TY - JOUR
AU - Oei,, Adam
AB - Abstract Objectives Experience-related neuroplasticity suggests that bilinguals who actively manage their two languages would develop more efficient neural organization at brain regions related to language control, which also overlap with areas involved in executive control. Our aim was to examine how active bilingualism—manifested as the regular balanced use of two languages and language switching—may be related to the different domains of executive control in highly proficient healthy older adult bilinguals, controlling for age, processing speed, and fluid intelligence. Methods Participants were 76 community-dwelling older adults who reported being physically and mentally healthy and showed no signs of cognitive impairment. They completed a self-report questionnaire on their language background, two computer measures for previously identified covariates (processing speed as measured by two-choice reaction time (RT) task and fluid intelligence as measured by the Raven’s Progressive Matrices), as well as a battery of computerized executive control tasks (Color-shape Task Switching, Stroop, Flanker, and Spatial 2-back task). Results Regression analyses showed that, even after controlling for age, processing speed, and fluid intelligence, more balanced bilingualism usage and less frequent language switching predicted higher goal maintenance (nonswitch trials RT in Color-shape Task Switching) and conflict monitoring abilities (global RT in Color-shape Task Switching and Flanker task). Discussion Results suggest that active bilingualism may provide benefits to maintaining specific executive control abilities in older adult bilinguals against the natural age-related declines. Balanced usage, Bilinguals, Executive control, Language switching Age-related declines in executive control, skills that tap on a set of general cognitive abilities centered around the prefrontal cortex (Treitz, Heyder, & Daum, 2007), have been well-documented. For example, decreased performance with aging has been observed in inhibitory control (Van der Elst, Van Boxtel, Van Breukelen, & Jolles, 2006), working memory and updating (Bopp & Verhaeghen, 2020), as well as mental set-shifting (Goffaux, Phillips, Sinai, & Pushkar, 2008). These declines are postulated to arise from age-related changes in the associated frontal system (Buckner, 2004). Recent research has attempted to identify lifestyle factors that may increase cognitive reserve, or the brain’s resilience to age-related neuropathological damage (Antoniou & Wright, 2017), such as physical activity (McAuley, Kramer, & Colcombe, 2004), formal education (Tucker-Drob, Johnson, & Jones, 2009), and more recently, bilingualism (Bialystok, Anderson, & Grundy, 2018). Gold (2015) suggested that “bilingual cognitive reserve effects appear to operate through protection of executive control circuits” (p.13). The aim of our study is to explore the executive control mechanisms and context under which bilingualism can be a protective source against cognitive decline in the normal aging process. Why might bilingualism provide protection against age-related cognitive decline? According to the experience-related neuroplasticity account, the brain is able to constantly adapt itself to the demands of the environment by changing and/or creating neural structures and pathways (Galván, 2010). Bilinguals’ everyday experience with language control, that is, regularly managing more than one language, is likely to result in positive adaptation in brain areas related to language control (Abutaliebi & Green, 2016). Importantly, these areas are found to overlap with areas related to domain-general executive control (Abutalebi & Green, 2016). Thus, neuroadaptive changes to the areas of the brain shaped by bilingual language control are likely to also positively affect the associated domain-general executive control processes. This suggests that the extensive experience of being bilingual in older adults might accrue cognitive reserve in these related brain areas, with either increased neural efficiency or greater neural tissue in compensation for age-related loss (Antoniou & Wright, 2017), which can then be exhibited as better performance in executive control tasks. Previous research on the possible benefits of bilingualism on executive control often compared group-level differences between bilinguals and monolinguals (for a meta-analysis of adult studies, see Lehtonen et al., 2018; for a review of older-adult studies, see Zhang, Wu, & Thierry, 2020). However, bilingualism is not a unitary construct, nor are bilinguals a homogenous group (Luk & Bialystok, 2013). Individual variances in bilingualism could modulate the effect of bilingualism on executive control. These variances are often measured based on several factors, of which Bak (2016) distinguished two types: competence or knowledge of languages, such as second language age of acquisition and proficiency of each language; and performance or active practice of languages, such as frequency of language use and language switching (defined here as alternating between two languages while conversing with others, no distinction is made between linguistically different types of language switching e.g., codeswitching, code-mixing; Rodriguez-Fornells, Kramer, Lorenzo-Seva, Festman, & Münte, 2012). Based on the experience-related neuroplasticity account, one can reason that the performance aspect, that is, the active experience of managing multiple languages, is that which encourages neural adaptation. Therefore, we hypothesize that active older bilinguals—those who regularly engage in performance of their multiple language systems—are more likely to develop executive control benefits than those who predominantly engage in one language. Although some recent neurocognitive studies have explored the relationship between bilingualism experience factors and executive control in young adults (DeLuca, Rothman, Bialystok, & Pilatsikas, 2019, 2020), there is currently no consistent relationship found between these individual bilingualism factors and executive control in studies that sample older adults (summarized in Zhang et al., 2020). For proficiency, Dash, Berroir, Joanette, and Ansaldo (2019) found that higher second language proficiency was related to greater neural efficiency in older adults performing the Attention Network Test, but Goral, Campanelli, and Spiro (2015) found that balanced proficiency and use of both languages were associated with worse performance of their older adults in the Simon task. This is in contrast to de Bruin, Bak, and Della Sala (2015) who concluded that there were no differences between active bilingual, inactive bilingual and monolingual older adults on the Simon task and color-shape task switching. For language switching, Soveri, Rodriguez-Fornells, and Laine (2011) found that bilinguals who reported more language switching had smaller mixing costs on a number-letter switching task (sample aged 30–75), while Jylkkä and colleagues (2017) found that greater language switching was associated with more errors in the spatial n-back task and larger switch costs in the number-letter switching task (sample aged 18–69). Sekerina, Spradlin, and Valian (2019) suggested several reasons for this inconsistency: inherent variability in conditions and experiences of bilingualism, presence of covariates (e.g., socioeconomic status, immigration), inherent differences in executive control tasks used, as well as task impurity. To illustrate, Goral and colleagues (2015) linked more balanced proficiency and use of both languages with worse executive control, but they did not gather any information about their older adults’ language switching practices. de Bruin and colleagues (2015) found no executive control differences between active bilingual, inactive bilingual, and monolingual older adults, but they examined language performance using a between-group categorical approach, which might have reduced the variances inherent in the sample. Furthermore, only a small number of studies (e.g., Jylkkä et al., 2017; Soveri et al., 2011) examined the variance of bilingualism across multiple domains of executive control, and these two studies sampled across a wide age range; hence, it is not clear if their results are generalizable to older adult populations. Other suggested reasons for the discrepant findings include differences in data preprocessing (Zhou & Krott, 2016), and use of unsuitable statistical procedures (Whitford & Luk, 2019). In the present study, we attempt to measure and control for the variability in bilingualism and effects of covariates on a series of executive control tasks across different domains. First, we focus on the performance aspect while assuming competence (Bak, 2016). That is, given older bilinguals who are highly competent in both their languages, how does variation in performance, that is, active bilingualism—in terms of regular balanced