Edited by: Andriy Myachykov, University of Glasgow, UK
Reviewed by: Lucy Jane MacGregor, Medical Research Council, UK; Kira Bailey, Iowa State University, USA
*Correspondence: Nicole Y. Y. Wicha, Department of Biology, University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249, USA. e-mail:
This article was submitted to Frontiers in Cognition, a specialty of Frontiers in Psychology.
This is an open-access article distributed under the terms of the
The color word Stroop effect in bilinguals is commonly half the magnitude when the written and naming languages are different (between) than when they are the same (within). This between-within language Stroop difference (BWLS) is likened to a response set effect, with greater response conflict for response relevant than irrelevant words. The nature of the BWLS was examined using a bilingual Stroop task. In a given block (Experiment 1), color congruent and incongruent words appeared in the naming language or not (single), or randomly in both languages (mixed). The BWLS effect was present for both balanced and unbalanced bilinguals, but only partially supported a response set explanation. As expected, color incongruent trials during single language blocks, lead to slower response times within than between languages. However, color congruent trials during mixed language blocks led to slower times between than within languages, indicating that response-irrelevant stimuli interfered with processing. In Experiment 2, to investigate the neural timing of the BWLS effect, event related potentials were recorded while balanced bilinguals named silently within and between languages. Replicating monolingual findings, an N450 effect was observed with larger negative amplitude for color incongruent than congruent trials (350–550 ms post-stimulus onset). This effect was equivalent within and between languages, indicating that color words from both languages created response conflict, contrary to a strict response set effect. A sustained negativity (SN) followed with larger amplitude for color incongruent than congruent trials, resolving earlier for between than within language Stroop. This effect shared timing (550–700 ms), but not morphology or scalp distribution with the commonly reported sustained potential. Finally, larger negative amplitude (200–350 ms) was observed between than within languages independent of color congruence. This negativity, likened to a no-go N2, may reflect processes of inhibitory control that facilitate the resolution of conflict at the SN, while the N450 reflects parallel processing of distracter words, independent of response set (or language). In sum, the BWLS reflects brain activity over time with contributions from language and color conflict at different points.
The Stroop effect has captivated researchers for over 75 years and has resulted in a vast (and daunting) body of literature. Versions of the Stroop paradigm have been used to study diverse cognitive phenomena, like selective attention, inhibition and executive control, conflict detection and monitoring, and automaticity and lexical access (see MacLeod,
The Stroop effect has commonly been explained as a response level conflict, by accounts like the relative speed of processing – where competition occurs strictly at response, in having to choose the color over the faster processed word – and automaticity of access – where faster spread of activation throughout a network of concepts, and inversely smaller attentional demands, occurs for more automatic processes, like reading than naming (see MacLeod,
The Stroop effect is modulated by factors unique to operating in a bilingual mode. There is even some evidence that bilinguals can perform better on the Stroop task compared to monolinguals (Bialystok et al.,
In addition, bilinguals experience different magnitude of Stroop interference based on the degree of overlap of the word forms across languages (Sumiya and Healy,
Under the accounts of the Stroop effect discussed above, which do not directly address the bilingual language system, it is clear how the proficiency of a language could affect the automaticity and/or speed of processing of the words in each language, but it is not clear how within language distracters elicit a significantly larger effect than between language distracters without further restrictions on the processors. This complexity is a result of bilinguals having two lexical representations for a single concept (“red” and “rojo” for concept RED Okuniewska,
