Letter Position Information and Printed Word Perception: The Relative-Position Priming Constraint

Transcription

Journal of Experimental Psychology:
Human Perception and Performance
2006, Vol. 32, No. 4, 865– 884
Copyright 2006 by the American Psychological Association
0096-1523/06/$12.00 DOI: 10.1037/0096-1523.32.4.865
Letter Position Information and Printed Word Perception:
The Relative-Position Priming Constraint
Jonathan Grainger
Jean-Pierre Granier
University of Provence and Centre National
de la Recherche Scientifique
University of Provence
Fernand Farioli
Eva Van Assche
University of Provence and Centre National
de la Recherche Scientifique
University of Ghent
Walter J. B. van Heuven
University of Nottingham
Six experiments apply the masked priming paradigm to investigate how letter position information is
computed during printed word perception. Primes formed by a subset of the target’s letters facilitated
target recognition as long as the relative position of letters was respected across prime and target (e.g.,
“arict” vs. “acirt” as primes for the target “apricot”). Priming effects were not influenced by whether or
not absolute, length-dependent position was respected (e.g., “a-ric-t” vs. “arict”/“ar-i-ct”). Position of
overlap of relative-position primes (e.g., apric-apricot; ricot-apricot; arict-apricot) was found to have little
influence on the size of priming effects, particularly in conditions (i.e., 33 ms prime durations) where
there was no evidence for phonological priming. The results constrain possible schemes for letter position
coding.
Keywords: letter position coding, masked priming, relative-position priming, orthographic processing,
word recognition
position priming. Relative-position priming is a form of orthographic priming in which priming effects depend on shared letters
having the same relative position in prime and target stimuli. Thus,
for example, given the target word “apricot,” the prime stimulus
“arct” is said to preserve relative letter positions (i.e., the letter “r”
is after “a” and before “c”) but to violate absolute, lengthdependent position. Most studies of orthographic priming to date
have used substitution primes (e.g., adricot) where shared letters
preserve absolute letter position (e.g., Forster, Davis, Schoknecht,
& Carter, 1987; Grainger & Jacobs, 1993). With brief prime
exposures (50 – 60 ms) and forward masking of prime stimuli,
substitution primes generally facilitate target word recognition
compared to unrelated control primes (see Grainger & Jacobs,
1999, for a review). Priming effects obtained with substitution
primes were taken as evidence in favor of orthographic coding
schemes that use length-dependent, position-specific letter detectors, such as in McClelland and Rumelhart’s (1981) interactiveactivation model. However, there are an increasing number of
behavioral results that are incompatible with such an approach (see
Grainger & van Heuven, 2003; and Perea & Lupker, 2003, for
reviews). Relative-position priming is one such phenomenon.
Humphreys, Evett, and Quinlan (1990) were the first to study
relative-position priming. They used a four-field masking procedure that involved brief presentations of both prime and target
stimuli. In this paradigm, primes (nonwords) and targets (words)
are briefly presented one after the other. Immediately before the
prime and after the target, two masking patterns are displayed, and
There is a general consensus today among researchers investigating printed word perception that abstract letter identities, which
are independent of type font and case, represent one particularly
relevant source of information for the word recognition process
(e.g., Besner, Coltheart, & Davelaar, 1984; Evett & Humphreys,
1981; Rayner, McConkie, & Zola, 1980). However, in mapping
letter identities onto whole-word representations in memory, it is
clear that information about letter position must also be computed.
The importance of this type of information is obvious given that
languages that use alphabetic orthographies, such as English and
French, have large numbers of anagrams. We are able to distinguish words containing the same letters (e.g., BALE-ABLE) on the
basis of the different position of the letters in the string, just as we are
able to recognize that BLAE is not an English word. The question to
be addressed in the present study is, therefore, how do skilled readers
code such position information during printed word perception?
In an attempt to answer this question, the present study provides
a further investigation of a phenomenon referred to as relativeJonathan Grainger and Fernand Farioli, University of Provence, France,
and Centre National de la Recherche Scientifique, France; Jean-Pierre
Granier, University of Provence; Eva Van Assche, University of Ghent,
Belgium; Walter J. B. van Heuven, University of Nottingham, United
Kingdom.
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
865
866
GRAINGER ET AL.
the participant’s task is to recognize the target word presented in
upper case letters. The exposure durations of the four fields are
adjusted so that participants correctly reported about 40% of
targets. The results showed that priming effects varied as a function of both the number and the position of letters shared by primes
and targets of the same length. Greater degrees of orthographic
overlap produced larger priming effects, but only when shared
letters occupied the same position in primes and targets. In the
same study however, priming effects were also obtained when
primes and targets differed in length. So, for example, the sequence “bvk” facilitated the identification of the word “black”
with respect to the neutral condition “ovf,” just as well as the
sequence “btvuk” with respect to the neutral condition “otvuf.” In
the case of “bvk” primes, letters shared by prime and target are
said to preserve their relative position (ordinal information) and
not their length-dependent absolute position (as is the case with
“btvuk” primes).
Peressotti and Grainger (1999) replicated the relative-position
priming reported by Humphreys et al. using the masked priming
technique of Forster and Davis (1984). In their study, Peressotti
and Grainger (1999) found that modifying the absolute position of
letters shared between prime and target while maintaining their
correct relative-position (e.g., blcn-balcon) did not affect priming
relative to unrelated primes (e.g., tpvf-balcon). Inserting filler
letters or characters (e.g., bslcrn, b-lc-n) to provide absolute position information never led to significantly larger priming effects.
Furthermore, the results of one specific experiment showed no
priming relative to an unrelated prime condition when the relativeposition of two out of four letters is violated in orthographically
related primes and 6-letter target words (e.g., bcln-balcon). On the
other hand, if all four prime letters maintain their relative-position
in the target string, but not their absolute position in the target,
significant priming is obtained. These results therefore add support
to the work of Humphreys et al. (1990) showing that some form of
relative-position coding operates on printed strings of letters.
The relative-position priming effects observed by Humphreys et
al. (1990) and Peressotti and Grainger (1999) show very clearly the
limits of length-dependent, position-specific coding schemes, such
as implemented in the interactive-activation model (McClelland &
Rumelhart, 1981). Furthermore, the vast majority of attempts to
increase the flexibility of such coding schemes (e.g., Coltheart,
Curtis, Atkins, & Haller, 1993; Coltheart, Rastle, Perry, & Ziegler,
2001; Plaut, McClelland, Seidenberg, & Patterson, 1996; Seidenberg & McClelland, 1989) have not lead to any greater success in
capturing the basic relative-position priming effects. For example,
none of the above-cited coding schemes can account for Peressotti
and Grainger’s (1999) Experiment 2, which used 4-letter primes
and 6-letter targets. In this experiment, priming was observed for
“1346” and not for “1436” primes. According to both the IAmodel and Seidenberg and McClelland’s wickelgraph coding
scheme, there is no overlap between prime and target stimuli for
either of these prime conditions. According to the DRC (dual route
cascaded) model, only the first letter overlaps, and so the two
prime conditions are matched in terms of their orthographic similarity with targets. In vowel-centered coding schemes for monosyllabic words (e.g., Plaut et al., 1996), letter identities are assigned to one of three positions that correspond to the orthographic
onset, nucleus, and coda of the word. Relative-position primes
often violate such structure and therefore these schemes cannot
account for these data (see Davis & Bowers, 2004, for a similar
analysis with related phenomena).
With these considerations in mind, Grainger and van Heuven
(2003) recently argued that relative-position priming is one of the
single most constraining pieces of evidence for models of orthographic processing. Relative-position priming clearly reflects a
stage of processing where retinotopic information is lost, and some
form of word-centered, location-invariant orthographic coding operates (Caramazza & Hillis, 1990). The main objective of the
present study is to provide a larger empirical foundation for this
theoretically important phenomenon. The larger empirical foundation will be provided by 1) examining the limits of relativeposition priming in terms of degree of orthographic overlap across
prime and target in words of different lengths (7 and 9-letters); 2)
evaluating possible sequential biases and the relative importance
of outer and inner letters in relative-position priming; 3) comparing relative-position priming effects in two different tasks (lexical
decision and perceptual identification); 4) evaluating the influence
of masking (presence of a mask and length of mask) on relativeposition priming; 5) examining priming effects at different prime
exposure durations; and 6) comparing relative-position priming
with phonological priming. Table 1 summarizes the different priming conditions to be tested in the present study. In the general
discussion we will present some recent theoretical proposals for
letter position coding, and examine how these fare in accounting
for the results of the present experiments.
Experiment 1
As a further test of relative-position versus absolute-position
priming, Experiment 1 uses longer words than tested in prior
research (Humphreys et al., 1990; Peressotti & Grainger, 1999). It
is possible that the use of length-dependent position information
becomes more useful as word length increases. (Since the number
of different words of a given length decreases with word length,
length-specific information becomes more informative.) Experiment 1 tests 7-letter words, and Experiments 2–5 include 9-letter
stimuli. Furthermore, Experiment 1a includes a new manipulation
Table 1
Summary of the Priming Conditions Tested in the Main
Experiments
Experiment 1a:
Experiment 1b:
Experiment 2:
7-letter:
9-letter:
Experiments 3–5:
7-letter:
9-letter:
Experiments 6:
RP:
PH:
1-345-7
1-345-7
13-4-57
1-543-7
13457
7-345-1
ddddd
d-ddd-d
12345
12345
34567
56789
13457
14569
ddddd
ddddd
1234
1234
4567
6789
1357
1469
dddd
dddd
1357
P⫹O⫹
1537
P⫺O⫹
7351
P⫹O⫺
dddd
P⫺O⫺
Note. The numbers in the example primes refer to letters shared between
prime and target in that specific position. Hyphens refer to the use of this
symbol in the prime stimulus and the letter “d” refers to the presence of a
different letter at a given position in the prime and target. Experiment 6
tests relative-position priming (RP) and phonological priming (PH) with
different levels of phonological (P⫹/P⫺) and orthographic (O⫹/O⫺)
overlap across primes and targets.
RELATIVE-POSITION PRIMING
of absolute versus relative-position in prime stimuli of the same
length. The prime stimuli 1-345-7 and 13-4-57 both have the same
length as target stimuli, and letters respect relative position in both
cases. However, in the second prime condition absolute, lengthdependent position is incorrect for two of the five letters. These
priming conditions are compared to a relative-position prime Condition 13457 where all prime letters are concatenated.
Method
Participants. Forty students at the University of Provence took part in
Experiment 1a and 44 in Experiment 1b. They all reported being native
speakers of French with normal or corrected-to-normal vision.
Stimuli and design. Sixty French words, seven letters long, with
printed frequencies ranging from 7 to 175 per million (Imbs, 1971) were
selected. The words were nouns, adjectives, or verbs in infinitive form.
Sixty pronounceable, orthographically regular nonwords were created that
were all seven letters long. These 120 items formed the targets. Four
priming conditions were tested in each subexperiment with different participants. In Experiment 1a each related prime was made up of the two
outer letters and of the central triplet of the corresponding target (respectively letters 3, 4 and 5). Two hyphen marks were used as filler characters
in place of the missing letters (i.e., letters 2 and 6). In Condition 1, the
central triplet of the prime was in the same absolute position as in the target
(1-345-7)1. In Condition 2, absolute position information was disrupted by
inserting hyphen marks within the triplet (13-4-57), while in Condition 3 it
was disrupted by removing the hyphen marks (13457). Finally, in the
fourth condition, the primes were formed by five unrelated letters (ddddd).
In Experiment 1b, the first prime condition was the same as in Experiment
1a (1-345-7). In Condition 2, the order of the letters in the central triplet
was reversed (1-543-7), and in Condition 3 the two outer letters were
reversed (7-345-1). In Condition 4, the prime string was formed by five
unrelated letters and two hyphen marks (d-ddd-d). Counterbalancing with
a Latin Square design allowed each target to be tested in the four priming
conditions, across four lists associated with four independent groups of
participants in each subexperiment.
Procedure. Each trial consisted of three stimuli presented one after the
other at the center of a computer screen. The first was a row of seven hash
marks (#######) that served as a forward pattern mask and remained in
view for 500 ms. The second was the prime stimulus, which was displayed
for 50 ms, and was immediately followed by the third stimulus, the target,
which lasted until participants’ response or for a maximum time of 1000
ms. Stimulus presentation and response collection were controlled using
Psyscope software (Cohen, MacWhinney, Flatt, & Provost, 1993) on a
Macintosh Centris computer. Primes and targets were strings of centerjustified lower-case letters presented in fixed-width courier font. They had
different sizes in order to minimize physical overlap: courier 14 for primes
and courier 24 for targets. Each letter of the prime was approximately 0.3
cm wide, and each letter of the target approximately 0.5 cm wide. Participants sat in front of the computer at a viewing distance of approximately
60 cm. At that distance, the horizontal visual angle subtended by each letter
of the prime was approximately 0.3 degrees, and for each letter of the target
it was approximately 0.5 degrees. Participants were instructed to attend to
the center of the string of hash marks when they appeared, and to decide
as rapidly and as accurately as possible whether the following string of
letters was or was not a French word. The presence of a prime was not
mentioned. They responded “Yes” by pressing one response button with
the forefinger of the preferred hand and “No” by pressing the other
response button with the forefinger of the other hand. The response buttons
selected were the two outer buttons of the Psyscope button box. The
intertrial interval was 800 ms. Stimulus presentation was randomized
within each block with a different order for each participant. Response
times (RTs) were measured to the nearest millisecond.
