What causes the bilingual disadvantage in verbal

C Cambridge University Press 2010 doi:10.1017/S1366728909990514 Bilingualism: Language and Cognition 13 (2), 2010, 231–252

What causes the bilingual disadvantage in verbal fluency? The dual-task analogy∗

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T I F FA N Y C . S A N D OVA L University of California San Diego, San Diego State University

TA M A R H . G O L L A N V I C TO R S . F E R R E I R A DAV I D P. SA L M O N University of California San Diego

(Received: September 18, 2008; Revised: December 2, 2008; Accepted: December 8, 2008; First published online 6 January 2010)

We investigated the consequences of bilingualism for verbal fluency by comparing bilinguals to monolinguals, and dominant versus non-dominant-language fluency. In Experiment 1, bilinguals produced fewer correct responses, slower first response times and proportionally delayed retrieval, relative to monolinguals. In Experiment 2, similar results were obtained comparing the dominant to the non-dominant languages within bilinguals. Additionally, bilinguals produced significantly lower-frequency words and a greater proportion of cognate responses than monolinguals, and bilinguals produced more cross-language intrusion errors when speaking the non-dominant language, but almost no such intrusions when speaking the dominant language. These results support an analogy between bilingualism and dual-task effects (Rohrer et al., 1995), implying a role for between-language interference in explaining the bilingual fluency disadvantage, and suggest that bilingual fluency will be maximized under testing conditions that minimize such interference. More generally, the findings suggest a role for selection by competition in language production, and that such competition is more influential in relatively unconstrained production tasks.

Introduction Throughout the world, many people routinely use more than one language to communicate (Moreno and Kutas, 2005), and they seem to carry the roughly doubled load associated with bilingualism without apparent difficulty. Bilingualism is somewhat less common in the United States, but the number of bilinguals is substantial (approximately 20 percent of the population) and rapidly increasing (US Census, 2000). The existence of both bilingualism and monolingualism provides an opportunity to examine the mechanisms of language production by asking how bilingualism influences the ability to rapidly produce words in each language. Bilinguals seem to effortlessly use both languages at high levels of proficiency in daily language use. However, bilingualism does introduce some processing costs. Compared to monolinguals, bilinguals name fewer pictures on standardized tests such as the Boston Naming Test (Roberts, Garcia, Desrochers and Hernandez, 2002; Gollan, Fennema-Notestine, Montoya and Jernigan, * This research was supported by a Predoctoral Individual National Research Service Award from NIA (F31AG028971) to Tiffany Sandoval, by an R01 from NICHD (HD050287) and a Career Development Award from NIDCD (DC00191), both awarded to Tamar H. Gollan, by an R01 from NIH (HD051030) awarded to Victor S. Ferreira, and by a P50 (AG05131) from NIH/NIA to the University of California.

2007), name pictures more slowly (Gollan, Montoya, Fennema-Notestine and Morris, 2005), experience more tip-of-the-tongue (TOT) retrieval failures (Gollan and Silverberg, 2001) and have reduced verbal fluency (Gollan, Montoya and Werner, 2002; Rosselli et al., 2000). Importantly, bilinguals are relatively less fluent than monolinguals, even when tested exclusively in their dominant (Gollan and Acenas, 2004, Gollan, Bonanni and Montoya, 2005) and first-learned language (Ivanova and Costa, 2008; Ransdell and Fischler, 1987). Although recent work confirms the presence of a bilingual disadvantage in the verbal fluency task (e.g., Portocarrero, Burright, and Donovick, 2007; Bialystok, Craik and Luk, 2008a), the mechanism explaining this disadvantage remains unclear. In the fluency task (see, e.g., Benton, Hamsher and Sivan, 1983), speakers are typically given one minute to name members of a semantic (e.g., “animals”) or letter category (e.g., “words that begin with s”). Perhaps the most obvious possible difference between bilinguals and monolinguals that could explain the bilingual disadvantage is that only bilinguals may need to simultaneously retrieve target language exemplars while controlling interference from the non-target language. Unintended activation of words from the nontarget language could delay retrieval of target language exemplars, thus leading bilinguals to produce fewer correct responses than monolinguals. A related alternative possibility is that bilinguals simply retrieve target

Address for correspondence: Tamar H. Gollan, University of California, San Diego, Shiley-Marcos Alzheimer’s Research Center, 9500 Gilman Drive #0949, La Jolla, California 92093–0949, USA [email protected]

