and as
accurately as possible. The presence of a prime was not mentioned. They
responded yes by pressing the right response button and no by pressing the
left response button of a Wingman Precision gamepad (Logitech, Baden-
VAN ASSCHE AND GRAINGER
404
Dattwil, Switzerland). The assignment of responses was reversed for
left-handed participants.
Results
Mean response times and percentage of errors are presented in
Table 3. Incorrect responses (2.3% of the data for word targets)
and RTs shorter than 250 ms or longer than 1,500 ms (0.6% of the
data for word targets) were excluded from the RT analysis. Analyses of variance (ANOVAs) by participants (F1) and items (F2)
were performed on the mean correct RTs and mean percentage of
errors to words and nonwords. We performed pairwise comparisons to examine priming effects in the various related prime
conditions. All comparisons against the unrelated prime condition
were performed with Dunnett’s test (Dunnett, 1955). Other pairwise comparisons that were critical in a specific experiment were
tested with planned comparisons. In this and the following experiments, all effects stated as being significant had p values lower
than 5% ( p ⬍ .05).
Word analyses. An ANOVA on mean RTs to word targets
revealed a significant main effect of prime type, F1(4, 156) ⫽
14.17, MSE ⫽ 1,070.93, F2(4, 236) ⫽ 13.18, MSE ⫽ 1,855.51.
Pairwise comparisons using Dunnett’s test showed that the unrelated prime condition produced significantly longer RTs than the
repeat condition, t1(39) ⫽ 5.83, SE ⫽ 7.19, t2(59) ⫽ 4.61, SE ⫽
9.38; the repeat– displace condition, t1(39) ⫽ 6.37, SE ⫽ 6.28,
t2(59) ⫽ 4.64, SE ⫽ 8.84; the insert condition, t1(39) ⫽ 6.85, SE ⫽
5.80, t2(59) ⫽ 4.75, SE ⫽ 8.30; and the identity condition,
t1(39) ⫽ 4.70, SE ⫽ 10.72, t2(59) ⫽ 4.48, SE ⫽ 11.73. Planned
comparisons between the superset prime conditions and the identity condition showed that identity primes did not differ significantly from repeat primes, F1(1, 39) ⫽ 1.07, MSE ⫽ 1,301.68,
F2(1, 59) ⫽ 3.02, MSE ⫽ 853.11; repeat– displace primes, F1(1,
39) ⫽ 1.80, MSE ⫽ 1,171.80, F2(1, 59) ⫽ 2.48, MSE ⫽ 1,584.39;
and insert primes, F1(1, 39) ⫽ 1.36, MSE ⫽ 1,637.87, F2(1, 59) ⫽
2.68, MSE ⫽ 1,918.06. A comparison of the identity prime condition and the combined data for the three superset primes was
nonsignificant, F1(1, 39) ⫽ 1.64, MSE ⫽ 1,734.70, F2(1, 59) ⫽
3.47, MSE ⫽ 1,644.22, p ⬍ .07. Planned comparisons across the
three superset prime conditions (repeat, repeat– displace, insert)
showed no significant differences (Fs ⬍ 1).
There was no effect of prime type in an ANOVA conducted on
the percentage of errors to word targets, F1(4, 156) ⫽ 1.94, MSE ⫽
10.26, F2(4, 236) ⫽ 2.03, MSE ⫽ 14.71. There were no significant
effects of the position of insertion manipulation (Experiment 1a vs.
Experiment 1b) in either the RT analysis (Fs ⬍ 1) or the error
analysis, F1(1, 39) ⫽ 3.35, MSE ⫽ 10.85, F2(1, 59) ⫽ 1.95,
MSE ⫽ 27.89, and this factor did not interact with priming in the
RT analysis, F1(2, 78) ⫽ 1.40, MSE ⫽ 1,027.82, F2 ⬍ 1, or in the
error analysis, F1(2, 78) ⫽ 1.92, MSE ⫽ 13.40, F2(2, 118) ⫽ 2.50,
MSE ⫽ 15.45.
Nonword analyses. An ANOVA with mean RT as a dependent
variable yielded a nonsignificant effect of prime type, F1(4,
156) ⫽ 2.15, MSE ⫽ 3,316.19, p ⬍ .08, F2(4, 236) ⫽ 2.30, MSE ⫽
4,223.88, p ⬍ .06. However, pairwise comparisons with Dunnett’s
test showed that RTs were not significantly longer for the unrelated primes compared with the repeat primes, t1(39) ⫽ 2.52, SE ⫽
14.06, t2(59) ⫽ 2.17, SE ⫽ 18.76; the repeat– displace primes,
t1(39) ⫽ 2.32, SE ⫽ 12.72, t2(59) ⫽ 2.06, SE ⫽ 17.01; the insert
primes, t1(39) ⫽ 1.71, SE ⫽ 14.49, t2(59) ⫽ 1.61, SE ⫽ 16.17; or
the identity primes, t1(39) ⫽ 1.15, SE ⫽ 20.80, t2(59) ⫽ 1.43,
SE ⫽ 21.50. Other planned comparisons yielded no significant
differences (Fs ⬍ 1), and there were no significant effects in the
ANOVA conducted on the error percentages (Fs ⬍ 1).
Discussion
The results of Experiment 1 showed large priming effects from
superset primes compared with the unrelated prime condition. To our
knowledge, this is the first report of a noncontiguous superset priming
effect in which primes are formed by inserting irrelevant letters in the
target word. This result provides further evidence for relative-position
priming, previously only obtained with subset primes. In line with
prior work on subset priming (Grainger et al., in press; Humphreys et
al., 1990; Peressotti & Grainger, 1999), the results of Experiment 1
show that letters shared by prime and target need not be contiguous
for orthographic priming to be obtained.
These superset priming effects obtained with a single letter
insertion were practically the same size as the identity priming
effect. Furthermore, the superset priming effects were statistically
equivalent for the immediate-repetition, displaced-repetition, and
insertion priming conditions. This pattern of results fits best with
the predictions of the unconstrained open-bigram model and the
SOLAR model. These two models differ in terms of whether
superset priming effects are the same size as identity priming
effects. The nonsignificant 10 ms difference between the superset
prime conditions and the identity prime condition does not allow
Table 3
Mean Response Times (RTs; in ms) and Percentage of Errors for Word and Nonword Targets in
Experiment 1
Type of prime
Identity
Target
Words
RT
Errors
Nonwords
RT
Errors
Repeat
Repeat–displace
Insert
Unrelated
M
SE
M
SE
M
SE
M
SE
M
SE
532
2.2
14.5
0.8
541
1.8
15.1
0.4
543
1.9
14.4
0.4
543
2.7
14.7
0.4
582
3.5
13.9
0.7
669
3.2
27.3
0.9
658
2.8
23.7
0.6
664
2.7
23.9
0.7
669
2.9
24.1
0.6
693
2.5
31.2
0.7
MASKED SUPERSET PRIMING
us to conclude on this point for the moment. Experiment 2 provides a further test of superset and identity priming while examining whether the insertion of two letters (as opposed to a single
letter in Experiment 1) modifies the pattern of priming effects.
This should help decide whether it is the SOLAR model or the
unconstrained open-bigram model that best captures the effects of
superset priming.
Experiment 2
Method
Participants. Thirty-six students at the University of Provence took
part in this experiment for course credit. They all reported being native
speakers of French with normal or corrected-to-normal vision and had not
participated in the previous experiment.
Stimuli and design. The target stimuli were the same as in Experiment 1.
A new set of nine-letter prime stimuli was generated for the three related prime
conditions: (a) in the repeat condition, the third or fifth letter was repeated
twice (e.g., jussstice or justiiice as a prime for JUSTICE); (b) in the repeat–
displace condition, the third or fifth letter appeared twice in the sixth or third
letter position, respectively (e.g., justissce or juiistice as a prime for JUSTICE);
and (c) in the insert condition, two letters that did not belong to the target were
inserted in the third or sixth position (e.g., jurqstice or justiaoce as a prime for
JUSTICE). There was an unrelated prime condition (e.g., bauelmoqi–
JUSTICE) and an identity prime condition (e.g., justice–JUSTICE). The word
targets and corresponding prime stimuli are listed in Appendix B. As in
Experiment 1, the eight prime conditions (Prime Type ⫻ Position) were
divided in two separate subexperiments, Experiment 2a and 2b, with each
participant being tested in the two subexperiments and the order of the
experiments counterbalanced across participants.
