# Searching beyond the looking glass with sandwich priming

Brice Brossette, Stéphanie Massol, Bernard Lété

► To cite this version:

Brice Brossette, Stéphanie Massol, Bernard Lété. Searching beyond the looking glass with sandwich priming. Attention, Perception, and Psychophysics, 2022, 84 (4), pp.1178-1192. 10.3758/s13414-021-02405-y. hal-04998245

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<figure><img src="image_1.png" /></figure>
Searching beyond the looking glass with sandwich priming.

Brice Brossette¹*, Stéphanie Massol¹, & Bernard Lété¹

¹ Université Lyon 2, Laboratoire d'Étude des Mécanismes Cognitifs (EA 3082), Bron, France

* Corresponding author: Brice Brossette, Laboratoire d'Étude des Mécanismes Cognitifs (EA 3082), 5 Avenue Pierre Mendès France, 69500 Bron, France. Email :

brice.brossette@univ-lyon2.fr
**Abstract**

Duñabeitia et al. (2011) demonstrated that mirror letters induce the same electrophysiological response as canonical letters during the orthographic stage of visual word recognition. However, behavioral evidence in support of such an effect has remained scarce. We hypothesize that the poor reliability of the behavioral data could be due to the lack of sensitivity of the paradigms used in the literature. In Experiment 1 and Experiment 2, we compared conventional and sandwich masked priming methods. Results showed that mirror primes (סיווג) produced a significant priming effect on high-frequency words in the case of sandwich priming only. In Experiment 3, we used sandwich priming with a new material set to address a number of concerns regarding prime-target visual overlap. We obtained a graded facilitatory mirror-letter priming effect which acted additively with lexical frequency, thus supporting the idea that it originates in the fast automatic orthographic stage. Given that the graded priming effect provides little support for the idea of the complete preservation of mirror invariance for non-reversal letters, complementary explanations are explored.

**Public significance statement**

Recent research has provided evidence for a mirror-letter inhibitory effect for reversal letters in orthographic processing, and for a mirror-letter facilitatory effect for non-reversal letters, suggesting that mirror invariance for letters is not fully inhibited during word recognition. However, behavioral evidence in favor of such an effect has so far remained scarce. Here, we test the mirror-letter facilitatory effect for non-reversal letters in a sandwich priming procedure. Our findings demonstrate a priming effect which, however, is graded in a purely additive way for high and low-frequency targets. This leads us to explore alternative explanations of the mirror invariance preservation hypothesis.
# 1. Introduction

What is the letter “a”? How can we categorize ‘a’ as identical to ‘A’ but different from ‘b’? How does the visual system compute abstract letter identities? These are central questions for the comprehension of the orthographic processing underlying visual word recognition. Abstract letter representations are assumed to be feature-based (Dehaene et al., 2005; Grainger et al., 2008), as well as size-insensitive, case-insensitive, typography-insensitive, and sufficiently flexible to ensure letter identification even when these are highly distorted, as in the case of captcha (Chauncey et al., 2008; Gil-López et al., 2011; Hannagan et al., 2012). The neural implementation of this abstraction process is supported by the rapid specialization of a subpart of the left fusiform gyrus during the early stages of literacy acquisition (Dehaene-Lambertz et al., 2018): the well-known Visual Word Form Area (VWFA hereafter) (Baker et al., 2007; Cohen et al., 2000). The VWFA benefits from inherited properties of the visual object recognition system to solve invariance issues like size-invariance or case-invariance (for a review, see Dehaene & Cohen, 2011). However, one of these inherited properties, namely mirror invariance, should be detrimental for the efficient coding of abstract letter identities. Mirror invariance allows the visual system to recognize objects independently of their left-right profile (Dehaene et al., 2015). Therefore, mirror invariance should make it impossible to have two distinct representations for mirror letters such as ‘b’ and ‘d’. To overcome this problem, the neural recycling hypothesis proposed that a cortical remapping operates within the VWFA-site in order to develop sensitivity to mirror contrasts (Dehaene et al., 2005; Dehaene & Cohen, 2007). In two fMRI experiments using an unmasked priming paradigm, Dehaene et al. (2010) and Pegado et al. (2011) reported a repetition suppression effect in the form of a decreased activation in the VWFA only for mirror-picture primes but not for mirror-word primes or mirror-letter primes. In both studies, the authors concluded that neurons in the VWFA-site are tuned during literacy acquisition to be sensitive to mirror contrasts of letters and words.

Since both letter-identity and letter-position coding are fast and automatic processes, to explore the behavioral correlates of the mirror-letter effect it is necessary to ensure that participants are unable to manipulate mirror information consciously. Masked priming, a method extensively used to investigate early orthographic processing (Forster & Davis,
1984; Perea & Lupker, 2004; Segui & Grainger, 1990), could meet this requirement. This
paradigm consists in briefly presenting a prime immediately prior to a target stimulus.
Participants are usually asked to perform a lexical decision task on the target stimulus.
Although participants are not able to report the identity of the prime, it still influences
target processing. This influence is measured in terms of the size of the priming effect,
considered as an index of orthographic similarity between prime and target.

In line with neuroimaging findings, Perea et al. (2011) and Soares et al. (2019) found that the processing of targets which contained reversal letters (such as b, d, p, q, whose mirror letters on the vertical axis correspond to other letters in the alphabet) was harder when they were preceded by a masked prime in which a critical letter was replaced by its mirror counterpart (ibea-IDEA) than when preceded by a masked prime in which the critical letter was replaced by a control one (ilea-IDEA). The authors interpreted these results as a consequence of mirror invariance unlearning, which makes it possible to code two distinct competitive orthographic units for a reversal letter: when the letter ‘b’ is activated, the letter ‘d’ is inhibited and vice versa. Furthermore, Soares et al. (2019) revealed that this mirror-letter interference effect is reliable for words containing left-oriented mirror-letters, such as ‘d’, but not for words containing right-oriented mirror-letters, such as ‘b’; and Soares et al. (2021) observed that this right-oriented bias was also present for words containing non-reversal letters.