Some contend that a mechanism of inhibition is required (Green,
A response set effect (or membership effect) is observed when distracter words that are actively used for responding on the task, e.g., GREEN, RED, YELLOW, BLUE, cause more interference (larger Stroop effect) than other color words that are not being actively used to respond, e.g., PINK (Klein,
This is the first study to use event related potentials (ERP) to address the source of the BWLS. In recent history, the debate over the source of Stroop interference, more generally, has been informed by electrophysiological techniques, which provide a way of experimentally disentangling semantic and response level effects. Scalp-recorded ERP, which have extraordinary temporal resolution (on the order of milliseconds), are especially well suited to investigate the timing of cognitive events. Early ERP studies of Stroop interference focused on the P300 –a component found to vary in latency with stimulus evaluation, but not response selection (Kutas et al.,
In fact robust Stroop effects have been observed later in time at the N450 (or medial frontal negativity – MFN) and the conflict sustained potential or SP (Rebai et al.,
The N450 precedes the SP as a medial fronto-central negativity between 300 and 500 ms post-stimulus onset. It is more negative in amplitude for color incongruent than color congruent stimuli, and increasing the degree of conflict increases N450 amplitude (West and Alain,
The N450 effect has been observed for both response and non-response type conflict on a counting task, suggesting that it might be sensitive to both incongruent but response eligible (i.e., response set) and incongruent but response ineligible items (West et al.,
Finally, response set (and the BWLS) may modulate earlier ERP components than the N450 and conflict SP, in particular the N2 (Folstein and Van Petten,
The current study used behavioral and electrophysiological measures to investigate how Spanish–English bilinguals process language and color congruence in a modified bilingual Stroop task across two experiments. Our central aims were to investigate (1) the unique contribution of language incongruence in the bilingual Stroop paradigm and (2) the temporal dynamics and neural correlates of cognitive control in balanced bilinguals while performing a bilingual Stroop task. In Experiment 1, we collected response time (RT) and error data across single and mixed language blocks to determine the pattern of within and between language effects for our sample (Spanish–English bilinguals) and to explore the possibility that balanced and unbalanced bilinguals use different strategies in mixed versus single language context to manage cross language interference. In Experiment 2, we collected ERP data using EEG to record brain activity while balanced bilinguals performed the single language blocks from Experiment 1 both overtly (for behavioral analysis) and covertly (for ERP analysis) to determine the source of the bilingual Stroop effect or BWLS.
The primary goal of Experiment 1 was to determine the pattern of within- and between language Stroop effects in our sample population of Spanish–English bilinguals. We manipulated several variables that had been tested separately in previous studies to attempt to create a complete picture within the same individuals. First, researchers have been inconsistent in their method of categorizing their study population, which may account for the variability in observing the BWLS across studies (e.g., Rosselli et al.,
Ninety-two Spanish–English bilinguals, recruited from the University of Texas at San Antonio (UTSA) and the University of Texas Health Science Center San Antonio (UTHSCSA) were paid for their participation. Data was excluded for 6 participants due to experimenter error or equipment failure and 12 participants as outliers (±2 SD from the mean) based on RT (4), accuracy (2), language dominance (4), or age
A total of 12 verbal fluency tests (VFT) were used to screen potential participants by phone; 1 min was given per test to name as many words as possible beginning with F, A, or S for English and P, T, or M for Spanish, or that fit into the categories of fruits, vegetables, or animals in each language. Proper names, repetition and variations of the same word were excluded; the number of remaining words were averaged for each language separately. Individuals with a minimum five-word average in the non-dominant language were subsequently tested on-site with a series of language measures. The 60-picture Boston naming test (BNT: Kaplan et al.,