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T. C. Sandoval, T. H. Gollan, V. S. Ferreira and D. P. Salmon

language exemplars more slowly than monolinguals, but without any direct interference from the non-target language (e.g., Gollan, Montoya, Cera and Sandoval, 2008). A third, and qualitatively distinct, mechanism that could also lead to a bilingual fluency disadvantage is betweengroup differences in language-specific vocabulary knowledge. Bilinguals clearly know many more words than monolinguals when words from both languages are counted, but within each language bilinguals may know fewer names than monolinguals (e.g., Bialystok et al., 2008a; Gollan and Acenas, 2004; Gollan and Brown, 2006). Of course, it is possible that more than one mechanism concurrently affects bilingual verbal fluency (i.e., that these accounts are not mutually exclusive), in which case the question can then be framed as to which mechanism is primarily responsible for producing the reported bilingual disadvantage in verbal fluency. To distinguish between the three alternative accounts of the bilingual disadvantage (interference between languages, retrieval slowing without interference, and reduced vocabulary), it is useful to consider the qualitative aspects of responses produced. Although all three mechanisms can explain the bilingual disadvantage, they make distinct predictions in terms of how bilingualism should influence retrieval time-course, the average wordfrequency count of exemplars produced, and the rate of cross-language intrusions. Retrieval slowing with interference between languages: the dual-task analogy A common assumption in models of bilingual language processing is the notion of active interference between languages (Green, 1998; for reviews of the evidence for and against the interference assumption, see Costa 2005; Kroll, Bobb and Wodniecka, 2006; Kroll, Bobb, Misra and Guo, 2008; La Heij, 2005). On this view, bilinguals cannot “turn one language off” to effectively act as monolingual speakers. As such, when bilinguals speak one language, the other language continues to be active and must be inhibited. Some of the most compelling evidence that bilingualism entails a constant exercise in inhibitory control comes indirectly in the form of enhanced executive control mechanisms for bilinguals throughout the lifespan. For example, bilingual children performed better than monolingual children on a card-sorting task (Bialystok and Martin, 2004), in which participants need to switch from previously learned sorting rules (e.g., color) to new rules (e.g., shape). Similarly, older bilinguals outperformed agematched monolinguals on a Simon task (Bilaystok, Craik, Klein and Viswanathan, 2004; see also Bialystok, Craik and Ryan, 2006; Craik and Bialystok, 2006; Bialystok, 2005), in which participants attempt to follow a rule (e.g., press the right key when you see a red square)

when it is presented either congruently (on the right side) or incongruently (on the left) with a competing prepotent cue (side of the screen). A similar advantage was recently reported in young adult bilinguals at the peak of their attentional control abilities (using the Attentional Network Task; Costa, Hernandez and Sebastián-Gallés, 2008). Finally, more recent evidence associates bi- or multilingualism with “cognitive reserve” and a delay in age- or dementia-related cognitive decline (Bialystok, Craik and Freedman, 2007; Kavé, Eyal, Shorek and Cohen-Mansfield, 2008). Such bilingual advantages are typically attributed to the need to control the non-target language each time bilinguals speak. By implication, bilingual advantages in such tasks imply selection by competition and the use of general mechanisms of executive control for resolving competition in lexical selection. In studies of bilingual language processing, the role of inhibitory control has been more controversial, sometimes revealing evidence for (e.g., Hermans, Bongaerts, De Bot and Schreuder, 1998) and other times evidence against (e.g., Costa and Carmazza, 1999) competition for selection between languages. Some experimental findings suggest that dominant language production is relatively immune to competition between languages (Gollan, Montoya et al., 2005; Gollan et al., 2008), particularly in balanced bilinguals (e.g., Costa and Caramazza, 1999; Costa and Santesteban, 2004). Notably, a similar debate is active within studies of monolingual language production, with some arguing for the notion of competition for selection between semantically related lexical representations (e.g., Levelt, Roelofs and Meyer, 1999), and others arguing against such competition (e.g., Costa, Alario and Caramazza, 2005). Although inhibitory control may play a limited role (or no role; Finkbeiner, Almeida, Janssen and Caramazza, 2006) in picture naming in the dominant language (e.g., Gollan, Montoya et al., 2005; Gollan et al., 2008), the role of inhibitory control may be greater in other tasks. For example, language mixing has relatively little effect on non-dominant language production, but a powerful effect on dominant language production (e.g., Meuter and Allport, 1999), in some cases leading language dominance to reverse (such that bilinguals name pictures more quickly in their usually non-dominant language; e.g., Christoffels, Firk and Schiller, 2007). Dominance reversal implies a strong role for inhibitory control of the dominant language during language mixing (Kroll et al., 2008; Gollan & Ferreira, 2009) and, by extension, support for the assumption of competition for selection between languages. The majority of studies designed to test the interference account have used the picture-naming task. The verbal fluency task differs from picture naming in important ways and affords the possibility of viewing production