Perea et al. (2011) showed that the mirror-letter effect operates differently for non-
reversal letters, defined as letters which do not have any valid letter representation for
their mirror counterpart (e.g., a, e, r, ...). In Experiment 2, they found that mirror primes
with a non-reversal letter produced a similar facilitatory effect to identity primes (arena-
ARENA vs. ákena-ARENA). Note, however, that a mirror-letter facilitatory effect for non-
reversal letters, which would suggest mirror invariance preservation for such letters, was
not definitively demonstrated given the null effect between control primes and mirror
primes (i.e., prime effect for ákena-ARENA was equivalent for ákena-ARENA).

The existence of a mirror-letter facilitatory effect for non-reversal letters was first
demonstrated by Duñabeitia et al. (2011) in an EEG study using masked priming (with
primes and targets in lowercase) in a go/no go semantic categorization task. In
Experiment 1, with four out of nine internal non-reversal mirror-letters, they showed that
identity primes and mirror primes induced the same electrophysiological response on the
N250 component, which is known to be an index of orthographic similarity (Grainger &
Holcomb, 2009). In Experiment 2, to attenuate visually overlapping features of the two strings, a mirror rotation of the whole target word on the vertical axis was used (leading also to invert letter-positions). The same pattern of results as in Experiment 1 was found. Using a same-different masked priming paradigm, Winskel and Perea (2018) studied the mirror invariance effect in Roman script with mirror letters and Thai script without mirror letters. Mirror primes were constructed by the mirror rotation on the vertical axis of the two internal non-reversal letters in four-letter words. For English readers, there was a facilitatory effect of the mirror prime in comparison to the control-mirror prime (-23 ms) but the mirror prime was not as facilitatory as the identity prime (-39 ms). For Thai readers, there was a similar facilitatory effect of both the mirror prime (-18 ms) and the identity prime (-22 ms) in comparison to the control-mirror prime. Consequently, and without needing to unlearn mirror letters, the Thais were more likely to perceive mirror letters as similar to identical letters than the English readers.

In sum, there is evidence for a mirror-letter inhibitory effect for reversal letters in orthographic processing, and for a mirror-letter facilitatory effect for non-reversal letters, suggesting that, contrary to Dehaene et al. (2005, 2010), mirror invariance is not fully inhibited or unlearned during word recognition. Considering the mirror-letter facilitatory effect, which is at the core of the present paper, note that Duñabeitia et al. (2011) found an equal priming effect for identity primes and mirror primes on N250, in the same way as in Perea et al.'s (2011) Experiment 2; whereas Winskel and Perea (2018) found a graded effect. No behavioral data were reported by Duñabeitia et al. (2011).

Thus, further investigations are required to demonstrate that the mirror-letter facilitatory effect for non-reversal letters originates in the fast automatic orthographic stage, and that mirror invariance preservation, if it exists, is achieved at the level of abstract letter representations. To focus on letter processing only, we limit our study to mirror letters, leaving aside whole word rotation as reported in Experiment 2 of Duñabeitia et al. (2011).

In Experiment 1, we attempt to demonstrate a mirror-letter facilitatory effect for non-reversal letters using the classical masked priming paradigm in a lexical decision task in order to better study the prelexical processes involved in visual word recognition, which operates at the level of abstract letter identities. Three priming conditions with non-reversal letters were used: (1) prime which was identical to target (triste-TRISTE), (2) mirror prime based on mirror rotation of each letter on the vertical axis (triste-TRISTE),
(3) control prime composed of digits (123456-TRISTE). To investigate letter-identity coding specifically, we chose a letter-by-letter rotation rather than a whole-word rotation, thus avoiding confounds with letter-order coding. Moreover, we decided to rotate all the letters contained in the word rather than only internal letters, unlike in Duñabeitia et al. (2011, exp. 2) and Perea et al. (2011). This manipulation therefore allowed us to counteract possible confounds arising from the differential visibility of the letters resulting from their position in the string (Marzouki & Grainger, 2014; Scaltritti & Balota, 2013). Hence, if mirror invariance operates for non-reversal letters at the level of orthographic processing, letter identification should be preserved. Consequently, shorter reaction times should be obtained in the mirror condition than the control condition. Lexical frequency (i.e., high- vs. low-frequency words) was also manipulated to provide information about the temporality of this effect, assuming that orthographic processing and lexical access are partially ordered. According to the additive factors method (Sternberg, 1969, 2011), if two factors act at different stages of processing then no interaction should be observed between these factors. If the opposite is true then these factors interact. Thus, if mirror invariance occurs during orthographic prelexical processing, then the Priming factor should not interact with the Lexical Frequency factor, which is known to occur at later processing stage.

**2. Experiment 1: Classical masked priming paradigm**

**2.1. Method**

**2.1.1. Participants**

Fifty-four students (40 females) from Lyon University, ranging in age between 18 and 33 years (mean age = 21.6 years old; SD = 2.8), gave informed consent to participate in this study. Participants were tested individually in a quiet room and reported being non-dyslexic, French native speakers, and having normal or corrected-to-normal vision.

**2.1.2. Design and Stimuli**

There were three priming conditions: (1) identical primes (identity condition), (2) mirror primes constructed using the letter-by-letter mirror rotation (mirror condition), (3)
control primes involving an ordered sequence of numbers of the length of the target word (control condition).

One hundred and eight words were selected from the Manulex database (Lété et al., 2004). The word length was between 4 and 6 letters (mean = 5.00; SD = 0.82). None of these words contained mirror letters (b, d, p, q) or diacritics. The number of symmetrical lowercase letters (i.e., i, j, l, m, n, o, u, v, w, x, y) was minimized (mean symmetrical letters per word = 1.09; SD = 0.29). The set included infinitive verbs, adjectives, participles, pronouns, adverbs and auxiliaries. Half of these words were of low frequency (mean word frequency per million = 1.88, mean Zipf value = 2.76; according to van Heuven et al., 2014) and the other half were of high frequency (mean word frequency per million = 94.30, mean Zipf value = 4.73). For the purposes of the lexical decision task, a set of 108 pseudowords was constructed based on existing words from the lexicon in which one to three letters were replaced.

### 2.1.3 Procedure

The experimental procedure was implemented with DMDX (Forster & Forster, 2003). Stimuli were presented on a Fujitsu Siemens 9400 monitor calibrated to 14-inch (1280x800 px). Stimuli were presented as white letters centered vertically and horizontally on a black background. Each trial started with a 500 ms centralized forward mask. The prime was then presented in lowercase (size: 12pt, font: Arial except for mirror primes, which were displayed in PRMirror) for a duration of 48 ms. The prime was immediately followed by the target, which was displayed until the participant's response or for a maximum of 3000 ms. All targets were displayed in uppercase, Arial font 12pt (see Figure 1 for a typical trial).