867
Results
RTs for correct responses were analyzed after removing all
values smaller than 300 ms and greater than 1500 ms. In all cases
this resulted in removal of less than 1% of the data for correct
responses. Analyses of variance (ANOVAs) were performed with
participants (F1) and items (F2) as random variables. The mean RT
and percent error for each condition are shown in Table 2. Given
the particular design of the present set of experiments, as well as
main effects, pairwise comparisons with the unrelated prime condition were performed in order to examine priming effects in the
various related prime conditions. All comparisons against the
unrelated prime condition were performed using Dunnett’s test
(Dunnett, 1955). Other pairwise comparisons that were critical in
a specific experiment were tested using planned comparisons. In
the by-participant analyses, a list was included as a betweenparticipants factor in order to extract the variance associated with
this (Pollatsek & Well, 1995).
Experiment 1a. An ANOVA on mean correct RTs to word
targets revealed a main effect of prime type (F1(3,108) ⫽ 6.72,
p ⬍ .001; F2(3,177) ⫽ 6.23, p ⬍ .001). Pairwise comparisons
using Dunnett’s test indicated that the unrelated prime condition
produced significantly longer RTs than the 1-345-7 condition
(t1(39) ⫽ 2.86, p ⬍ .05; t2(59) ⫽ 2.74, p ⬍ .05), than the 13-4-57
condition (t1(39) ⫽ 3.61, p ⬍ .01; t2(59) ⫽ 3.60, p ⬍ .01), and the
13457 condition (t1(39) ⫽ 4.10, p ⬍ .01; t2(59) ⫽ 3.22, p ⬍ .01).
No significant effects were revealed in ANOVAs performed on the
percentages of error to word targets, nor on the mean correct RTs
and percentages of error to nonword targets.
Experiment 1b. An ANOVA on mean correct RTs to word
targets showed a main effect of prime type (F1(3,120) ⫽ 7.89, p ⬍
.001; F2(3,177) ⫽ 14.27, p ⬍ .001). Pairwise comparisons using
Dunnett’s test revealed a significant difference between the
1-345-7 condition and the all different letter primes (t1(43) ⫽ 3.77,
p ⬍ .01; t2(59) ⫽ 5.61, p ⬍ .01). The other comparisons were not
significant. No significant effects were revealed in ANOVAs performed on the percentages of error to word targets, nor on the
mean correct RTs and percentages of error to nonword targets.
Discussion
The results of Experiment 1a show that disrupting absolute
position information by inserting hyphens in the wrong place
(13-4-57) or removing the hyphens (13457) does not modify
priming effects compared with the absolute position condition
(1-345-7). All of these priming conditions produced significantly
faster RTs to target words than the unrelated prime condition. This
is therefore further evidence in favor of some form of relativeposition coding of letter strings. The results of Experiment 1b are
perfectly in line with those reported by Peressotti and Grainger
(1999, Experiment 2). In the Peressotti and Grainger study using
6-letter target words, only 1346 primes produced significant effects on RT. The 1436 and 6341 prime conditions did not differ
1
Related priming conditions are described using the numbered letters of
the target (e.g., 12345 for a 5-letter target) to indicate which of the target
letters appeared in the prime and in which location they appeared. So the
prime “135” indicates that primes were composed of the first, third, and
fifth letters of the target.
GRAINGER ET AL.
868
Table 2
Mean Response Times (RT in ms) and Percentages of Error
(PE) for the Different Priming Conditions Tested in
Experiment 1
Priming condition
Experiment 1a
Word targets
RT
PE
Nonword targets
RT
PE
1-345-7
13-4-57
13457
ddddd
560*
2.8
558*
1.9
555*
2.2
580
2.9
616
2.5
615
3.0
622
3.1
626
3.5
Experiment 1b
Word targets
RT
PE
Nonword targets
RT
PE
1-345-7
1-543-7
7-345-1
d-ddd-d
565*
1.8
591
2.9
581
2.0
589
1.5
659
3.6
653
3.5
661
2.5
669
3.9
* Significantly different from the ddddd condition, p ⬍ .05 by participant
using Dunnett’s test.
significantly from the unrelated prime condition. In Experiment
1b, the same pattern was observed with 7-letter target words, such
that priming effects disappeared when the order of letters shared
by prime and target no longer matched (the 1-543-7 and 7-345-1
prime conditions). Furthermore, the results of Experiment 1b
showed no sign of an advantage when outer letters were maintained in their correct position compared to when they were not.
Indeed, the 1-543-7 priming condition generated numerically
slower RTs and more errors than the 7-345-1 condition. The
following experiments will provide further evidence on this point.
Experiment 2
Experiment 2 examines relative-position priming with 7-letter
and 9-letter targets with primes sharing the first five letters of
target words (initial primes), the last five letters (final primes), or
the first and last letter plus three central letters (outer-central
primes). In all the related prime conditions, the prime letters
respected their order in the corresponding target stimulus (i.e., the
relative position of letters was respected across prime and target,
but not absolute position). This manipulation allows us to examine
possible positional biases in relative-position priming. Whether
word-initial overlap generates stronger priming than word-final
overlap, and whether primes sharing both of the targets’ outer
letters are more effective than primes with just a single outer letter.
Concerning sequential biases in masked orthographic priming,
the evidence at present from both perceptual identification experiments (Humphreys et al., 1990) and lexical decision experiments
(Grainger & Jacobs, 1993) suggests that word-initial letters do not
have any privileged status over word-final letters. However, these
experiments were performed on short (4 and 5-letter) words, so it
remains to be seen whether increasing word length will allow
sequential biases to emerge. On the other hand, there is evidence
that a word’s outer letters enjoy a privileged status relative to inner
letters (e.g., Jordan, Thomas, Patching, & Scott-Brown, 2003;
Humphreys et al., 1990). This stands in contrast to the results
observed in Experiment 1. Since masks were longer than the prime
stimuli in Experiment 1, and primes were presented in a smaller
font size than the targets, this might have led to less accurate
coding of the prime’s outer letters. A mask that is longer than the
prime could generate visual noise in the space before and after the
prime stimulus, and therefore hinder the assignment of letter
identities to the first and last positions. Furthermore, the fact that
targets were larger than primes would also contribute to rendering
the boundaries of the prime stimulus less detectable. This should
not be the case when the forward mask is the same size as the
prime stimulus, and when the prime is bigger than the target. These
two types of masking conditions are compared in Experiment 2.
Method
Participants. Fifty-six students at the University of Provence took part
in this experiment. 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. A new set of sixty 7-letter words was selected
using the Lexique database (New, Pallier, Ferrand, & Matos, 2001). Their
printed frequencies ranged from 7 to 290 per million (mean 82 per million).
A set of sixty 9-letter words was selected with printed frequencies ranging
from 4 to 179 per million (mean 40 per million). Only nouns were used in
this experiment in order to reduce possible variance caused by different
grammatical categories. One hundred twenty pronounceable, orthographically regular nonwords were created, half of which were 7-letters long and
the other half 9-letters long. Four priming conditions were constructed. In
the first condition the prime was made up of the first five letters of the
target (initial letter primes), in the second condition it was formed by the
last five letters of the target (final letter primes), and in the third condition
by both outer letters and the central triplet of the target (outer-central
primes). In the baseline condition, the prime string consisted of five
unrelated letters. The size of the forward mask and prime stimulus was
manipulated. In one condition, masks were composed of 11 hash marks
that extended either one or two spaces to the left and to the right of prime
stimuli, with mask and primes presented in Arial 12 point and targets in
Arial 16. In the other condition, masks were the same length as primes and
both were presented in a bigger font size (Arial 16) than the targets (Arial
12). Mask, prime, and target size was manipulated between participants.
Prime-target pairs were counterbalanced across four experimental lists
following a Latin-Square design.
Procedure. This was the same as in the previous experiment except
that DMDX software (Forster & Forster, 2003) was used on a PC computer. In one condition, prime stimuli were presented in Arial 16 font and
the targets in Arial 12 font, and in another condition primes were presented
in Arial 12 and targets in Arial 16. In Arial 16 font each letter was
approximately 0.3 cm wide, and in Arial 12 font each letter was about 0.2
cm wide (respectively about 0.3 degrees and 0.2 degrees of horizontal
visual angle for a viewing distance of 60 cm).
Results
Mean RTs and percentages of error per experimental condition
are shown in Table 3. An ANOVA on mean correct RTs to word
targets showed a main effect of prime type (F1(3,144) ⫽ 39.76,
p ⬍ .0001; F2(3,354) ⫽ 40.45, p ⬍ .0001), an effect of length
(F1(1,48) ⫽ 124.04, p ⬍ .0001; F2(1,118) ⫽ 36.4, p ⬍ .0001), no
effect of mask size, and no interactions (all Fs ⬍1). Pairwise
comparisons against the unrelated condition using Dunnett’s test
revealed significant differences for all three related prime conditions, respectively: initial primes (t1(55) ⫽ 8.69, p ⬍ .01 and
Table 3
Experiment 2
Priming condition
7-letter words
RT
PE
9-letter words
RT
PE
7-letter nonwords
RT
PE
9-letter nonwords
RT
PE
12345
531*
1.1*
12345
567*
1.9
12345
638
1.4*
12345
692
4.4
34567
539*
1.6*
56789
571*
1.3*
34567
643
2.3
56789
688
4.5
13457
547*
0.7*
14569
585
2.7
13457
631
1.1*
14569
686
4.4
ddddd
576
3.7
ddddd
597
2.7
ddddd
632
3.4
ddddd
694
5.2
869
should generate incorrect coding of the end letters of the prime.
This result is also evidence against a privileged role played by
outer letters in printed word perception as previously reported in
experiments using degraded target presentation (e.g., Jordan et al.,
2003; Humphreys et al., 1990). In line with this reasoning, we also
failed to observe an influence of forward mask length on relativeposition priming effects in Experiment 2. Given a privileged role
for outer letters, it was expected that forward masks that were the
same length as primes ought to facilitate the processing of such
letters compared to a condition with masks that extended beyond
the prime stimulus. There was no evidence for such an influence in
Experiment 2.
Experiment 3
Experiment 3 tests a set of priming conditions similar to those
tested in Experiment 2, but with a lower level of orthographic
overlap (primes share four letters with 7-letter and 9-letter targets
words). In the extreme condition (4-letter primes for 9-letter targets) the orthographic overlap is less than 50%.
t2(119) ⫽ 9.96, p ⬍ .01); final primes (t1(55) ⫽ 9.18, p ⬍ .01 and
t2(119) ⫽ 7.81, p ⬍ .01); outer-central primes (t1(55) ⫽ 5.12, p ⬍
.01 and t2(119) ⫽ 5.89, p ⬍ .01). Furthermore, planned comparisons showed that outer-central primes differed significantly from
both initial, F(1, 48) ⫽ 36.61, p ⬍ .01; F2(1,118 ⫽ 24.2, p ⬍ .01),
and final primes, F(1, 48) ⫽ 8.75, p ⬍ .01; F2(1,118 ⫽ 8.22, p ⬍
.01). Priming generated by initial and final primes did not differ
significantly (F(1, 48) ⫽ 2.54; F2(1,118) ⫽ 3.5).
An ANOVA performed on the percentages of error to word
targets showed an effect of prime type, F(3, 144) ⫽ 6.8, p ⬍ .001,
no effect of word length, no effect of mask size, and no interactions. An analysis of the mean correct RTs to nonword targets
showed no effect of prime type, no effect of mask size, but a
significant effect of length (F1(1,48) ⫽ 112.36, p ⬍ .0001;
F2(1,118) ⫽ 41.24, p ⬍ .0001). None of the interactions between
these factors were significant (all Fs ⬍1). Significant effects were
observed in the error data to nonword targets for both prime type,
in the analysis by participants (F1(3,144) ⫽ 2.85, p ⬍ .05), and
length (F1(1,48) ⫽ 22.94, p ⬍ .00025; F2(1,118) ⫽ 22.83, p ⬍
.0001).
Method
Discussion
Mean RTs and percentages of error per experimental condition
are shown in Table 4. An ANOVA on mean correct RTs to word
targets showed a main effect of prime type (F1(3,120) ⫽ 8.69, p ⬍
.001; F2(3, 354) ⫽ 8.40, p ⬍ .001), an effect of length (F1(1,40) ⫽
42.70, p ⬍ .0001; F2(1,118) ⫽ 28.30, p ⬍ .0001), and no effect of
list. Length did not interact with the effects of prime type (Fs ⬍ 1)
and the list factor did not interact with these two factors.
Pairwise comparisons against the unrelated conditions using
Dunnett’s test revealed significant differences for initial primes
(t1(43) ⫽ 4.92, p ⬍ .01; t2(119) ⫽ 4.75, p ⬍ .01), and final primes
(t1(43) ⫽ 3.11, p ⬍ .01; t2(119) ⫽ 3.47, p ⬍ .01). On the other
hand, outer-central primes (1357 or 1469) did not differ significantly from the unrelated condition. Planned comparisons between
related prime conditions showed that initial primes differed significantly from outer-central primes (F1(1,40) ⫽ 10.63, p ⬍ .01;
F2(1,118) ⫽ 7.83, p ⬍ .01). None of the other planned comparisons reached significance.