Procedure. The procedure was the same as in Experiment 1.
Results
Mean response times and percentage errors are presented in
Table 4. Errors (2.6% of the data for word targets) and RTs that
were shorter than 250 ms or longer than 1,500 ms (0.7% of the data
for word targets) were excluded from the latency analysis.
Word analyses. An ANOVA on RTs to word targets yielded a
significant effect of prime type, F1(4, 140) ⫽ 8.99, MSE ⫽
1,416.10, F2(4, 236) ⫽ 11.18, MSE ⫽ 1,965.90. Pairwise comparisons with Dunnett’s test showed that all the superset prime conditions and the identity condition generated shorter RTs than the
unrelated condition: repeat primes, t1(35) ⫽ 5.53, SE ⫽ 8.00,
t2(59) ⫽ 5.81, SE ⫽ 7.59; repeat– displace primes, t1(35) ⫽ 5.01,
SE ⫽ 8.11, t2(59) ⫽ 5.40, SE ⫽ 7.34; insert primes, t1(35) ⫽ 4.53,
405
SE ⫽ 8.11, t2(59) ⫽ 5.42, SE ⫽ 6.93; and identity primes, t1(35) ⫽
3.31, SE ⫽ 13.91, t2(59) ⫽ 5.03, SE ⫽ 9.48. Planned comparisons
against the identity prime condition showed no significant differences with the repeat condition (Fs ⬍ 1), the repeat– displace
condition (Fs ⬍ 1), and the insert condition, F1 ⬍ 1, F2(1, 59) ⫽
1.34, MSE ⫽ 2,277.69. A comparison of the identity primes and
the combined data of the three superset primes showed no significant difference (Fs ⬍ 1). Planned comparisons of the repeat and
repeat– displace primes (Fs ⬍ 1); the repeat and insert primes,
F1(1, 35) ⫽ 1.70, MSE ⫽ 578.24, F2 ⬍ 1; and the repeat– displace
and insert primes (Fs ⬍ 1) showed no significant differences.
An ANOVA on the error percentages revealed a significant effect
of prime type, F1(4, 140) ⫽ 4.64, MSE ⫽ 12.36, F2(4, 236) ⫽ 5.26,
MSE ⫽ 18.15. Dunnett’s test revealed significantly more errors for
the unrelated condition compared with the repeat– displace condition,
t1(35) ⫽ 2.91, SE ⫽ 0.90, t2(59) ⫽ 2.57, SE ⫽ 10.18, and the identity
condition, t1(35) ⫽ 3.01, SE ⫽ 1.06, t2(59) ⫽ 3.29, SE ⫽ 0.96. In the
RT analysis, there was a significant effect of position of insertion
(Experiment 2a vs. Experiment 2b) in the analysis by items, F1(1,
35) ⫽ 2.39, MSE ⫽ 3,207.98, F2(1, 59) ⫽ 7.74, MSE ⫽ 1,415.10, and
no effect of this variable in the error analysis (Fs ⬍ 1). Most important, the interaction between position of insertion and prime type was
not significant in either the RT analysis, F1(2, 70) ⫽ 3.08, MSE ⫽
874.56, F2(2, 118) ⫽ 2.35, MSE ⫽ 1,958.52, or the error analysis
(Fs ⬍ 1).
Nonword analyses. There was no effect of prime type in the
ANOVA on mean RTs to nonword targets and no effect in the
error rates (Fs ⬍1).
Combined analysis of Experiments 1 and 2. The results of
Experiments 1 and 2 were analyzed together, with experiment as a
between-participants variable. There was a main effect of prime
type, F1(4, 296) ⫽ 22.38, MSE ⫽ 1,234.19, F2(4, 236) ⫽ 23.01,
MSE ⫽ 2,012.50, and no interaction between prime type and
experiment (Fs ⬍ 1). Most important, a comparison of identity
primes against the three superset prime conditions was not significant, F1(1, 74) ⫽ 1.53, MSE ⫽ 2,136.25, F2(1, 59) ⫽ 2.68,
MSE ⫽ 2,864.96.
Discussion
Experiment 2 generated the same pattern of results as Experiment
1. The repeat, repeat– displace, and insert primes did not differ significantly from the identity condition, and all related primes produced
significantly shorter RTs and less errors than the unrelated condition.
Table 4
Mean Response Times (RTs; in ms) and Percentage of Errors for Word and Nonword Targets in
Experiment 2
Type of prime
Identity
Target
Words
RT
Errors
Nonwords
RT
Errors
Repeat
Repeat–displace
Insert
Unrelated
M
SE
M
SE
M
SE
M
SE
M
SE
531
1.5
19.8
0.7
533
2.1
14.9
0.6
536
2.0
16.8
0.4
540
3.3
14.0
0.6
576
4.6
15.5
1.0
635
3.7
24.8
1.0
638
3.1
21.4
0.7
627
3.8
20.5
0.7
642
3.0
21.4
0.5
634
3.3
19.5
0.8
VAN ASSCHE AND GRAINGER
406
Superset primes formed by adding two irrelevant letters to the target
word generated almost as much priming as the identity prime condition, and the small numerical difference was not significant. This
provides further evidence against a strong role for contiguity in
relative-position priming. Furthermore, the different superset primes
did not produce different priming effects as a function of letter
repetition. The fact that superset priming continued to be statistically
just as strong as identity priming is in line with the predictions of the
unconstrained open-bigram model and not in line with the predictions
of the other models (see Table 2).
It could be argued, however, that any form of prime-target
orthographic overlap would suffice to generate maximum priming in the present testing conditions. Although we know from
prior research that this is very unlikely, it is nevertheless
important to compare superset priming with other forms of
orthographic priming that are likely to generate smaller effects.
This is the case for so-called substitution primes, where the
prime is formed by substituting one or more of the target’s
letters with unrelated letters. There is evidence for strong effects of single-letter substitution primes (e.g., bontrast–
CONTRAST) in relatively long words (Forster et al., 1987).
However, when two letters are substituted, then prior work
suggests that priming effects disappear. Peressotti and Grainger
(1999) used six-letter stimuli in which two letters were substituted by two different letters (e.g., bslcrn–BALCON). These
primes generated no priming relative to an unrelated condition.
Schoonbaert and Grainger (2004) tested two-letter substitution
primes for five- and seven-letter target words. They varied the
position of substitution so that the first two letters, the internal
two letters, or the final two letters were substituted (e.g., sfoit,
dafit, or dronu, respectively, as a prime for the French word
DROIT). The results indicated that the level of orthographic
overlap across prime and target was not great enough to induce
significant priming compared to an unrelated condition. However, for the seven-letter words, there was some evidence for
substitution priming when the two substituted letters were the
last two letters of the target word. Perea and Lupker (2003) also
found significant effects of two-letter substitution primes when
these occupied the two final positions of six-letter words, and
Perea and Lupker (2004) found evidence for nonadjacent twoletter substitution priming (e.g., anomel-ANIMAL) with sixletter words in their Experiment 2.
Experiment 3 of the present study tests for subset priming and
for adjacent and nonadjacent substitution priming in exactly the
same conditions as used in Experiments 1 and 2. All the models
analyzed in Table 2 predict lower levels of priming in these
conditions compared with both superset priming and identity priming. However, the models differ in their predictions concerning the
relative size of substitution priming and subset priming. The unconstrained open-bigram model predicts no difference, both the
overlap open-bigram model and the SERIOL model predict more
priming from subset primes, and the SOLAR model predicts more
priming from substitute primes.
Experiment 3
Method
Participants. Forty-four students at the University of Provence participated in this experiment in return for course credit. They all reported being
native speakers of French with normal or corrected-to-normal vision and
had not participated in Experiments 1 and 2.