Boston naming test scores and reading and naming times were used as objective productive-language measures to group participants as balanced (
Bilingual group | Balanced (BB) |
Unbalanced (UB) |
|
---|---|---|---|
Experiment | 1 | 2 | 1 |
Word-reading times (ms) | |||
English (BB)/dominant (UB) | 156.49 (92.20) | 135.74 (97.70) | 95.98 (50.92) |
Spanish (BB)/non-dominant (UB) | 140.06 (81.52) | 156.77 (92.89) | 143.47 (67.84) |
Difference | 16.43 (44.07) | 21.03 (63.51) | 47.48 (54.14)** |
Color-naming times (ms) | |||
English (BB)/dominant (UB) | 236.70 (83.97) | 247.98 (88.38) | 177.99 (60.50) |
Spanish (BB)/non-dominant (UB) | 221.66 (85.26) | 206.14 (87.27) | 251.71 (83.86) |
Difference | 15.04 (28.02)* | 41.84 (57.30)* | 73.71 (59.30)** |
Boston naming test (BNT) | |||
English (BB)/dominant (UB) | 44.67 (5.84) | 45.33 (5.89) | 48.64 (6.92) |
Spanish (BB)/non-dominant (UB) | 43.08 (8.10) | 43.13 (7.58) | 32.52 (11.45) |
Difference | 2.21 (9.43) | −1.04 (8.61) | 16.12 (15.09)** |
Verbal fluency test | |||
English (BB)/dominant (UB) | 13.36 (2.74) | 14.56 (3.55) | 14.92 (2.76) |
Spanish (BB)/non-dominant (UB) | 13.98 (3.27) | 14.79 (3.58 | 11.98 (2.91) |
Difference | −0.19 (2.53) | −1.10 (2.56) | 2.93 (3.30)** |
Percentage of daily use | |||
English (BB)/dominant (UB) | 54.38% (20.92) | 63.04% (19.53) | 61.76% (23.25) |
Spanish (BB)/non-dominant (UB) | 44.79% (21.34) | 36.96% (19.53) | 38.18% (23.21) |
Age of exposure | |||
English | 6.25 years (4.91) | 6.71 years (5.30) | 5.35 years (4.78) |
Spanish | 0.08 years (0.41) | 0.57 years (2.71) | 1.52 years (4.61) |
Perceived language ability (scale of 1–7) | |||
English (BB)/dominant (UB) | |||
Speaking | 6.29 (0.81) | 6.21 (1.02) | 6.74 (0.57) |
Comprehension | 6.50 (0.78) | 6.17 (1.13) | 6.76 (0.43) |
Reading | 6.42 (0.83) | 6.23 (1.18) | 6.76 (0.63) |
Writing | 6.25 (0.99) | 6.08 (0.93) | 6.60 (0.76) |
Spanish (BB)/non-dominant (UB) | |||
Speaking | 6.50 (0.78) | 6.42 (0.83) | 5.32 (1.25) |
Comprehension | 6.63 (0.71) | 6.50 (0.83) | 5.86 (1.16) |
Reading | 6.12 (1.36)† | 6.08 (1.50)† | 5.76 (1.29) |
Writing | 5.83 (1.52)† | 5.88 (1.48)† | 5.26 (1.40)† |
Qualified participants read and signed a consent form under the guidelines of UTSA’s and UTHSCSA’s Institutional Review Boards for Human Subject Research, after which they sat approximately 55′′ away from a 19′′ color CRT monitor and named the font color of capitalized centered half-inch tall color words (GREEN, BLUE, YELLOW, RED, VERDE, AZUL, AMARILLO, ROJO). Each color word appeared equally in each of the four font colors (green, blue, yellow, red). Stimuli were randomized and presented on a light gray background using E-Prime software (Psychological Software Tools, Inc., Pittsburgh, PA, USA). Each trial started with the presentation of three fixation crosses (“+++”; randomly 500–750 ms duration, with 200 ms blank screen ISI), followed by the stimulus (150 ms duration with 200 ms blank screen ISI; per Liotti et al.,
A total of 8 blocks were presented, consisting of 96 trials each (768 total trials). In each block, half of the words were color congruent (CC, e.g., “RED” written in red) and half were color incongruent (CI, e.g., “BLUE” written in red), see Table
Stimulus | Language congruent response (within language trails) | Language incongruent response (between language trials) | |
---|---|---|---|
English color congruent | RED | red | rojo |
English color incongruent | BLUE | red | rojo |
Spanish color congruent | ROJO | rojo | red |
Spanish color incongruent | AZUL | rojo | red |
Error trials and accurate RTs were analyzed for each group separately. RTs in milliseconds were measured from the onset of the visual word to detection of the voice response (Balanced Bilinguals,
The Color Congruence effect was observed both within and between languages (
Bilingual group | Balanced (BB) |
Unbalanced (UB) | |
---|---|---|---|
Experiment | 1 | 2 | 1 |
English (BB)/dominant language (UB) single language blocks | |||
Color congruent language congruent (CCLC) | 349.41 (96.95) | 321.90 (91.44) | 299.25 (113.92) |
Color incongruent language congruent (CILC) | 446.88 (102.94) | 409.25 (94.82) | 385.05 (112.77) |
Color congruent language incongruent (CCLI) | 331.66 (98.32) | 320.52 (102.94) | 347.88 (104.79) |
Color incongruent language incongruent (CILI) | 415.24 (121.57) | 388.76 (101.90) | 377.43 (105.95) |
English (BB)/dominant language (UB) mixed language blocks | |||