The results of Experiment 2 are clear-cut. There was very little
evidence for any beginning-to-end positional bias in relativeposition priming. The clearest evidence against a beginning-to-end
processing bias is the fact that primes that did not contain the
target’s initial letters (final letter primes) actually produced significantly faster RTs than one set of primes containing the target’s
first letter (outer-central primes).
Another important result obtained in Experiment 2 is that primes
that contained both of the targets’ outer letters did not produce
more priming than primes containing only a single outer letter.
Indeed, the former condition actually produced slower RTs than
the other two conditions. This result contradicts coding schemes
that use the word center as an anchor point for relative-position
coding (e.g., Caramazza & Hillis, 1990). According to this type of
scheme, asymmetrical primes such as 12345 for a 7-letter target,
Participants. Forty-four students at the University of Provence took
part in this experiment. 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 words and nonwords were the same as in
Experiment 2. A new set of 4-letter prime stimuli were generated for the
four priming conditions. In the first condition the prime was composed of
the first four letters of the target, in the second condition it was composed
of the last four letters of the target, and in the third condition it was
composed of the two outer letters plus two inner letters (the two letters
flanking the target’s central letter). Finally, in the baseline condition the
prime string was formed by four unrelated letters. These four priming
conditions were crossed with target length (7-letter or 9-letter targets) in a
2 (word length) ⫻ 4 (prime type) factorial design (see Table 1 for a
summary of the priming conditions).
Procedure. This was the same as in Experiment 2 except that primes
were always presented in Arial 12 font and targets in Arial 16 font. (Font
and mask size were not manipulated in this experiment.)
Results
GRAINGER ET AL.
870
Table 4
Experiment 3
Priming condition
7-letter words
RT
PE
9-letter words
RT
PE
7-letter nonwords
RT
PE
9-letter nonwords
RT
PE
1234
562*
1.9
1234
591*
1.3
1234
668
1.2
1234
723
2.1
4567
573
1.6
6789
594*
1.2
4567
675
1.5
6789
727
1.9
1357
577
1.2*
1469
606
1.9
1357
664
1.8
1469
716
2.1
dddd
585
3.6
dddd
614
1.2
dddd
669
2.5
dddd
725
1.9
An ANOVA performed on the percentages of error to word
targets showed no significant main effects or interactions. An
analysis of the mean correct RTs to nonword targets showed no
effect of prime type, but a significant effect of length (F1(1,40) ⫽
79.73, p ⬍ .0001; F2(1,118) ⫽ 120, p ⬍ .0001). There was no
interaction between these factors. No effects were observed in the
error data to nonword targets.
Discussion
The most important result of Experiment 3 is the fact that robust
priming can be obtained with very low levels (less than 50%) of
orthographic overlap between prime and target (4-letter primes and
9-letter targets). In terms of positional biases, the results of Experiment 3 perfectly replicate those of Experiment 2, showing very
little evidence of any beginning-to-end bias (no significant difference between initial and final prime conditions), and no evidence
in favor of primes containing both of the target’s outer letters. On
the contrary, primes containing the two outer letters of target
words produced smaller priming effects than the other related
prime conditions, and were not significant relative to the alldifferent prime condition. This therefore once again counters prior
observations of an outer letter advantage in visual word recognition (Humphreys et al., 1990; Jordan et al., 2003). However, the
fairly meager evidence obtained so far for positional biases in
relative-position priming could possibly reflect the conjoint influence of other factors that differ across the priming conditions we
tested. The following post hoc analyses were designed to examine
this possibility.
Post Hoc Analyses of Experiments 2 and 3
In priming conditions similar to those tested in the present
experiments, prior research has provided evidence that structural
variables, such as morphemic and syllabic structure, can influence
priming. For example, Ferrand and Grainger (1993) reported phonological priming that emerged with prime exposures of around 50
ms, and Diependaele, Sandra, and Grainger (2005) found morphological priming with prime exposures of 43 ms. Hence, part of the
relative-position priming effects reported here could be due to such
structural influences. In order to rule out this possibility, a series of
post hoc analyses were performed on the results of Experiments 2
and 3. The hypothesized relevant variables were: syllable structure, morphological structure, consonant/vowel (CV) status of
letters shared by prime and target, and amount of phonological
overlap across prime and target. We also examined the possible
influence of target word frequency and the bigram frequency of
prime stimuli on priming effects in Experiments 2 and 3.
Syllable Structure
In this post hoc analysis we separated out cases where prime
stimuli formed one of the target word’s syllables (e.g., lencesilence). Obviously, this situation only arose in the contiguous
priming conditions (initial and final primes), and therefore could
explain the nonsignificant priming for outer-central primes observed in Experiments 2 and 3. Averaging across experiments and
word length (240 items), we found a quite stable pattern of priming
for the no-syllable (average priming effect ⫽ 28 ms, N ⫽ 73),
initial-syllable (word-initial priming effect ⫽ 34ms, N ⫽ 64), and
final-syllable (word-final priming effect ⫽ 27ms, N ⫽ 95). An
ANOVA with Prime Type and Syllable Structure (prime is a
syllable of the target or not) showed that syllable structure did not
affect priming (all Fs ⬍ 1).
Morphological Structure and Embedded Words
In the same manner as the preceding analysis, here we separated
out cases where prime stimuli formed one of the target word’s
morphemes (either a root or an affix). Prime stimuli never formed
a free root, but some of the word-final primes (N ⫽ 26) did form
a derivational suffix in Experiments 2 and 3. An analysis showed
that primes that were suffixes of the target word actually produced
numerically less priming. However, the interaction with priming
was not significant (F ⬍ 1), and an analysis limited to only cases
without suffix primes showed exactly the same pattern as the
overall analysis.
We also checked for a possible influence of the lexical status of
prime stimuli that arose on a small number of occasions. In
Experiment 2, removing the seventeen 9-letter targets for which
one prime condition did form a word, produced a pattern that was
almost identical to the complete analysis. The same was true for
the 7-letter (N ⫽ 13) and 9-letter (N ⫽ 13) targets in Experiment
3. Thus the fact that a small number of prime stimuli formed
embedded words or derivational affixes had no significant impact
on the priming effects we observed.
CV Status and Phonological Overlap
In order to check whether priming effects were modulated by
the number of vowels versus consonants shared by prime and
target, these values were correlated with priming effect size across
items. The average proportion of shared vowels was quite stable
across the three related priming conditions (0.67, 0.55, and 0.66 for
the initial, final, and outer-central primes respectively). The overall
correlation between priming effect (three priming effects for each
word target) and proportion of vowels was not significant (r ⫽
⫺0.02, N ⫽ 720) for Experiments 2 and 3 together, and doing
separate correlations for each word-length and experiment never
produced a significant effect.
Phonological overlap across primes and targets was estimated
by counting the number of phonemes of the target word that were
present in the prime stimulus. For the French target word “silence”
for example, the prime stimulus “sile” shares three phonemes (/s/,
/i/, and /L/) out of five (60%). Averaging across all items, the
amount of phonological overlap was 65% for initial primes, 56%
for final primes, and 41% for outer-central primes. T tests showed
that all pairwise comparisons of degree of phonological overlap
were highly significant (all ps ⬍.001). The overall correlation
between priming effect size and degree of phonological overlap
was significant (r ⫽ .17, p ⬍ .01, N ⫽ 720) for Experiments 2 and
3 (and approximately the same size in each experiment). Primes
that shared more phonemes with targets (for a fixed number of
shared letters) produced stronger priming effects. The significant
correlation suggests that part of the observed differences in priming effects across the different prime conditions tested in Experiments 2 and 3 is due to differences in the level of phonological
overlap across primes and targets in these different conditions.
Word Frequency and Bigram Frequency
In this analysis we examined whether the pattern of priming
effects varied as a function of either target word frequency or the
mean positional bigram frequency of prime stimuli. It is possible
that priming effect sizes, especially in the outer-central prime
conditions of Experiments 2 and 3, vary as a function of the
familiarity of the letter sequences that they are composed of. This
might explain why initial letter and final letter primes (composed
of completely contiguous letter sequences from the target word)
were more effective than outer-central primes (composed of noncontiguous letter sequences), since the latter will generally have
lower bigram frequencies. The mean positional bigram frequency
of prime stimuli did not correlate with priming effect size across
Experiments 2 and 3 (r ⫽ .05, N ⫽ 720), and none of the
correlations done separately for Experiment or word length were
close to being significant. Similarly, there was a nonsignificant
correlation between target word frequency and priming effect size
(averaged across the three prime conditions) for both experiments
(r ⫽ .08, N ⫽ 240), and again this correlation was not significant
when calculated separately for Experiment or word length. These
post hoc analyses clearly show that neither the bigram frequency
of prime stimuli nor target word frequency is having any significant influence on priming effects sizes in Experiments 2 and 3.
As a further test of any possible influence of target word
frequency on priming effects in Experiments 2 and 3, the target
words were split in two halves according to their printed frequencies (mean frequency ⫽ 21 per million and 97 per million respectively, New et al., 2001). An ANOVA was performed on RTs to
word targets (both 7-letter and 9-letter targets) with prime type and
target frequency as within-participant factors and experiment as a
between-participants factor. There was an effect of frequency, F(1,
118) ⫽ 26.5, p ⬍ .01, an effect of prime type, F(3, 177) ⫽ 18.34,
p ⬍ .01, and no interaction between prime type and frequency
(F ⬍ 1). The ANOVA therefore confirms the correlational analysis
showing no significant influence of target word frequency on
priming effect sizes in Experiments 2 and 3.
871
Discussion
The results of these post hoc analyses therefore suggest that the
stronger priming observed for the initial and final primes conditions relative to the outer-central prime condition, observed in
Experiments 2 and 3, may be due to the higher levels of primetarget phonological overlap in the former conditions. The post hoc
analyses showed no significant influence of the other variables we
examined, including the relative proportion of consonants and
vowels present in the prime stimulus. However, Perea and Lupker
(2004) found an influence of CV status on priming from nonadjacent transposed-letter primes (e.g., caniso-CASINO), observing
nonsignificant priming when the two transposed letters were vowels. Our correlation, although not significant, goes in the same
direction, with weaker priming as the proportion of vowels increases. Clearly, a direct manipulation of the proportion of consonants and vowels shared by prime and target is necessary to clarify
the role of this factor in relative-position priming.
Given the significant correlation between prime-target phonological overlap and mean RT per item in Experiments 2 and 3, it
is possible that it is phonological and not orthographic overlap that
is the main driving force behind the pattern of results obtained with
this task. We believe that this is unlikely given that Peressotti and
Grainger (1999) found strong relative-position priming with 33 ms
prime durations, in conditions where Ferrand and Grainger (1992,
1994) had systematically failed to find any evidence for phonological priming in French. In order to be completely sure about the
pattern of results obtained with the priming conditions tested in
Experiments 2 and 3, we ran two further experiments using reduced (33 ms) prime exposures. Here we do not expect to observe
any correlation with phonological overlap and priming effect size.
Furthermore, since prior experiments showing an outer letter
advantage have used degraded target stimuli (e.g., Humphreys et
al., 1990, used the perceptual identification task), an obvious next
step in our investigation was to test the same priming conditions in
a masked priming experiment where targets are masked as well as
primes. However, it could also be argued that it is the presence of
pattern masking in the present studies that reduces the inherent
advantage of outer letters. Thus, in order to test these different
possibilities, Experiment 4 uses the four-field masking perceptual
identification paradigm of Humphreys et al. (1990), and Experiment 5 uses the same paradigm as our previous experiments but
with a 33 ms prime duration, and including a condition with
pattern masking of the prime stimulus and a condition where no
pattern mask is present.
Experiment 4
Experiment 4 uses the same stimuli and priming conditions as in
Experiment 3 with a perceptual identification task, as used in the
work of Humphreys et al. (1990).
Method
Participants. Thirty-two students at the University of Provence took
Stimuli and design. These were the same as in Experiment 3.
GRAINGER ET AL.
872
Procedure. A four-field masking procedure was employed similar to
that used by Humphreys et al. (1990). On each trial, participants first saw
a forward mask (a row of 11 hash marks) for 500 ms, immediately followed
by a prime for 33 ms, then by the target word for 33 ms, and finally by
another row of hash marks for another 500 ms. Participants were instructed
to identify word stimuli presented in uppercase letters and they typed in
their response using the computer keyboard. Primes and targets were
displayed in the same font and size as in Experiment 3 except that primes
were in lower case and targets in upper case in the present experiment.
Results
Mean percent correct target identification for each experimental
condition is given in Table 5. An ANOVA on these percentage
scores showed a main effect of prime type (F1(3,84) ⫽ 13.99, p ⬍
.0001; F2(3,354) ⫽ 7.11, p ⬍ .0001), and an effect of length
(F1(1,28) ⫽ 48.53, p ⬍ .0001; F2(1,118) ⫽ 16.86, p ⬍ .0001).
There was no effect of list and no interactions between these three
factors. Pairwise comparisons using Dunnett’s test revealed significant differences between the unrelated condition and the initial
prime condition (t1(31) ⫽ 4.09, p ⬍ .01; t2(119) ⫽ 5.07, p ⬍ .01),
the final prime condition (t1(31) ⫽ 4.86, p ⬍ .0; t2(119) ⫽ 3.08,
p ⬍ .01), and the outer-central prime condition (t1(31) ⫽ 5.23, p ⬍
.01; t2(119) ⫽ 3.78, p ⬍ .01). Planned comparisons across the
related prime conditions showed no significant differences.