usage of both languages and language switching—affect the different domains of executive control? Second, we measure and control for known covariates such as age, processing speed, and fluid intelligence (Bak, 2016; Deary, Johnson, & Starr, 2010; Manard, Carabin, Jaspar, & Collette, 2014). Despite the lack of clear trends in previous literature, based on the experience-related neuroplasticity theory, we expect that greater balanced usage and/or more language switching would relate to better performance in executive control tasks, even after controlling for these covariates. Finally, for a more holistic examination, we measured six different domains of executive control using four different tasks, all of which had been previously associated with bilingualism (summarized in Lehtonen et al., 2018). Tasks selected were commonly used in previous studies and identified with reference to theories from Miyake and Friedman (2012), Friedman and Miyake (2004), Weissberger, Gollan, Bondi, Clark, and Wierenga (2015), and Costa, Hernández, Costa-Faidella, and Sebastián-Gallés (2009). Table 1 details the domains, the tasks involved, their operationalization, and relationship to bilingualism in previous studies involving older adults. Table 1. Domains of Executive Control Involved in the Present Study, Tasks, Operationalizations, and Relationship to Bilingualism in Previous Studies Involving Older Adults Domain . Task . Operationalization . Relationship to bilingualism in previous older adult studies . Inhibition of prepotent responses Stroop task Stroop interference effect = RT of incongruent trials – RT of neutral trials ✓ Kousaie & Phillips (2017): BL showed smaller Stroop interference effect than ML. ✘ Antón, Garcia, Carreiras, & Dunabeitia (2016): No BL-ML difference, no correlation between L2 proficiency and task performance. Interference resistance Flanker task Flanker effect = RT of incongruent trials – RT of congruent trials ✓ Gollan, Sandoval, Salmon (2011): BL cross-language intrusions related with flanker task errors. ✘ Soveri et al. (2011); Jylkkä et al. (2017): No relationship between language switching and flanker performance. Transient set-shifting control Color-shape switching task Switch cost = RT of switch trials in mixed block – RT of nonswitch trials in mixed block ✓ Gold, Kim, Johnson, Kryscio, & Smith (2013): BL showed smaller switch cost than ML. ✘ De Bruin, Bak, & Della Sala (2015): Active BL showed smaller raw switch cost than ML, but not statistically significant after correcting for baseline speed. Working memory updating Spatial 2-back task d’, sensitivity index used in signal detection theory = Zp(correct detections) – Zp(false alarms) ✓ Jylkkä et al. (2017): More unintended language switches were related to more errors in the n-back (both 1-back and 2-back) task. ✘ Soveri et al. (2011): No relationship found between language switching and the n-back (both 1-back and 2-back) task. Task goal maintenance Color-shape switching task RT of nonswitch trials in mixed block ✓ Weissberger et al. (2015): When comparing stay (nonswitch) trials, BL show greater efficiency (less widespread brain activation) during language switching as compared to task switching. Conflict monitoring Stroop task Flanker task Color-shape switching task Global RT (Mean overall RT) ✘ Anton et al. (2016): No difference between BL and ML on Stroop global RT. ✓ Hilchey & Klein (2011): BL show faster global RT than ML on Stroop and Flanker tasks (review of 14 studies). ✓ Abutalebi and colleagues (2015): BL show faster global RT than ML on Flanker task. Domain . Task . Operationalization . Relationship to bilingualism in previous older adult studies . Inhibition of prepotent responses Stroop task Stroop interference effect = RT of incongruent trials – RT of neutral trials ✓ Kousaie & Phillips (2017): BL showed smaller Stroop interference effect than ML. ✘ Antón, Garcia, Carreiras, & Dunabeitia (2016): No BL-ML difference, no correlation between L2 proficiency and task performance. Interference resistance Flanker task Flanker effect = RT of incongruent trials – RT of congruent trials ✓ Gollan, Sandoval, Salmon (2011): BL cross-language intrusions related with flanker task errors. ✘ Soveri et al. (2011); Jylkkä et al. (2017): No relationship between language switching and flanker performance. Transient set-shifting control Color-shape switching task Switch cost = RT of switch trials in mixed block – RT of nonswitch trials in mixed block ✓ Gold, Kim, Johnson, Kryscio, & Smith (2013): BL showed smaller switch cost than ML. ✘ De Bruin, Bak, & Della Sala (2015): Active BL showed smaller raw switch cost than ML, but not statistically significant after correcting for baseline speed. Working memory updating Spatial 2-back task d’, sensitivity index used in signal detection theory = Zp(correct detections) – Zp(false alarms) ✓ Jylkkä et al. (2017): More unintended language switches were related to more errors in the n-back (both 1-back and 2-back) task. ✘ Soveri et al. (2011): No relationship found between language switching and the n-back (both 1-back and 2-back) task. Task goal maintenance Color-shape switching task RT of nonswitch trials in mixed block ✓ Weissberger et al. (2015): When comparing stay (nonswitch) trials, BL show greater efficiency (less widespread brain activation) during language switching as compared to task switching. Conflict monitoring Stroop task Flanker task Color-shape switching task Global RT (Mean overall RT) ✘ Anton et al. (2016): No difference between BL and ML on Stroop global RT. ✓ Hilchey & Klein (2011): BL show faster global RT than ML on Stroop and Flanker tasks (review of 14 studies). ✓ Abutalebi and colleagues (2015): BL show faster global RT than ML on Flanker task. Note: BL = Bilinguals; ML = Monolinguals; RT = reaction time; ✓ = Relationship found between bilingualism and task measure; ✘ = No relationship found between bilingualism and task measure. Open in new tab Table 1. Domains of Executive Control Involved in the Present Study, Tasks, Operationalizations, and Relationship to Bilingualism in Previous Studies Involving Older Adults Domain . Task . Operationalization . Relationship to bilingualism in previous older adult studies . Inhibition of prepotent responses Stroop task Stroop interference effect = RT of incongruent trials – RT of neutral trials ✓ Kousaie & Phillips (2017): BL showed smaller Stroop interference effect than ML. ✘ Antón, Garcia, Carreiras, & Dunabeitia (2016): No BL-ML difference, no correlation between L2 proficiency and task performance. Interference resistance Flanker task Flanker effect = RT of incongruent trials – RT of congruent trials ✓ Gollan, Sandoval, Salmon (2011): BL cross-language intrusions related with flanker task errors. ✘ Soveri et al. (2011); Jylkkä et al. (2017): No relationship between language switching and flanker performance. Transient set-shifting control Color-shape switching task Switch cost = RT of switch trials in mixed block – RT of nonswitch trials in mixed block ✓ Gold, Kim, Johnson, Kryscio, & Smith (2013): BL showed smaller switch cost than ML. ✘ De Bruin, Bak, & Della Sala (2015): Active BL showed smaller raw switch cost than ML, but not statistically significant after correcting for baseline speed. Working memory updating Spatial 2-back task d’, sensitivity index used in signal detection theory = Zp(correct detections) – Zp(false alarms) ✓ Jylkkä et al. (2017): More unintended language switches were related to more errors in the n-back (both 1-back and 2-back) task. ✘ Soveri et al. (2011): No relationship found between language switching and the n-back (both 1-back and 2-back) task. Task goal maintenance Color-shape switching task RT of nonswitch trials in mixed block ✓ Weissberger et al. (2015): When comparing stay (nonswitch) trials, BL show greater efficiency (less widespread brain activation) during language switching as compared to task switching. Conflict monitoring Stroop task Flanker task Color-shape switching task Global RT (Mean overall RT) ✘ Anton et al. (2016): No difference between BL and ML on Stroop global RT. ✓ Hilchey & Klein (2011): BL show faster global RT than ML on Stroop and Flanker tasks (review of 14 studies). ✓ Abutalebi and colleagues (2015): BL show faster global RT than ML on Flanker task. Domain . Task . Operationalization . Relationship to bilingualism in previous older adult studies . Inhibition of prepotent responses Stroop task Stroop interference effect = RT of incongruent trials – RT of neutral trials ✓ Kousaie & Phillips (2017): BL showed smaller Stroop interference effect than ML. ✘ Antón, Garcia, Carreiras, & Dunabeitia (2016): No BL-ML difference, no correlation between L2 proficiency and task performance. Interference resistance Flanker task Flanker effect = RT of incongruent trials – RT of congruent trials ✓ Gollan, Sandoval, Salmon (2011): BL cross-language intrusions related with flanker task errors. ✘ Soveri et al. (2011); Jylkkä