Participants were seated at a distance of 60 cm from the screen. Their task was to decide whether or not the target was a French word by pressing the “Right Shift” key when the target was a word or the “Left Shift” key otherwise (or the "Left Shift" and "Right Shift" keys, respectively, if the participant was left-handed).

Using a Latin-square design, all items (i.e., both words and pseudowords) were presented in all priming conditions, but only once per participant. Three lists were constructed to ensure a counterbalanced presentation. The set of 216 items was divided into 9 blocks of 24 trials each. Items within blocks and blocks within lists were presented in a randomized
order for each participant. To avoid fatigue, a break was offered between each block. The total duration of the task was about 15 minutes.

<figure><img src="image_2.png" /></figure>

<table><thead><tr><th colspan="3">Experiment 1 and Experiment 2</th></tr><tr><th>condition</th><th>prime</th><th>target</th></tr></thead><tbody><tr><td>identity</td><td>triste</td><td>TRISTE</td></tr><tr><td>mirror</td><td>histe</td><td>TRISTE</td></tr><tr><td>control</td><td>123456</td><td>TRISTE</td></tr></tbody></table>

<table><caption>Figure 1. (A) Schematic representation of the classic masked priming method used in Experiment 1-a. (B) Schematic representation of the sandwich masked procedure used in Experiment 1-b and Experiment 2. (C) Example of items used in Experiment 1 and Experiment 2.</caption><thead><tr><th colspan="3">Experiment 3</th></tr><tr><th>condition</th><th>prime</th><th>target</th></tr></thead><tbody><tr><td>identity</td><td>triste</td><td>TRISTE</td></tr><tr><td>mirror</td><td>histe</td><td>TRISTE</td></tr><tr><td>control</td><td>trist</td><td>TRISTE</td></tr></tbody></table>

## 2.2. Results

The dataset retained for analysis consisted of 972 observations per condition. RTs and accuracy data were analyzed using linear mixed effects and generalized linear mixed effects (lme4 package in R; Bates, Maechler, Bolker, & Walker, 2015). For RTs, the - 1,000/RT transformation was used. The LME analyses were conducted using Frequency (high frequency vs. low frequency) and Type of prime (mirror vs. control vs. identity) as fixed factors. For each model, the maximal random structure model that successfully converged was used. We tested overall effects using Type III sum of squares and χ² Wald tests. Post-hoc contrasts were calculated using the emmeans package (Lenth, 2019). Full model outputs are given in Supplemental material. Mean RTs per condition are presented in Table 1.
<table><caption>Table 1. Mean response times (in ms) and standard errors (in parentheses) for each experimental condition in Experiment 1.</caption><thead><tr><th rowspan="2">Prime condition</th><th colspan="2">Target Frequency</th></tr><tr><th>High frequency</th><th>Low frequency</th></tr></thead><tbody><tr><td>identity</td><td>595 (10)</td><td>700 (15)</td></tr><tr><td>mirror</td><td>627 (12)</td><td>723 (14)</td></tr><tr><td>control</td><td>623 (9)</td><td>741 (15)</td></tr><tr><td>identity - mirror contrast</td><td><strong>-32*</strong></td><td><strong>-23*</strong></td></tr><tr><td>mirror - control contrast</td><td>+3</td><td>-18</td></tr></tbody></table>

Note : * *p* < .001 for main effect in the complementary restricted LME analysis conducted for both control vs. identity and control vs. mirror contrasts independently for high-frequency and low-frequency words.

### 2.2.1. RTs

Only the data for words were analyzed. Four items with overall accuracy below 50% were excluded. Incorrect responses (7.26%) and correct responses with RTs less than 300 ms (0.08%) were first excluded from the analyses. Then, trials with outliers, defined as RTs more than 2.5 SD above or below the participant's mean, were excluded (2.94% of the correct answers).

The analysis of RTs showed a significant main effect of Frequency ($\chi^2 = 126.53, t = 11.25, p < .001$): RTs were shorter for high-frequency than for low-frequency words ($\Delta RT = 106$ ms). There was also a main effect of Type of prime ($\chi^2 = 50.69, p < .001$): RTs for identity primes were significantly faster than for mirror primes ($\Delta RT = 27$ ms, $z = 6.26, p < .001$) or for control primes ($\Delta RT = 34$ ms, $z = 6.47, p < .001$) and there was no significant difference between RTs for mirror and control primes ($\Delta RT = 7$ ms, $z = 1.21, p = .45$). In addition, the interaction between Frequency and Type of Prime was non-significant ($\chi^2 = 1.56, p = 0.46$).

### 2.2.2. Accuracy

The analyses of the accuracy data showed a significant main effect of Frequency ($\chi^2 = 46.50, z = 6.82, p < .001$) with higher error rates for low-frequency words than for high-frequency words ($\Delta ER = 10.50\%$). There was a non-significant main effect of Type of Prime ($\chi^2 = 1.41, p = .49$). In addition, the interaction between Frequency and Type of Prime was non-significant ($\chi^2 = 1.32, p = .52$).
## 2.3. Discussion

In Experiment 1, we conducted a classical masked priming lexical decision task. Results revealed that identity primes produced shorter RTs compared to control and mirror primes, which did not differ. Thus, the use of the classical masked priming paradigm in the present study failed to reveal a significant mirror priming effect for non-reversal letters. These results conflict with previous behavioral (Winskel & Perea, 2018) and electrophysiological (Duñabeitia et al., 2011) results indicating such an effect.

One way to reconcile these results is to examine the nature of the tasks that were used. In our experiment, we used the well-known lexical decision task combined with the classical version of the masked priming paradigm. In recent decades, this combination has proven to be very useful for revealing a wide range of orthographic effects (for a review, see Grainger, 2008). Nevertheless, as pointed out by Kinoshita and Norris (2012), this task primarily reflects lexical priming. According to this view, small orthographic effects produced by mirror-letter primes (Davis & Lupker, 2017) or superset primes (Lupker et al., 2020) could be drowned out by lexical competition occurring during the decision stage. This could explain why no mirror priming effect was observed in Experiment 1.