Discussion
In the perceptual identification task of Experiment 4, there is no
evidence for any positional biases in relative-position priming
effects. Priming effects were very similar for the three priming
conditions and the two target word lengths, and all highly significant compared with the all-different letter primes. The perceptual
identification task has generated stronger priming effects for the
outer-central primes compared to Experiment 3, since these are
now significant relative to the unrelated condition. However,
outer-central primes (containing both of the targets’ outer letters)
still did not generate stronger priming than either initial or final
primes (containing only one of the target’s outer letters). A correlational analysis on priming effects and degree of prime-target
phonological overlap showed that this was not significant in Experiment 4 (r ⫽ .03).
Comparing the results of Experiments 3 and 4, where the same
set of stimuli were tested in a lexical decision and a perceptual
identification task, it seems that only the outer-central priming
Table 5
Mean Percent Correct Word Identification Scores for the
Different Priming Conditions Tested in the Perceptual
Identification Task of Experiment 4 With 33 ms Prime
Exposures
9-letter words
1234
52.4*
1234
41.1*
4567
50.8*
6789
39.8*
1357
52.3*
1469
41.1*
Experiment 5
Method
Participants. Eighty students at the University of Provence took part in
this experiment. Thirty-six were tested in the condition where primes were
masked, and 44 tested in the condition where no masks were used. They all
reported being native speakers of French with normal or corrected-tonormal vision, and had not participated in the previous experiments.
Stimuli and design. These were the same as in Experiment 3 except for
the masking factor. In one condition prime stimuli were masked, as in
Experiment 3, and in another condition no pattern mask was presented.
Two independent groups of participants were tested in these two masking
conditions.
Procedure. This was the same as in Experiment 3 except for the use of
a prime exposure duration of 33 ms and the absence of any masking
stimulus in one condition.
Results
Priming condition
7-letter words
condition was affected by task. This priming condition produced
nonsignificant effects in the lexical-decision task, and robust priming in perceptual identification. It is possible that the perceptual
identification task is more sensitive to the influence of outer letters
in prime stimuli, as attested by the effects of this factor reported by
Humphreys et al. (1990), and this compensates for the disadvantage for these primes relative to the initial and final prime conditions. There are two possible sources of this hypothesized disadvantage for outer-central primes compared to initial and final
prime conditions. These are 1) as shown above, the lower level of
phonological overlap across primes and targets in the outer-central
prime condition; and 2) the lower level of contiguity (the number
of adjacent letter combinations in the target that are also adjacent
in the prime stimulus) in the outer-central prime condition. In the
General Discussion we will present preliminary explorations of
contiguity effects in one recent account of letter position coding
(Grainger & van Heuven, 2003). However, at present the most
straightforward and most conservative conclusion is that when
phonological influences on priming effects are minimized then the
different priming conditions tested in Experiments 2– 4 show statistically equivalent effects.
The reason why phonological influences were neutralized in
Experiment 4 is likely due to the shorter prime exposure duration
used in this experiment rather than the particular task used. In
order to test this, the following experiment uses the procedure of
Experiment 3 (with lexical decision on target words), but with a
shorter (33 ms) prime duration. The possible influence of pattern
masking on relative-position priming effects is further studied in
Experiment 5 by manipulating the presence or absence of a forward mask.
dddd
43.1
dddd
31.5
* Significantly different from the dddd condition, p ⬍ .01 by participant
The condition means are given in Table 6. An ANOVA on mean
correct RTs to word targets showed a main effect of prime type
(F1(3,216) ⫽ 16.52, p ⬍ .00001; F2(3,336) ⫽ 15.00, p ⬍ .00001),
an effect of length (F1(1,72) ⫽ 117.12, p ⬍ .00001; F2(1,112) ⫽
28.73, p ⬍ .00001) and an effect of masking (F2(1,112) ⫽ 23.75,
p ⬍ .00001). There was an interaction between prime type and
masking (F1(3,216) ⫽ 5.25, p ⬍ .01; F2(3,336) ⫽ 4.34, p ⬍ .01)
and between length and masking (F1(1,72) ⫽ 4.17, p ⬍ .05;
F2(1,112) ⫽ 6.59, p ⬍ .05).
Table 6
(PE) for the Different Priming Conditions Tested in Experiment
5 With 33 ms Prime Exposures
With Masking
Priming condition
7-letter words
RT
PE
9-letter words
RT
PE
1234
536
1.5
1234
574
1.3
Without Masking
4567
547
0.7
6789
566
1.5
1357
535
0.7
1469
565
2.6
dddd
552
1.9
dddd
572
3.5
Priming Condition
7-letter words
RT
PE
9-letter words
RT
PE
1234
513*
0.8
1234
555*
1.7
4567
519*
1.7
6789
564*
1.2
1357
518*
1.2
1469
558*
1.5
dddd
549
2.3
dddd
581
2.0
In the mask condition, there was a main effect of length
(F1(1,32) ⫽ 64.98, p ⬍ .00001; F2(1,112) ⫽ 16.37, p ⬍ .001), no
effect of prime type, and no interaction. Comparisons against the
unrelated condition using Dunnett’s test showed that only the
outer-central condition produced significantly faster RTs in the
analysis by participants (t1(35) ⫽ 2.47, p ⬍ .05) when primes were
masked. In the no-mask condition, on the other hand, there was a
main effect of prime type (F1(3,120) ⫽ 21.76, p ⬍ .00001;
F2(3,336) ⫽ 19.51; p ⬍ .00001), an effect of length (F1(1,40) ⫽
67.17, p ⬍ .00001; F2(1,112) ⫽ 36.23, p ⬍ .00001), and no
interaction. Dunnett’s test indicated that the unrelated prime condition produced significantly longer RTs than the initial condition
(t1(43) ⫽ 6.22, p ⬍ .01; t2(119) ⫽ 6.19, p ⬍ .01), the final
condition (t1(43) ⫽ 4.65, p ⬍ .01; t2(119) ⫽ 4.18, p ⬍ .01), and
the outer-central condition (t1(43) ⫽ 5.79, p ⬍ .01; t2(119) ⫽
5.49, p ⬍ .01).
An ANOVA on percentages of error to word targets revealed a
significant main effect of prime type (F1(3,216) ⫽ 5.25, p ⬍ .01;
F2(3,336) ⫽ 4.02, p ⬍ .01) and an effect of length by participant
(F1(1,72) ⫽ 4.19, p ⬍ .05) that failed to reach significance in the
item analysis (F2(1,112) ⫽ 3.58, p ⬍ .07). There was no effect of
masking and there were no significant interactions. Dunnet’s test
revealed significant differences between the unrelated condition
and the initial prime condition (t1(79) ⫽ 2.86, p ⬍ .05; t2(119) ⫽
2.64, p ⬍ .05), the final prime condition (t1(79) ⫽ 2.93, p ⬍ .05;
t2(119) ⫽ 2.61, p ⬍ .05), and the outer-central prime condition in
the analysis by participants (t1(79) ⫽ 2.54, p ⬍ .05).
An analysis of the mean correct RTs to nonword targets showed
a main effect of length (F1(1,72) ⫽ 160.46, p ⬍ .0001;
F2(1,112) ⫽ 56.06, p ⬍ .00001) and an effect of masking in the
item analysis (F2(1,112) ⫽ 41.44, p ⬍ .00001). RTs were slower
with the longer nonwords and in the condition where primes were
masked. An ANOVA on percentages of error to nonword targets
revealed a significant main effect of length (F1(1,72) ⫽ 15.64, p ⬍
.001; F2(1,112) ⫽ 4.00, p ⬍ .05). There was no effect of prime
type or masking, and no interaction.
873
Discussion
Experiment 5 successfully replicated the pattern of priming
effects obtained with the perceptual identification task in Experiment 4 in conditions where prime stimuli were presented very
briefly (33 ms) and with no pattern masking. In line with the
results of Experiment 4, the outer-central primes now show just as
much priming as initial and final prime conditions. Also in line
with the results of Experiment 4 is the fact that there was no hint
of a correlation between prime-target phonological overlap and
priming effect size in either the mask or no-mask conditions tested
in Experiment 5 (r ⫽ .006 and 0.015, respectively). This implies
that it is not the particular masking conditions nor the type of task
that was essential for obtaining the pattern of priming effects in
Experiment 4. It appears that presentation conditions that allow
orthographic effects to emerge in the absence of phonological
effects are sufficient for obtaining priming effects that are unaffected by positional biases.
The presence of a pattern mask significantly affected the amount
of priming observed in Experiment 5. In the RT analysis, priming
effects were only robust in the absence of a pattern mask, although
priming effects in the error data were not affected by masking.
This is contrary to previous reports of relative-position priming at
such short prime durations (Peressotti & Grainger, 1999). However, the level of orthographic overlap across prime and target was
lower in the present study, suggesting that this is one factor that
determines whether or not significant priming effects will be
obtained. The present experiment also shows that whether or not
the prime stimulus is masked is another critical factor, and other
visual factors such as the type of pattern mask, and the size and
luminance of mask, prime, and target stimuli, could also be critical
(e.g., Frost, Ahissar, Gotesman, & Tayeb, 2003). With all other
factors held constant, the presence of a forward mask significantly
affects the amount of orthographic priming that is obtained.
Combined Analysis of Experiments 2, 3, and 5
Although Experiment 5 once again failed to show a significant
difference between initial primes and the other related prime
conditions, this is the fourth experiment to show a small nonsignificant advantage for initial primes compared with final primes.
We therefore performed an ANOVA by participants combining the
data of Experiments 2, 3, and the unmasked condition of Experiment 5. (Experiment 4 was not included because a different dependent variable had been used.) This combined analysis showed
that initial primes generated RTs that were on average 7 ms faster
than RTs to targets following final primes, F(1, 141) ⫽ 7.74, p ⬍
.01, and this effect was stable across experiments (F ⬍ 1 for partial
interaction). On the other hand, the 13 ms advantage for targets
following initial primes compared to outer-central primes, F(1,
141) ⫽ 34.13, p ⬍ .001, did interact with Experiment, F(2, 141) ⫽
4.27, p ⬍ .05. Final primes were also significantly faster than RTs
to targets following outer-central primes, F(1, 141) ⫽ 5.17, p ⬍
.05, and this also interacted with Experiment, F(2, 141) ⫽ 4.04,
p ⬍ .05. Therefore, there is evidence for a small but systematic
advantage when primes are formed of a contiguous sequence of
beginning letters compared to when they are formed of a contiguous sequence of final letters. Differences relative to the noncontiguous (outer-central) prime condition were, however, not stable
GRAINGER ET AL.
874
across experiments, probably as a result of the influence of prime
duration on these particular priming effects.
Finally, since the three priming conditions differ in terms of
their phonological overlap with targets, we performed an
ANCOVA on the data of Experiments 2, 3, and 5, with percent
phonological overlap as a covariate. Only the three related prime
conditions were included in this analysis as a further test of
differences among these three priming conditions. In the by-items
ANOVA including these three conditions (i.e., without the unrelated prime condition), there was a main effect of prime type, F(2,
708) ⫽ 5.34, p ⬍ .01 that did not interact with Experiment, F(4,
708) ⫽ 1.42. This therefore confirms the significant differences
across priming conditions found in the planned comparisons in the
by-participants ANOVA described above.
However, in the ANCOVA this main effect of prime type was
no longer significant, F(2, 706) ⫽ 2.69, and again did not interact
with Experiment, F(4, 706) ⫽ 1.28. Furthermore, the critical
pairwise comparison between word-initial and word-final primes
was not significant in the ANCOVA, F(1, 353) ⫽ 1.14. This result
strongly suggests that differences across the three related priming
conditions, including the word-initial prime advantage, are being
driven by differences in the amount of phonological overlap between primes and targets.
Experiment 6
Experiment 5 has provided evidence for relative-position priming effects in conditions where it is unlikely that phonological
prime-target overlap is significantly affecting processing. Experiment 6 was designed to test for the absence of phonological
processing using a traditional measure of such influences: priming
from pseudohomophones (e.g., “brane” as a prime for the target
word “brain”). Prior research in French has systematically shown
effects of orthographic priming and no pseudohomphone priming
at very brief prime durations (⬍50 ms), while pseudohomophone
priming effects emerge at longer prime durations (Ferrand &
Grainger, 1992, 1993, 1994; Grainger, Diependaele, Spinelli, Ferrand, & Farioli, 2003; Ziegler, Ferrand, Jacobs, Rey, & Grainger,
2000). Experiment 6 tests relative-position priming and
pseudohomophone priming at 33 ms and 83 ms prime durations
with no pattern masking. Experiment 6 also provides a further
exploration of the relative importance of outer versus inner letters
in relative-position priming using a manipulation similar to Experiment 1b but with 4-letter primes.