Bilingual verbal fluency processes under a different magnifying glass. Picturenaming tasks are relatively constrained in that speakers must produce a single specific target word when provided with a stimulus that activates a single concept. Once the picture name is retrieved, the speaker can move on to the next word and is again provided with a stimulus (a different picture) that activates another single concept. In contrast, in the verbal fluency task, speakers are given a single cue (a category name) which activates multiple concepts, and then they must select one name at a time, selecting among several alternatives without being given any additional cues to assist them in selecting one concept over another, and while also needing to suppress justproduced exemplars, and to continue to search their lexicon to maintain production as fluently as possible. Because natural language production no doubt also entails simultaneous activation of multiple concepts and extended production of more than a single word at a time, the verbal fluency task is at least in some respects more similar to natural production than is picture naming. Of course picture naming is arguably more similar to natural production in other respects, particularly considering letter fluency (speakers seldom, if ever, need to produce a sequence of words that begin with the same sound), but also semantic fluency (e.g., sequences of content words are not typically all semantically related). Given that the verbal fluency task necessarily activates multiple related lexical representations, it may be ideally suited for revealing the possible effects of between-language interference in bilinguals, and competition for selection within languages in monolinguals. Retrieval slowing without interference: the weaker links account A different view of bilingual disadvantages assumes that bilingualism affects language production indirectly via frequency of use. On this account, bilingual disadvantages arise simply because bilinguals use each language only some of the time, and therefore use words in each language relatively less often than monolinguals, who use just one language all the time (for detailed explanation, see Gollan et al., 2008; see also Ivanova and Costa, 2008; Lehtonen and Laine, 2003; Mägiste, 1979; Nicoladis, Palmer and Marentette, 2007; Pearson, 1997; Ransdell and Fischler, 1987). This account has been called the “weaker links” account to distinguish it from interference (Gollan et al., 2008), and explains bilingual disadvantages in an emergent way by relying on the well-established relationship between degree of language use and lexical accessibility, such that high-frequency words are accessed more quickly than low-frequency words (e.g., Oldfield and Wingfield, 1965; Scarborough, Cortese and Scarborough, 1977). The most direct evidence supporting the weaker links account is that the bilingual disadvantage in

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picture naming is greater when producing low-frequency than high-frequency picture names (Gollan et al., 2008; Ivanova and Costa, 2008). The greater bilingual disadvantage for low-frequency words is expected, according to the weaker links hypothesis, because lowfrequency words are more sensitive to small differences in degree of use than high-frequency words (for review, see Murray and Forster, 2004). Also consistent with weaker links is that language dominance effects patterned similarly; bilinguals named pictures in the less-frequently used language more slowly than the dominant language, but language dominance effects were especially large for low-frequency words. A different way of stating both results is to say that bilinguals showed a greater frequency effect than monolinguals, and the non-dominant language showed a greater frequency effect than the dominant language. The increased size of the frequency effect in bilinguals relative to monolinguals suggests that bilinguals lag behind monolinguals in language-specific language use. Because of a ceiling effect on the extent to which increased frequency of use can increase lexical accessibility (e.g., Griffin and Bock, 1998), decreased language use associated with bilingualism leads to a greater disadvantage for accessing low- rather than highfrequency words. To distinguish weaker links from interference mechanisms of the bilingual advantage we examine word-frequency counts of exemplars that bilinguals and monolinguals produce. Having identified a greater bilingual disadvantage for low-frequency words in picture naming (Gollan et al., 2008; Ivanova and Costa, 2008), the weaker links account predicts that bilinguals will be less likely than monolinguals to retrieve low-frequency words, and thus on average will produce higherfrequency exemplars than monolinguals. The interference hypothesis makes the opposite prediction concerning word frequency. Because high-frequency words are more readily accessible in both languages than low-frequency words (e.g., most Spanish–English bilinguals know how to say “carrot” in both languages, but they might know “eggplant” in just one language), the possibility for interference between languages should be greatest for high-frequency words (for detailed explanation, see Gollan et al., 2008). If competition between languages is greater for high-frequency translations, then bilinguals should produce fewer high-frequency exemplars than monolinguals, and thus on average will produce lowerfrequency exemplars than monolinguals in the fluency task (the opposite prediction of the weaker links account). Note the counter-intuitive nature of this prediction, given the finding that production of low-frequency words is particularly difficult for bilinguals (Gollan et al., 2008; Ivanova and Costa, 2008). Thus, the frequency of words produced in the verbal fluency task provides a further test of competition mechanisms and the possibility of