Color congruent language congruent (CCLC) | 336.46 (110.95) | 286.08 (101.93) | |
Color incongruent language congruent (CILC) | 438.25 (100.87) | 390.32 (114.71) | |
Color congruent language incongruent (CCLI) | 355.24 (101.56) | 312.45 (102.66) | |
Color incongruent language incongruent (CILI) | 435.91 (107.05) | 369.25 (108.78) | |
Spanish (BB)/non-dominant language (UB) single language blocks | |||
Color congruent language congruent (CCLC) | 318.22 (98.96) | 297.02 (105.57) | 320.67 (107.78) |
Color incongruent language congruent (CILC) | 405.88 (111.63) | 380.26 (101.11) | 424.50 (117.29) |
Color congruent language incongruent (CCLI) | 310.80 (107.27) | 285.16 (100.91) | 322.86 (103.08) |
Color incongruent language incongruent (CILI) | 391.86 (101.45) | 350.66 (100.29) | 406.98 (113.27) |
Spanish (BB)/non-dominant language (UB) mixed language blocks | |||
Color congruent language congruent (CCLC) | 312.25 (97.22) | 317.27 (105.28) | |
Color incongruent language congruent (CILC) | 420.02 (102.47) | 419.27 (116.78) | |
Color congruent language incongruent (CCLI) | 326.01 (91.33) | 337.79 (100.39) | |
Color incongruent language incongruent (CILI) | 415.47 (94.84) | 410.31 (112.08) |
Specifically, when color was congruent, language congruent trials were significantly
Finally, with regard to naming language, unbalanced bilinguals were faster overall when responding in their dominant than in their non-dominant language [
No other effects were significant.
Overall, balanced bilinguals made more errors on color incongruent than congruent trials [
There were no main effects of Naming Language or Block Type. These factors did, however, interact: Naming Language × Block Type,
There was no main effect of Block Type, and no interaction between Block Type and Color Congruence, or Block Type, Color Congruence, and Language Congruence, indicating that, contrary to unbalanced bilinguals, this within- versus between language difference on the color congruence effect was not larger during mixed- than single language presentation, Figure
However, similar to unbalanced bilinguals, a Block Type by Language Congruence interaction revealed a trend for faster naming times on language incongruent than congruent items [
Although the participants were considered balanced in their two languages based on performance on the language measures (see Table
The primary goal of Experiment 1 was to determine the pattern of within- and between language Stroop effects in our sample population of Spanish–English balanced and unbalanced bilinguals. In brief, we observed the classic Stroop effect, with longer RTs for color incongruent than congruent trials. This effect was observed both when the naming and reading languages were the same (within language) and when they were different (between language). In addition, we observed a larger Stroop effect within than between languages –the bilingual Stroop effect or BWLS, which was present across all conditions, regardless of group, block type or naming language (Figure
The pattern of Stroop effects was very similar for both groups of bilinguals. The primary difference between the groups was a larger Stroop effect for unbalanced bilinguals when naming in the non-dominant language – showing more cross language interference from reading the dominant than non-dominant language. Balanced bilinguals showed the same pattern in both languages. These findings are consistent with previous research (Dyer,
Bilingual word recognition models, such as BIA+ (Dijkstra et al.,
An alternative explanation for the slower naming times on mixed than single language trials could be a cost from switching languages from trial to trial, in line with the idea that a language switch reverses activation and inhibition patterns in the languages (e.g., BIA+ or Green Inhibitory control model; Jackson et al.,
Despite these group differences, the presence of a between language Stroop effect across all conditions (groups, blocks, naming language) indicates that the words from the non-target language consistently cause interference, in line with our bilinguals performing in a “bilingual mode” (Grosjean,
Figure
Second, if the BWLS is a response set effect then color incongruent items should be named slower for the response relevant than irrelevant language. This was true during single language presentation (Figures
In brief, the results from Experiment 1 indicate that both balanced and unbalanced bilinguals were unable to ignore the task-irrelevant language (Rodriguez-Fornells et al.,