In addition, lexical access is not required in order to perform the comparison between the reference and the target in the same-different matching task. Hence, Kinoshita and Norris (2012) argue that this task is insensitive to lexical competition and is more likely to reveal a clearer measure of orthographic effect. This could explain why Winskel and Perea (2018) succeeded in revealing a mirror priming effect for non-reversal letters.

If these assumptions are correct, an alternative paradigm aimed at reducing the lexical competition in the lexical decision task could allow a mirror priming effect for non-reversal letters to emerge. This is possible thanks to the sandwich priming paradigm proposed by Lupker and Davis (2009).

## 3. Experiment 2: Sandwich priming

As noted above, the classical version of the masked priming paradigm combined with a lexical decision task has limited sensitivity, especially when primes and targets are moderately similar. For example, Grainger (2008) highlighted that priming effects
obtained by contrasting double substitution primes (e.g., galpen-GARDEN) with
completely unrelated primes (e.g, tolpam-GARDEN) are generally not robust. This could
be explained by the fact that during the course of visual word recognition, the prime does
not activate only the target unit but also neighboring orthographic units which compete
via lateral inhibitory connections (see McClelland & Rumelhard, 1981, for a model; and
Davis & Lupker, 2006; Segui & Grainger, 1990, Massol et al., 2010, for empirical evidence).
Thus, the observed priming effects consist of a combination of bottom-up support for the
target unit (i.e., facilitation) and influences from activated neighboring orthographic units
(i.e., inhibition). The advantage of the sandwich masked priming method proposed by
Lupker and Davis (2009) is that it reduces the weight of the inhibition process by
reinforcing that of the facilitation process (i.e. the weight of target unit activation). Lupker
and Davis (2009) proposed incorporating an additional 33-ms presentation of the target
immediately prior to the prime, which is now sandwiched between the two presentations
of the target. Hence, the first presentation of the target provides an initial boost to the
activation of the target unit which makes it possible to counteract the inhibition process
arising from activated neighboring orthographic units. This methodological procedure
has been proved to be useful for revealing small orthographic priming effects, both at the
behavioral (Davis & Lupker, 2017; Lupker et al., 2020; Ziegler et al, 2014) and
electrophysiological levels (Ktori et al., 2012). Therefore, in Experiment 2, we replicated
Experiment 1 using the sandwich masked priming method in order to better detect a
mirror priming effect for non-reversal letters.

**3.1. Method**

3.1.1. *Participants*

Fifty-four students (32 females) from Lyon University, ranging in age between 18 and 33 years (mean age = 22.6 years old; SD = 3.0), gave informed consent to participate in this study. Participants were tested individually in a quiet room and reported being non-dyslexic, French native speakers, and having normal or corrected-to-normal vision.

3.1.2. *Design and Stimuli*

The primes, targets, experimental design, and computer equipment were the same as in
Experiment 1.
### 3.1.3 Procedure

There was only one procedural difference between Experiments 1 and 2. In the latter, the target word itself was presented in uppercase for 33 ms in each trial immediately following the forward mask and immediately prior to the prime according to Lupker and Davis's procedure (Lupker et Davis, 2009).

## 3.2. Results

The dataset retained for analysis consisted of 972 observations per condition. RTs and accuracy data were fitted using the same procedure as described in Experiment 1a. Mean RTs per condition are presented in Table 2.

<table><caption>Table 2. Mean response times (in ms) and standard errors (in parentheses) for each experimental condition in Experiment 2.</caption><thead><tr><th rowspan="2">Prime condition</th><th colspan="2">Target Frequency</th></tr><tr><th>High frequency</th><th>Low frequency</th></tr></thead><tbody><tr><td>identity</td><td>553 (9)</td><td>628 (13)</td></tr><tr><td>mirror</td><td>570 (9)</td><td>662 (14)</td></tr><tr><td>control</td><td>596 (10)</td><td>670 (15)</td></tr><tr><td>identity - mirror contrast</td><td>-17*</td><td>-34*</td></tr><tr><td>mirror - control contrast</td><td>-26*</td><td>-8</td></tr></tbody></table>

Note : * *p* < .001 for main effect in complementary restricted LME analysis conducted for both control vs. identity and control vs. mirror contrasts independently for high-frequency and low-frequency words.

### 3.2.1. RTs

Only the data for words were analyzed. Six items with overall accuracy below 50% were excluded. Incorrect responses (8.39%) and correct responses with RTs less than 300 ms (0 observation) were first excluded from the analyses. Then, trials with outliers, defined as RTs more than 2.5 SD above or below the participant's mean, were deleted (2.85% of the correct answers).

The analysis of RTs showed a significant main effect of Frequency ($\chi^2$ = 82.25, *t* = 9.07, *p* < .001): RTs were shorter for high-frequency words than for low-frequency words ($\Delta$RT = 80 ms). There was also a main effect of Type of Prime ($\chi^2$ = 129.06, *p* < .001): RTs for identity primes were significantly faster than for mirror primes ($\Delta$RT = 25 ms, *z* = 6.07,
$p < .001$) or for control primes ($\Delta RT = 42$ ms, $z = 11.21$, $p < .001$) and, contrary to Experiment 1, there was a significant difference between RTs for mirror and control primes ($\Delta RT = 17$ ms, $z = 4.08$, $p < .001$). Moreover, the interaction between Frequency and Type of Prime was significant ($\chi^2 = 8.83$, $p < .05$): the difference between mirror and control primes was only significant for high-frequency words ($\Delta RT = 26$ ms, $z = 5.24$, $p < .001$) but not for low-frequency words ($\Delta RT = 8$ ms, $z = .88$, $p = .66$).

### 3.2.2. Accuracy

The analyses of the accuracy data showed a significant main effect of Frequency ($\chi^2 = 44.23$, $z = 6.65$, $p < .001$), with higher error rates for low-frequency than for high-frequency words ($\Delta ER = 12.10\%$). There was a significant main effect of Type of Prime ($\chi^2 = 7.24$, $p < .05$): identity primes elicited lower error rates than mirror primes ($\Delta ER = 2.30\%$, $z = 2.69$, $p < .05$) and no other contrasts reached significance (all $p > .05$). In addition, the interaction between Frequency and Type of Prime was non-significant ($\chi^2 < 1$).