Stimuli and design. The target words and nonwords of Experiments 1
and 2 were used again. Three new related prime types were created for the
purpose of the present experiment. In the substitute– group condition, two
letters of the target were replaced by different letters on the third and fourth
or on the fourth and fifth letter position (e.g., jumlice or jusmoce as a prime
for JUSTICE). The same manipulation was used in the substitute– disperse
condition, except that the unrelated letters replaced the two letters of the
target in the third and sixth or on the second and fifth letter position (e.g.,
jultiqe or jastuce as a prime for JUSTICE). The consonant–verb structure
of the target word was respected when substituting letters. In the remove
condition, two letters of the target were removed so that a subset prime was
created. The removal of the letters occurred in the third and sixth or in the
second and fifth letter position (e.g., jutie or jstce as a prime for JUSTICE).
As in Experiments 1 and 2, we included an unrelated prime condition and
an identity prime condition. The word targets and corresponding prime
stimuli are given in Appendix C. As in the previous experiments, the eight
prime conditions were tested in two separate subexperiments, with each
participant being tested in the two subexperiments and the order of the
experiments counterbalanced across participants.
Procedure. The same procedure as in Experiments 1 and 2 was used.
Results
Mean response times and percentage of errors are presented
in Table 5. Incorrect responses (1.8% of the data for word
targets) and RTs less than 250 ms or greater than 1,500 ms
(0.1% of the data for word targets) were excluded from the
latency analysis.
Word analyses. An ANOVA on mean correct RTs showed a
significant effect of prime type, F1(4, 172) ⫽ 19.73, MSE ⫽
852.47, F2(4, 236) ⫽ 23.78, MSE ⫽ 1,023.30. Pairwise comparisons with Dunnett’s test revealed significantly longer RTs for
unrelated primes compared with substitute– group primes, t1(43) ⫽
4.38, SE ⫽ 6.18, t2(59) ⫽ 6.15, SE ⫽ 4.53; substitute– disperse
primes, t1(43) ⫽ 3.62, SE ⫽ 6.26, t2(59) ⫽ 4.34, SE ⫽ 5.36;
remove primes, t1(43) ⫽ 5.11, SE ⫽ 7.73, t2(59) ⫽ 6.32, SE ⫽
6.37; and identity primes, t1(43) ⫽ 5.46, SE ⫽ 9.69, t2(59) ⫽ 6.66,
SE ⫽ 8.17. Planned comparisons showed that identity primes
differed significantly from substitute– group primes, F1(1, 43) ⫽
15.63, MSE ⫽ 916.92, F2(1, 59) ⫽ 15.52, MSE ⫽ 1,344.79;
substitute– disperse primes, F1(1, 43) ⫽ 24.70, MSE ⫽ 793.47,
F2(1, 59) ⫽ 22.48, MSE ⫽ 1,277.41; and remove primes, F1(1,
43) ⫽ 5.19, MSE ⫽ 740.87, F2(1, 59) ⫽ 5.41, MSE ⫽ 1,105.76.
Furthermore, significant differences were found between the remove and substitute– group conditions, F1(1, 43) ⫽ 9.03, MSE ⫽
368.73, F2(1, 59) ⫽ 6.17, MSE ⫽ 729.92, and between the remove
and substitute– disperse conditions, F1(1, 43) ⫽ 15.00, MSE ⫽
405.26, F2(1, 59) ⫽ 12.17, MSE ⫽ 696.96.
An analysis on the error data yielded a significant effect of
prime type, F1(4, 172) ⫽ 3.15, MSE ⫽ 7.63, F2(4, 236) ⫽ 3.47,
MSE ⫽ 9.46. Pairwise comparisons with Dunnett’s test revealed
that unrelated primes produced significantly more errors than
identity primes, t1(43) ⫽ 2.79, SE ⫽ 4.68, t2(59) ⫽ 2.74, SE ⫽
0.73. Planned comparisons between the related prime conditions
and the identity condition showed a significant difference for the
substitute– disperse condition, F1(1, 43) ⫽ 7.54, MSE ⫽ 6.05,
F2(1, 59) ⫽ 7.25, MSE ⫽ 8.58, and for the substitute– group
condition in the item analysis, F1(1, 43) ⫽ 3.58, MSE ⫽ 6.92, p ⬍
.07, F2(1, 59) ⫽ 4.98, MSE ⫽ 6.78. There was no effect of position
MASKED SUPERSET PRIMING
407
Table 5
Mean Response Times (RTs; in ms) and Percentage of Errors for Word and Nonword Targets in Experiment 3
Type of prime
Identity
Target
Words
RT
Errors
Nonwords
RT
Errors
Substitute–group
Substitute–disperse
Remove
Unrelated
M
SE
M
SE
M
SE
M
SE
M
SE
517
0.8
11.1
0.3
543
1.8
9.0
0.5
547
2.2
8.9
0.5
530
1.5
10.2
0.4
569
2.7
8.7
0.7
641
2.6
16.7
0.6
640
2.1
11.8
0.5
637
2.5
12.1
0.6
638
2.0
13.0
0.4
655
1.5
16.3
0.5
of overlap in both the RT and error analyses (Fs ⬍ 1), and this
factor did not interact with prime type in either the RT analysis,
F1(2, 86) ⫽ 1.43, MSE ⫽ 790, F2 ⬍ 1, or the error analysis, F1(2,
86) ⫽ 1.78, MSE ⫽ 13.89, F2(2, 118) ⫽ 1.60, MSE ⫽ 21.14.
Nonword analyses. There was no effect of prime type in the
analysis of mean RTs to nonword targets, F1 ⬍ 1, F2(4, 236) ⫽
1.23, MSE ⫽ 2,541.98, and no effect in an analysis of the error
data, F1 ⬍ 1, F2(4, 236) ⫽ 1.01, MSE ⫽ 10.67.
model and the SOLAR model. However, none of the match
calculations presented in Table 2 take into consideration the
possible inhibitory influence of unrelated letters (via bottomup, letter-word inhibition, for example). The significant advantage for subset primes over substitution primes could reflect the
influence of such a mechanism that emerges when primes do
not contain all of the target’s letters. We return to this issue in
the General Discussion.
Discussion
The results of Experiment 3 show, once again, significant
priming effects for all the related priming conditions relative to
the unrelated condition. However, in this experiment significant
differences were observed across the various related prime
conditions. The identity condition produced significantly
shorter RTs than both of the substitute conditions and the
remove condition, and the substitute conditions generated significantly longer RTs than the remove condition. The significantly lower levels of priming obtained in the substitute and
remove priming conditions compared with the identity priming
condition provide an important point of reference for the superset priming effects observed in Experiments 1 and 2. At the
very least, we can conclude that the particular testing conditions
used in the present study were sensitive to variations in the
degree of prime–target orthographic overlap. The significant
priming obtained with the remove prime condition in Experiment 3 is a further replication of relative-position priming with
subset primes. Grainger et al. (in press) found significant priming in very similar conditions (13457 primes for seven-letter
target words). Finally, Experiment 3 showed significant priming from substitution primes formed by replacing two of the
target word’s letters with unrelated letters, and these effects
were the same for adjacent and nonadjacent substitutions.
The fact that substitution primes generated significantly
longer RTs than the subset prime condition of Experiment 3 is
in line with the results of Peressotti and Grainger (1999), who
found significant subset priming when primes contained four
letters of six-letter target words (e.g., blcn–BALCON) but no
priming when unrelated letters were substituted for the missing
letters (e.g., bslcrn–BALCON). This pattern fits with the predictions of the overlap open-bigram model and the SERIOL
model (see Table 2) but not of the unconstrained open-bigram
Experiment 4
Experiment 2 found little evidence for interference from the
insertion of two irrelevant letters in superset primes. Experiment 3
demonstrated that our testing conditions are sufficiently sensitive
to pick up a full range of priming effects lying between the
unrelated prime condition and the identity priming condition. In
Experiment 4, we further tested the limits of superset priming by
using primes with three unrelated letters. These three unrelated
letters were either evenly dispersed across the target word or
grouped together within the target word.
Method
Participants. Twenty-four students at the University of Provence took
part in this experiment for course credit. They all reported being native
speakers of French with normal or corrected-to-normal vision and had not
participated in the previous experiments.