Experiment 2 was designed to uncover the cognitive and neural correlates of the bilingual Stroop effect. To make this initial ERP analysis of the BWLS feasible, we chose to begin exploring this question with balanced bilinguals during single language presentation, given that language dominance in the unbalanced bilinguals played a role in both the language and color congruence effects, and to isolate the BWLS effect in the absence of any mixing effects. Future studies are planned to explore the nature of the mixing effect and the effect of language dominance on the ERP BWLS. Thus, ERPs were recorded while balanced bilinguals performed the single language bilingual Stroop task from Experiment 1, naming the colors of color words first overtly then covertly. RT and accuracy from overt naming trials and ERPs from covert naming trails are presented herein.
The monolingual ERP literature does not provide clear predictions for the ERP correlates of the BWLS, and often do not align with the debate over the source of the BWLS in the behavioral literature. However, we predicted that, consistent with the monolingual ERP Stroop literature, color congruence would modulate the N450 (Liotti et al.,
Participants were recruited from the UTSA and UTHSCSA general populations. Screening procedures were the same as for balanced bilinguals in Experiment 1 (see Table
The stimuli and paradigm were similar to Experiment 1 for the single language blocks only, with a few methodological changes. First, naming on the critical ERP trials was silent (covert). Second, two measures were used to ensure naming language and performance accuracy. An overt naming block preceded each covert naming block in the same language, and eight probe trials were included in the covert blocks. These trials were underlined color words cuing the participant to name that trial aloud. Third, the fixation cross that appeared after each word remained on the screen for 1000 ms before the onset of the next trial, see Figure
As in Experiment 1, the covert naming trials consisted of four single language blocks, two in Spanish and two in English (language order was randomized across subjects), for a total of 384 critical trials (equal number of randomly presented trials per condition and color in each block). An E-Prime coding error occurred that resulted in a loss of 4 trials of CCLI and 12 trials of CILI when naming in Spanish, thus, pairwise analyses of conditions were performed with trials collapsed across English and Spanish. For each language, 1 block was named in the same language as the written words (language congruent) and 1 block in the incongruent language.
Participants read and signed a consent form under the guidelines of the UTSA and UTHSCSA Institutional Review Board for Human Subject Research. Participants were fitted with EEG electrodes and sat in a sound attenuating, RF shielded chamber approximately 55′′ away from a 19′′ color CRT monitor. Participants were allowed to take breaks between blocks; no single break lasted longer than 5 min. The entire ERP session lasted approximately 2.5 h.
Continuous scalp-recorded EEG was acquired using a geodesic array of 26 pre-amplified sintered Ag–AgCl electrodes embedded in a custom electrode cap (Electro-Cap International Inc.). Additional electrodes were placed below and at the outer canthi of the left and right eyes to record blinks and eye movement respectively, and on the left and right mastoid processes to serve as offline reference. Preamplifiers in each electrode reduced induced noise between the electrode and the amplification/digitization system (BioSemi ActiveTwo, BioSemi B.V., Amsterdam), allowing high electrode impedances. Electrode offsets were kept below 40 mV. A first-order analog anti-aliasing filter with a half-power cutoff at 3.6 kHz was applied (see
Prefrontal channels were removed from analyses due to excessive artifacts restricted to those channels. The remaining 21 channels were processed using the following artifact rejection measures: maximum step of 75 μV/ms to capture voltage spikes, maximum amplitude difference of 150 μV/200 ms to capture signal drift, maximum amplitude of ±70 μV to capture blinks, and minimum amplitude difference of 0.5 μV/50 ms to capture flat lining and saccades. Only participants who retained 70% or more of the critical trials were included in the averages. The mean trials lost to artifact or error was 14.17%. Average waveforms were calculated for each condition time-locked to the onset of each word.