Method
Participants. Twenty-eight students at the University of Provence took
Stimuli and design. A new set of sixty 7-letter French words with
printed frequencies ranging from 1 to 313 occurrences per million (M ⫽
29; New et al., 2001) was generated with the constraint that two different
pseudohomophones could be generated from each word: one that maximized orthographic overlap with its corresponding baseword (one different
letter, e.g., silance-silence), and one that minimized orthographic overlap
(at least two different letters, e.g., cylance-silence). This represents the
“orthographic overlap” factor (minimal vs. maximal). Each pseudohomophone prime was matched to an orthographic control prime in terms of the
number of shared letters and the position of these letters (e.g., “silunce” for
the pseudohomophone “silance”), and every prime stimulus was tested at
two different prime durations (33 ms and 83 ms). Thus orthographic
overlap was crossed with prime type (pseudohomophone vs. orthographic
control) and prime duration in a 2 ⫻ 2 ⫻ 2 factorial design that forms the
“phonological priming” subpart of Experiment 6. The same set of target
words and nonwords were also tested with relative-position primes formed
of the first letter, last letter, and the 3rd and 5th letters of targets in three
different orders (1357, 1537, 7351) and an unrelated 4-letter prime (dddd),
also tested at two prime durations (see Table 1). Thus the “relative-position
priming” subpart of Experiment 6 involved the manipulation of prime type
and prime duration in a 4 ⫻ 2 factorial design. Given the strong constraints
on stimulus selection and the need for both a within-participants and a
within-items design (i.e., the same targets tested in both the phonological
priming and the relative-position priming conditions), target repetition
could not be avoided in Experiment 6. The counterbalancing procedure
applied in Experiments 1–5 was again used to form four lists presented to
four independent groups of participants. Within each list, each target
appeared four times paired with one of the four prime types associated with
each subpart of the experiment (i.e., one of the four possible primes in the
phonological priming subpart, and one of the four possible primes in the
relative-position priming subpart, determined by the standard counterbalancing procedure), and at both prime durations. Sixty 7-letter nonword
targets were constructed such that an orthographically similar (one letter
different) and an orthographically dissimilar (at least two letters different)
pseudohomophone prime could be created for each target. The nonwords
were tested in exactly the same priming conditions as the word targets.
Thus each participant received 480 trials, half of which had word targets.
Procedure. This was the same as the condition with no pattern mask in
Experiment 5 except for the use of two prime exposure durations: 33 ms
and 83 ms.
Results
The condition means are given in Table 7. Separate ANOVAs
were performed for the relative-position priming conditions and
the pseudohomophone priming conditions.
Relative-position priming. The ANOVA on mean correct RTs
to word targets showed a main effect of prime duration
(F1(1,27) ⫽ 40.72, p ⬍ .00001; F2(1, 58) ⫽ 44.24, p ⬍ .00001),
no effect of prime type (F1 ⬍ 1; F2 ⬍ 1), and a trend to an
interaction in the item analysis (F1(3,81) ⫽ 1.58; F2(3,174) ⫽
2.58, p ⫽ .056). As can be seen in Table 7, prime type was only
influencing RT at the 33 ms prime duration, F(3, 81) ⫽ 6.78, p ⬍
.01; F2(3,174 ⫽ 6.89, p ⬍ .01), but not at the 83 ms prime duration
(both Fs ⬍1). The 1357 prime condition was significantly faster
than the three other prime conditions with prime exposures of 33
ms, F(1, 27) ⫽ 8.94, p ⬍ .01; F2(1,58 ⫽ 4.85, p ⬍ .05). This
priming effect did not interact with target word repetition, and the
triple interaction between prime type, prime duration, and target
repetition was not significant (all Fs ⬍1). None of the main effects
or interactions were significant in an analysis of the percent errors
to word targets.
An analysis of the mean correct RTs to nonword targets revealed an effect of prime type (F1(3,81) ⫽ 6.04, p ⬍ .001;
F2(3,177) ⫽ 5.34, p ⬍ .01) that interacted with prime duration
(F1(3,81) ⫽ 7.02, p ⬍ .001; F2(3,177) ⫽ 6.48, p ⬍ .001).
Significant priming effects only appeared at the 83 ms prime
duration (1357 ⫽ 606 ms, 1537 ⫽ 635 ms, 7351 ⫽ 626 ms,
dddd ⫽ 655 ms). There were no significant effects in the error data
for nonword targets.
Table 7
(PE) for the Different Priming Conditions and the Two Prime
Durations (33 ms and 83 ms) of Experiment 6 Testing for
Relative-Position Priming and Phonological Priming With
Different Levels of Phonological (P⫹/P⫺) and Orthographic
(O⫹/O⫺) Overlap Across Primes and Targets
Relative-Position priming
33 ms
RT
PE
83 ms
RT
PE
Priming Condition
1357
577*
3.3
1537
589
3.1
7351
590
4.8
dddd
597
4.1
613
4.5
613
4.5
619
2.9
610
5.0
Priming Condition
O⫹
Phonological priming
33 ms
RT
PE
83 ms
RT
PE
O⫺
P⫹
P⫺
P⫹
P⫺
581
3.3
584
2.4
590
4.3
593
4.1
564
4.8
570
4.3
604
5.0
633
4.1
Phonological priming. The ANOVA on mean correct RTs to
word targets showed a main effect of prime type in the analysis by
participant (F1(1,27) ⫽ 4.27, p ⬍ .05; F2(1,58) ⫽ 1.62), with
pseudohomophone primes generating faster RTs than their orthographic controls. Orthographically similar primes generated faster
RTs than the dissimilar primes (F1(1,27) ⫽ 57.29, p ⬍ .0001;
F2(1,58) ⫽ 40.87, p ⬍ .0001), and there was a trend to an effect
of prime duration in the items analysis (F1(1,27) ⫽ 2.53;
F2(1,58) ⫽ 3.11, p ⬍ .10). The effects of orthographic overlap
interacted with prime duration (F1(1,27) ⫽ 23.42, p ⬍ .0001;
F2(1,58) ⫽ 27.61, p ⬍ .0001), since the effects of this factor were
much larger at the 83 ms prime duration. There was a significant
triple interaction in the participants’ analysis (F1(1,27) ⫽ 4.29,
p ⬍ .05; F2(1,58) ⫽ 2.46), reflecting the fact that the two-way
interaction between prime duration and prime type was significant
(in the analysis by participants) for the orthographically dissimilar
pseudohomophones (F1(1,27 ⫽ 4.18, p ⬍ .05) but not for the
orthographically similar pseudohomophones (both Fs ⬍ 1). Pairwise comparisons revealed that only orthographically dissimilar
pseudohomophones generated a significant priming effect, and
only at the 83 ms prime duration (F1(1,27) ⫽ 11.06, p ⬍ .01;
F2(1,58) ⫽ 6.51, p ⬍ .05). None of the other comparisons were
significant. Neither the effects of prime type nor the effects of
orthographic overlap interacted with target word repetition (both
Fs ⬍ 1). None of the main effects or interactions were significant
in an analysis of the percentages of error to word targets.
An analysis of the mean correct RTs to nonword targets showed
a trend to an effect of prime duration (F1(1,27) ⫽ 4.13, p ⬍ .10;
F2(1,58) ⫽ 5.66, p ⬍ .05).There was a main effect of orthographic
overlap (F1(1,27) ⫽ 24.52, p ⬍ .0001; F2(1,58) ⫽ 23.62, p ⬍
875
.0001), with orthographically more similar primes generating
slower RTs. There were no significant effects in the error data for
nonword targets.
Discussion
The results of Experiment 6 replicate those of Experiment 5,
showing relative-position priming effects with short prime durations (33 ms) and no pattern masking, while demonstrating that
phonological priming effects are absent in the same testing conditions. This therefore adds direct support to the evidence provided
by nonsignificant correlations between prime-target phonological
overlap and priming effect sizes found with short prime durations
(Experiments 4 & 5). In line with this reasoning, phonological
priming did emerge with longer prime durations (83 ms) in Experiment 6. This in itself is an important replication of prior
research showing priming from pseudohomophone stimuli, particularly since Experiment 6 tested pseudohomophone priming with
longer words than typically tested in phonological priming experiments. On the other hand, the effects of relative-position primes
actually diminished and were nonsignificant at the longer prime
duration. The level of phonological overlap of the noncontiguous
relative-position primes tested in Experiment 6 was clearly not
high enough to generate priming at the longer prime duration.
However, the fact that higher levels of orthographic overlap generated stronger priming effects at this prime duration suggests that
some form of orthographic priming continues to develop with
increasing prime exposures. It appears that single-letter substitution primes (the O ⫹ primes tested in the phonological priming
subpart of Experiment 6) are generating maximum facilitation
(relative to the O- primes) that grows with increasing prime
exposure duration. The relative-position primes, on the other hand,
generate a weaker and more short-lived facilitation.
One possible explanation for the distinct time-course of relativeposition and substitution priming effects is in terms of the different
degrees of phonological overlap with target words. Relativeposition primes formed of noncontiguous letter sequences (as was
the case in Experiment 6, e.g., slne-silence) will tend to generate
phonological codes that are incompatible with the target word’s
phonology, while this is not the case with single-letter substitution
primes (e.g., silunce-silence). Assuming that the phonological
code for a word requires precise order information, then the prime
stimulus “slne” will only have one phoneme (/s/) that is compatible
with the French target word “silence,” whereas the substitution
prime stimulus “silunce” will have four out of five compatible
phonemes. Therefore, as prime duration increases, it appears that
orthographic prime-target overlap continues to facilitate target
word processing only to the extent that there is also a minimal
level of compatibility between the phonological code generated by
the prime stimulus and the target’s phonological representation.
We return to this point in the section on contiguity effects in the
General Discussion.
The results of Experiment 6 show once again no sign of an outer
letter advantage in the testing conditions of the present study.
Primes that maintained the target’s outer letters (1537 primes) did
not differ from primes in which the two outer letters were transposed (7351) primes. Finally, Experiment 6 provided further evidence (following the post hoc analyses of Experiments 2 and 3)
that letter cluster frequency is not influencing the size of relative-
GRAINGER ET AL.
876
position priming effects. The mean positional bigram frequency of
the 1357, 1537 and 7351 primes were respectively 689, 922, and
832 occurrences per million (New et al., 2001). The observed
advantage for primes respecting relative-position information cannot therefore be attributed to prime stimuli having higher bigram
frequencies in this particular condition.
General Discussion
The present results speak to several key issues in printed word
perception. First, they provide further evidence for the role of
individual letter representations in this process (Besner, et al.,
1984; Evett & Humphreys, 1981; Rayner et al., 1980). Any possible influence of global shape information from lower-case
primes would be greatly reduced in the relative-position primes
compared to absolute position primes. Probably one of the most
critical sources of global information about a word is its length,
and this information was incorrect in the relative-position prime
condition. This is in line with recent eye-movement research
suggesting that length information is used essentially for nonlinguistic purposes (visual object selection and saccade specification)
during reading (Inhoff, Radach, Eiter, & Juhasz, 2003). Furthermore, relative-position primes modified the visual configuration
formed of ascending, descending, and neutral letters, thus again
providing information that was incompatible with the upcoming
target word’s global shape.
Our results show significant priming from very briefly presented, pattern-masked prime stimuli when they are composed of
a subset of the upcoming target’s component letters. This subset of
letters can be quite small. In Experiments 3–5, significant priming
was obtained when primes shared only four letters with 9-letter
target words. However, one key result of the present study is that
when primes are composed of only a subset of the target’s letters,
then letter order is critical for obtaining significant priming. Experiment 1 replicated the basic findings of Humphreys et al. (1990)
and Peressotti and Grainger (1999). With primes that shared five
letters with 7-letter target words, significant priming arose only
when the prime letters respected their order in the target word, and
inserting hyphens to provide length-dependent, absolute position
information did not increase the amount of priming. This pattern
was replicated with a different set of target words in Experiment 6
(relative-position priming) with no pattern masking. However,
relative-position priming was only robust at the shortest prime
duration (33 ms) in this experiment, and no longer influenced
performance to target words at the 83 ms prime duration. These
results provide a solid empirical foundation for relative-position
priming that will be important for developing our understanding of
how letter position information is coded during printed word
perception.
Positional Biases in Masked Priming
Position of overlap, in terms of whether the prime letters were
mainly from the beginning or from the end of target words, did not
have a major influence on the results obtained in the present
experiments. In each individual experiment, primes containing the
initial letters of the target word did not provide significantly
greater facilitation than primes containing the target’s final letters.
Nevertheless, a combined analysis of three different experiments
did reveal a significant word-beginning advantage, and this advantage, relative to word-final primes, was systematic across the three
experiments. This pattern fits with the results obtained with eyemovement recordings (parafoveal priming) that showed a systematic advantage when parafoveal previews share the target word’s
initial letters compared to when only word-final letters are shared
(e.g., Briihl & Inhoff, 1995; Inhoff, 1989). However, further analyses of this word-initial advantage showed that it is likely due to
a confound with level of prime-target phonological overlap. Including this variable as a covariate removed the significant advantage of word-initial primes.
Therefore, the most parsimonious account of the present results
is that positional biases are minimal in conditions where the
influence of phonological factors is minimized. This fits with a
model of orthographic processing that allows the parallel identification of a string of letters (Grainger & van Heuven, 2003).
