Cognitive control, word retrieval and bilingual aphasia: Is there ... - Umd

Journal of Neurolinguistics xxx (2016) 1e15

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Cognitive control, word retrieval and bilingual aphasia: Is there a relationship? Yasmeen Faroqi-Shah a, *, Monica Sampson b, Mariah Pranger a, Susan Baughman c a

Department of Hearing & Speech Sciences, University of Maryland, College Park, MD, USA American Speech-Language-Hearing Association, Rockville, MD, USA c Hallmark Rehabilitation, Eureka, CA, USA b

a r t i c l e i n f o

a b s t r a c t

Article history: Received 22 January 2015 Received in revised form 9 June 2016 Accepted 6 July 2016 Available online xxx

It is proposed that successful word retrieval involves lateral inhibition of lexical competitors, and suppression of the non-target language in bilingual speakers. Thus cognitive control is crucial for word production. Given that word retrieval difficulty is a hallmark feature of aphasia, the relationship between word retrieval and cognitive control in aphasia has not been sufficiently explored. This study examined whether persons with aphasia show 1) evidence of a cognitive control deficit, 2) bilingual status interacts with cognitive control deficit in persons with aphasia, and (3) a relationship between measures of word naming and cognitive control. Thirty-eight persons with aphasia were administered a task of cognitive control (Stroop color-word task) and two word production tasks (picture naming and category fluency). We found weakened cognitive control in aphasia relative to age-matched neurologically healthy adults. A bilingual advantage in cognitive control was found in neurologically healthy adults and in one group of bilingual speakers with aphasia, but not the other group. Word retrieval in persons with aphasia was not correlated with Stroop task performance. These findings show that cognitive control performance (as measured by the Stroop task) is compromised in persons with aphasia, irrespective of bilingual status. There was a bilingual advantage in two out of three groups, showing a general support for the bilingual inhibitory control advantage (BICA) hypothesis. © 2016 Elsevier Ltd. All rights reserved.

Keywords: Bilingualism Aphasia Word fluency Bilingual advantage Cognitive control

1. Introduction The cognitive processes underlying word production involve selecting a target lexical representation from numerous similar representations. For example, if a speaker wants to produce the word horse, the lexical representations of saddle, stable, dog, mule, stallion, etc. are co-activated. The mechanism by which a specific target word is rapidly narrowed down for production is debated. One prominent view proposes that lexical selection involves competition between co-activated semantically related representations (Levelt, 2001; Rahman & Melinger, 2009; Roelofs & Piai, 2015). Alternately, lexical selection is viewed as a non-competitive process, where the overall cumulative activation level of lexical representations

* Corresponding author. Department of Hearing and Speech Sciences, University of Maryland, 0100 Lefrak Hall, College Park, MD 20742, USA. E-mail addresses: [email protected] (Y. Faroqi-Shah), [email protected] (M. Sampson), [email protected] (M. Pranger), sus5an.baughman@ gmail.com (S. Baughman). http://dx.doi.org/10.1016/j.jneuroling.2016.07.001 0911-6044/© 2016 Elsevier Ltd. All rights reserved.

Please cite this article in press as: Faroqi-Shah, Y., et al., Cognitive control, word retrieval and bilingual aphasia: Is there a relationship?, Journal of Neurolinguistics (2016), http://dx.doi.org/10.1016/j.jneuroling.2016.07.001

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Y. Faroqi-Shah et al. / Journal of Neurolinguistics xxx (2016) 1e15