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distinguishing between the weaker links and interference mechanisms of the bilingual fluency disadvantage1 . If bilinguals and monolinguals differ with respect to the word frequency of responses produced, it will be important to determine whether this result could be attributed to COGNATE status – translations that are similar between languages (e.g., saxophone–saxofón). Bilinguals produce cognates more easily than noncognates (Costa, Caramazza and Sebastián-Gallés, 2000; Gollan and Acenas, 2004). If cognates are updated for frequency in both languages each time they occur in either language, then cognates will be about as high frequency for bilinguals as they are for monolinguals, non-cognates (in both languages) will be lower frequency for bilinguals than they are for monolinguals, and cognate frequencies in the bilingual lexicon would be systematically underestimated by monolingual frequency counts in terms of their rank order relative to noncognate frequencies. As such, below we consider whether bilinguals produce more cognates than monolinguals, and if so how this influences the frequency count of exemplars produced by bilinguals and monolinguals. Consideration of cognate status also provides an additional opportunity to evaluate the possible effects of bilingualism on verbal fluency; cognate effects would support the notion that dual-language activation affects verbal fluency. The reduced vocabulary hypothesis: the category size analogy The third alternative explanation for the bilingual verbal fluency disadvantage is that bilinguals may be retrieving words from a slightly smaller pool of exemplar names than monolinguals. The fluency task typically restricts responses to just one language (but see Gollan et al., 2002; de Picciotto and Friedland, 2001), and within each language, bilinguals may not know, or may be unable to access, as many words as monolinguals. Supporting the notion of vocabulary differences between bilinguals and monolinguals, studies reveal that bilinguals have lower receptive vocabulary scores than monolinguals on standardized tests such as the Peabody Picture Vocabulary Test (PPVT; e.g., Bialystok, Craik and 1

Note that the interference account could be modified to accommodate the findings by Gollan et al. (2008). Specifically, it might be suggested that interference between languages is greatest when retrieving lowfrequency words which are more difficult to retrieve. In this case the interference account would make similar predictions with respect to response word frequency in the fluency task. Although there is some evidence from studies of monolingual language production suggesting greater effects of competition for selection for lowfrequency alternative names (e.g., limousine and limo) than for highfrequency alternatives (e.g., TV and television; Spieler & Griffin, 2006; but see Griffin, 2001) this interpretation of the interference account is tentative at best given the lack of additional evidence to support it.

Luk, 2008b). Because comprehension generally precedes production in lexical accessibility, any differences that can be observed on comprehension-based measures (such as the PPVT) will likely be present in tasks (like verbal fluency) that require language production. In both production and comprehension, reduced vocabulary knowledge in bilinguals is likely to specifically reflect reduced knowledge of relatively low-frequency words (because higher-frequency words will be learned before low-frequency words). Consistent with this notion, studies of the TOT phenomenon (which focus exclusively on production of very-low-frequency words, e.g., periscope) suggest that bilinguals are more likely to fail to retrieve a known word (have more TOTs) than monolinguals. The same studies also show that bilinguals reported recognizing fewer target words than monolinguals, that is, they have reduced knowledge of low-frequency vocabulary words in their dominant language relative to monolinguals (Gollan and Silverberg, 2001; Gollan and Acenas, 2004; Gollan, Bonanni and Montoya, 2005; Gollan and Brown, 2006). Thus, the reduced vocabulary hypothesis leads to similar predictions as the weaker links account in terms the frequency of exemplars. However, it is possible to distinguish between weaker links and vocabulary by examining the time-course of retrieval. Because speakers produce progressively lower-frequency words with increased time into the fluency trial (Crowe, 1998), and bilinguals’ vocabulary knowledge is smaller at the low-frequency end of the lexicon, the reduced vocabulary mechanism predicts that the bilingual disadvantage should be absent at the beginning of the trial, and should emerge primarily towards the end of the fluency trial. In contrast, the interference account predicts a robust bilingual disadvantage at the beginning of the fluency trial (where competition between languages is most likely), as does the weaker links account, because, although smaller for high-frequency words, a bilingual disadvantage was observed for both high- and low-frequency words (Gollan, Montoya et al., 2005; Gollan et al., 2008). Measuring the time-course of retrieval: the fulcrum point To measure the retrieval time-course we rely on a measure that was developed in the context of research on monolingual verbal fluency performance. To this end, we draw an analogy between the mechanisms of the bilingual disadvantage and factors known to influence fluency performance in monolinguals. The first analogy is between the interference account and dual-task effects on verbal fluency production. After a bilingual speaker retrieves an exemplar in the target language, the search for additional category members could easily trigger activation of translation equivalents in the non-target