Stimuli and design. The target stimuli were the same as in the
previous experiments. A new set of 10-letter prime stimuli containing
three unrelated letters was generated: (a) In the insert– disperse condition, three letters were inserted at the third, fifth, and seventh positions
or at the fourth, sixth, and eighth positions (e.g., jusktridce as a prime
for JUSTICE), and (b) in the insert– group condition, three letters were
inserted at the third, fourth, and fifth positions; the fourth, fifth, and
sixth positions; the fifth, sixth, and seventh positions; or the sixth,
seventh, and eighth positions (e.g., justikrdce as a prime for JUSTICE).
As in the previous experiments, there was an unrelated prime condition
(e.g., gaklrbdopé as a prime for JUSTICE) and an identity prime
condition. The word targets and corresponding prime stimuli are given
in Appendix D.
Procedure. The procedure was the same as in the previous
experiments.
VAN ASSCHE AND GRAINGER
408
Results
Discussion
Mean response times and percentage errors are presented in
Table 6. Errors (1.9% of the data for word targets) and RTs that
were shorter than 250 ms or longer than 1,500 ms (0.1% of the data
for word targets) were excluded from the latency analysis.
Word analyses. An ANOVA on mean correct RTs to word
targets revealed a significant main effect of prime type, F1(3,
69) ⫽ 18.39, MSE ⫽ 899.66, F2(3, 177) ⫽ 23.96, MSE ⫽
1,835.52. Pairwise comparisons with Dunnett’s test showed that
the unrelated prime condition produced significantly longer RTs
than the insert– group condition, t1(23) ⫽ 2.78, SE ⫽ 8.07,
t2(59) ⫽ 3.12, SE ⫽ 7.98; the insert– disperse condition, t1(23) ⫽
2.53, SE ⫽ 8.68, t2(59) ⫽ 2.45, SE ⫽ 9.22; and the identity
condition, t1(23) ⫽ 7.53, SE ⫽ 8.52, t2(59) ⫽ 8.93, SE ⫽ 7.34.
Planned comparisons showed significant differences between
identity primes and insert– group primes, F1(1, 23) ⫽ 18.65,
MSE ⫽ 1,075.95, F2(1, 59) ⫽ 30.71, MSE ⫽ 1,589.07, and
between identity primes and insert– disperse primes, F1(1, 23) ⫽
18.99, MSE ⫽ 1,079.60, F2(1,59) ⫽ 32.65, MSE ⫽ 1,672.48.
There was no significant difference between the two insert conditions (Fs ⬍ 1). There was no effect of prime type in an ANOVA
on the percentage of errors to word targets (Fs ⬍ 1).
Nonword analyses. There was no effect of prime type in an
ANOVA on mean correct RTs to nonword targets (Fs ⬍ 1) and no
effect in the error analysis, F1(3, 69) ⫽ 2.17, MSE ⫽ 12.50, F2(3,
177) ⫽ 1.89, MSE ⫽ 41.44.
Cross-experiment comparison. The effects of one-letter, twoletter and three-letter insert– group primes were compared across
Experiments 1, 2, and 4 including the identity and unrelated
conditions. There was a main effect of prime type, F1(2, 194) ⫽
41.57, MSE ⫽ 1,617.66, F2(2, 118) ⫽ 54.33, MSE ⫽ 2,533.45, and
a marginally significant interaction between prime type and experiment in the item analysis, F1(4, 194) ⫽ 1.38, MSE ⫽ 1,617.66,
F2(4, 236) ⫽ 2.15, MSE ⫽ 1,968.97, p ⬍ .08. An analysis that
tested the interaction of prime type and experiment for the insert
and unrelated conditions showed no significant interaction, F1(2,
97) ⫽ 1.39, MSE ⫽ 856.48, F2 ⬍ 1. An analysis that tested for the
interaction of insert and identity primes with experiment was
significant in the item analysis and marginally significant by
participants, F1(2, 97) ⫽ 2.62, MSE ⫽ 1,676.62, p ⬍ .08, F2(2,
118) ⫽ 4.71, MSE ⫽ 1,770.27.
As can be seen in Figure 2, the effect of number of inserted
letters shows a sharp discontinuity between two- and three-letter
insertions that none of the models presented in Table 2 predicted.
The unconstrained open-bigram model incorrectly predicted no
change in priming effects as a function of number of inserted
letters, and the other three models incorrectly predicted either a
linear decrease in priming effect size as a function of number of
inserted letters or a nonlinear decrease in the wrong direction (less
change in the priming effect as the number of letters increases).
The observed discontinuity in the effects of number of inserted
letters on superset priming should nevertheless be interpreted with
caution given the nonsignificant interactions between priming effects and number of inserted letters. It certainly is a potentially
highly constraining result that should be further explored in future
work.
General Discussion
The present set of experiments provide a further exploration of
a general phenomenon referred to as relative-position priming,
first examined in the work of Humphreys et al. (1990). Relativeposition primes share letters with target words such that the order
of letters, but not the absolute length-dependent position of letters,
is respected in prime and target stimuli. There are two ways to
form relative-position primes. One is to remove letters from the
target and concatenate the remaining letters to form a subset prime
(e.g., the prime arict for the target word APRICOT). This type of
priming has been extensively investigated in the work of Humphreys et al. (1990), Peressotti and Grainger (1999), Schoonbaert
and Grainger (2004), and Grainger et al. (in press). The other way
to form relative-position primes is to add irrelevant letters to the
target word, thus forming superset primes (e.g., the prime apgricfot for the target APRICOT). The present study provides, to our
knowledge, the first investigation of superset priming in which
target words do not form a series of contiguous letters in prime
stimuli.
Experiments 1 and 2 found clear evidence for superset priming
when primes contained one or two additional letters, and this
superset priming did not differ significantly from the identity
priming condition. Furthermore, these superset priming effects did
not vary as a function of the type of inserted letter (an unrelated
Table 6
Mean Response Times (RTs; in ms) and Percentage of Errors for Word and Nonword Targets in
Experiment 4
Type of prime
Identity
Target
Words
RT
Errors
Nonwords
RT
Errors
Insert–group
Insert–disperse
Unrelated
M
SE
M
SE
M
SE
M
SE
508
1.3
16.7
0.8
549
1.6
14.2
0.6
549
2.4
13.0
1.0
571
3.0
16.7
0.9
579
2.6
21.1
1.1
584
3.7
20.4
1.2
578
1.6
18.9
0.7
589
1.4
18.5
0.7
MASKED SUPERSET PRIMING
Figure 2. Summary of effects of letter insertion (unrelated letters) in the
grouped-insert conditions of Experiment 1 (one-letter insertion), Experiment 2 (two-letter insertion), and Experiment 4 (three-letter insertion).
Priming effect sizes for insert primes are measured relative to the unrelated
condition on the left and relative to the identity prime condition on the
right.
letter or a repeat of one of the target’s letters) or of the position of
the insertion. This suggests that as long as all the target’s letters are
present in the prime in the correct order, then adding one or two
irrelevant letters to the prime stimulus has little influence on the
size of priming effects. Experiment 3 showed that this is not true
when primes form a subset of the target’s letters. Subset primes
(with no additional letters) generated significantly shorter RTs
than substitution primes (where missing letters are replaced by
unrelated letters). Both of these priming conditions generated
significantly shorter RTs than the unrelated prime condition and
significantly longer RTs than the identity prime condition. Finally,
Experiment 4 showed that inserting three unrelated letters in
superset primes continued to produce significant facilitation relative to the unrelated condition but significantly less so than the
identity prime condition.
Contiguity Effects in Relative-Position Priming
The present study used superset priming as a tool to further
investigate the role of letter contiguity in relative-position priming.
Letter contiguity refers to the extent to which adjacent letters in the
target word are also adjacent in the prime stimulus (and vice
versa). With superset primes, adding in irrelevant letters decreases
the level of contiguity of the target’s letters in the prime stimulus.