However, the results do not exclude the possibility of serial
(beginning-to-end) processing of phonological information. Our
correlational analyses of priming effects obtained at 50 ms prime
durations in Experiments 2 and 3 suggested a small but significant
phonological influence on priming effect size. (Priming effects
increased with an increase in the number of phonemes shared by
prime and targets.) Indeed, in other studies using slightly longer
prime durations, robust effects of phonological priming have been
systematically found in the masked priming paradigm (e.g., Ferrand & Grainger, 1992, 1994; Grainger et al., 2003; Ziegler et al.,
2000). This was confirmed in Experiment 6 where phonological
priming was evaluated by comparing effects of pseudohomophone
primes with nonhomophonic orthographic control primes. Phonological priming was absent at the shorter (33 ms) prime duration,
and emerged at the longer (83 ms) prime duration in this experiment. Recently, Carreiras, Ferrand, Grainger, and Perea (2005)
found evidence for sequential processing of phonology using
longer words than traditionally tested in studies of masked phonological priming. Carreiras et al. found priming for initial phonological overlap (the first syllable of bisyllabic words) and no
priming for final phonological overlap (the last syllable of bisyllabic words), and this pattern was obtained in both the naming and
lexical decision tasks. Since the length of words tested by Carreiras
et al. was similar to the length of words in the present study, it can
be tentatively concluded that fast parallel orthographic processing
precedes the sequential computation of a sublexical, phonological
code.
The other positional bias investigated in the present study concerns a possible advantage for outer letters compared with inner
letters. Contrary to a number of studies, the present work provided
no evidence in favor of an outer letter advantage in visual word
recognition. Using a masked priming paradigm similar to that used
in the present study, Humphreys et al. (1990) found that primes
containing both of the target’s outer letters tended to produce
stronger priming than primes that contained only one outer letter or
neither of the target’s outer letters. However, these differences
were always marginal and not always in the appropriate direction.
For example, in Humphreys et al.’s Experiment 1a, the ssds prime
condition was actually numerically worse than the sssd and dsss
prime conditions (where “s” is a letter shared by prime and target,
and “d” is a different letter). It is in their Experiment 1b that
Humphreys et al. found the strongest evidence for an outer letter
advantage with prime condition sdds generating significantly
higher levels of target identification than either of the following
conditions: ssdd, dssd, ddss. Given that Experiments 2 and 3 of the
present study showed exactly the opposite effect (in some conditions primes containing both of the targets’ outer letters produced
less priming than primes containing a single outer letter), it was
tentatively hypothesized that the perceptual identification task
might be more sensitive to outer letter effects. However, using the
same paradigm as Humphreys et al. (1990), Experiment 4 of the
present study found no evidence for an outer letter advantage. We
would therefore suggest that the type of priming (substitution
priming in Humphreys et al.’s experiments vs. relative-position
priming in our experiments) could be the source of the discrepancy. Substitution primes include unrelated letters (that replace
one or more of the target’s letters), and it may well be the position
of the two unrelated letters in Humphreys et al.’s (1990) Experiment 1b that determined the pattern they observed.
However, robust and systematic advantages for outer letters
have been obtained with other paradigms. For example, in a recent
study Jordan et al. (2003) presented participants with words that
had two of their letters degraded by spatial filtering (producing a
blurred version of the letter). In an otherwise normal reading
situation, they found that reading rate was significantly faster when
two inner letters were degraded compared to when the two outer
letters were degraded. Nevertheless, an analysis of the complete
pattern of data presented by Jordan et al. (2003) shows that their
data only partly support the hypothesis that outer letters enjoy a
privileged status in visual word recognition. The condition where
both outer letters were intact (interior letters degraded) did not
improve reading rate compared to a condition where only one
outer letter was intact (when the first two letters were degraded).
So these results are compatible with the present data and are not
compatible with a straightforward outer letter advantage in visual
word recognition.2
Letter Position Coding
The central aim of the present study was to provide further
critical data to inform our ongoing attempt to describe how letter
position information is coded during printed word perception.
Some standard letter position coding schemes were mentioned in
the introduction. The length-dependent position-specific coding
scheme of the interactive-activation model (McClelland & Rumelhart, 1981) codes the position of each letter at a specific position
in a string of a given length. This is a highly efficient but very
uneconomical means of coding letter position, requiring a large
number of duplications of letter representations for each lengthdependent position in a word. The number of duplications can be
reduced by introducing one or more anchor points in the coding
scheme. Thus in Coltheart et al.’s (1993; 2001) DRC model, the
beginning of a word forms the anchor point for coding letter
position independently of word length. In the multiple read-out
model with phonology (MROM-p) Jacobs, Rey, Ziegler and
Grainger (1998) used the first and last letters as anchor points for
position coding, such that inner letters are either coded as being n
positions from the beginning, or n positions from the end of the
string. Another possible means of coding letter-in-string position
was adopted by Seidenberg and McClelland (1989). In this
scheme, words are coded as unordered sets of letter triples where
the space before and after the word is included as a character. Thus
877
the word “MAKE” is coded as #MA, MAK, AKE, KE#, where the
hash mark represents a space. The order of the letters in each triplet
is critical, but no order information is provided for the triplets
themselves. As noted in the introduction, none of these approaches
to letter position coding can account for the relative-position
priming effects that were replicated and extended in the present
study.
A number of more recent models of letter position coding can
account for the basic phenomenon of relative-position priming (see
Davis & Bowers, 2004; Grainger & van Heuven, 2003; & Perea &
Lupker, 2004, for more detailed descriptions of recent coding
schemes). In spatial coding schemes, the relative position of a
spatially distributed set of items is coded in terms of their relative
activation level. This is best achieved when the items in the list
form a monotonically increasing or decreasing set of activation
values, referred to as an activation gradient (Grossberg, 1978). For
the purposes of letter position coding, the activation gradient must
form a monotonically decreasing activation function across letter
position with the highest value for initial letters and the lowest
value for the final letter of the string. This is the case in the
SOLAR model (Davis, 1999), and the SERIOL model of Whitney
(2001), where a set of position-independent letter detectors are
activated by the orthographic input, and the relative position of
these letter identities is coded by the relative activation levels of
the corresponding detectors. In the SERIOL model, relative activation values at the letter level are used to activate noncontiguous
bigram units, to be discussed in more depth below. In the SOLAR
model, information about letter identity and letter order serves as
input to an equation that determines the match between incoming
information and whole-word orthographic representations in longterm memory3. This match calculation, which is admittedly only
part of the complex set of computations used by the SOLAR
model, actually operates like a fuzzy slot-based coding scheme. In
this particular case, letter order is given from beginning-to-end (as
in the DRC model, Coltheart et al., 2001), with Gaussian noise
added at each position. The match value is a function of the degree
of displacement of letters shared across input and the bestmatching stored representation. In the Appendix we provide the
match calculations generated by the SOLAR and SERIOL models
for the priming conditions tested in the presented experiments.
The central idea in Grainger and van Heuven’s (2003) approach
is that higher-level sublexical representations code for the presence
of contiguous and noncontiguous letter sequences at lower levels
of processing (i.e., the alphabetic array in Figure 1). The principle
of coding the relative position of nonadjacent letters is also used in
Whitney’s (2001) model where, for example, the word “CART” is
coded as the following set of bigrams: CA, CR, CT, AR, AT, RT.
Thus bigrams are formed across adjacent and nonadjacent letters in
the correct order, the basis of what Grainger and van Heuven
2
Ongoing work in our laboratory is currently exploring possible differences in outer versus inner letters in relative-position priming. The results
at present suggest that primes with no outer letter (e.g., 23456 for a 7-letter
target) are at a disadvantage compared with primes that contain at least one
outer letter (e.g., 13456, 23457).
3
Information about the match calculation equation, the SOLAR model,
and the match calculator program used to calculate the match values for the
SOLAR model can found at http://www.maccs.mq.edu.au/⬃colin.
878
GRAINGER ET AL.
Figure 1. Functional architecture for orthographic processing. A letter
string is first processed by 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. (The example shows an unconstrained
version of Grainger & van Heuven’s open-bigram coding.) These relativeposition coded letter identities control activation at the level of whole-word
orthographic representations (O-words) via bidirectional excitatory connections with all units at the relative position level.
(2003) later referred to as “open-bigram” coding. The critical
difference between our account and the one developed by Whitney
(2001), concerns the mechanism used to activate the appropriate
open-bigrams. Whitney (2001) described a method for translating
acuity-dependent activations of letter representations into a monotonically decreasing gradient. Relative activation at the letter level
is then transformed into activation of ordered bigram units. Our
approach is more in the tradition of Mozer (1987) using a hierarchical, parallel activation mechanism, as shown in Figure 1. The
first stage of orthographic processing involves a specialized bank
of letter detectors (the alphabetic array) that simultaneously receive input about visual feature information at a particular retinal
location along the horizontal meridian (i.e., there are different
letter detectors for different retinal locations). Each letter detector
in the alphabetic array signals the presence of one out of 26
possible letters at a given retinal location. Open-bigram units
receive activation from the alphabetic array such that a given letter
order A-B, which is realized at any of the possible combinations of
location in the alphabetic array, activates the open-bigram for that
sequence (with possible constraints on the distance separating the
two component letters, Grainger & van Heuven, 2003). Thus, in
recoding information represented in the alphabetic array, a
location-specific map of letter identities is replaced by a wordcentered, location-invariant code.
All of the more recent proposals for letter position coding during
printed word perception can accommodate the basic relativeposition priming effect that was replicated and extended in the
present study (see Appendix). This is because all these coding
schemes (Davis, 1999; Grainger & van Heuven, 2003; Whitney,
2001) code for the relative position of letters in a string somewhat
independently of the absolute, length-dependent position of each
letter in the string. This increased flexibility in the way letter
position is computed has endowed such coding schemes with the
ability to explain another equally important empirical phenome-
non: transposed-letter priming. Open-bigram coding, for example,
was developed explicitly to account for relative-position priming
effects, yet this theoretical approach provides a principled account
of transposed-letter priming (Grainger & Whitney, 2004).
Transposed-letter primes are formed by changing the order of
letters in a word without removing any of the letters. In standard
masked priming with the lexical-decision task and relatively long
target words, Forster et al. (1987) found that effects of transposed
letter primes (e.g., salior-SAILOR) were practically the same as
identity primes (e.g., sailor-SAILOR). This finding has been replicated and extended by Perea and Lupker (2003, 2004), and
Schoonbaert and Grainger (2004), using more appropriate substitution primes as the baseline for evaluating transposed-letter priming (e.g., “sateor” as a control for “salior”). However, with shorter
words (Humphreys et al., 1990), or when primes do not contain all
of the target’s letters (Peressotti & Grainger, 1999), then transposition priming is greatly diminished. Using their 4-field masking
procedure and perceptual identification responses to targets, Humphreys et al. (1990) found only a nonsignificant 3.1% increase in
response accuracy for transposed letter primes (e.g., snad-SAND)
compared to primes sharing two out of four letters with targets
(e.g., smed-SAND). Similarly, Peressotti and Grainger (1999, Experiment 2a) observed a nonsignificant 5 ms advantage relative to
all different primes when the two central letters were transposed in
primes sharing four out of six letters with targets (e.g., bclnBALCON). This is in line with the results of Experiments 1 and 6
of the present study, showing no priming relative to an unrelated
baseline for subset primes with transposed letters.
Although at first sight contradictory, the robust effects of
transposed-letter primes when primes contain all of the target’s
letters, and the absence of such effects when primes are formed of
a subset of the target’s letters, are both predicted by the models
tested in the present study. Indeed, these two phenomena
(transposed-letter priming and relative-position priming) provide
the strongest evidence in favor of such coding schemes. More
fine-grained manipulations are required to begin the difficult task
of selecting among these models, and one such manipulation
involves the level of contiguity of letters shared by prime and
target stimuli.
Contiguity and Orthographic Priming
In relative-position primes, the letters shared by prime and target
can vary in terms of the level of contiguity of these letters in the
target stimulus. Thus, in Experiments 2, 3, 4, and 5 of the present
study, primes could be completely contiguous letter sequences
(e.g., 12345, 34567) or noncontiguous sequences of letters (e.g.,
13457). The models presented above (except for an unconstrained
version of open-bigram coding, see Appendix) all predict an influence of this factor on the size of relative-position priming
effects. However, the way contiguity affects orthographic processing varies across the different models as a function of the specific
mechanism used to code for letter position. To complete the
present investigation, we will examine the possible role of letter
contiguity as a factor determining the efficacy of orthographic
primes.
In an open-bigram coding scheme, contiguity can influence
performance by having bigram activation vary as a function of the
distance separating the component letters. This is the case in
Whitney’s (2001) SERIOL model where more contiguous bigrams
receive greater activation. In Grainger and van Heuven’s (2003)
simulations, a simple binary weighting was used such that bigrams
that involved more than two intervening letters (e.g., the bigram
TE in the word TABLE) were ignored (see description of constrained open-bigram model in Appendix). At a more general level
of theorizing, one can draw a distinction between models that
deliberately code for noncontiguous letter combinations (e.g.,
Grainger & van Heuven, 2003; Whitney, 2001), and an approach
in which noncontiguous letter combinations are coded as a result
of positional coding errors in more traditional contiguous bigram
coding schemes. If letter detector units in the alphabetic array are
assumed to have overlapping receptive fields (see Figure 2), as in
the overlap model of Perea, Gómez, and Ratcliff (2003), then
coding for adjacent letter combinations will lead to certain noncontiguous combinations being coded as well as letter transpositions. The amount of overlap in the receptive fields of letter
detectors determines the limits of open-bigram coding via this
mechanism (see Dehaene, Cohen, Sigman, & Vinckier, 2005, for
a similar proposal). Thus, coding for adjacent bigrams in a fuzzy
slot-based coding scheme generates a graded activation in contiguous and noncontiguous bigrams, and provides a natural means of
constraining the degree of separation of letters forming an openbigram. Furthermore, the differential weighting of open-bigrams
as a function of contiguity provides more precise positional information in such a coding scheme (see Appendix for more details).