Bilingual verbal fluency language. If bilinguals cannot prevent retrieval of exemplar names from both languages, they would need to monitor the language of output to avoid producing cross-language intrusions. In contrast, monolinguals need only retrieve category names in the one language they know. On this view, the task demands associated with verbal fluency are greater for bilinguals, who are essentially engaged in two concurrent tasks. Rohrer, Wixted, Salmon and Butters (1995) found that when monolingual speakers were asked to produce category members while concurrently performing a secondary task (i.e., monitoring the number of dots that appeared on a computer screen by finger tapping), they produced fewer category members, took longer to produce a first response and, most importantly in the present context, their subsequent responses were delayed such that a greater proportion were produced towards the end of the trial, when compared with single-task settings. As a measure of the relative distribution of responses across the fluency trial in single- versus dual-task situations, Rohrer et al. (1995) introduced a measure that they called “mean response latency”, which is the average time to produce each response with each time calculated from the beginning of the trial. The effect of dual tasking on mean retrieval latency is most easily understood by considering a hypothetical case in which the same number of correct responses is produced in both single- and dualtask settings. For example, assume speakers correctly retrieve in both single- and dual-task settings all four exemplars of a category with just four exemplars (e.g., primary directions on a compass). In the single task these might be retrieved at 2, 4, 6 and 8 seconds, resulting in a mean retrieval latency of (4 + 6 + 8) / 3 (i.e., 6.0) (first response latencies are excluded because they may reflect different processes related to initiating production, though this exclusion does not have a very big effect on mean retrieval latencies; Rohrer et al., 1995). During the dual task, each response is delayed because of the need to carry out the secondary task, and so responses might be retrieved at 3, 6, 9 and 12 seconds for a mean time of (6 + 9 + 12) / 3 (i.e., 9.0). Importantly, when measured this way (with each exemplar time counted from the beginning of the trial), mean retrieval latency is not a simple measure of response speed; generalized slowing does not necessarily lead to longer mean response latencies. To avoid confusion between Rohrer et al.’s mean response latency measure and simple measures of response speed, we refer to mean response latency as the “fulcrum point’, which illustrates that the measure reflects the balance of responses in terms of when they occur across the fluency trial. As an example, monolinguals with Alzheimer’s disease named pictures much more slowly than agematched controls (between 14% and 22% more slowly in Thompson-Schill, Gabrieli and Fleischman, 1999;

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see also Vandenberghe, Vandenbulcke and Weintraub, 2005), but produced significantly SHORTER fulcrum points than age-matched controls in the fluency task (Rohrer et al., 1995; Rohrer, Salmon, Wixted and Paulsen, 1999). This point illustrates how straightforward comparisons of reaction times and fulcrum points are misleading. What is critical for influencing the fulcrum point is the relative distribution of responses during the trial; longer fulcrum points indicate a greater proportion of the total responses produced toward the end of the trial. Patients with Alzheimer’s disease have shorter (but not faster) mean retrieval latencies in category fluency because they produce exemplars at the beginning of the trial but then exhaust their pool of retrievable responses more quickly. In contrast, age-matched controls continue retrieving exemplars well into the minute-long trial, consequently yielding longer mean retrieval latencies. Figure 1a displays the expected differences between bilinguals and monolinguals in predicted the mean fulcrum point if the bilingual fluency disadvantage arises because of interference between languages that effectively places bilinguals under dual-task demands. Here, we assume that the bilingual to monolingual comparison should resemble the dual- to single-task comparison reported in prior studies. As such, bilinguals should produce fewer correct responses, delayed first response times, and a later fulcrum point than monolinguals. The pronounced delay in fulcrum point is expected because some of the time, and particularly early on in the fluency trial (where between-language interference should be greatest), bilinguals will retrieve names in the non-target language, and will need to suppress the production of these words before retrieving additional target language exemplars. The prediction of the weaker links hypothesis with respect to fulcrum points depends on an additional assumption: Can speakers search a semantic category for exemplars at the same time as they produce the name of an already identified category member? If search and production cannot proceed in parallel, then retrieval slowing will be cumulative across the fluency trial, such that with each consecutive exemplar produced, bilinguals’ fulcrum points will be increasingly delayed relative to those of monolinguals. For example, in picture-naming studies, the extent of slowing related to bilingualism for producing each picture name was 80–150 ms (Gollan, Montoya et al., 2005; Gollan et al., 2008). As such, a category that leads speakers to retrieve approximately 10 exemplars should yield a delay in fulcrum point on the order of about 0.8 to 1.5 seconds (e.g., 10 × 150 ms = 1,500 ms), and the weaker links account would predict a small delay in fulcrum point for bilinguals relative to monolinguals. Alternatively, if category search can proceed in parallel with production of a selected exemplar (for review, see