## 3.3. Discussion

The aim of Experiment 2 was to extend Experiment 1 by using the sandwich masked priming paradigm. The prior presentation of the target is thought to provide an initial boost to the activation of the target unit, thus counteracting the inhibition process arising from activated neighboring orthographic units. Without any modification of the experimental stimuli, results showed that the sandwich masked priming paradigm produced a graded mirror priming effect for non-reversal letters which, however, was limited to high-frequency words.

We hypothesized that if mirror invariance occurs during orthographic prelexical processing, then priming should not interact with lexical frequency, which is known to occur at a later processing stage. The fact that the mirror priming effect was restricted to high-frequency words could be due to the more informative nature of their primes carrying by the symmetrical letters compared to those of low-frequency words. Indeed, the non-reversal letter type is not a uniform category. Non-reversal letters can be symmetrical (such as i, l, m, etc.) or not (such as a, e, s, etc.). Symmetrical letters are characterized by the fact that they have identical mirror and canonical images. In our
material, the number of symmetrical letters was minimized and did not differ between
high- and low-frequency words. However, the orthographic processing system can be able
to extract enough information from the symmetrical letters, thus producing the observed
mirror priming effect only for the high-frequency words because these need less
activation than low-frequency words. Another reason why this mirror priming effect was
restricted to high-frequency words could be associated with the higher error rates for
low-frequency words (20.8%) than for high-frequency words (2.7%) which led to the
removal of a certain amount of data. Taken together with the extra time required to
retrieve low-frequency words, this may have led to the disappearance of the priming
effect on RTs.

Furthermore, one can argue that the use of digits in the control condition might be
debatable even though they provide absolutely no orthographic information about the
letters in the target. Indeed, the way digits and letters are processed by the orthographic
processing system seems to differ. For example, Duñabeitia et al. (2012) and Massol et al.
(2013) found that the transposed-character effect was more robust for letters than for
digits. At the neuronal level, Hannagan et al. (2015) showed that the encoding of letters
and digits could be underpinned by close but distinct neural regions. Thus, control primes
consisting of mirror letters might be a more suitable way of adequately comparing the
same mechanisms engaged in target processing for each priming condition.

In Experiment 3, we retained the sandwich masked priming procedure since the results
of Experiment 2 showed its relevance for revealing a mirror priming effect for non-
reversal letters. However, we used a new set of material with control primes consisting of
letter strings.

**4. Experiment 3**

**4.1. Method**

4.1.1. Participants

Sixty students (36 females) from Lyon University, ranging in age between 18 and 30 years (mean age = 21.1 years old; SD = 2.2), gave informed consent to participate in this study. Participants were tested individually in a quiet room and reported being non-dyslexic, French native speakers, and having normal or corrected-to-normal vision.
4.1.2. *Design and Stimuli*

There were three priming conditions. Identical primes and Mirror primes were based on the design used in the preceding experiment. To rule out the previously indicated limitations of the control condition in Experiments 1 and 2, digit string primes were replaced by letter string primes. Control primes were constructed based on their associated target word by replacing non-symmetrical letters by different-consonant letters. An additional constraint was that two adjacent replaced consonants could not have the same identity. Finally, to avoid an artificial mirror priming effect, the putative informativeness of symmetrical letters was maintained across priming conditions by keeping the symmetrical letters at the same position in the control primes (e.g., control: **étienne**, mirror: **gauche**, identity: **gauche** for target **GAUCHE**). In sum, with these constraints imposed for the control primes, any mirror-priming effect could only be due to the orthographic information conveyed by the mirror letters.

To increase the statistical power of Experiment 3 compared to Experiments 1 and 2, 306 words (instead of 108) were selected from the Manulex database (Lété et al., 2004). The set included verbs, adjectives, participles, pronouns, adverbs and auxiliaries. One hundred and fifty-three were low-frequency words (mean word frequency per million = 117.44, mean ZipF value = 4.87) and 153 were high-frequency words (mean word frequency per million = 3.20, mean ZipF value = 3.38). Word length was between 5 and 7 letters. None of these words contained mirror letters (b, d, p, q) or diacritics. The number of symmetrical lowercase letters (i.e., i, j, l, m, n, o, u, v, w, x, y) was minimized so that the words contained a maximum of two symmetrical letters (mean symmetrical letters per word = 1.42; SD = 0.63). To reduce the error rate observed in Experiments 1 and 2, we ensured that the selected words did not induce too many errors, based on the data provided by the French Lexicon Project (Ferrand et al., 2010). The results showed that the selected words had error rates of less than 20%<fnref n="1" />. Based on the *French Lexicon Project*, we selected a set of 306 pseudowords with error rates lower than 10% and a matched orthographic similarity with words (mean word OLD20 = 1.86, SD = 0.36 and mean pseudo-word OLD20 = 1.83, SD = 0.24) obtained using the *vwr R package* (Keuleers, 2013) based on the old20 measure reported by Yarkoni et al. (2008). Pseudowords were also matched with words in terms of the absence of reversible letters, the minimization of

<footnote n="1">¹ Except for seven selected words which were not included in the French Lexicon Project.</footnote>
symmetrical letters and their length. The lexical characteristics of the material are listed in Table 3.

<table><caption>Table 3. Means and SDs (in parentheses) for lexical characteristics of stimuli for the three experiments</caption><thead><tr><th rowspan="2">Lexical<br>Characteristics</th><th colspan="3">Experiment 1 and Experiment 2</th><th colspan="3">Experiment 3</th></tr><tr><th>Low-<br>frequency<br>word</th><th>High-<br>frequency<br>word</th><th>Pseudoword</th><th>Low-<br>frequency<br>word</th><th>High-<br>frequency<br>word</th><th>Pseudoword</th></tr></thead><tbody><tr><td>Word length</td><td>5.00<br>(0.82)</td><td>5.00<br>(0.82)</td><td>5.00<br>(0.82)</td><td>6.00<br>(0.82)</td><td>6.00<br>(0.82)</td><td>6.00<br>(0.82)</td></tr><tr><td>Lexical<br>frequency</td><td>3.00<br>(4.29)</td><td>94.30<br>(97.08)</td><td>-</td><td>3.20<br>(1.65)</td><td>117.44<br>(193.64)</td><td>-</td></tr><tr><td>Old 20</td><td>1.88<br>(0.35)</td><td>1.62<br>(0.28)</td><td>1.93<br>(0.39)</td><td>1.93<br>(0.32)</td><td>1.79<br>(0.39)</td><td>1.83<br>(0.24)</td></tr><tr><td>Number of<br>symmetrical<br>letters</td><td>1.15<br>(0.41)</td><td>1.04<br>(0.19)</td><td>1.09<br>(0.29)</td><td>1.50<br>(0.57)</td><td>1.35<br>(0.68)</td><td>1.42<br>(0.63)</td></tr></tbody></table>

### 4.1.3 Procedure

Computer equipment and experimental procedure were the same as in Experiment 2. A Latin-square design with three lists was used to ensure that all items (i.e., both words and pseudowords) were presented in the three priming conditions, but only once per participant. The set of 612 items were divided into 17 blocks of 36 trials. Items within blocks and blocks within list were presented in a randomized order for each participant. The total duration of the task was about 25 minutes.