These two different coding schemes can be seen as trading off
local versus more global position information in opposite ways.
The contiguous coding scheme optimizes local combinations at the
cost of an increase in the risk of making position coding errors,
while the noncontiguous scheme optimizes accurate relativeposition coding (knowledge that a given letter is positioned left or
Figure 2. Description of the overlap open-bigram model. Letter detectors
in the alphabetic array have large overlapping receptive fields (RFs) such
that for a given letter at a given retinal location one letter identity will be
maximally activated, and other letter identities falling within the receptive
field of the letter detector will also receive some activation (see Appendix
for details). Bigrams are computed across adjacent locations in the alphabetic array on the basis of all letter identities (several at any given location)
activated above a criterion value. Thus bigrams are formed from adjacent
letters in the correct order, nonadjacent letters in the correct order (openbigrams), and adjacent letters in the incorrect order (transposed bigrams).
879
right of another letter) at the cost of not directly specifying local
information (knowledge that a given letter is next to another letter).
More generally, contiguous and noncontiguous letter combinations (whatever the mechanism that generates them) can be seen as
providing two different types of orthographic code, possibly with
different time-courses. Noncontiguous combinations would provide a fast, approximate orthographic code useful for providing an
initial constraint on word identity, whereas contiguous letter combinations would provide a more fine-grained orthographic representation that would be useful for deriving a phonological code.
Therefore, under this view the contiguous code should start to
dominate processing as soon as phonology starts to exert an
influence during visual word recognition. On the other hand, the
influence of noncontiguous orthographic codes will diminish as
phonological codes start to dominate processing, since they map
poorly onto phonology (many noncontiguous letter combinations
will not have a corresponding phonological representation). The
observed difference in the time-courses of noncontiguous relative
position primes, single letter substitution primes, and
pseudohomophone primes in Experiment 6 is in line with this
proposition.
The results of match calculations for the different versions of
open-bigram coding and the SERIOL and SOLAR models are
given in the Appendix. Not surprisingly, a model in which contiguity does not affect orthographic processing (i.e., the unconstrained open-bigram model) does the worse in conditions where
we suspect phonological prime-target overlap is partly driving
priming effects (see Table A2 in Appendix). This is because it is
precisely in these conditions that we found the clearest evidence
for an influence of contiguity: Primes formed of completely contiguous sequences of letters from the target (e.g., 12345, 34567)
were more effective than primes formed of noncontiguous letter
sequences (e.g., 13457). All models, except for the unconstrained
open-bigram model, predict that the level of contiguity of prime
letters in the target stimulus will influence priming, hence the
relatively strong correlations between the match values generated
by these models and priming effects sizes. However, what is more
important is that even in conditions where phonology was not
found to significantly affect priming, the unconstrained openbigram model continues to generate the poorest predictions (see
Table A1 in Appendix). This is because the model overestimates
the amount of priming generated by the transposition of inner
letters (the 15437 condition of Experiment 1 and the 1537 condition of Experiment 6). The SOLAR model also has difficulty with
these particular priming conditions, again overestimating the size
of priming effects compared to certain conditions where letter
order is respected (e.g., 1469 prime for 9-letter targets).
Therefore, the match calculations shown in the Appendix reveal
that models of orthographic processing that include contiguity
constraints (particularly the overlap open-bigram model and the
SERIOL model) actually do a better job in capturing the overall
pattern of results in testing conditions where contiguity was not
expected have a strong influence. However, these models do fail to
account for the robust priming effect found with extreme cases of
noncontiguous primes (i.e., the 1469 primes in Experiment 5).
Clearly more experimentation is required on effects of contiguity
in relative-position priming in order to provide more discriminatory data with respect to current accounts of letter position coding.
These experiments should provide more information concerning
GRAINGER ET AL.
880
the precise time-course of effects of contiguous and noncontiguous
orthographic primes.
Conclusions
The present study replicates and extends the relative-position
priming effects first demonstrated by Humphreys et al. (1990) and
Peressotti and Grainger (1999). Relative-position primes contain a
subset of the target’s letters that are concatenated such that while
letter order information is respected across prime and target stimuli, absolute, length-dependent information is violated. Experiments 1 and 6 showed that order information is important, since
priming effects disappeared when the subset of letters forming the
prime stimulus did not respect their order in the target. Experiments 2 and 3 compared relative-position priming using different
subsets of a target’s letters: initial letters, final letters, and a
combination of the first, last, and central letters (outer-central
primes). Initial and final letter primes produced significant priming
and these two conditions did not differ significantly, while the
outer-central primes produced less priming. One possibility is that
the reduced priming for the outer-central primes is due to the lower
level of contiguity in this prime condition, and match calculations
using Grainger and van Heuven’s (2003) constrained open-bigram
model, the overlap open-bigram model, the SERIOL model (Whitney, 2001), and the SOLAR model (Davis, 1999) indeed predict
such an effect of contiguity (see Appendix). However, post hoc
analyses showed that differences in priming effect sizes could be
due to differences in the level of prime-target phonological overlap
across the different priming conditions. Experiments 4 and 5
confirmed this hypothesis by showing statistically equivalent
priming effects for initial, final, and outer-central primes in conditions where prime-target phonological overlap did not influence
priming (i.e., with short, 33 ms prime exposures). Experiment 6
further confirmed that phonological priming only emerges with
longer prime exposures. On the basis of these results, it was
concluded that when phonological influences on priming effects
are minimized, then the level of contiguity of relative-position
primes does not influence priming.
Whether or not orthographic priming is indeed affected by the
level of contiguity of letters shared by prime and target remains an
important issue for future research. Ongoing research in our laboratory has further attempted to answer this question by using
superset primes, that is primes that include all of the target’s letters
in the correct order, plus some irrelevant letters (Van Assche &
Grainger, 2006). Another very interesting extension of the present
work would be to test for similar types of orthographic priming
using parafoveal priming techniques (see Rayner, 1998, for a
review). Since parafoveal priming is thought to reflect the earliest
phases of printed word perception operating before the eyes are
actually fixating the target word, we would expect to observe
priming effects very much in line with those observed in the
present study. Another methodology that has recently proved sensitive to early orthographic processing involves recording eventrelated brain potentials (ERPs). In recent work combining ERP
recordings with masked priming methodology, Misra and Holcomb (2003) found priming effects arising as early as 200 ms
posttarget onset (see also Holcomb & Grainger, 2006). It will
therefore be interesting to see whether ERPs are sensitive to the
type of priming manipulated in the present study, and at what time
during target processing such influences appear. Converging evidence of this kind will be critical for defining the type of phenomena that computational models of orthographic processing must be
able to accommodate.
References
Besner, D., Coltheart, M., & Davelaar, E. (1984). Basic processes in
reading: Computation of abstract letter identities. Canadian Journal of
Experimental Psychology, 38, 126 –134.
Briihl, D., & Inhoff, A. W. (1995). Integrating information across fixations
during reading: The use of orthographic bodies and of exterior letters.
Journal of Experimental Psychology: Learning, Memory, and Cognition, 21, 55– 67.
Caramazza, A., & Hillis, A. (1990). Levels of representation, coordinate
frames, and unilateral neglect. Cognitive Neuropsychology, 7, 391– 445.
Carreiras, M., Ferrand, L., Grainger, J., & Perea, M. (2005). Sequential
effects of phonological priming in visual word recognition. Psychological Science, 16, 585–589.
Cohen, J., MacWhinney, B., Flatt, M., & Provost, J. (1993). PsyScope: An
interactive graphic system for designing and controlling experiments in
the psychology laboratory using Macintosh computers. Behavior Research Methods, Instruments and Computers, 25, 257–271.
Coltheart, M., Curtis, B., Atkins, P., & Haller, M. (1993). Models of
reading aloud: Dual-route and parallel-distributed-processing approaches. Psychological Review, 100, 589 – 608.
Coltheart, M., Rastle, K., Perry, C., & Ziegler, J. (2001). DRC: A dual
route cascaded model of visual word recognition and reading aloud.
Psychological Review, 108, 204 –256.
Davis, C. J. (1999). The Self-Organising Lexical Acquisition and Recognition (SOLAR) model of visual word recognition. Unpublished doctoral
dissertation, University of New South Wales, Australia.
Davis, C. J., & Bowers, J. S. (2004). What do letter migration errors reveal
about letter position coding in visual word recognition? Journal of
Experimental Psychology: Human Perception and Performance, 30,
923–941.
Dehaene, S., Cohen, L., Sigman, M., & Vinckier, F. (2005). The neural
code for written words: A proposal. Trends in Cognitive Sciences, 9,
335–341.
Diependaele, K., Sandra, D., & Grainger, J. (2005). Masked cross-modal
morphological priming: Unravelling morpho-orthographic and morphosemantic influences in early word recognition. Language and Cognitive
Processes, 20, 75–114.
Dunnett, C. W. (1955). A multiple comparison procedure for comparing
several treatments with a control. Journal of the American Statistical
Association, 50, 1096 –1121.
Evett, L. J., & Humphreys, G. W. (1981). The use of abstract graphemic
information in lexical access. Quarterly Journal of Experimental Psychology, 33A, 325–350.
Ferrand, L., & Grainger, J. (1992). Phonology and orthography in visual
word recognition: Evidence from masked nonword priming. Quarterly
Journal of Experimental Psychology, 45A, 353–372.
Ferrand, L., & Grainger, J. (1993). The time-course of phonological and
orthographic code activation in the early phases of visual word recognition. Bulletin of the Psychonomic Society, 31, 119 –122.
Ferrand, L., & Grainger, J. (1994). Effects of orthography are independent
of phonology in masked form priming. Quarterly Journal of Experimental Psychology, 47A, 365–382.
Forster, K. I., & Davis, C. (1984). Repetition priming and frequency
attenuation in lexical access. Journal of Experimental Psychology:
Learning, Memory, and Cognition, 10, 680 – 698.
Forster, K. I., Davis, C., Schoknecht, C., & Carter, R. (1987). Masked
priming with graphemically related forms: Repetition or partial activation? Quarterly Journal of Experimental Psychology, 39A, 211–251.
Forster, K. I., & Forster, J. (2003). DMDX: A Windows display program
with millisecond accuracy. Behavioral Research Methods: Instruments
& Computers, 35, 116 –124.
Frost, R., Ahissar, M., Gotesman, R., & Tayeb, S. (2003). Are phonological effects fragile? The effect of luminance and exposure duration on
form priming and phonological priming. Journal of Memory and Language, 48, 346 –378.
Grainger, J., Diependaele, K. Spinelli, E. Ferrand, L., & Farioli, F. (2003).
Masked repetition and phonological priming within and across modalities, Journal of Experimental Psychology: Learning, Memory, and Cognition, 29, 1256 –1269.
Grainger, J., & Jacobs, A. M. (1993). Masked partial-word priming in
visual word recognition: Effects of positional letter frequency. Journal
of Experimental Psychology: Human Perception and Performance, 19,
951–964.
Grainger, J., & Jacobs, A. M. (1999). Temporal integration of information
in orthographic priming. Visual Cognition, 6, 461– 492.
Grainger, J., & Van Heuven, W. (2003). Modeling letter position coding in
printed word perception. In P. Bonin (Ed.), The mental lexicon (pp.
1–24). New York: Nova Science Publishers.
Grainger, J., & Whitney, C. (2004). Does the huamn mnid raed wrods as
a wlohe? Trends in Cognitive Sciences, 8, 58 –59.
Grossberg, S. (1978). A theory of human memory: Self-organization and
performance of sensory-motor codes, maps, and plans. In R. Rosen & F.
Snell (Eds.), Progress in theoretical biology (pp. 233–374). New York:
Academic Press.
Holcomb, P. J., & Grainger, J. (2006). On the time-course of visual word
recognition: An ERP investigation using masked repetition priming.
Journal of Cognitive Neuroscience, in press.
Humphreys, G. W., Evett, L. J., & Quinlan, P. T. (1990). Orthographic
processing in visual word identification. Cognitive Psychology, 22,
517–560.
Imbs, P. (1971). Etudes statistiques sur le vocabulaire français: Dictionnaire des fréquences. Vocabulaire littéraire des XIXe et XXe siècles.
Paris: Librairie Marcel Didier.
Inhoff, A. W. (1989). Lexical access during eye fixations in reading: Are
word access codes used to integrate lexical information across interword
fixations? Journal of Memory and Language, 28, 444 – 461.
Inhoff, A. W., Radach, R., Eiter, B. M., & Juhasz, B. (2003). Distinct
subsystems for the parafoveal processing of spatial and linguistic information during eye fixations in reading. Quarterly Journal of Experimental Psychology, 56A, 803– 827.
Jacobs, A. M., Rey, A., Ziegler, J. C., & Grainger, J. (1998). MROM-p: An
interactive activation, multiple read-out model of orthographic and phonological processes in visual word recognition. In J. Grainger & A. M.
Jacobs (Eds.), Localist connectionist approaches to human cognition
(pp. 147–188). Mawah, NJ: Erlbaum.
Jordan, T. R., Thomas, S. M., Patching, G. R., & Scott-Brown, K. C.
(2003). Assessing the importance of letter pairs in initial, exterior, and
interior positions in reading. Journal of Experimental Psychology:
Learning, Memory, and Cognition, 29, 883– 893.