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Figure 1. Idealized response latencies representing (1a) retrieval slowing and (1b) the reduced vocabulary hypothesis in a single trial of verbal fluency. Bilingual data are represented by circles and monolinguals’ data are represented by the diamonds. The solid rectangles on the x-axis indicate the fulcrum points for bilinguals and monolinguals in each hypothetical case. The panel entitled “Retrieval Slowing” illustrates the predictions of the interference account (1a): bilinguals’ responses are shifted to the right, particularly at the beginning of the trial where between-language interference is greatest. The panel entitled “Vocabulary Size” illustrates the reduced vocabulary hypothesis (1b): bilinguals have shorter fulcrum points because they exhaust their pool of retrievable responses prior to monolinguals.

Rohrer, Pashler and Etchegaray, 1998), then there should be virtually no change in fulcrum points associated with bilingualism, according to the weaker links account. This is because differences of 80–150 ms are negligible when considered with respect to fulcrum points on the order of 25–30 seconds within a minute-long verbal fluency trial, and in a parallel model, the delay associated with bilingualism would not be cumulative across exemplars because bilinguals could search for subsequent exemplars while producing each exemplar. Note that the fulcrum point is an average, therefore, if each bilingual response is slowed by (for example) 150 ms, but category search can proceed at the same time as production, then the fulcrum point will only be right-shifted by 150 ms, according to the weaker links account. To outline the predictions of the vocabulary size account, we draw a second analogy between category size effects on monolingual fluency and the bilingual effect. Smaller category size introduced the opposite effect

on fulcrum point relative to dual-task effects (Rohrer et al., 1995). Whereas dual-task conditions delayed the fulcrum point, when speakers retrieved exemplars from smaller categories they had earlier fulcrum points than when retrieving exemplars from larger categories (Rohrer et al., 1995). This difference was obtained because, when producing exemplars from smaller categories, speakers produced a greater proportion of exemplars at the beginning of the trial, and then approached asymptote more quickly than when retrieving from larger categories. Thus, when speakers can retrieve a smaller number of exemplars, whether because of smaller category size or because of reduction in knowledge as a consequence of Alzheimer’s disease, speakers exhaust their knowledge of exemplars by the end of the trial and fulcrum points are shortened (or pushed to the left). Figure 1b illustrates the expected difference between bilinguals and monolinguals in mean fulcrum point if the bilingual fluency disadvantage stems from reduced

Bilingual verbal fluency

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Table 1. Means (M) and standard deviations (SD) of participant characteristics in Experiment 1. Experiment 1 Englishdominant bilinguals (n = 24)

Age Education Age of first exposure to English Age of exposure to other language % English used daily Self-ratinga for spoken English Self-ratinga for spoken other language

Experiment 1 monolinguals (n = 30)

Experiment 2 Englishdominant bilinguals (n = 45)

M

SD

M

SD

M

SD

F-ratiob

p value

20.33 14.22 2.09 0.46 87.33 6.88 5.92

2.94 2.65 2.09 0.90 12.81 0.45 1.25

19.67 14.28 0.21 10.80 99.53 6.93 2.74

1.32 1.66 0.49 5.73 1.31 0.26 1.29

21.16 14.37 2.70 0.30 90.02 6.68 5.89

4.19 1.46 2.27 0.76 9.36 0.79 1.11

1.23