All the letter-position coding schemes described in the introduction, with the exception of the unconstrained open-bigram model
described in Grainger et al. (in press), predicted that priming
effects should vary as a function of the level of contiguity of the
prime’s letters in the target stimuli. The results of Experiments 1
and 2 of the present study show that this was not the case, because
the identity prime condition should have generated more priming
than the superset prime conditions (although there was a small
numerical advantage). However, in Experiment 4 we found that
inserting three irrelevant letters had a major impact on superset
priming, bringing the superset prime condition closer to the unrelated condition than to the identity prime condition. Therefore,
contrary to the unconstrained open-bigram model, contiguity does
appear to affect orthographic priming, but not in the graded continuous way predicted by the other models we chose to put to test.
Grainger et al. (in press) provided a similar investigation of the
role of contiguity in masked orthographic priming using subset
409
primes. They reasoned that if contiguity had any influence on
subset priming, then a completely contiguous prime 1234 for a
target word 1234567 should be more effective than the less contiguous prime 1357. Grainger et al. (in press) found that this was
not the case when the confounding effects of prime–target phonological overlap were controlled for (completely contiguous subset
primes will always tend to have greater levels of phonological
overlap with their corresponding targets). Thus, in priming conditions in which phonological overlap was shown to not influence
priming effects, the level of contiguity of subset primes did not
influence the size of priming effects. Grainger et al. took these
results as support for the hypothesis that noncontiguous letter
sequences are deliberately coded during orthographic processing
and offer a fast and reliable means of activating whole-word
representations in long-term memory. The results of the present
study clearly show the limits of such a coding mechanism as the
level of contiguity diminishes.
When we compare the empirical effects of number of inserted
letters summarized in Figure 2 with the predictions of the models
given in Table 2, it is clear that none of the models can capture the
discontinuous relation between superset priming and number of
inserted letters. One possibility is to replace the overlap openbigram model with a constrained version of open-bigram coding as
proposed in the original work of Grainger and van Heuven (2003)
and Schoonbaert and Grainger (2004). In this version of openbigram coding, a discontinuity is introduced in terms of the maximum number of intervening letters. However, even an apparently
discontinuous form of coding such as this predicts a fairly graded
decrease in priming effects as a function of the number of inserted
letters.
Another possibility is to locate the underlying mechanism elsewhere. Within the theoretical framework described in Figure 1,
one possibility would be to locate the disruptive effects of threeletter insertion found in Experiment 4 as being due to limitations
in the number of letters that can be processed in parallel by the
bank of letter detectors. This proposal predicts that shorter words
should not show the same disruptive effect of three-letter insertion.
Thus, for example, the prime 1d2d3d4 for a four-letter target word
(e.g., rbenasd–READ) should generate just as much priming as
one- and two-letter insertions. Alternatively, the discontinuity observed in the present study might reflect the limits of a system
designed to concatenate appropriate letters while ignoring irrelevant letters. We return to this possibility in our analysis of the
effects of unrelated letters below.
Effects of Letter Repetition
The present study included a comparison of the effects of
inserting unrelated letters compared with repeating a letter from
the target word. In Experiment 1, for example, superset primes
were formed by either directly repeating one of the target’s letters
(e.g., 12334567), repeating a letter at a different position (e.g.,
12345367), or inserting an unrelated letter (e.g., 12d34567). Contrary to the predictions of the overlap open-bigram model and the
SERIOL model, this manipulation did not affect the size of superset priming effects. Both of these models predicted stronger priming when the inserted letter was a repetition of one of the target’s
letters, especially for adjacent repetitions. Only the unconstrained
open-bigram model (Grainger et al., in press) and Davis’ (1999)
410
VAN ASSCHE AND GRAINGER
SOLAR model predicted equivalent priming for the three superset
prime conditions.
Schoonbaert and Grainger (2004) had previously tested a similar
manipulation with subset primes. In their study, primes were
formed by removing a letter from the target stimulus, and the letter
that was removed could either be a letter that was repeated in the
target (e.g., the letter A in BALANCE to form the prime balnce) or
not (e.g., balace). Subset priming effects were found not to vary as
a function of the status of the removed letter. The match values of
the SERIOL, SOLAR, and open-bigram models for these particular priming conditions show that only the SOLAR model successfully captures the observed null effect. The other models
predicted that subset primes without repeated letters should generate greater priming than subset primes that contain repeated
letters. Therefore, in terms of the influence of letter repetition on
relative-position priming effects, it appears that the SOLAR model
generates superior predictions relative to the other models examined in the present study. This remains a critical point for further
investigation.
Effects of Unrelated Letters
One problem in comparing the effects of superset primes with
the effects of identity primes is that the superset primes not only
have less contiguous letter sequences but also include unrelated
letters. However, the fact that the superset primes did not differ
significantly from the identity priming condition in either Experiment 1 or Experiment 2 of the present study suggests that unrelated letters have little influence on priming effects in these conditions. Indeed, the absence of any significant reduction in priming
effects with the insertion of one or two unrelated letters is strong
evidence against any bottom-up letter–word inhibition as implemented in the interactive-activation model (McClelland & Rumelhart, 1981). According to this mechanism, any unrelated letter in
the prime stimulus will send inhibition to the target word representation, hence slowing RTs compared to a condition with no
unrelated letters (i.e., the identity prime condition).
Nevertheless, the fact that substitution primes generated significantly longer RTs than subset primes in Experiment 3 is evidence
that, at least in some conditions, the presence of unrelated letters
has an inhibitory influence on priming effects. Peressotti and
Grainger (1999) demonstrated a similar inhibitory effect of substitution primes relative to a subset prime condition (with no
unrelated letters) and a prime condition where nonalphabetic symbols were inserted. More precisely, Peressotti and Grainger (1999)
found that two-letter substitution primes (e.g., bslcrn–BALCON)
had no influence on six-letter target words compared with the
unrelated prime condition, whereas subset primes (e.g., blcn–
BALCON) did facilitate target processing in the same experiment.
In another experiment, Peressotti and Grainger (1999) found that
using hyphen marks rather than different letters (e.g., b-lc-n) in
substitution primes generated just as much priming as subset
primes. This result was replicated by Grainger et al. (in press) with
seven-letter targets and primes sharing five letters with targets
(e.g., 1-345-7). Thus it appears that unrelated letters do, in certain
conditions, hinder prime processing, and this could be because of
their status as letters or their visual complexity (compared with
hyphen marks, for example) or both.
The present study suggests that the inhibitory effects of unrelated letters may vary as a function of the number of missing letters
(number of the target’s letters that are not in the prime). When
primes contained all of the target word’s letters (superset primes),
then the presence of one or two unrelated letters had no influence
on priming. However, when primes contained a subset of the target
word’s letters, then the presence of two unrelated letters (the
substitution condition of Experiment 3) significantly reduced the
amount of priming compared to a condition with no unrelated
letters (the subset condition of Experiment 3). This pattern of
results suggests that bottom-up inhibitory influences depend on the
amount of bottom-up facilitation generated by a prime stimulus.
This could arise in the interactive-activation model (McClelland &
Rumelhart, 1981) if inhibitory letter–word influences took longer
to spread than excitatory letter–word influences. Thus, in the case
of superset primes, a fast feedforward excitatory activation flow
could rapidly activate the target word representation, allowing it in
turn to suppress activation of incompatible representations at the
letter level via top-down inhibition. Substitution primes, on the
other hand, would not provide as much bottom-up excitatory input
to the target word representation and therefore would not benefit as
much from top-down suppression of irrelevant letters.
An alternative possibility, more in line with Grossberg’s (1978)
adaptive resonance framework (which does not allow for
bottom-up inhibition), is that superset primes are accurately
matched with the target word representation by ignoring irrelevant
letters (which is possible when the proportion of irrelevant letters
is small—i.e., one or two letters out of seven). On the other hand,
with substitution primes, the matching process would be handicapped by the missing letters, and the resulting lower levels of
activation generated in word representations would trigger a verification process (i.e., the system decides that there is not enough
bottom-up information to accurately select a word representation).
This verification process would compare bottom-up letter-level
activation with top-down activation from a given word representation, and it is during such a process that the presence of unrelated
letters (i.e., substitution primes) might affect processing compared
with when there are none (i.e., subset primes).