881
McClelland, J. L., & Rumelhart, D. E. (1981). An interactive activation
model of context effects in letter perception: Pt. 1. An account of basic
findings. Psychological Review, 88, 375– 407.
Misra, M., & Holcomb, P. J. (2003). The electrophysiology of word-level
masked repetition priming. Psychophysiology, 40, 115–130.
Mozer, M. (1987). Early parallel processing in reading: A connectionist
approach. In M. Coltheart (Ed.), Attention and performance XII (pp.
83–104). Hillsdale, NJ: Erlbaum.
New, B., Pallier, C., Ferrand, L., & Matos, R. (2001). Une base de données
lexicales du français contemporain sur internet: LEXIQUE. L’Année
Psychologique, 101, 447– 462.
Perea, M., Gómez, P., & Ratcliff, R. (2003). A model of encoding letter
positions: The overlap model. Proceedings of the XIIth Congress of the
European Society for Cognitive Psychology, Granada, Spain.
Perea, M., & Lupker, S. J. (2003). Transposed-letter confusability effects
in masked form priming. In S. Kinoshita and S. J. Lupker (Eds.), Masked
priming: State of the art (pp. 97–120). Hove, UK: Psychology Press.
Perea, M., & Lupker, S. J. (2004). Can Caniso activate Casino?
Transposed-letter similarity effects with nonadjacent letter positions.
Journal of Memory and Language, 51, 231–246.
Peressotti, F., & Grainger, J. (1999). The role of letter identity and letter
position in orthographic priming. Perception & Psychophysics, 61, 691–
706.
Plaut, D., McClelland, J. L., Seidenberg, M. S., & Patterson, K. (1996).
Understanding normal and impaired reading: Computational principles
in quasi-regular domains. Psychological Review, 103, 56 –115.
Pollatsek, A., & Well, A. (1995). On the use of counterbalanced designs in
cognitive research: A suggestion for a better and more powerful analysis.
Journal of Experimental Psychology: Learning, Memory, and Cognition, 21, 785–794.
Rayner, K. (1998). Eye movements in reading and information processing:
20 years of research. Psychological Bulletin, 124, 372– 422.
Rayner, K., McConkie, G. W., & Zola, D. (1980). Integrating information
across eye movements. Cognitive Psychology, 12, 206 –226.
Schoonbaert, S., & Grainger, J. (2004). Letter position coding in printed
word perception: Effects of repeated and transposed letters. Language
and Cognitive Processes, 19, 333–367.
Seidenberg, M. S., & McClelland, J. L. (1989). A distributed, developmental model of word recognition and naming. Psychological Review,
96, 523–568.
Van Assche, E., & Grainger, J. (2006). A study of relative-position priming
with superset primes. Journal of Experimental Psychology: Learning,
Memory, and Cognition, in press.
Whitney, C. (2001). How the brain codes the order of letters in a printed
word: The SERIOL model and selective literature review. Psychonomic
Bulletin & Review, 8, 221–243.
Ziegler, J., Ferrand, L., Jacobs, A. M., Rey, A., & Grainger, J. (2000).
Visual and phonological codes in letter and word recognition: Evidence
from incremental priming. Quarterly Journal of Experimental Psychology, 53A, 671– 692.
(Appendix follows)
GRAINGER ET AL.
882
Appendix
The appendix describes the method of calculating match values between
incoming orthographic information (prime) and a whole-word orthographic
representation (target) for an unconstrained open-bigram model (UOB), a
constrained open-bigram model (COB, Grainger & van Heuven, 2003), and
the overlap open-bigram model (OOB) discussed in the present work. The
match values generated by these models are compared with the net priming
effects obtained in the present study and the corresponding match values
generated by the SOLAR model (see footnote 3) and the SERIOL modelA1.
The results of these calculations and the correlations with priming effects
are given in Table A1 for three Experiments (Experiments 1, 5, and 6)
where phonological prime-target overlap are hypothesized not to have
influenced differences in priming effects across conditions. (Experiment 4
is not included because of the different dependent variable used in that
experiment.) Table A2 provides the match calculations and correlations
with net priming effects in Experiments 2 and 3 where priming effects were
shown to be influenced by prime-target phonological overlap.
Unconstrained Open-Bigram Model (UOB)
To calculate match values for this model we first determine the openbigrams that are activated by the prime and target string. Open-bigrams are
activated from an input string by adjacent and non-adjacent letter pairs in
the correct order. For example, the input string 12345 activates the openbigrams 12, 13, 14, 15, 23, 24, 25, 34, 35, and 45. Each open-bigram (OB)
receives an activation value of 1.0. Equation (1) is then used to calculate
the match value of the prime and target string. In this formula the sum of
products of activations of matching OBs of primes and targets is divided by
the sum of products of activations from all target OBs.
match value ⫽
⌺OB共 prime兲*OB共target兲
⌺OB共target兲 2
Example:
Target ⫽ 1234567
Open-bigrams: 12, 13, 14, 15, 16, 17, 23, 24, 25, 26, 27
34, 35, 36, 37, 45, 46, 47, 56, 57, 67
Prime ⫽ 15437
Open-bigrams: 15, 14, 13, 17, 54, 53, 57, 43, 47, 37
The open-bigrams 15, 14, 13, 17, 57, 47, and 37 are activated by the
prime and target string, thus the match value is 0.33.
match value ⫽
7
1⫹1⫹1⫹1⫹1⫹1⫹1
⫽
⫽ 0.33
21
21
Constrained Open-Bigram Model (COB)
This model is similar to the previous model except that it includes a
constraint on the maximum distance (in number of letters) separating the
constituent letters of open-bigrams in the input string. Following Grainger
and van Heuven (2003) this is set at two letters (e.g., the string 12345 only
activates the open-bigrams 12, 13, 14, 23, 24, 25, 34, 35, and 45). Each
A1
The match values for the SERIOL model and the equations used to
calculate these are given in the following unpublished manuscript: Whitney, C., Supporting the Serial in the SERIOL model (available upon
request from the author).
Table A1
Match Values Generated by the Unconstrained Open-Bigram Model (UOB), the Constrained
Open-Bigram Model (COB), the Overlap Open-Bigram Model (OOB), the SERIOL Model
(Whitney, 2001; Footnote A1), and the SOLAR Model (Davis, 1999; Footnote 3) for the Priming
Conditions Tested in Experiments 1, 5 (Unmasked), and 6 (33 ms Prime Duration)
Prime
Priming
effect
UOB
COB
OOB
1a
1-345-7
13-4-57
13457
20*
22*
25*
0.48
0.48
0.48
0.47
0.47
0.47
0.47
0.47
0.47
0.57
0.57
0.57
0.64
0.64
0.64
1b
1-345-7
1-543-7
7-345-1
23*
⫺2
7
0.48
0.33
0.14
0.47
0.27
0.20
0.47
0.11
0.30
0.57
0.27
0.23
0.64
0.45
0.39
5 (7-letter)
1234
4567
1357
36*
30*
31*
0.29
0.29
0.29
0.40
0.40
0.20
0.48
0.48
0.23
0.48
0.45
0.38
0.58
0.55
0.40
5 (9-letter)
1234
6789
1469
26*
17*
23*
0.17
0.17
0.17
0.29
0.29
0.14
0.35
0.35
0.08
0.36
0.35
0.18
0.46
0.44
0.23
6
1357
1537
7351
20*
8
7
0.29
0.24
0.05
0.40
0.13
0.07
0.48
0.10
0.08
0.38
0.19
0.02
0.58
0.33
0.24
0.28
0.48
0.61⫹
0.59⫹
0.43
Experiment
Correlation with net
priming effect
SERIOL
SOLAR
Note. ⫹ Correlation is significant at the 0.05 level (2-tailed); * significantly different from the ddddd
condition, p ⬍ .05 by participant using Dunnett’s test; parameters of the SOLAR model: sigma ⫽ 3.0, w_IMR ⫽
1.4, w_FMR ⫽ 1.2; ‘-’ characters were removed from input strings in the match calculations.
883
Table A2
Match Values Generated by the unconstrained Open-Bigram Model (UOB), the Constrained
Open-Bigram Model (COB), the Overlap Open-Bigram Model (OOB), the SERIOL Model
(Whitney, 2001; Footnote A1), and the SOLAR Model (Davis, 1999; Footnote 3) for the Priming
Conditions Tested in Experiments 2 and 3
Prime
Priming
effect
2 (7-letter)
12345
34567
13457
45*
37*
29*
0.48
0.48
0.28
0.60
0.60
0.47
0.65
0.65
0.47
0.61
0.60
0.57
0.71
0.68
0.64
2 (9-letter)
12345
56789
14569
30*
28*
12
0.28
0.28
0.28
0.43
0.43
0.24
0.48
0.48
0.25
0.46
0.46
0.32
0.56
0.54
0.38
3 (7-letter)
1234
4567
1357
23*
12
8
0.29
0.29
0.29
0.40
0.40
0.20
0.48
0.48
0.23
0.48
0.45
0.38
0.58
0.55
0.40
3 (9-letter)
1234
6789
1469
23*
20*
8
0.17
0.17
0.17
0.29
0.29
0.14
0.35
0.35
0.08
0.36
0.35
0.18
0.46
0.44
0.23
0.68⫹
0.90⫹⫹
0.87⫹⫹
0.82⫹
0.85⫹⫹
Experiment
Correlation with net
priming effect
UOB
COB
OOB
SERIOL
SOLAR
Note. ⫹ Correlation is significant at the 0.05 level (2-tailed); ⫹⫹ Correlation is significant at the 0.01 level
(2-tailed); * significantly different from the ddddd condition, p ⬍ .05 by participant using Dunnett’s test;
parameters of the SOLAR model: sigma ⫽ 3.0, w_IMR ⫽ 1.4, w_FMR ⫽ 1.2.
open-bigram receives an activation value of 1.0, and Equation (1) is used
to calculate the match value of the prime and target string.
Example:
Target ⫽ 1234567
Open-bigrams: 12, 13, 14, 23, 24, 25, 34, 35, 36, 45, 46, 47, 56, 57, 67
Prime ⫽ 15437
Open-bigrams; 15, 14, 13, 54, 53, 57, 43, 47, 37
Only the open-bigrams 13, 14, 47, and 57 are activated by the prime and
target string, thus the match value is 0.27.
match value ⫽
4
1⫹1⫹1⫹1
⫽
⫽ 0.27
15
15
Overlap Open-Bigram Model (OOB)
Contrary to the two previous versions of open-bigram coding, the
overlap open-bigram model attempts to code for contiguous letter sequences (bigrams) only. However, the noisy coding of letter position
implies that non-contiguous letter sequences (open-bigrams) will also be
coded. Noisy position coding is introduced as overlapping receptive fields
for each letter detector in the alphabetic array (see Figure 2). The receptive
fields place a normal distribution of activation values on top of each letter
position (e.g., 0.607, 1.0, 0.607 for the three-letter receptive field adopted
in the present simulations), such that for a given letter detector in the
alphabetic array, the letter present at that location receives full activation
(1.0) and the neighboring letters (immediately left and right of that location) receive partial activation (0.607). Thus in the example Table A3 the
letter detector that is aligned with the letter B signals the presence of B at
that location with 100% likelihood, but also signals the possible presence
of A and L at that same location with a probability of 0.607. Contiguous
bigrams are then coded by examining the activity of different letter
identities at each location in the alphabetic array. Bigram activation is
equal to the product of the activations of its component letters. When
identical bigrams are constructed, only the one with the highest activation remains. Note that both contiguous and non-contiguous bigrams
are formed as well as transposed bigrams, as illustrated in the following
example.
(Appendix continues)
GRAINGER ET AL.
884
Table A3
Activation of Letters in the Alphabetic Letter Array for Each Receptive Field
First letter
Receptive field
...
. .T
.TA
TAB
ABL
BLE
LE.
E. .
...
Second letter
Activation
.
.
.
T
A
B
L
E
.
0.607
0.607
0.607
0.607
0.607
0.607
0.607
0.607
0.607
Third letter
Activation
.
.
T
A
B
L
E
.
.
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
Activation
.
T
A
B
L
E
.
.
.
0.607
0.607
0.607
0.607
0.607
0.607
0.607
0.607
0.607
Note. Moving from top to bottom in the above example (i.e., along the alphabetic array from left to right),
ordered pairs of adjacent letters are formed, leading to the activation of the following bigrams (activation values
between brackets): TA (1.0), AB (1.0), BL (1.0), LE (1.0), TB (0.607), AL (0.607), BE (0.607), TL (0.135), AE
(0.135), AT (0.135), BA (0.135), LB (0.135), EL (0.135). These bigrams are then used to calculate the match
value between prime and target stimuli using the match value Equation (1) described above. Note that bigrams
formed of repeated letters (e.g., TT, AA, etc.) have been ignored here since they do not affect the match
calculation.
Received January 17, 2005
Revision received January 18, 2006
Accepted January 22, 2006 䡲

Letter Position Information and Printed Word Perception: The Relative-Position Priming Constraint

Transcription

Similar documents

Transformers Alternators Optimus Prime Dodge 81327 Instructions

Olivia Fiske, Alix Alto, Olivia Dooley, Dana Walker, Nicole Betz, Lisa

Transformers Masterpiece Rodimus Prime 32108 Instructions

01-Jan-2012Prime Elements Jan 2012 - English

PRIME WELCOMES CHRIS PASTRAS

judgmental primes - Columbia Business School

Document 6431976