To determine the pattern of behavioral effects for the participants in Experiment 2, naming errors and RTs in milliseconds for the overt naming trails were analyzed using the same procedure as for balanced bilinguals in Experiment 1. As in Experiment 1, color incongruent trials elicited more errors than color congruent trials [
Similarly, slower naming times were observed for color incongruent than congruent trials, [
Naming accuracy on probe trials for the covert naming blocks was at 95.4%, indicating that participants were performing the task correctly. Because responses were covert, we were unable to remove trials with naming errors. However, previous studies have shown equivalent ERP patterns from covert and overt performance on a Stroop task, supporting the validity of this task (Liotti et al.,
Overall, the ERP to each word was characterized by early sensory components – N1 and P2 – followed by two successive biphasic negative–positive deflections, with negative peaks at approximately 300 and 530 ms post-stimulus onset (note that the N400 that typically occurs to words is presumably suppressed due to the extensive repetition of each item), see Figure
Mean amplitudes for each ERP component were subjected to repeated-measures ANOVAs with Naming Language (English, Spanish) × Color Congruence (congruent, incongruent) × Language Congruence (congruent, incongruent) × Electrode. Omnibus ANOVAs with 21 electrodes were used in each window, followed by ANOVAs including 16 electrodes for scalp distribution analyses, with factors of Hemisphere (left, right), Anteriority (frontal, central, occipital), and Laterality (medial, lateral). In addition, region of interest analyses were used as appropriate for each effect. Effects for repeated-measures with greater than one degree of freedom are reported after Greenhouse–Geisser correction; planned contrasts were Bonferroni adjusted for multiple comparisons.
Figure
The distributional analysis revealed a Language Congruence by Laterality interaction [
As expected, the omnibus ANOVA revealed a color-Stroop effect with a larger negativity for color incongruent than congruent trials, see Figure
The omnibus ANOVA revealed a color-Stroop effect with larger negativity for color incongruent than color congruent trials [Color Congruence,
The interaction between Color Congruence and Language Congruence trended toward significance,
The goal of Experiment 2 was to study the temporal dynamics, and the corresponding neural and cognitive correlates, of the bilingual Stroop. The findings have implications for explaining the Stroop effect, both for bilinguals and monolinguals. Our data speak to the suggestion that the bilingual Stroop effect reflects a response set effect. We discuss the implications of our findings after a brief summary.