### 4.2. Results

The dataset retained for analysis consisted of 3,060 observations per condition. RTs and accuracy data were fitted using the same procedure as described in Experiments 1 and 2. Mean RTs per condition are presented in Table 4.

<caption>Table 4. Mean response times (in ms) and standard errors (in parentheses) for each experimental condition in Experiment 3.</caption>
<table><thead><tr><th rowspan="2">Prime condition</th><th colspan="2">Target Frequency</th></tr><tr><th>High frequency</th><th>Low frequency</th></tr></thead><tbody><tr><td>identity</td><td>576 (12)</td><td>648 (14)</td></tr><tr><td>mirror</td><td>597 (12)</td><td>668 (15)</td></tr><tr><td>control</td><td>616 (12)</td><td>686 (14)</td></tr><tr><td>identity - mirror contrast</td><td>-21*</td><td>-20*</td></tr><tr><td>mirror - control contrast</td><td>-19*</td><td>-18*</td></tr></tbody></table>

Note : * *p* < .001 for main effect in complementary restricted LME analysis conducted for both control vs. identity and control vs. mirror contrasts independently for high-frequency and low-frequency words.

### 4.2.1. RTs

Only the data for words were analyzed. Incorrect responses (4.97% for word targets) and correct responses with RTs less than 300 ms (0.14%) were first excluded from the analyses. Then, trials with outliers, defined as RTs more than 2.5 SD above or below the participant's mean, were excluded (2.70% of the correct answers).

The analysis of RTs showed a significant main effect of Frequency ($\chi^2 = 183.05, t = 13.53, p < .001$): RTs were shorter for high-frequency than for low-frequency words ($\Delta RT = 71$ ms). There was also a main effect of Type of Prime ($\chi^2 = 179.18, p < .001$): RTs for identity primes were significantly faster than for mirror primes ($\Delta RT = 22$ ms, $z = 7.52, p < .001$) or for control primes ($\Delta RT = 40$ ms, $z = 13.35, p < .001$) and, critically, there was a significant difference between RTs for mirror and control primes ($\Delta RT = 18$ ms, $z = 8.32, p < .001$). In addition, the interaction between Frequency and Type of Prime was non-significant ($\chi^2 = 2.64, p = .27$).

### 4.2.2. Accuracy

The analyses of the accuracy data showed a significant main effect of Frequency ($\chi^2 = 101.77, z = 10.08, p < .001$), with higher error rates for low-frequency than for high-frequency words ($\Delta ER = 12.10\%$). There was significant main effect of Type of Prime ($\chi^2 = 9.33, p < .01$): control primes elicited lower error rates than identity primes ($\Delta ER = 0.96\%$, $z = 3.05, p < .05$) and no other contrasts reached significance (all $p > .10$). In addition, the interaction between Frequency and Type of Prime was non-significant ($\chi^2 = 1.03, p = .60$).
## 4.3. Discussion

In Experiment 3, we used the sandwich masked priming method already used in Experiment 2, and we paid careful attention to the control condition in order to preserve the informativeness of symmetrical letters across priming conditions. Results of Experiment 3 revealed a strong mirror priming effect for non-reversal letters, independently of lexical frequency. Moreover, confidence in the reliability of this effect is strengthened for several reasons. First, the total of 3,060 measurements per experimental condition exceeds the recommendation of Brysbaert and Stevens (2018) for ensuring strong statistical power (their recommendation being 1,600 measurements per condition). Second, the modification of the material made it possible to considerably reduce the error rate (5.0%) as compared to Experiments 1 and 2 (9.5% vs. 11.8%, respectively). Third, the modification of the control condition, undertaken in order to maintain the informativeness of symmetrical letters across priming conditions, ensured that the observed priming effect can be attributed solely to the elements that differ between the control and mirror conditions, namely the mirror letters.

## 5. General Discussion

The aim of the present research was to reconcile divergent results on the reliability of a mirror-letter facilitatory effect for non-reversal letters. In Experiment 1, using a classical masked priming paradigm, and in line with the previous non-significant results of Perea et al.'s (2011) Experiment 2, we failed to reveal a mirror priming effect. We argued that this failure could be due to the lack of sensitivity of the classical masked priming paradigm. To test this hypothesis, we conducted a second Experiment using the sandwich masked priming paradigm. Results showed a significant mirror priming effect for high-frequency words only. However, we acknowledged that some concerns could possibly limit the interpretation of these results, and more specifically the choice of the control condition. To address these concerns, we conducted a third experiment. We found a graded priming effect, with RTs for Identity primes < Mirror primes < Control primes. This pattern was in line with Winskel and Perea (2018), who found the same graded effect in English readers on RTs, but not with Duñabeita et al. (2011), who found Identity
primes = Mirror primes < Control primes on N250, and also not with Perea et al. (2011, Experiments 2 and 3), who found Identity primes < Mirror primes = Control primes on RTs. Additionally, our graded priming effect acted purely additively with Lexical Frequency. Overall, these results provide new evidence in support of a letter facilitatory effect for non-reversal letters.

However, given that a graded priming effect was found, it seems that complete mirror invariance preservation for such letters is not the most likely hypothesis. Alternative explanations of our findings are therefore discussed below. First, we examine how the priming paradigm constrains the mirror priming effect. Then, we discuss whether visual similarity between prime and target mirror-letters plays a role in the mirror priming effect for non-reversal letters. Finally, at a more theoretical level, we discuss how the mapping of mirror letters onto abstract letter representations can underlie the graded mirror-letter facilitatory priming effect.