et al. (2017): No relationship between language switching and flanker performance. Transient set-shifting control Color-shape switching task Switch cost = RT of switch trials in mixed block – RT of nonswitch trials in mixed block ✓ Gold, Kim, Johnson, Kryscio, & Smith (2013): BL showed smaller switch cost than ML. ✘ De Bruin, Bak, & Della Sala (2015): Active BL showed smaller raw switch cost than ML, but not statistically significant after correcting for baseline speed. Working memory updating Spatial 2-back task d’, sensitivity index used in signal detection theory = Zp(correct detections) – Zp(false alarms) ✓ Jylkkä et al. (2017): More unintended language switches were related to more errors in the n-back (both 1-back and 2-back) task. ✘ Soveri et al. (2011): No relationship found between language switching and the n-back (both 1-back and 2-back) task. Task goal maintenance Color-shape switching task RT of nonswitch trials in mixed block ✓ Weissberger et al. (2015): When comparing stay (nonswitch) trials, BL show greater efficiency (less widespread brain activation) during language switching as compared to task switching. Conflict monitoring Stroop task Flanker task Color-shape switching task Global RT (Mean overall RT) ✘ Anton et al. (2016): No difference between BL and ML on Stroop global RT. ✓ Hilchey & Klein (2011): BL show faster global RT than ML on Stroop and Flanker tasks (review of 14 studies). ✓ Abutalebi and colleagues (2015): BL show faster global RT than ML on Flanker task. Note: BL = Bilinguals; ML = Monolinguals; RT = reaction time; ✓ = Relationship found between bilingualism and task measure; ✘ = No relationship found between bilingualism and task measure. Open in new tab Method Seventy-six healthy Chinese bilingual community-dwelling older adults (53 females, Mage = 67.20, SD = 6.18, range = 60–84 years) participated in the study. All participants were Singapore citizens; 60 reported living their whole life in Singapore, while the remaining 16 spent at least 20 years in Singapore. Singapore is a multilingual, multicultural society. Most older adults in Singapore can speak at least two languages fluently and proficiently, but there are individual variations in the amount of usage of the languages, as well as in frequencies of language switching. The inclusion criteria for the study were: (a) 60 years old and above, (b) speak at least two languages, (c) free of any neurological conditions, (d) physically and mentally healthy (as assessed by the Montreal Cognitive Assessment [MoCA]; Nasreddine et al., 2005), and (e) have at least three years of formal education. Additionally, all participants were tested and ascertained to have normal color vision. Participants reported having, on average, 10.38 years of education (SD = 3.96; range = 3–18 years). They also reported their household income using the following scale: 1 = less than S$2000; 2 = S$2000 to less than S$3000; 3 = S$3000 to less than S$5000; or 4 = above S$5000; Md = 2.00, SD = 1.33. Materials Screening tools Participants completed a physical and mental health questionnaire; no participant reported poor health or high frequency of negative emotions, nor any history of head injury, stroke, or Parkinson’s disease. We also administered the modified version of MoCA that was validated for use in the local population (Dong et al., 2010) to assess for risk of cognitive impairment. A score of below 20 is indicative of high risk of cognitive impairment. The participants’ MoCA scores ranged from 21 to 30 (maximum possible score of 30; M = 25.93; SD = 2.35). Participants were also asked about their experience playing speeded videogames. Regular playing of action videogames enhances visual selective attention and visual processing in computer tasks (e.g., Green & Bavelier, 2003, 2007), which could in turn affect participants’ performance on our computerized executive control tasks. Ten participants reported having some experience playing speeded videogames and only one reported playing such games daily. These participants were not excluded in the final analyses as preliminary analyses showed that their performances in our executive control tasks were not significantly better than the rest of the participants. Language Background Questionnaire (LBQ) This questionnaire was used to derive participants’ bilingualism characteristics. All participants were multilingual; they reported knowing Mandarin, plus two or more of the following languages: English, Cantonese, Hokkien, Teochew, Hakka, and Hainanese. Twenty-nine knew three languages and 47 knew four languages. However, participants reported much less usage of their third-most (M = 10.2% of time in a typical week) and fourth-most (M = 4.6%) used languages as compared to their most and second-most used languages (Table 2), hence they were treated as bilinguals for the purposes of this study. Proficiency in listening and speaking were reported on a 5-point scale (1 = not proficient; 5 = very proficient), then averaged to form one score per language. As some of the languages participants listed consist of Chinese dialects that are not taught in formal education and do not have a complete writing system (e.g., Cantonese, Hokkien, Teochew, Hakka, and Hainanese share some aspects of the Chinese writing system as Mandarin but differ in others, such as certain unique characters and syntax, as well as pronunciation and usage even for the same written characters), only ratings of proficiency in listening and speaking (excluding reading and writing) were used to calculate participants’ proficiency in each of the languages. These scores were used to ascertain that participants were highly proficient bilinguals (Most proficient language: M = 4.68, SD = 0.54; Second-most proficient language: M = 4.41, SD = 0.70; see Supplementary Table 1 for participants’ language proficiencies and usage frequencies by language). Table 2. Descriptive Statistics of Language, Control Variables, and Executive Control Variables . Mean . SD . Language variables  Frequency of most used languagea 0.62 0.19  Frequency of second-most used languagea 0.24 0.12  Balanced usage (Most used minus second-most used)b 0.38 0.29  Language switching 30.38 6.94 Control variables  Processing speed 705.02 248.90  Fluid intelligence 21.76 6.27 Executive control variables  Stroop interference effect (n = 73) 178.94 204.24  Flanker effect (n = 73) 731.66 598.25  Task switching switch cost 134.71 135.19  Spatial 2-back d’ (n = 72) 1.54 0.98  Task switching nonswitch trials RT 1,021.30 322.54  Stroop task global RT 1,127.34 248.00  Flanker task global RT 1,178.58 403.61  Task switching global RT 1,078.65 326.37 . Mean . SD . Language variables  Frequency of most used languagea 0.62 0.19  Frequency of second-most used languagea 0.24 0.12  Balanced usage (Most used minus second-most used)b 0.38 0.29  Language switching 30.38 6.94 Control variables  Processing speed 705.02 248.90  Fluid intelligence 21.76 6.27 Executive control variables  Stroop interference effect (n = 73) 178.94 204.24  Flanker effect (n = 73) 731.66 598.25  Task switching switch cost 134.71 135.19  Spatial 2-back d’ (n = 72) 1.54 0.98  Task switching nonswitch trials RT 1,021.30 322.54  Stroop task global RT 1,127.34 248.00  Flanker task global RT 1,178.58 403.61  Task switching global RT 1,078.65 326.37 Note: N = 76 unless otherwise stated. RT = reaction time in milliseconds. aUsage frequencies are in proportions, from 0 (no usage of this language) to 1 (complete usage of this language only). bA score closer to 0 indicates more balance between two languages; a score closer to 1 indicates more dominant usage in one language over the other. Open in new tab Table 2. Descriptive Statistics of Language, Control Variables, and Executive Control Variables . Mean . SD . Language variables  Frequency of most used languagea 0.62 0.19  Frequency of second-most used languagea 0.24 0.12  Balanced usage (Most used minus second-most used)b 0.38 0.29  Language switching 30.38 6.94 Control variables  Processing speed 705.02 248.90  Fluid intelligence 21.76 6.27 Executive control variables  Stroop interference effect (n = 73) 178.94 204.24  Flanker effect (n = 73) 731.66 598.25  Task switching switch cost 134.71 135.19  Spatial 2-back d’ (n = 72) 1.54 0.98  Task switching nonswitch trials RT 1,021.30 322.54  Stroop task global RT 1,127.34 248.00  Flanker task global RT 1,178.58 403.61  Task switching global RT 1,078.65 326.37 . Mean . SD . Language variables  Frequency of most used languagea 0.62 0.19  Frequency of second-most used languagea 0.24 0.12  Balanced usage (Most used minus second-most used)b 0.38 0.29  Language switching 30.38 6.94 Control variables  Processing speed 705.02 248.90  Fluid intelligence 21.76 6.27 Executive control variables  Stroop interference effect (n = 73) 178.94 204.24  Flanker effect (n = 73) 731.66 598.25  Task switching switch cost 134.71 135.19  Spatial 2-back d’ (n = 72) 1.54 0.98  Task switching