According to both of these frameworks (interactive-activation
and adaptive resonance), it is the proportion of matching letters
that will determine whether the initial feedforward match is successful. The evidence is in favor of this prediction with both
single-letter and two-letter substitution primes generating strong
priming effects in longer target words (Forster et al., 1987; Perea
& Lupker, 2003, 2004; Schoonbaert & Grainger, 2004). Furthermore, the number of alternative words that receive bottom-up
activation from both the prime and the target stimulus is also
predicted to be a factor determining the size of substitution priming effects (Forster & Davis, 1991; Van Heuven, Dijkstra,
Grainger, & Schriefers, 2001). In both the interactive-activation
and adaptative resonance models, representations of words other
than the target itself that receive bottom-up support from prime
and target stimuli send inhibition to the target word representation,
thus slowing its identification.
Conclusion
The present study has highlighted a new phenomenon related
to how skilled readers process strings of letters. Inserting one or
two unrelated letters in a target word, hence creating what we
have called superset primes, generated strong priming effects in
the masked priming paradigm. All recent accounts of letter
MASKED SUPERSET PRIMING
position coding correctly predicted strong superset priming
relative to other forms of orthographic priming such as subset
and substitution primes. These results therefore provide further
support in favor of the general approach adopted by all of these
models that describe flexible mechanisms for coding letter
position information. However, no single model clearly
emerged when we considered the finer details of the present
results. Continued exploration of superset priming should provide further information about the effects of number of inserted
letters, the time course of these priming effects, and their
possible dependence on word length.
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(Appendixes follow)
VAN ASSCHE AND GRAINGER
412
Appendix A
Word Targets and Corresponding Prime Stimuli for the Conditions Tested in Experiment 1
Word
target
Repeat
Repeat–displace
Insert
Unrelated
Identity
1234567
12334567
12345567
12534567
12345367
12d34567
12345d67
dddddddd
1234567
charbon
prudent
plafond
fromage
fragile
spécial
chaleur
produit
méchant
fortune
machine
costume
diplôme
symbole
bagnole
section
gardien
facteur
mondial
malheur
morceau
miracle
durable
chômage
faculté
hôpital
délicat
habiter
naturel
dominer
cabinet
robinet
relatif
fatigue
logique
domaine
solaire
citoyen
couvert
courage
voiture
qualité
soutien
article
verdict
justice
journal
conseil
univers
moduler
docteur
bonheur
spirale
guitare
palmier
facture
dispute
sardine
robuste
galoper
chaarbon
pruudent
plaafond
froomage
fraagile
spéécial
chaaleur
prooduit
mécchant
forrtune
macchine
cosstume
dipplôme
symmbole
baggnole
secction
garrdien
faccteur
monndial
mallheur
morrceau
mirracle
durrable
chôômage
facculté
hôppital
déllicat
habbiter
natturel
domminer
cabbinet
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rellatif
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pruoduit
méachant
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déclicat
hatbiter
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coeuvert
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molduler
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guaitare
pailmier
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sairdine
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charbaon
prudeunt
plafoand
fromaoge
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costusme
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galopler
chuarbon
praudent
pleafond
friomage
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spuécial
choaleur
preoduit
mérchant
foartune
matchine
coastume
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galrdien
faicteur
mopndial
maolheur
mofrceau
misracle
dumrable
chiômage
fahculté
hônpital
déglicat
hafbiter
nagturel
dofminer
casbinet
roqbinet
remlatif
faltigue
lodgique
doumaine
soqlaire
ciatoyen
coauvert
coiurage
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soautien
armticle
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jofurnal
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paglmier
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fromauge
fragiole
spéciual
chaleour
produeit
méchaint
fortubne
machione
costugme
diplôume
symbotle
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sectiron
gardioen
factedur
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malhedur
morceiau
miracqle
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chômauge
faculnté
hôpitqal
délicsat
habitper
naturmel
dominver
cabinhet
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relatmif
fatignue
logiqdue
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citoypen
couveart
couraige
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qualioté
soutiaen
articmle
verdiact
justimce
journeal
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univeors
modulcer
docteaur
bonhefur
spiraole
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palmiuer
factugre
dispuate
sardilne
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pleivdus
chabiosm
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thuilone
chounape
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stinoeaq
snauviel
virdo̧ols
gémbacli
sergouli
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genbruca
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coifnaed
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verudqim
mogusrén
gelmopud
jochifag
sahugtil
dorumlaf
camludix
misbuqoc
midoprau
bétachoi
beugoali
penfuago
resaolum
maideunp
heuimofa
lauesigo
boineuda
vailoeud
onsmudge
bamglosp
benpalqo
meutspif
gouvteax
efoamuld
ganichut
fabnoiem
liamcoep
chounife
loepaumi
cudnoaet
poislane
rocqmage
tomgulce
palichme
tichunef
charbon
prudent
plafond
fromage
fragile
spécial
chaleur
produit
méchant
fortune
machine
costume
diplôme
symbole
bagnole
section
gardien
facteur
mondial
malheur
morceau
miracle
durable
chômage
faculté
hôpital
délicat
habiter
naturel
dominer
cabinet
robinet
relatif
fatigue
logique
domaine
solaire
citoyen
couvert
courage
voiture
qualité
soutien
article
verdict
justice
journal
conseil
univers
moduler
docteur
bonheur
spirale
guitare
palmier
facture
dispute
sardine
robuste
galoper
Note. The numbers refer to the position of a given prime letter in the target word. The letter d refers to the presence of a different letter at a given position
in the prime and target.
MASKED SUPERSET PRIMING
413
Appendix B
Word Targets and corresponding Prime Stimuli for the Conditions Tested in Experiment 2