*How does the priming paradigm constrain the mirror priming effect?*

The choice of the sandwich priming paradigm was motivated by the discrepancy between the absence of mirror priming with conventional masked priming (Experiment 2 of Perea et al., 2011) and the presence of such an effect in a masked prime same-different matching task (Winskel & Perea, 2018). Several studies have reported the same discrepancy between these two paradigms (Davis & Lupker, 2017; Lupker et al., 2020). The most common explanation refers to the contamination of response times in conventional masked priming when used in combination with the lexical decision task by the lexical competition which occurs during a post-orthographic stage. In contrast, the masked same-different matching paradigm is insensitive to this kind of contamination because the matching process between the reference word and the target does not require activation of lexical representations (Kinoshita & Norris, 2009; Norris & Kinoshita, 2008; but see Kelly et al., 2013). Therefore, the suppression of lexical competition would make it possible to render prelexical orthographic effects more salient. Unlike in Experiment 1, the sandwich masked priming method used in Experiments 2 and 3 permits us to address this issue. This reduction of the lexical competition was associated with a mirror priming effect in line with Winskel and Perea (2018) in a masked same-different matching paradigm. On the other hand, in Experiment 1, in which there was no control of the lexical
competition, the mirror priming effect was not significant, a finding which is consistent
with Perea et al. (2011).

While the explanation in terms of the reduction of lexical competition has generally been
favored over the others, Davis and Lupker (2017) concede “that the exact mechanisms
underlying sandwich priming are not fully understood”. One alternative explanation
suggested by these authors is that the priming effect could be generated by the activation
of a composite prime constituted by orthographic information from both the initial prime
(target) and the prime itself. For example, the brief presentation of the initial target might
make it possible to extract orthographic information only from the first three letters (e.g.,
gau??? for the target GAUCHE). Next, the orthographic information from the subsequent
prime is integrated to form a mixed prime (gauche) containing both canonical and mirror
orthographic information. The possibility that our mirror priming effect could be
obtained on the basis of such canonical orthographic information (gau***) cannot be
excluded and might explain why a graded effect was obtained. However, such an
assumption contradicts a general consensus according to which the presentation of a new
string of letters interrupts the processing of the previous one. Moreover, there is no doubt
that such a process would increase the activation of whole-word, lexical representations.
Assuming that orthographic processing and lexical access are partially ordered, the fact
that mirror priming and lexical frequency produce additive effects argues in favor of the
contribution of prelexical processes in the mirror priming effect and limits the role of a
global lexical activation.

*Does visual similarity between mirror-letter primes and targets play a role in the mirror priming effect?*

A second step in our discussion is to examine if visual similarity between mirror-letter
primes and targets can generate the graded priming effect.

Firstly, the mirror priming effect observed in Experiment 2 could be accounted for by the
close resemblance to letters of mirror primes as compared to control primes. Indeed, the
control primes were digit strings. Some evidence exists in favor of distinct processes for
digits and letter strings, at both the behavioral (Duñabeitia et al., 2012; Massol et al., 2013)
and neural levels (for a discussion, see Hannagan et al., 2015). Therefore, the mirror
priming effect in Experiment 2 could be due to the fact that mirror primes benefit from
their visual similarity with targets by pre-activating the letter-string processing network,
which cannot be pre-activated by digit-string control primes. To address these concerns,
we decided to design a third experiment in which we used letter strings as control primes
in order to rule out this alternative account.

Secondly, considering that “the most stable existing attractor for a mirror-letter will
undeniably be the correct letter, due to the high visual overlap between them”
(Duñabeitia et al., 2011), one can argue that the mirror effect in Experiment 3 was not
orthographic per se, but simply reflects the visual similarity between mirror primes and
targets, as compared to the visual similarity between control primes and targets.
However, these authors demonstrated that mirror priming was independent of the visual
similarity and modulated the N250 component, which is known to reflect prelexical
orthographic processing. They found a similar N250 effect for overlapping prime-target
pairs (**operação-operación**) and dissimilar prime-target pairs (**nuestro-cesta**). In our
three experiments, this concern was addressed by presenting the prime in lowercase and
the target in uppercase. This type of manipulation is common in masked priming
experiments to ensure that the observed priming effect can be attributed to the activation
of abstract letter representations by eliminating any influence due to a purely visual
overlap between the prime and the target.

Nevertheless, and thirdly, one can argue that many lower- and upper-case letters share
most of their features. Two types of letters can be distinguished: similar letters (e.g., c/C,
u/U) and dissimilar letters (e.g., a/A, e/E). Among similar letters, symmetrical letters (e.g.,
u/U) and non-symmetrical ones (e.g., c/C) can be distinguished.

On the one hand, the first critical point concerns the contribution of symmetrical letters
in the observed mirror priming effect. Mirror primes contain symmetrical letters which
have identical canonical and mirror representations. These symmetrical letters can
provide enough information to activate the representation of the target word. For
example, the target “GAUCHE” could be primed by the mirror prime (“psuche”) only on
the basis of the canonical letter (“**u**”) but not by the control prime “123456”, which
contains no valid orthographic information (“******”) to prime the target. If this is indeed
the case, mirror letter processing is unnecessary for explaining the mirror priming effect:
the priming effect could be solely attributable to the contribution of symmetrical letters.
Nevertheless, it seems unlikely that this account could explain the size of the observed
mirror priming effect. Firstly, this contribution should have been greater for frequent
words than for rare words, something which was not observed in our results. Secondly,
particular attention was paid to minimizing the number of symmetrical letters per word since each word contained at most 2 symmetrical letters. Moreover, in Experiment 3, symmetrical letters were maintained across the three priming conditions. Thus, control and mirror primes did not differ in terms of the symmetrical letters (e.g., mirror prime: **טנחי**, control prime: **לארחי**). Consequently, the priming effect could only be attributed to the non-shared information between these two primes, i.e., the correct mirror letters. On the other hand, even if symmetrical letters represent a large percentage of similar letters in the Latin alphabet (11/16), the remaining similar letters were not controlled (c, f, k, s, z). The latter do not share a strict visual overlap in the mirror condition (c/C). However, given that visual configurations are preserved in the lowercase mirror letters, these letters could act as a visual attractor for the uppercase letters of the target. In fact, some studies using an alphabetic decision task in a masked priming paradigm (e.g., Bowers et al., 1998; Jacobs & Grainger, 1991) have shown greater masked priming effects across lower- and uppercase versions of the same letter when they were visually similar (c-C) than when they were visually dissimilar (a-A) (for a synthesis, see Carreiras et al., 2012). To rule out this alternative explanation, we conducted a supplementary analysis on Experiment 3. If mirror letters are processed at an abstract level of letter representations, then the size of mirror priming should not differ when the number of visually similar letters in both the primes and targets differs. By contrast, if mirror priming is purely visual in nature, then the size of priming should be modulated by the number of visually similar letters.