nonswitch trials RT 1,021.30 322.54  Stroop task global RT 1,127.34 248.00  Flanker task global RT 1,178.58 403.61  Task switching global RT 1,078.65 326.37 Note: N = 76 unless otherwise stated. RT = reaction time in milliseconds. aUsage frequencies are in proportions, from 0 (no usage of this language) to 1 (complete usage of this language only). bA score closer to 0 indicates more balance between two languages; a score closer to 1 indicates more dominant usage in one language over the other. Open in new tab For age of second language acquisition, participants found it challenging to recall the exact age when they first learnt a language. Hence, they reported an approximate age range (marked at significant life stages) instead. Twenty-eight participants reported that they acquired their second language between ages 0 and 6 (before formal schooling), while the remaining 48 reported that they acquired their second language between ages 7 and 18 (formal schooling). Importantly, none of our participants reported any “loss” in usage of their two languages over the years; some participants reported speaking some languages less as they aged, but no participant reported that they stopped using their languages completely such that they became functionally monolingual. For language usage, participants estimated their current usage frequency (in proportion) of each of their languages in a typical week. There were significant differences in self-rated frequency of usage between their most and second-most used languages (paired samples t-test, t(75) = 11.29, p < .001). Balanced usage was calculated as participants’ most used language frequency minus second-most used language frequency (Yow & Li, 2015). This served as a proxy for the extent of language control regularly practiced by the bilingual participants. Scores varied along the continuum of balanced (score of 0) indicating equal usage of both languages, to dominant (score of 1) indicating usage of only one language. Language switching was measured using the sum of scores from the 5-point, 12-item Bilingual Switching Questionnaire (Rodriguez-Fornells et al., 2012). Higher aggregate scores represent more frequent language switching (refer to Table 2 for descriptives). Control Variables Raven’s progressive matrices (Raven, Raven, & Court, 2004) This is a measure of abstract reasoning and widely regarded as a measure of nonverbal fluid intelligence. Participants were tasked to identify the one figure, out of six possible options, that completed the pattern presented. The final score was calculated as the total number of correct items completed in 10 min (out of 36). Two-choice reaction time (RT) Task (adapted from Deary et al., 2010) This task is used to measure processing speed and to account for individual differences in psychomotor speed, which could influence speeded responses on computerized executive control tasks (Albinet, Boucard, Bouquet, & Audiffren, 2012). Participant were presented a white or black circle of about 1cm in diameter against a gray background and had to determine the color of the circle as fast as they could by key press (“B” for black or “N” for white). There were 30 trials consisting of an equal number of black and white trials. Participants were scored on the mean RT for correct trials. Executive Control Tasks Color-shape task switching (adapted from Prior & Macwhinney, 2009) Participants were asked to categorize a colored shape either by its color (green or red) or by its shape (square or triangle) based on a task cue. The task cue was either a rectangular strip of color gradient for the color task or a row of small circles for the shape task. A switch/nonswitch trial involved using a different/same sorting rule from the previous trial. Responses were by key press (“O” for red/triangle and “P” for green/square). Participants completed 20 shape trials and 20 color trials (order counterbalanced across participants), and then a mixed block of 40 shape and 40 color trials. The variables of interest for this task are switching cost RT, global RT (i.e., mean overall RT), as well as RT of nonswitch trials within the mixed block. Switching costs reflect the specific cost of managing two different types of trials within the same environment, which is the difference in RT between task-switch trials (e.g., a shape trial followed by a color trial) and task-repeat trials in the mixed block. Conflict monitoring ability has been previously examined using global RT (Lehtonen et al., 2018), with lower RT indicative of higher monitoring. Additionally, drawing from Weissberger and colleagues (2015), task goal maintenance ability is examined using the RT of nonswitch trials within the mixed block. Stroop task Participants were instructed to press one of four color-labeled keys on the keyboard that matched the color of the print as fast as they could. In this study, we have used manual key-press as a response modality for the Stroop task rather than the standard voice response that has been found to be associated with a bilingual advantage (e.g., Bialystok, Craik, & Luk, 2008). Previous literature has suggested that Stroop interference effects do occur in both manual and voice response modalities (MacLeod, 1991). This current version of the Stroop task was previously used with bilinguals and was found to be associated with bilingualism (Yow & Li, 2015). Other researches have also found a bilingual advantage using Stroop tasks with manual responses (e.g., Kousaie & Phillips, 2017). Stimuli involved either a string of five asterisks (neutral condition) or printed color names (“red,” “green,” “blue” or “yellow” in red, green, blue, or yellow). In the congruent condition, the color name presented was the same as what it was printed in, while in the incongruent condition, the color name presented was printed in a different color from its name. There were 24 neutral trials, 24 congruent trials, and 24 incongruent trials (order counterbalanced across participants), followed by a mixed block of 24 congruent and 24 incongruent trials. The variables of interest for this task are global RT and the Stroop interference effect, where the latter is expressed as a difference between the mean RT in incongruent trials (from both the incongruent and mixed blocks) and neutral trials. The Stroop interference effect reflects the cognitive cost associated with the inhibition of prepotent responses (Miyake & Friedman, 2012). There were three participants who were removed from the Stroop interference effect analyses as they had zero accuracy in the incongruent condition. These three participants were included in the global RT analyses as results remained the same when they were included. Flanker Task (Eriksen & Eriksen, 1974) Participants were instructed to judge whether the center arrow among seven arrows was pointing to the left or right by pressing the left or right arrow keys on the keyboard, and to disregard the direction of the flanking arrowheads (congruent/facing the same direction, or incongruent/facing the opposite direction). The task consisted of 20 congruent trials, and 20 incongruent trials (order counterbalanced across participants), and a mixed block of 20 congruent and 20 incongruent trials. The variables of interest for this task are global RT and the Flanker effect (defined as the difference in RT between the incongruent trials from both the incongruent and mixed blocks, and congruent trials from the congruent and mixed blocks). The Flanker effect reflects the ability to resist interference from distractors. Three respondents were removed from the Flanker effect analyses; one had zero accuracy on the congruent trials, and the other two had zero accuracy on the incongruent trials. These three respondents were not the same individuals as those with low Stroop accuracy. They were included in the analyses of global RT as results remained the same when they were included. Spatial 2-back Task (Schmiedek, Li, & Lindenberger, 2009) Trials involved a black circle appearing in one of the cells of a 3X3 grid, then disappearing and reappearing in another (or the same) cell. Participants were instructed to press the spacebar if the position of the black circle in the current trial matched the position of the black circle two trials prior, otherwise no response was needed. Participants completed 48 trials, of which 16 were target trials that needed a response and 32 were lure trials that did not. The variable of interest for this task is d’, reflecting the sensitivity index used in signal detection theory (Tanner & Swets, 1954), where d’ = Zp(correct detections) – Zp(False alarms). Hit and false alarm rates of 0 or 1 were adjusted using the convention recommended in Stanislaw and Todorov (1999). There were four participants who did not have any data; three were due to technical error and one participant was unwilling to complete the task. Procedure All tasks were administered individually in a quiet room