Word
target
Repeat
Repeat–displace
Insert
Unrelated
Identity
1234567
1233334567
123455567
125534567
123453367
12dd34567
12345dd67
ddddddddd
1234567
charbon
prudent
plafond
fromage
fragile
spécial
chaleur
produit
méchant
fortune
machine
costume
diplôme
symbole
bagnole
section
gardien
facteur
mondial
malheur
morceau
miracle
durable
chômage
faculté
hôpital
délicat
habiter
naturel
dominer
cabinet
robinet
relatif
fatigue
logique
domaine
solaire
citoyen
couvert
courage
voiture
qualité
soutien
article
verdict
justice
journal
conseil
univers
moduler
docteur
bonheur
spirale
guitare
palmier
facture
dispute
sardine
robuste
galoper
chaaarbon
pruuudent
plaaafond
frooomage
fraaagile
spééécial
chaaaleur
proooduit
méccchant
forrrtune
maccchine
cossstume
dippplôme
symmmbole
bagggnole
seccction
garrrdien
facccteur
monnndial
malllheur
morrrceau
mirrracle
durrrable
chôôômage
faccculté
hôpppital
délllicat
habbbiter
nattturel
dommminer
cabbbinet
robbbinet
relllatif
fatttigue
logggique
dommmaine
solllaire
citttoyen
couuuvert
couuurage
voiiiture
quaaalité
souuutien
arttticle
verrrdict
jussstice
jouuurnal
connnseil
uniiivers
moddduler
docccteur
bonnnheur
spiiirale
guiiitare
palllmier
facccture
dissspute
sarrrdine
robbbuste
gallloper
charbbbon
prudeeent
plafooond
fromaaage
fragiiile
spéciiial
chaleeeur
produuuit
méchaaant
fortuuune
machiiine
costuuume
diplôôôme
symbooole
bagnooole
sectiiion
gardiiien
facteeeur
mondiiial
malheeeur
morceeeau
miracccle
durabbble
chômaaage
faculllté
hôpitttal
délicccat
habittter
naturrrel
dominnner
cabinnnet
robinnnet
relatttif
fatigggue
logiqqque
domaiiine
solaiiire
citoyyyen
couveeert
couraaage
voituuure
qualiiité
soutiiien
articccle
verdiiict
justiiice
journnnal
conseeeil
univeeers
modulller
docteeeur
bonheeeur
spiraaale
guitaaare
palmiiier
factuuure
dispuuute
sardiiine
robussste
galoppper
chbbarbon
preeudent
plooafond
fraaomage
friiagile
spiiécial
cheealeur
pruuoduit
méaachant
fouurtune
maiichine
couustume
diôôplôme
syoombole
baoognole
seiiction
gaiirdien
faeecteur
moiindial
maeelheur
moeerceau
miccracle
dubbrable
chaaômage
fallculté
hôttpital
décclicat
hattbiter
narrturel
donnminer
cannbinet
ronnbinet
rettlatif
faggtigue
loqqgique
doiimaine
soiilaire
ciyytoyen
coeeuvert
coaaurage
vouuiture
quiialité
soiiutien
arccticle
veiirdict
juiistice
jonnurnal
coeenseil
uneeivers
mollduler
doeecteur
boeenheur
spaairale
guaaitare
paiilmier
fauucture
diuuspute
saiirdine
rossbuste
gapploper
charbaaon
prudeuunt
plafoaand
fromaooge
fragiaale
spéciééal
chaleaaur
produooit
méchaccnt
forturrne
machiccne
costussme
diplôppme
symbommle
bagnoggle
secticcon
gardirren
facteccur
mondinnal
malhellur
morcerrau
miracrrle
durabrrle
chômaôôge
faculccté
hôpitppal
délicllat
habitbber
naturttel
dominmmer
cabinbbet
robinbbet
relatllif
fatigttue
logiqggue
domaimmne
solaillre
citoytten
couveuurt
courauuge
voituiire
qualiaaté
soutiuuen
articttle
verdirrct
justissce
journuual
consennil
univeiirs
moduldder
docteccur
bonhennur
spiraiile
guitaiire
palmiller
factuccre
dispusste
sardirme
robusbbte
galopller
chgfarbon
praiudent
plieafond
friuomage
frouagile
spouécial
choialeur
praeoduit
méiuchant
foplrtune
maouchine
coqrstume
diauplôme
syncmbole
baiugnole
sehdction
gauordien
falmcteur
moeundial
mastlheur
moierceau
mingracle
dunqrable
chuiômage
fabgculté
hôrspital
déhnlicat
halmbiter
nafgturel
doclminer
caprbinet
rolhbinet
renglatif
facltigue
lompgique
dofgmaine
soeulaire
cibltoyen
coaiuvert
coieurage
voaeiture
quoealité
soaeutien
argdticle
veaurdict
jurqstice
joieurnal
cobfnseil
unaoivers
mopsduler
doaicteur
bocdnheur
spouirale
guoeitare
paoulmier
fahmcture
dioaspute
sabcrdine
roclbuste
gatmloper
charbuion
prudeiont
plafoeund
fromaiuge
fragioule
spécioual
chaleiour
produeait
méchaprnt
fortuaine
machirlne
costuiame
diplôfhme
symboaule
bagnostle
sectiuaon
gardilqen
facteiour
mondipral
malheoiur
morceblau
miracgfle
durabtsle
chômaiuge
faculsrté
hôpitcmal
délichvat
habitgmer
naturqdel
dominpter
cabinlpet
robinfdet
relatcmif
fatigsmue
logiqdfue
domaiuone
solaiptre
citoyauen
couveairt
couraiuge
voituaire
qualiouté
soutiauen
articsnle
verdibgct
justiaoce
journqfal
conseauil
univeaors
modulgher
docteplur
bonheaiur
spirauole
guitaoure
palmicger
factuiore
dispurcte
sardioune
robushpte
galopnter
stieulmaf
chaoibusm
brugieats
thipuaeno
ptouimesa
gruoivaen
stiquaoex
gnecaious
pivrdsolg
héoabmigu
serpauofi
narqilgpu
fastchure
quiefharo
perdauico
bupmarheg
pulmscoat
doiegnaum
qervouais
findacgot
fahgstoui
bevnhupso
soneptcfi
dupirstfa
rogmnisde
geqrsudim
migoprvun
melocgfun
sopchigam
tapsfugoq
doremqfus
lacumghix
mischunog
diprcoqéa
batuchmei
gutiechpo
fenphuami
saiudeoif
maideuofg
heumioave
laueomige
boeuigace
laidoueax
onsudghme
joghbnams
bauelmoqi
teichfmod
gaprumtef
efouabich
bachnipos
gabnuieom
lamqipcos
chouemifa
luioafome
cugnoeaif
posqinghe
rochmnali
toeuchami
palichmqe
finuqhmec
charbon
prudent
plafond
fromage
fragile
spécial
chaleur
produit
méchant
fortune
machine
costume
diplôme
symbole
bagnole
section
gardien
facteur
mondial
malheur
morceau
miracle
durable
chômage
faculté
hôpital
délicat
habiter
naturel
dominer
cabinet
robinet
relatif
fatigue
logique
domaine
solaire
citoyen
couvert
courage
voiture
qualité
soutien
article
verdict
justice
journal
conseil
univers
moduler
docteur
bonheur
spirale
guitare
palmier
facture
dispute
sardine
robuste
galoper
Note. The numbers refer to the position of a given prime letter in the target word. The letter d refers to the presence of a different letter at a given position
in the prime and target.
(Appendixes continue)
VAN ASSCHE AND GRAINGER
414
Appendix C
Word Targets and Corresponding Prime Stimuli for the Conditions Tested in Experiment 3
Word
target
Substitute–group
Substitute–disperse
Remove
Unrelated
Identity
1234567
12dd567
123dd67
12d45d7
1d34d67
12457
13467
ddddddd
1234567
charbon
prudent
plafond
fromage
fragile
spécial
chaleur
produit
méchant
fortune
machine
costume
diplôme
symbole
bagnole
section
gardien
facteur
mondial
malheur
morceau
miracle
durable
chômage
faculté
hôpital
délicat
habiter
naturel
dominer
cabinet
robinet
relatif
fatigue
logique
domaine
solaire
citoyen
couvert
courage
voiture
qualité
soutien
article
verdict
justice
journal
conseil
univers
moduler
docteur
bonheur
spirale
guitare
palmier
facture
dispute
sardine
robuste
galoper
chigbon
prabent
plirond
frutage
frepile
spunial
choteur
pranuit
mévrant
fogbune
mafsine
cogrume
ditfôme
sycfole
bapdole
semrion
gamlien
fadmeur
morvial
magteur
motseau
mihucle
dupeble
chitage
famolté
hôqutal
dépocat
hanoter
napirel
dotaner
carunet
roganet
resotif
facogue
lotaque
doluine
sonuire
cidayen
coamert
coivage
voagure
quobité
soalien
arsocle
venhict
jumlice
joetnal
copreil
unocers
mobaler
dongeur
bomqeur
spumale
guofare
pachier
fasgure
dimlute
samtine
roliste