In a supplementary analysis, we calculated, for each item, the priming difference between identity and mirror primes as well as between mirror and control primes. We then defined two Visual Similarity Measures (VSM) per item: The Wide VSM, i.e., Number of similar letters (including symmetrical letters) / length of the item; and the Restrained VSM, i.e., Number of similar letters (excluding symmetrical letters) / length of the item. Regression analyses were conducted for each combination of priming effect and the two VSM scores. None of these analyses revealed any significant modulation of the priming effect by the visual similarity of the letters (see Supplemental Analysis).

To sum up, visual similarity between prime and target mirror-letters seems to be unable on its own to fully explain the graded mirror priming effect. Leaving aside the role of overlapping visual information in the priming effect, we now consider the question of how
the mapping of mirror letters onto abstract letter representations can underlie the graded
mirror-letter facilitatory priming effect.

How to explain the graded mirror-letter facilitatory priming effect?

A first account, provided by the Local Combination Detector model of Dehaene et al. (2005), could explain how mirror letters can produce a graded facilitatory priming effect. In the LCD model, abstract letter representations are reached through a hierarchical activation of lower-level feature detectors. At the lowest level, these detectors simply respond to orientation features. Then, the combined activation of these detectors permits the activation of a higher-level detector which codes for letters in a specific case. Next, these specific-letter detectors send feedforward activation to higher-level detectors which respond to letters independently of case. This mechanism is used to code abstract representations for a large variety of letters with physical variations (size, font, etc.). As mentioned by Dehaene et al. (2005), the system is sufficiently flexible to identify letters whose canonical format has been distorted. In the case of mirror letters, the redundancy between mirror letters and their canonical format could be sufficient to at least partly activate the feature detector for the canonical letter and, in turn, activate the higher-level abstract letter representations. The priming effect could be graded as a result of this partial activation of detectors.

An alternative account, referred as regularization of letter-like character, is provided by
Carreiras et al. (2007). For the authors, the mapping of letters onto abstract letter
representations does not operate in a fully feedforward manner, unlike in the LCD model,
but is instead influenced by feedback activation of whole-word orthographic
representations. Their main idea is that in a task requiring access to abstract letter
representations, the system is tuned to regularized letter-like units. This could explain
Perea et al.'s (2008) results, in which the priming effect was similar for target words
(MATERIAL) when the prime was fully alphabetic (MATERIAL) compared to when it
contained letter-like numbers (M4T3R14L) ("1" regularized as "I", "2" as "S", ...). In our
study, the mirror-letter prime "6" would be regularized as "a". Moreover, considering that
this regularization process was only observed for words, Carreiras et al. (2007) proposed
that the mapping of letter-like representations onto abstract letter representations was
enabled by the activation provided by the whole-word orthographic representation, as
has been highlighted by electrophysiological data (Molinaro et al., 2010). This proposal
needs to be carefully considered here since the initial prime in the sandwich procedure
pre-activates a whole-word representation which could, in turn, reinforce the influence
of the regularization process. Thus, the mirror prime would be regularized (psuedo in
gauche) but partial regularization of letter-like character across primes would result in a
graded priming effect. By contrast, even if the control prime was regularized (אַל־תָּו in
tfutrk), no reliable information could be extracted to facilitate target processing.

These two alternative accounts providing clear, testable predictions. As Duñabeitia et al. (2013) proposed, future studies need to be performed to explore the exploitation of mirror information embedded in words as well as in pseudo-words. On the one hand, according to the LCD proposal, this should operate in the same way across words and pseudowords. On the other, the regularization proposal postulates that mirror information could only be extracted from words because pseudowords do not have a stored lexical representation which could permit feedback regularization. An extension of this proposal entails that the size of the mirror priming effect should be modulated by target frequency. Indeed, high-frequency words elicit higher activation than low-frequency words and this, in turn, impacts the strength of feedback. The additive effects observed in Experiment 3 run counter to this proposal. According to the additive factors method used by Sternberg (1969), an interaction between Frequency and Type of Prime would be expected if a regularization process operates. That was not the case. However, the exact way in which the mirror-letter information is exploited at an abstract representation level in the sandwich procedure remains to be clarified. The use of very-high temporal resolution techniques like electroencephalography could be a more suitable way of finding a clear response.

**6. Conclusion**

The present study makes it possible to reconcile the observed discrepancy in the
literature regarding the reliability of a mirror-letter facilitatory effect for non-reversal
letters. Results of Experiment 1 provided evidence in favor of the lack of sensitivity of the
conventional masked priming method to the mirror priming effect. In Experiments 2 and
3, we showed that the use of a method that is more sensitive to orthographic effects makes
it possible to reveal a mirror effect for non-reversal letters. The way in which mirror
letters activate abstract letter representations remains to be clarified. The use of a
technique with high temporal resolution is necessary to dissociate bottom-up and top-
down process which could compete during the identification of mirror letters.

Acknowledgment

We thank Florès d'Alès, Logan Bars, Clara Gasne, and I Chan Teng for their assistance in
data collection during their master's degrees. We are grateful to Jonathan Mirault for his
helpful comments on a previous draft of this manuscript, to Jana Hasenäcker for her
advice regarding statistical analyses, and to Tim Pownall for his assistance with English.

Declaration of conflicting interests

The author(s) declare that there are no potential conflicts of interest with respect to the
research, authorship, and/or publication this article.

Funding

This work was performed within the framework of the LABEX CORTEX (ANR-11-LABX-0042) of Université de Lyon, within the program "Investissements d'Avenir" (ANR-11-IDEX-0007) operated by the French National Research Agency (ANR). Brice Brossette was supported by a PhD scholarship from the *Ecole Normale Supérieure* (ENS) of Lyon.

Open practice

All data, materials, and code are available at
https://osf.io/4v9nj/?view_only=8df9504d1ff74fc59fcaa6d48dfb8927

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