with the informed consent of the participants. Participants completed the tasks in the following order: colorblindness test, MoCA, Raven’s matrices, Two-choice RT, the four executive control tasks in a counterbalanced order, and background questionnaires. The MoCA and questionnaires were presented on paper-and-pen, while all other tasks were administered with a Matlab program on a desktop computer or laptop (Screen resolution: 1600 by 900). All participants were told to maintain a distance of approximately 70–85 cm from the screen. Results In addition to the two planned control variables of processing speed and fluid intelligence, age was added as a control variable due to its importance as illustrated in previous studies (e.g., Goral et al., 2015). Two other control variables, monthly income and number of years of education, were considered but eventually not included. Monthly income did not correlate with any of the executive control task performance (Spearman correlations, ps > .18), while the number of years of education did not affect the results. Performance across all tasks did not differ by order of executive control tasks presented (all ps > .12) Thirty-seven participants completed the Stroop task using English stimuli, and 39 participants completed the task using Chinese stimuli. Participants who did the task in Chinese (M = 1,072.40) had faster overall RT than those who did the task in English (M = 1,185.25, t(74) = 2.02, p = .05), and also exhibited smaller interference effects (MChinese = 131.68, MEnglish = 224.92, t(71) = 1.99, p = .05. Hence, language of Stroop task was included in subsequent analyses involving Stroop. We conducted separate hierarchical multiple regressions for each executive control variable of interest. Control variables of age, speed of processing and fluid intelligence were added in Step 1, while the two bilingualism variables of interest—balanced usage and language switching—were included in Step 2 of each regression model. Previous similar studies (e.g., Goral et al., 2015) suggested that the expected effect size is moderate in magnitude. Hence, using G*Power calculator, with a sample size of 76 using two tested predictors in a five-predictor model, the power to detect any moderate effect is sufficient at 0.85 (Faul, Erdfelder, Buchner, & Lang, 2009). For RT calculation, only accurate trials were included. Additionally, trials with RT above and below 2.5 SD from each participant’s mean were discarded (<2.1% of the data). All regression models met the assumption of independent errors (Durbin–Watson values = 1.61–2.42). Scatterplots and normal P-P plots of standardized residuals indicated that the data met assumptions of homoscedasticity, linearity, and normally distributed errors. No evidence of multicollinearity was detected (all predictor correlations below .7 and VIFs below 10; Pallant, 2013). Results of the three models of which the bilingualism variables emerged as significant predictors are presented in Table 3. Table 3. Multiple Regression Results of Models with Balanced Usage and Language Switching as Significant Predictors . Task goal maintenance . . . Conflict monitoring: global RT . . . . . . . Nonswitch trials RT . . . Task switching . . . Flanker . . . β t ∆R2 β t ∆R2 β t ∆R2 Step 1 .32*** .36*** .33***  Age .16 1.47 .13 1.23 .28 2.60*  Processing speed .57 5.15*** .61 5.74*** .11 1.02  Fluid intelligence .21 1.80 .19 1.70 -.32 -2.81** Step 2 .10** .09** .06*  Age .22 2.09* .19 1.85 .33 3.06**  Processing speed .54 5.14*** .59 5.73*** .07 0.65  Fluid intelligence .16 1.43 .14 1.32 -.36 -3.18**  Balanced usagea .27 2.84** .26 2.82** .25 2.59*  Language switchingb .23 2.42* .22 2.38* .08 0.85 . Task goal maintenance . . . Conflict monitoring: global RT . . . . . . . Nonswitch trials RT . . . Task switching . . . Flanker . . . β t ∆R2 β t ∆R2 β t ∆R2 Step 1 .32*** .36*** .33***  Age .16 1.47 .13 1.23 .28 2.60*  Processing speed .57 5.15*** .61 5.74*** .11 1.02  Fluid intelligence .21 1.80 .19 1.70 -.32 -2.81** Step 2 .10** .09** .06*  Age .22 2.09* .19 1.85 .33 3.06**  Processing speed .54 5.14*** .59 5.73*** .07 0.65  Fluid intelligence .16 1.43 .14 1.32 -.36 -3.18**  Balanced usagea .27 2.84** .26 2.82** .25 2.59*  Language switchingb .23 2.42* .22 2.38* .08 0.85 Note: N = 76. aThe lower the score, the more balance between two languages. bThe lower the score, the less language switching reported by participants. *p < .05; **p < .01; ***p < .001. Open in new tab Table 3. Multiple Regression Results of Models with Balanced Usage and Language Switching as Significant Predictors . Task goal maintenance . . . Conflict monitoring: global RT . . . . . . . Nonswitch trials RT . . . Task switching . . . Flanker . . . β t ∆R2 β t ∆R2 β t ∆R2 Step 1 .32*** .36*** .33***  Age .16 1.47 .13 1.23 .28 2.60*  Processing speed .57 5.15*** .61 5.74*** .11 1.02  Fluid intelligence .21 1.80 .19 1.70 -.32 -2.81** Step 2 .10** .09** .06*  Age .22 2.09* .19 1.85 .33 3.06**  Processing speed .54 5.14*** .59 5.73*** .07 0.65  Fluid intelligence .16 1.43 .14 1.32 -.36 -3.18**  Balanced usagea .27 2.84** .26 2.82** .25 2.59*  Language switchingb .23 2.42* .22 2.38* .08 0.85 . Task goal maintenance . . . Conflict monitoring: global RT . . . . . . . Nonswitch trials RT . . . Task switching . . . Flanker . . . β t ∆R2 β t ∆R2 β t ∆R2 Step 1 .32*** .36*** .33***  Age .16 1.47 .13 1.23 .28 2.60*  Processing speed .57 5.15*** .61 5.74*** .11 1.02  Fluid intelligence .21 1.80 .19 1.70 -.32 -2.81** Step 2 .10** .09** .06*  Age .22 2.09* .19 1.85 .33 3.06**  Processing speed .54 5.14*** .59 5.73*** .07 0.65  Fluid intelligence .16 1.43 .14 1.32 -.36 -3.18**  Balanced usagea .27 2.84** .26 2.82** .25 2.59*  Language switchingb .23 2.42* .22 2.38* .08 0.85 Note: N = 76. aThe lower the score, the more balance between two languages. bThe lower the score, the less language switching reported by participants. *p < .05; **p < .01; ***p < .001. Open in new tab For Task switching nonswitch trials RT, the final regression model was significant, F(5, 70) = 9.83, p < .001. The predictors accounted for 41.2% (Adjusted R2 = 0.37) of the model variance. Age (β = .22, t(70) = 2.09, p = .04) and processing speed (β = .54, t(70) = 5.14, p < .001) emerged as significant predictors, but more importantly, both balanced usage (β = .27, t(70) = 2.84, p = .01) and language switching (β = .23, t(70) = 2.42, p = .02) were associated with RT of nonswitch trials in the mixed block, with more balanced usage and less language switching predicting faster RT. For Task switching global RT, the final regression model was significant, F(5, 70) = 11.24, p < .001. The predictors accounted for 44.5% (Adjusted R2 = 0.41) of the model variance. Processing speed was a significant predictor, β = .59, t(70) = 5.73, p < .001. Additionally, balanced usage (β = .26, t(70) = 2.82, p = .01) and language switching (β = .22, t(70) = 2.38, p = .02) were both associated with overall RT, with more balanced usage and less language switching predicting faster RT. For Flanker global RT, the final regression model was significant, F(5, 70) = 8.83, p < .001. The predictors accounted for 38.7% (Adjusted R2 = 0.34) of the model variance. Age (β = .33, t(70) = 3.06, p = .003) and fluid intelligence (β = −.36, t(70) = −3.18, p = .002) were both significant predictors. Additionally, balanced usage (β = .25, t(70) = 2.59, p = .01) was associated with global RT in the Flanker task, with more balanced usage of both languages predicting faster RT in the task. Several models emerged significant but were not predicted by any of the bilingualism variables (see Supplementary Tables 2 and 3). These include the models for Stroop global RT, Stroop Interference effect, Flanker effect, and Spatial 2-back. The model for switching costs also did not emerge significant, F(5, 70) = 1.11, p = .36. Taken together, these results suggest that bilinguals who were more balanced in their usage of two languages and reported less frequent language switching showed better performance in the goal maintenance and conflict monitoring aspects of executive control. On the other hand, balanced usage and language switching were not related to inhibition, resistance to interference, set-shifting, and working memory updating, over and above the effects of age, processing speed, and intelligence. Discussion Our results revealed that active bilingualism, expressed as more balanced usage of both languages and less frequent language switching, accounted for significant variance in conflict monitoring (as indicated by overall RT in the color-shape task switching and the Flanker task) and goal maintenance task performance (as indicated by the RT on nonswitch trials in the mixed block of the color-shape task) in our sample of highly proficient older bilinguals, over and above the effects of age, processing speed, and fluid intelligence. We did not find significant effects of color-shape task switching costs, Stroop global RT and