ganuper
chalmon
prubont
plagind
fropuge
framule
spévoal
chatiur
proneit
mécdont
formine
macpone
cosgame
diphume
symfale
bagdile
secmaon
garsuen
facniur
monvual
malgour
mortiau
miruple
duronle
chôpige
facogté
hôpudal
délunat
habuner
natopel
domuger
cabomet
robalet
relunif
fatoque
logamue
domiune
soliure
citauen
coudart
coumige
voimare
quagoté
soudaen
artudle
vernact
jusmoce
jouftal
conruil
unibars
modaser
docniur
bonpaur
spimole
guifore
palgoer
facpore
dismate
sarhune
robicte
galufer
chirbun
pradebt
plefogd
frumape
frogise
spociul
choleir
preduat
mévhast
fomtuhe
mafhipe
cortule
diflôce
syhbope
bapnode
segtian
galdion
fanteir
mosdiul
mafheor
motceiu
mivacpe
dufabte
chimase
famuldé
hôgitul
dépicot
halitur
nahurol
dosinar
carinot
roginat
regatof
faqigoe
lomiqae
dotaipe
sonaihe
cifoyan
coavegt
coirave
voatume
quolibé
soatiun
argicme
vendigt
jultiqe
joernil
cotseul
unavebs
mocular
dontear
bosheir
sporafe
guotale
pagmiur
faptuge
dimpule
satdihe
romuspe
ganopur
ctarfon
psudint
pgafund
fnomuge
fmagole
svécual
cqaliur
pnodait
mochint
fartine
mochune
cistame
daplume
sumbile
bignule
sactuon
gorduen
foctiur
mendual
milhour
mircoau
moraple
dorafle
crômige
focudté
hupigal
dulipat
hobimer
nituhel
damiter
cobiret
rabicet
rolanif
fotipue
lagimue
dumaone
sulaore
catouen
ciuvart
ciuroge
vaitore
qoaluté
sautoen
astigle
vordact
jastuce
jeurfal
cansuil
ubivars
maduher
dictaur
banhiur
smirole
goiture
polmuer
fictore
daspote
sordune
ribumte
gilofer
chrbn
prdet
plfod
frmae
frgie
spcil
chler
prdut
méhat
fotue
mahie
cotue
dilôe
syboe
banoe
setin
gadin
fater
modil
maher
moceu
miace
duabe
chmae
faulé
hôitl
déict
haitr
naurl
doinr
caint
roint
reatf
faige
loiqe
doaie
soaie
cioyn
covet
corae
votue
qulié
sotin
arice
vedit
jutie
jornl
cosel
unves
moulr
doter
boher
sprae
gutae
pamir
fatue
dipue
sadie
rouse
gaopr
caron
pudnt
pafnd
fomge
fagle
sécal
calur
podit
mchnt
frtne
mchne
cstme
dplme
smble
bgnle
scton
grden
fctur
mndal
mlhur
mrcau
mrale
drale
cômge
fcuté
hpial
dliat
hbier
ntuel
dmier
cbiet
rbiet
rlaif
ftiue
lgiue
dmane
slare
ctoen
cuvrt
curge
vitre
qalté
suten
atile
vrdct
jstce
jural
cnsil
uivrs
mduer
dctur
bnhur
sirle
gitre
plmer
fctre
dspte
srdne
rbute
gloer
stilmuf
chabism
brugets
thipuno
ptomesu
gruvoen
stiqoex
gnecoas
pirdolg
hébmiga
serpofu
narpigu
fasture
qufhari
perduci
bupmaug
pulmoat
dogniem
qervuis
findoet
fahgoui
bevupso
sonepfi
fridute
rogisde
gequdim
migopun
melocun
sopigam
tapugog
doremus
lacumig
misunog
dipoqéa
batumei
gutiepo
fenuami
sapeuif
maidofg
hiomuve
laumige
boegaci
laideux
onsudge
joghams
balmeqo
teichod
gapruef
efaboch
banipos
gabniom
lamqios
chomifu
loafemu
cugnoaf
pesqino
rochali
toplumi
palimqe
fenimuc
charbon
prudent
plafond
fromage
fragile
spécial
chaleur
produit
méchant
fortune
machine
costume
diplôme
symbole
bagnole
section
gardien
facteur
mondial
malheur
morceau
miracle
durable
chômage
faculté
hôpital
délicat
habiter
naturel
dominer
cabinet
robinet
relatif
fatigue
logique
domaine
solaire
citoyen
couvert
courage
voiture
qualité
soutien
article
verdict
justice
journal
conseil
univers
moduler
docteur
bonheur
spirale
guitare
palmier
facture
dispute
sardine
robuste
galoper
Note. The numbers refer to the position of a given prime letter in the target word. The letter d refers to the presence of a different letter at a given position
in the prime and target.
MASKED SUPERSET PRIMING
415
Appendix D
Word Targets and Corresponding Prime Stimuli for the Conditions Tested in Experiment 4
Word target
Insert–disperse
Insert–group
Unrelated
Identity
1234567
e.g. 12d3d4d567
e.g. 12ddd34567
dddddddddd
1234567
charbon
prudent
plafond
fromage
fragile
spécial
chaleur
produit
méchant
fortune
machine
costume
diplôme
symbole
bagnole
section
gardien
facteur
mondial
malheur
morceau
miracle
durable
chômage
faculté
hôpital
délicat
habiter
naturel
dominer
cabinet
robinet
relatif
fatigue
logique
domaine
solaire
citoyen
couvert
courage
voiture
qualité
soutien
article
verdict
justice
journal
conseil
univers
moduler
docteur
bonheur
spirale
guitare
palmier
facture
dispute
sardine
robuste
galoper
chfamrvbon
prvukdbent
plcahfrond
frbodmpage
frdangsile
sprédcmial
chmaglteur
prfobdnuit
mécvhraknt
forbtsupne
macphgilne
cosftvurme
dipglsônme
symtbgople
bagvnfomle
secrtbipon
gaprbdlien
fagcptveur
morntdsial
manlghpeur
moprfcdeau
minrpafcle
dugrvamble
chdôpmkage
facgudlnté
hôprivtmal
délfincvat
habdiptser
natpusrvel
dombipnter
cabdifnret
robsifnmet
revlnagtif
fadtvikgue
longfirque
dormpavine
sotlmagire
cidtvopyen
cofubvsert
cobuprkage
voiptzubre
quarlmipté
souvtrilen
artsivcfle
versdgibct
jusktridce
joumrsnpal
condsteril
unpilvters
mondfusler
dobcptveur
bocnphteur
spdivrnale
gujiptsare
paslnmdier
fabcvtsure
discpruvte
sartdgilne
robpufsvte
galdonpser
chfmvarbon
prvkbudent
plchrafond
frbdpomage
fradnsgile
spérdmcial
chamgtleur
profbnduit
méchvrkant
fortbspune
machpgline
costfvrume
diplôgsnme
symbotgple
bagnovfmle
sectirbpon
gapblrdien
fagpvcteur
mortsndial
mangplheur
morpfdceau
mimpfacle
durgvmable
chôdpkmage
facugdnlté
hôpirvmtal
délifnvcat
habidpster
naturpsvel
dominbpter
cabindfret
robinsfmet
revnglatif
fadvktigue
lonfrgique
dorpvmaine
soltmgaire
citdvpoyen
coufbsvert
coubpkrage
voitpzbure
qualrmpité
soutvrlien
artisvfcle
verdisgbct
justikrdce
journmspal
consedtril
unpltivers
monfsduler
dobpvcteur
bocptnheur
spidvnrale
guijpstare
palsndmier
facbvsture
dispcrvute
sardtgline
robupfvste
galodnsper
ptfemsvcil
clvokmbafs
btcuhgrimt
tlbidnpuké
ctodmnésvu
tnorddemuf
bsimngotép
clafgbunes
buvrkdlips
dabsplcimé
dotpglrébu
balfvrdézi
bartgsnévu
candtgpifu
déchivfmsu
déslarbpuv
cusplboléz
libgzpovés
pécrztesuf
bicndgépos
nipbfsdèyé
sungpéfbdo
fignvompsé
trdépbkusi
bosivgdnre
busédrvmec
bosufnvger
cofédpsvuz
migpsvébof
cugbptéfal
gédfrluvos
désfmcugaz
bomvngésud
bordvkèpyé
mèjynfrsaé
cunybpvèté
vudèytmgné
bèféadvpuz
gafbsinéld
fibpkédèzy
daèpgsybvé
nèorbmypde
paèvbryléd
ubdsovgfhé
faslgnbopz
gaklrbdopé
gémisvpdet
bédmtfrauz
ampltodébz
bénfsgapit
fagbpvliés
fécptmgai
ctdovbnugé
bèjypdsové
zéscnbdout
mébpvlsodi
bafcgrovlé
btogvlpu
cédpaflvmi
cubdénrsit
charbon
prudent
plafond
fromage
fragile
spécial
chaleur
produit
méchant
fortune
machine
costume
diplôme
symbole
bagnole
section
gardien
facteur
mondial
malheur
morceau
miracle
durable
chômage
faculté
hôpital
délicat
habiter
naturel
dominer
cabinet
robinet
relatif
fatigue
logique
domaine
solaire
citoyen
couvert
courage
voiture
qualité
soutien
article
verdict
justice
journal
conseil
univers
moduler
docteur
bonheur
spirale
guitare
palmier
facture
dispute
sardine
robuste
galoper
Note. The numbers refer to the position of a given prime letter in the target word. The letter d refers to the presence of a different letter at a given position
in the prime and target.
Received February 22, 2005
Revision received November 24, 2005
Accepted November 27, 2005 䡲