A large N450 effect was observed for the color congruence manipulation, replicating monolingual findings. Color incongruent trials elicited larger negative amplitude than color congruent trials between 350 and 550 ms post-stimulus onset. This effect was the same within and between languages, indicating that the N450 was sensitive to color congruence regardless of whether the distracters were from the response set or not. Following the N450, there was an effect of color congruence with SN amplitude for color incongruent compared to congruent trials. This effect was observed in the same time window as the conflict SP (550–700 ms post-stimulus onset), but did not share the typical distribution reported in monolingual studies (a sustained positivity over central–parietal scalp sites that reverses in polarity over lateral frontal sites; West,
A majority of monolingual Stroop ERP studies suggests that the N450 reflects response conflict and the SP reflects both response and stimulus level conflict. In particular, based on Chen et al. (
Another characteristic of the N450 in this balanced bilingual sample is the broader distribution compared to monolinguals, which might reflect recruitment of additional neural substrates to process the dueling sources of interference (color and language) in the bilingual paradigm. There is growing evidence that bilinguals activate information in both of their languages even when using only one (Marian and Spivey,
The results also reveal that language membership information is processed prior to the N450 – specifically at the N2. The N2 is thought to be a complex of components that are functionally and distributionally distinct based on stimuli and task demands (for a review of N2 findings, see Folstein and Van Petten,
Instead, our data is most consistent with a third type of N2 effect. The direction and scalp distribution of the N2 effect in the current study (slight right-lateralization with a fronto-central maximum; c.f. Aron et al.,
The behavioral findings from Experiments 1 and 2 were consistent with the majority of the literature, showing a larger color word Stroop effect within language than between languages (MacLeod,
It is possible that the BWLS is purely due to the underlying processes reflected in the brief interaction at the late SN. Our data reflect a broadly distributed, SN, inline with earlier reports of ERP effects in a complex Stroop task (West and Alain,
In summary, data from two bilingual Stroop experiments aimed at uncovering the source of the well-documented bilingual Stroop effect – referred to herein as the between-within language Stroop effect or BWLS. Experiment 1 replicated the BWLS in both balanced and unbalanced bilinguals. This effect was present regardless of language dominance, and during both single language and mixed language presentation. However, by taking an unconventional look at the Stroop data, analyzing the effect of language congruence in the presence or absence of color-Stroop interference, we were able to show that the source of the BWLS varied based on these manipulations. In the process of thoroughly delineating the behavior of our population on the bilingual Stroop task, we were able to address the leading explanation for the BWLS. We show that a response set effect can only partially explain this effect. Experiment 2 delineated the time course and stage of processing at which the BWLS occurs using a real time electrophysiological measure. Our ERP data provide evidence that balanced bilinguals process language congruence prior to color congruence on a bilingual color word Stroop task, as indexed by a language effect at the N2. Importantly, distinguishing the distracters based on language did not affect later processes at the N450, indicating that color incongruent words created equal conflict and cognitive control demands regardless of whether they belonged to the response set or not. Rather than complete inhibition of the between language distracters, the N2 may reflect processes of inhibitory control that facilitate the resolution of conflict at the SN, while the N450 reflects parallel processing of the distracter words, regardless of response set (or language). In sum, the behavioral BWLS reflects summed brain activity over time, with contributions from language conflict and color conflict at different time points. Our findings add to a vast literature, informing models of both monolingual and bilingual conflict processing on the Stroop task, and present new questions for the field.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
We have many individuals to thank for advice and technical assistance on this project, including Ryan J. Giuliano, Amanda Martinez-Lincoln, Shukhan Ng, David Pillow, Elena Salillas, Mai-Anh Tran Ngoc, and especially Delia Kothmann Paskos who inspired this research study. Resources and support were provided by the Computational Biology Initiative. Funding was provided by NICHD/NIGMH HD060435 and the UTSA College of Science to N. Y. Y. Wicha.
1Participants excluded for age were done so based on findings that indicate Stroop performance declines after age 55 (Jolles et al.,
2Performance on the VFT and BNT were highly correlated [
3One participant was included as balanced having scored as English dominant on one measure, Spanish dominant on another and balanced on the third, resulting in no clearly dominant language. This participant tested as balanced on two of the three measures upon retesting the naming and reading time measures for participation in Experiment 2. This occurred with other participants as well, who switched from dominant in one language to balanced in both, or vice versa, on a specific measure. This highlights the dynamic nature of bilinguals over time, and the importance of collecting more than one measure of language proficiency/dominance, in particular when classifying individuals as balanced.
4Balanced bilinguals as a group (but not all individuals) were faster at naming colors in Spanish than English on the baseline color-naming task, paired samples
5Our color-naming baseline produced faster naming times than all other trials. Future studies could employ an improved neutral baseline to determine if this difference is facilitatory for within language or inhibitory for between language trials.
6The average reference and average mastoid reference have shown equivalent results in previous studies (see Chen et al.,
7Complex interactions with Naming Language in the distribution analysis could be explained by the loss of trials in Spanish (see Methods) and were not analyzed further.