interference effect, Flanker effect, and spatial 2-back task d’. The findings suggest that experience-related bilingualism, that is, active bilingualism, appear to moderate some executive control components beyond natural age-related declines. In line with the proposal by Costa and colleagues (2009) and Hilchey and Klein (2011), the relationship between more balanced bilingual language usage and faster global reaction times may stem from better conflict monitoring. Hilchey and Klein (2011) used the term “conflict adaptation” (p.646) to describe how bilinguals increase regulation of cognitive processes in response to differing task demands. Active bilinguals’ frequent engagement in the management of multiple languages is thus analogous to the regular practice of managing high task demands in conflict monitoring, resulting in the faster global reaction times that were observed in our study. Contrary to expectations, we also found that lower frequency of reported language switching was related to better conflict monitoring and goal maintenance. We speculate that, for our active and proficient bilingual older adults, the effort involved in not switching between languages (i.e., the ability to “stay” in the target language) is more cognitively demanding than switching between languages (as suggested by Weissberger et al., 2015). Thus, the frequent practice of not switching between languages (i.e., low frequency of language switching) while actively using both languages could have translated to better goal maintenance and conflict monitoring abilities. This account is aligned with Green and Abutalebi (2013)’s adaptive control hypothesis where participants’ less frequent language switching is akin to engaging their languages separately in a dual-language context, which is actually more demanding on goal maintenance. Frequent language switching, on the other hand, is related to the tendency to engage in dense code switching and is theorized not to engage additional demands on goal maintenance. As the language switching measure used in the present study was not designed to distinguish specifically the different types of language switching contexts (see Jylkkä et al., 2017), more fine-grained language switching measures to tease apart the different language contexts are recommended for future studies. Nevertheless, our findings offer important implications regarding bilingualism as a lifestyle factor contributing to cognitive reserve in the normal aging process. In accordance to the experience-related neuroplasticity account, simply being a passive proficient bilingual does not attribute cognitive benefits. Instead, active usage of two languages and regular management of the languages to stay relevant are two crucial determinants of “lifestyle bilingualism” that could attenuate the negative effects of cognitive aging. Managing the usage of multiple languages is suggested to enhance executive control, which in turn provides protection against neuronal loss (Gold, 2015) and/or increase neural efficiency (Bialystok et al., 2018). This suggests that the cognitive buffer against age-related declines as offered by bilingualism may only be accrued to older adults who actively use both languages and manage language switching in their daily lives. It is important to note that differences in bilingualism experience could arise from differences in sociocultural and sociolinguistic environments (Whitford & Luk, 2019). For instance, older participants who reside in a bilingual community would differ from those who reside in a monolingual community in the context of their daily engagement of the two languages. The experience-based neuroplasticity theory would suggest that variations in such sociocultural and sociolinguistic environments could indirectly influence bilinguals’ cognitive reserve due to the engagement of different language control processes to meet the demands of the respective communities. Hence, further studies should include bilinguals from different sociocultural and sociolinguistic environments, including those who vary in language proficiencies but similar in dual-language usage, in order to better understand how the bilingualism experience could affect executive control across the life span. In the present study, we examined several variables as components of executive control, identified with reference to Miyake and Friedman (2012), Friedman and Miyake (2004), Weissberger and colleagues (2015), and Costa and colleagues (2009). Although we did not explicitly endorse a particular framework, the tasks we employed were typical of studies adopting Miyake and Friedman (2012)’s three-component model of executive function. However, we did not find a relationship between active bilingualism and inhibition (of prepotent responses or distractor interference), set-shifting, or working memory updating. More recently, Bialystok (2017) has challenged the appropriateness of this model and argued for executive attention as a single construct upon which the cognitive benefits of bilingualism may be accrued. Attention is suggested as the underlying commonality between inhibition and facilitation, both of which are engaged in language processing (Costa, Santesteban, & Ivanova, 2006). Hence, the bilingual experience may result in greater adaptation of attentional processes, which may then manifest as faster performance on executive control tasks. Crucially, Bialystok drew parallels between her proposed attention-based account and the conflict monitoring account by Costa and colleagues (2009) and Hilchey and Klein (2011). By extension, our findings linking active bilingualism and conflict monitoring seem to provide some support to Bialystok’s approach. The role of executive attention in the relationship between bilingualism and executive control should be further explored in future studies. It is noted that one of the limitations of our study is the use of self-reports to measure various aspects of bilingualism. While self-reports have been used in many studies and regarded as reliable and practically viable (Marian, Blumenfeld, & Kaushanskaya, 2007), they may result in less accurate ratings as compared to objective measures (MacIntyre, Noels, & Clement, 1997). Future studies should consider including more objective measures such as standardized language proficiency tests and/or language diaries of language use and language switching behavior. In addition, consistent with many previous studies, we used RT difference scores as one of the measures of several executive control variables. However, there are recent concerns on the reliability issues of RT difference scores (Draheim, Mashburn, Martin, & Engle, 2019; for bilingualism-specific discussions, see Hilchey & Klein, 2011), especially in individual differences studies. Draheim and colleagues (2019) suggested that such issues may contribute to the inconsistencies in bilingualism-executive control research. We concur that future studies should rely less on pure RT measures (and difference scores) and more on accuracy-based adaptive-difficulty tasks to assess individual differences in executive control. In conclusion, our study has sought to examine the cognitive effects related to the experience of bilingualism in the various components of executive control within a single population, over and beyond known covariates. We have specifically distinguished between bilingual competence (proficiency and age of acquisition) and performance (usage and language switching) and found significant effects of active bilingualism experience on conflict monitoring and goal maintenance, suggesting an experience-based effect of bilingualism on executive control. The active practice of managing two different languages could potentially be an important factor that helps build cognitive reserve to protect natural age-related declines in cognitive functions. Given that language control is part of a bilingual’s daily routine, encouraging active bilingualism as a lifestyle approach may yield positive effects on older adults’ cognitive health. Funding This work was partially supported by Singapore University of Technology and Design (SUTD)-Zhejiang University Research Collaboration Grant (grant number ZJUSP1200101), Ministry of Health (Singapore)-National Innovative Challenge on Active and Confident Aging Cognition Grant (grant number RGMOH170401), SUTD-MIT International Design Centre Research Grant (grant number IDG31700102), and SUTD Growth Plan Grant for Healthcare (grant number SGPHCRS1902) awarded to W. Q. Yow. Acknowledgments The authors would like to express their appreciation to Yong-en Care Centre, Clementi Community Club, Leng Kee Community Club, and Ulu Pandan Community Club for their support in the data collection process, the participants who took part in the study and the following researchers for their assistance in task design, data collection and analysis: Shimin Chua, Wilfred Tan Kwan Fu, Shirlyn Sia, Liyang Zhang, and Xiaoqian Li. Portions of this work were previously presented at the Cognitive and Behavioral Psychology Conference (March 2017). This study was approved by the Institutional Review Board of Singapore University of Technology and Design, Approval Number 14–046. No preregistration was conducted. Data and study materials are available on request. Please direct all requests to the corresponding author. Conflict of Interest None reported. References Abutalebi , J. , & Green , D. W. ( 2016 ). Neuroimaging of language control in bilinguals: Neural adaptation and reserve . Bilingualism: Language and Cognition , 19 ( 4 ), 689 – 698 . doi:10.1017/S1366728916000225 Google Scholar Crossref Search ADS WorldCat Abutalebi , J. , Guidi , L., Borsa , V., Canini , M., Della Rosa , P. A., Parris , B. A., & Weekes , B. S. ( 2015 ). Bilingualism provides a neural reserve for aging populations Neuropsychologia , 69 , 201 – 210 . doi:10.1016/j.neuropsychologia.2015.01.040 Google Scholar Crossref Search ADS PubMed WorldCat Albinet , C. T. , Boucard , G., Bouquet , C. A., & Audiffren , M. ( 2012 ). Processing speed and executive functions in cognitive aging: How to disentangle their mutual relationship? Brain and Cognition, 79 ( 1 ), 1 – 11 . doi:10.1016/j.bandc.2012.02.001 Google Scholar Crossref Search ADS WorldCat Antón , E. , García , Y. F., Carreiras , M., & Duñabeitia , J. A. ( 2016 ). Does bilingualism shape inhibitory control in the elderly? Journal of Memory and Language , 90 , 147 – 160 . doi:10.1016/j.jml.2016.04.007 Google Scholar Crossref Search ADS WorldCat Antoniou , M . ( 2019 ). The advantages of bilingualism debate . Annual Review of Linguistics , 5 , 395 – 415 . doi:10.1146/annurev-linguistics-011718-011820 Google Scholar Crossref Search ADS WorldCat Antoniou , M. , & Wright , S. M. ( 2017 ). Uncovering the mechanisms responsible for why language learning may promote healthy cognitive aging . Frontiers in Psychology, 8 , 2217 . doi:10.3389/fpsyg.2017.02217 Google Scholar Crossref Search ADS WorldCat Bak , T ( 2016 ). The impact of bilinguism on cognitive aging and dementia , Linguistic Approaches to Bilingualism , 6 ( 1 ), 205 – 226 . doi:10.1075/lab.15002.bak Google Scholar Crossref Search ADS WorldCat Bialystok , E . ( 2017 ). The bilingual adaptation: How minds accommodate experience , Psychological bulletin , 143 ( 3 ), 233 – 262 . doi:10.1037/bul0000099 Google Scholar Crossref Search ADS PubMed WorldCat Bialystok , E. , Anderson , J. A., & Grundy , J. G. ( 2018 ). Interpreting cognitive decline in the face of cognitive reserve: Does bilingualism affect cognitive aging? Linguistic Approaches to Bilingualism , 1 – 20 . doi: 10.1075/lab.18040.bia Google Scholar OpenURL Placeholder Text WorldCat Bialystok , E. , Craik , F., & Luk , G. ( 2008 ). Cognitive control and lexical access in younger and older bilinguals . Journal of Experimental Psychology. Learning, Memory, and Cognition, 34 ( 4 ), 859 – 873 . doi:10.1037/0278-7393.34.4.859 Google Scholar Crossref Search ADS WorldCat Bopp , K. L. , & Verhaeghen , P. (2020 ). Aging and n-back performance: A meta-analysis . The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences. 75 (2) , 229 – 240 . doi:10.1093/geronb/gby024 Google Scholar OpenURL Placeholder Text WorldCat Buckner , R. L . ( 2004 ). Memory and executive function in aging and AD: Multiple factors that cause decline and reserve factors that compensate . Neuron, 44 ( 1 ), 195 – 208 . doi:10.1016/j.neuron.2004.09.006 Google Scholar Crossref Search ADS WorldCat Costa , A. , Hernández , M., Costa-Faidella , J., & Sebastián-Gallés , N. ( 2009 ). On the bilingual advantage in conflict processing: Now you see it, now you don’t . Cognition, 113 ( 2 ), 135 – 149 . doi:10.1016/j.cognition.2009.08.001 Google Scholar Crossref Search ADS WorldCat Costa , A. , Santesteban , M., & Ivanova , I. ( 2006 ). How do highly proficient bilinguals control their lexicalization process? Inhibitory and language-specific selection mechanisms are both functional . Journal of Experimental Psychology. Learning, Memory, and Cognition, 32 ( 5 ), 1057 – 1074 . doi:10.1037/0278-7393.32.5.1057 Google Scholar Crossref Search ADS WorldCat Dash , T. , Berroir , P., Joanette , Y., & Ansaldo , A. I. ( 2019 ). Alerting, orienting, and executive control: The effect of bilingualism and age on the subcomponents of attention . Frontiers in Neurology, 10 , 1122 . doi:10.3389/fneur.2019.01122 Google Scholar Crossref Search ADS WorldCat Deary , I. J. , Johnson , W., & Starr , J. M. ( 2010 ). Are processing speed tasks biomarkers of cognitive aging? Psychology and Aging, 25 ( 1 ), 219 – 228 . doi:10.1037/a0017750 Google Scholar Crossref Search ADS WorldCat de Bruin , A. , Bak , T. H., & Della Sala , S. ( 2015 ). Examining the effects of active versus inactive bilingualism on executive control in a carefully matched non-immigrant sample . Journal of Memory and Language , 85 , 15 – 26 . doi:10.1016/j.jml.2015.07.001 Google Scholar Crossref Search ADS WorldCat DeLuca , V. , Rothman , J., Bialystok , E., & Pliatsikas , C. ( 2019 ). Redefining bilingualism as a spectrum of experiences that differentially affects brain structure and function . Proceedings of the National Academy of Sciences of the United States of America, 116 ( 15 ), 7565 – 7574 . doi:10.1073/pnas.1811513116 Google Scholar Crossref Search ADS WorldCat DeLuca , V. , Rothman , J., Bialystok , E., & Pliatsikas , C. ( 2020 ). Duration and extent of bilingual experience modulate neurocognitive outcomes . NeuroImage, 204 , 116222 . doi:10.1016/j.neuroimage.2019.116222 Google Scholar Crossref Search ADS WorldCat Dong , Y. , Sharma , V. K., Chan , B. P.-L., Venketasubramanian , N., Teoh , H. L., Seet , R. C. S., . . . Chen , C. ( 2010 ). The Montreal Cognitive Assessment (MoCA) is superior to the Mini-Mental State Examination (MMSE) for the detection of vascular cognitive impairment after acute stroke . Journal of the Neurological Sciences , 299 ( 1–2 ), 15 – 18 . doi:10.1016/j.jns.2010.08.051 Google Scholar Crossref Search ADS PubMed WorldCat Draheim , C. , Mashburn , C. A., Martin , J. D., & Engle , R. W. ( 2019 ). Reaction time in differential and developmental research: A review and commentary on the problems and alternatives . Psychological Bulletin, 145 ( 5 ), 508 – 535 . doi:10.1037/bul0000192 Google Scholar Crossref Search ADS WorldCat Eriksen , B. A. , & Eriksen , C. W. ( 1974 ). Effects of noise letters upon the identification of a target letter in a nonsearch task . Attention, Perception & Psychophysics , 16 ( 1 ), 143 – 149 . Google Scholar Crossref Search ADS WorldCat Faul , F. , Erdfelder , E., Buchner , A., & Lang , A. G. ( 2009 ). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses . Behavior Research Methods, 41 ( 4 ), 1149 – 1160 . doi:10.3758/BRM.41.4.1149 Google Scholar Crossref Search ADS WorldCat Friedman , N. P. , & Miyake , A. ( 2004 ). The relations among inhibition and interference control functions: A latent-variable analysis . Journal of Experimental Psychology. General, 133 ( 1 ), 101 – 135 . doi:10.1037/0096-3445.133.1.101 Google Scholar Crossref Search ADS WorldCat Galván , A . ( 2010 ). Neural plasticity of development and learning . Human Brain Mapping , 31 ( 6 ), 879 – 890 . doi: 10.1002/hbm.21029 Google Scholar Crossref Search ADS PubMed WorldCat Goffaux , P. , Phillips , N. A., Sinai , M., & Pushkar , D. ( 2008 ). Neurophysiological measures of task-set switching: Effects of working memory and aging . The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences, 63 ( 2 ), P57 – P66 . doi:10.1093/geronb/63.2.p57 Google Scholar Crossref Search ADS WorldCat Gold , B. T . ( 2015 ). Lifelong bilingualism and neural reserve against Alzheimer’s disease: A review of findings and potential mechanisms . Behavioural Brain Research, 281 , 9 – 15 . doi:10.1016/j.bbr.2014.12.006 Google Scholar Crossref Search ADS WorldCat Gold , B. T. , Kim , C., Johnson , N. F., Kryscio , R. J., & Smith , C. D., ( 2013 ). Lifelong bilingualism maintains neural efficiency for cognitive control in aging . Journal of Neuroscience, 33 ( 2 ), 387 – 396 . doi:10.1523/JNEUROSCI.3837-12.2013 Google Scholar Crossref Search ADS WorldCat Gollan , T. H. , Sandoval , T., & Salmon , D. P. ( 2011 ). Cross-language intrusion errors in aging bilinguals reveal the link between executive control and language selection . Psychological Science, 22 ( 9 ), 1155 – 1164 . doi:10.1177/0956797611417002 Google Scholar Crossref Search ADS WorldCat Goral , M. , Campanelli , L., & Spiro , A. 3rd. ( 2015 ). Language dominance and inhibition abilities in bilingual older adults . Bilingualism (Cambridge, England), 18 ( 1 ), 79 – 89 . doi:10.1017/S1366728913000126 Google Scholar OpenURL Placeholder Text WorldCat Green , D. W. , & Abutalebi , J. ( 2013 ). Language control in bilinguals: The adaptive control hypothesis . Journal of Cognitive Psychology (Hove, England), 25 ( 5 ), 515 – 530 . doi:10.1080/20445911.2013.796377 Google Scholar Crossref Search ADS WorldCat Green , C. S. , & Bavelier , D. ( 2003 ). Action video game modifies visual selective attention . Nature, 423 ( 6939 ), 534 – 537 . doi:10.1038/nature01647 Google Scholar Crossref Search ADS WorldCat Green , C.S. & Bavelier , D. ( 2007 ). Action video game experience alters the spatial resolution of attention . Psychological Science , 18 , 88 – 94 . doi:10.1111/j.1467-9280.2007.01853.x Google Scholar Crossref Search ADS PubMed WorldCat Hilchey , M. D. , & Klein , R. M. ( 2011 ). Are there bilingual advantages on nonlinguistic interference tasks? Implications for the plasticity of executive control processes . Psychonomic Bulletin & Review, 18 ( 4 ), 625 – 658 . doi:10.3758/s13423-011-0116-7 Google Scholar Crossref Search ADS WorldCat Jylkkä , J. , Soveri , A., Wahlström , J., Lehtonen , M., Rodríguez-Fornells , A., & Laine , M. ( 2017 ). Relationship between language switching experience and executive functions in bilinguals: An Internet-based study . Journal of Cognitive Psychology, 29 ( 4 ), 404 – 419 . doi:10.1080/20445911.2017.1282489 Google Scholar Crossref Search ADS WorldCat Kousaie , S. , & Phillips , N. A. ( 2017 ). A behavioural and electrophysiological investigation of the effect of bilingualism on aging and cognitive control . Neuropsychologia, 94 , 23 – 35 . doi:10.1016/j.neuropsychologia.2016.11.013 Google Scholar Crossref Search ADS WorldCat Lehtonen , M. , Soveri , A., Laine , A., Järvenpää , J., de Bruin , A., & Antfolk , J. ( 2018 ). Is bilingualism associated with enhanced executive functioning in adults? A meta-analytic review . Psychological Bulletin, 144 ( 4 ), 394 – 425 . doi:10.1037/bul0000142 Google Scholar Crossref Search ADS WorldCat Luk , G. , & Bialystok , E. ( 2013 ). Bilingualism is not a categorical variable: Interaction between language proficiency and usage . Journal of Cognitive Psychology (Hove, England), 25 ( 5 ), 605 – 621 . doi:10.1080/20445911.2013.795574 Google Scholar Crossref Search ADS WorldCat MacIntyre , P. D. , Noels , K. A., & Clément , R. ( 1997 ). Biases in self‐ratings of second language proficiency: The role of language anxiety . Language Learning , 47 ( 2 ), 265 – 287 . doi:10.1111/0023-8333.81997008 Google Scholar Crossref Search ADS WorldCat MacLeod , C. M . ( 1991 ). Half a century of research on the Stroop effect: An integrative review . Psychological Bulletin, 109 ( 2 ), 163 – 203 . doi:10.1037/0033-2909.109.2.163 Google Scholar Crossref Search ADS WorldCat Manard , M. , Carabin , D., Jaspar , M., & Collette , F. ( 2014 ). Age-related decline in cognitive control: The role of fluid intelligence and processing speed . BMC Neuroscience, 15 , 7 . doi:10.1186/1471-2202-15-7 Google Scholar Crossref Search ADS WorldCat Marian , V. , Blumenfeld , H. K., & Kaushanskaya , M. ( 2007 ). The Language Experience and Proficiency Questionnaire (LEAP-Q): Assessing language profiles in bilinguals and multilinguals . Journal of Speech, Language, and Hearing Research, 50 ( 4 ), 940 – 967 . doi:10.1044/1092-4388(2007/067) Google Scholar Crossref Search ADS WorldCat McAuley , E. , Kramer , A. F., & Colcombe , S. J. ( 2004 ). Cardiovascular fitness and neurocognitive function in older adults: A brief review . Brain, Behavior, and Immunity, 18 ( 3 ), 214 – 220 . doi:10.1016/j.bbi.2003.12.007 Google Scholar Crossref Search ADS WorldCat Miyake , A. , & Friedman , N. P. ( 2012 ). The nature and organization of individual differences in executive functions: Four general conclusions . Current Directions in Psychological Science, 21 ( 1 ), 8 – 14 . doi:10.1177/0963721411429458 Google Scholar Crossref Search ADS WorldCat Nasreddine , Z. S. , Phillips , N. A., Bédirian , V., Charbonneau , S., Whitehead , V., Collin , I., . . . Chertkow , H. ( 2005 ). The Montreal Cognitive Assessment, MoCA: A brief screening tool for mild cognitive impairment . Journal of the American Geriatrics Society, 53 ( 4 ), 695 – 699 . doi:10.1111/j.1532-5415.2005.53221.x Google Scholar Crossref Search ADS WorldCat Pallant , J . ( 2013 ). SPSS survival manual . UK : McGraw-Hill Education . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Prior , A. , & Macwhinney , B. ( 2009 ). A bilingual advantage in task switching . Bilingualism: Language and Cognition , 13 ( 2 ), 253 – 262 . doi:10.1017/S1366728909990526 Google Scholar Crossref Search ADS WorldCat Raven , J. , Raven , J. C., & Court , J. H. ( 2004 ). Manual for Raven’s progressive matrices and vocabulary scales. San Antonio, TX : Harcourt . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Rodriguez-Fornells , A. , Krämer , U. M., Lorenzo-Seva , U., Festman , J., & Münte , T. F. ( 2012 ). Self-assessment of individual differences in language switching . Frontiers in Psychology, 2 , 388 . doi:10.3389/fpsyg.2011.00388 Google Scholar Crossref Search ADS WorldCat Schmiedek , F. , Li , S. C., & Lindenberger , U. ( 2009 ). Interference and facilitation in spatial working memory: Age-associated differences in lure effects in the n-back paradigm . Psychology and Aging , 24 ( 1 ), 203 – 210 . doi:10.1037/a0014685. Google Scholar Crossref Search ADS PubMed WorldCat Sekerina , I. A. , Spradlin , L., & Valian , V. ( 2019 ). Bilingualism, executive function, and beyond . Bilingualism, Executive Function, and Beyond: Questions and insights . Retrieved from http://books.google.com. Soveri , A. , Rodriguez-Fornells , A., & Laine , M. ( 2011 ). Is there a relationship between language switching and executive functions in bilingualism? Introducing a within group analysis approach . Frontiers in Psychology, 2 , 183 . doi:10.3389/fpsyg.2011.00183 Google Scholar Crossref Search ADS WorldCat Stanislaw , H. , & Todorov , N. ( 1999 ). Calculation of signal detection theory measures . Behavior Research Methods, Instruments, & Computers, 31 ( 1 ), 137 – 149 . doi:10.3758/bf03207704 Google Scholar Crossref Search ADS WorldCat Tanner , W. P. Jr, & Swets , J. A. ( 1954 ). A decision-making theory of visual detection . Psychological Review, 61 ( 6 ), 401 – 409 . doi:10.1037/h0058700 Google Scholar Crossref Search ADS WorldCat Treitz , F. H. , Heyder , K., & Daum , I. ( 2007 ). Differential course of executive control changes during normal aging . Neuropsychology, Development, and Cognition. Section B, Aging, Neuropsychology and Cognition, 14 ( 4 ), 370 – 393 . doi:10.1080/13825580600678442 Google Scholar Crossref Search ADS WorldCat Tucker-Drob , E. M. , Johnson , K. E., & Jones , R. N. ( 2009 ). The cognitive reserve hypothesis: A longitudinal examination of age-associated declines in reasoning and processing speed . Developmental Psychology , 45 ( 2 ), 431 – 446 . doi: 10.1037/a0014012 Google Scholar Crossref Search ADS PubMed WorldCat Van der Elst , W. , Van Boxtel , M. P., Van Breukelen , G. J., & Jolles , J. ( 2006 ). The Stroop color-word test: Influence of age, sex, and education; and normative data for a large sample across the adult age range . Assessment, 13 ( 1 ), 62 – 79 . doi:10.1177/1073191105283427 Google Scholar Crossref Search ADS WorldCat Weissberger , G. H. , Gollan , T. H., Bondi , M. W., Clark , L. R., & Wierenga , C. E. ( 2015 ). Language and task switching in the bilingual brain: Bilinguals are staying, not switching, experts . Neuropsychologia, 66 , 193 – 203 . doi:10.1016/j.neuropsychologia.2014.10.037 Google Scholar Crossref Search ADS WorldCat Whitford , V. , & Luk , G. ( 2019 ). Comparing executive functions in monolinguals and bilinguals . Bilingualism, executive function, and beyond: Questions and insights , 67 – 79 . Retrieved from http://books.google.com. Yow , W. Q. , & Li , X. ( 2015 ). Balanced bilingualism and early age of second language acquisition as the underlying mechanisms of a bilingual executive control advantage: Why variations in bilingual experiences matter . Frontiers in Psychology, 6 , 164 . doi:10.3389/fpsyg.2015.00164 Google Scholar Crossref Search ADS WorldCat Zhang , H. , Wu , Y. J., & Thierry , G. ( 2020 ). Bilingualism and aging: A focused neuroscientific review . Journal of Neurolinguistics , 54 , 100890 . doi:10.1016/j.jneuroling.2020.100890 Google Scholar Crossref Search ADS WorldCat Zhou , B. , & Krott , A. ( 2016 ). Data trimming procedure can eliminate bilingual cognitive advantage . Psychonomic Bulletin & Review , 23 (4) , 1221 – 1230 . doi:10.3758/s13423-015-0981-6 Google Scholar Crossref Search ADS PubMed WorldCat Author notes These authors contributed equally to this work. © The Author(s) 2020. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)
TI - Active Bilingualism in Aging: Balanced Bilingualism Usage and Less Frequent Language Switching Relate to Better Conflict Monitoring and Goal Maintenance Ability
JF - The Journals of Gerontology Series B: Psychological Sciences and Social Sciences
DO - 10.1093/geronb/gbaa058
DA - 2020-10-16
UR - https://www.deepdyve.com/lp/oxford-university-press/active-bilingualism-in-aging-balanced-bilingualism-usage-and-less-I4om91Vl4N
SP - e231
EP - e241
VL - 75
IS - 9
DP - DeepDyve
ER -