determines which word is eventually articulated (Dell, 1986; Finkbeiner & Caramazza, 2006; Mahon, Costa, Peterson, Vargas, & Caramazza, 2007; Miozzo & Caramazza, 2003). Irrespective of whether lexical selection proceeds via competition among related representations or not, it is assumed that lexical selection involves some level of interference resolution of unwanted candidates. Some authors propose that this occurs via an early top-down cognitive control mechanism triggered by language schema or contextual demands (Green, 1998). Others propose that unwanted lexical candidates are subdued by local inhibitory connections between lexical representations, also called lateral inhibition (Colzato et al., 2008; Dijkstra & Van Heuven, 1998; La Heij, 2005). Thus, cognitive control, which refers to processes of detection and resolution of interference and maintenance of goal-relevant representations, is crucial for word production. This study aims to elucidate the relationship between word retrieval and cognitive control by focusing on two variables: one that negatively influences word retrieval (aphasia) and the other supposedly poses cognitive control advantages (bilingualism). Lexical selection is especially vulnerable in persons with aphasia (PWA), a language impairment resulting from brain damage. PWA frequently report that the target word is at the tip-of-their tongue, and produce semantic paraphasias, which are semantic errors such as dog for horse. Such semantic paraphasias are indicative of a difficulty in lexical selection, perhaps due to insufficient resolution of the interference caused by related non-target lexical representations (Biegler, Crowther, & Martin, 2008). Could lexical selection difficulties in aphasia be a manifestation of weak interference resolution of lexical competitors? The primary goal of this study is to examine cognitive control in aphasia and its relationship with word retrieval success. For bilinguals (speakers of multiple languages), cognitive control is claimed to play an even larger role in word retrieval because of the additional need to suppress the lexical representations of the non-target language (Green’s inhibitory control model, 1998). Hence, a secondary goal of this study is to investigate cognitive control in bilingual aphasia, given the recent debate on cognitive advantages in neurologically healthy bilingual speakers (Hilchey & Klein, 2011; Paap & Greenberg, 2013). In the following sections, we will examine the evidence for the role of cognitive control in word retrieval, aphasia and bilingualism. 1.1. Cognitive control and word retrieval One approach to establishing a connection between cognitive control and word retrieval is based on identifying overlap in neural activation in functional brain imaging studies. The middle-to-inferior prefrontal cortex and dorsal anterior cingulate cortex are two regions frequently associated with tasks involving both domain general cognitive control and lexical selection (Bokde, Tagamets, Friedman, & Horwitz, 2005; Braver, 2012; Kerns et al., 2004; Piai, Roelofs, Acheson, & Takashima, 2013; de Zubicaray, McMahon, Eastburn, & Pringle, 2006; ; evidence reviewed in Abutalebi & Green, 2007 and Green & Abutalabi, 2013). Piai et al. (2013) examined neural correlates of picture word interference (PWI) and Stroop (Golden, 1978; Stroop, 1935) tasks in the same group of participants. Both PWI and Stroop have conflict conditions that demand higher cognitive control (semantically related distractors in PWI and incongruent trials in Stroop). Piai et al. (2013) found activation of anterior cingulate cortex in both tasks for only the conflict conditions, suggesting recruitment of similar cognitive control networks. The prefrontal and dorsal anterior cingulate regions are also found to be recruited by bilingual speakers who constantly negotiate cross-language competition, especially during language switching (Abutalebi et al., 2012; Crinion et al., 2006). The connection between cognitive control and word retrieval has also been investigated using an individual differences approach: performance on tasks known to tap cognitive control is correlated with performance on word retrieval. Bialystok, Craik, and Luk (2008) examined cognitive control using an adaptation of the Simon task that used arrows and Stroop color naming tasks, and word retrieval using verbal fluency (category and letter) and naming-to-definition tasks. In both the Simon arrows and Stroop color naming tasks, there are congruent and incongruent trials. The incongruent trials are designed to tap cognitive control, and the relative performance between incongruent and congruent trials is a measure of inhibition. In Simon arrows, participants indicate the direction of an arrow by pressing left and right arrow keys. In congruent trials the response key is in the same direction as the arrow and incongruent trials require pressing of the right arrow key for left pointing arrows and vice versa. In the Stroop task, participants name the font color of words, congruent trials show the word (e.g., GREEN) in the same font color, and incongruent trials show the word in a different font color (e.g., red). Bialystok et al. (2008) did not find a correlation between cognitive control and word retrieval measures in young or old monolingual or bilingual speakers. In contrast, Shao, Roelofs, and Meyer (2012) found a significant positive correlation between speed of lexical access and cognitive control in young adults. They examined cognitive control using the stop-signal task, in which participants respond to shapes (circle or square) by pressing specific keys on a keyboard, but have to withhold their response if they hear an auditory tone. Not only did Bialystok et al. (2008) and Shao et al. (2012) use different cognitive control and lexical tasks, but more crucially, they used different metrics for lexical access: speed and accuracy. While these differences could have accounted for the contradictory findings of the two studies, whether cognitive control correlates with lexical selection remains an open question. 1.1.1. Dual mechanisms of cognitive control For the sake of simplicity, until this point in the paper, we have treated cognitive control as a unitary concept. In reality, at least two types of mechanisms are identified (although the specifics of this division differ across authors and are beyond the scope of this paper): 1) a conscious level, used, for example, to actively maintain an abstract goal or task set, and 2) a more automatic (and sometimes local) mechanism that resolves interference arising during any cognitive process. The former cognitive control mechanism is can be thought of as ‘Do not do X’ (Munakata et al., 2011) and is implemented in anticipation Please cite this article in press as: Faroqi-Shah, Y., et al., Cognitive control, word retrieval and bilingual aphasia: Is there a relationship?, Journal of Neurolinguistics (2016), http://dx.doi.org/10.1016/j.jneuroling.2016.07.001


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of a cognitively demanding event. It has been called proactive (Braver, 2012; Green & Abutalabi, 2013; Hilchey & Klein, 2011; Kerns et al., 2004), directed global (Munakata et al., 2011), intentional (Miyake et al., 2000), or effortful (Sinopoli & Dennis, 2012). Examples of proactive inhibition include inhibiting fear response while coping with stress, or inhibiting reading responses during the Stroop task. The second cognitive control mechanism is automatically engaged during an activity and serves to aid selection by resolving local competition among candidate representations. It is viewed as transient, stimulusdriven activation triggered by interference demands or episodic associations (Braver, 2012). This cognitive control mechanism has been labeled reactive (Braver, 2012; Colzato et al., 2008; Green, 1998), indirect competitive (Munakata et al., 2011), or effortless (Sinopoli & Dennis, 2012). Examples of automatic cognitive control are instances of selective auditory attention while following a conversation in a noisy environment (cocktail party effect) and selection of word representations during speaking. Recent neurocognitive frameworks recognize this dichotomy of cognitive control mechanisms, and acknowledge that these two mechanisms are complementary, work in tandem based on cognitive demands, and have partially overlapping neural circuitry (Braver, 2012; Munakata et al., 2011). According to these frameworks, the prefrontal cortex is the hub for directed global inhibition, which then exerts its control on other regions. Indirect competitive inhibition occurs via excitatory neurons from the prefrontal cortex that enhances processing within specific cortical or subcortical regions depending on task demands. This regulates overall levels of activity of that region, enabling the most competitive representations to be selected for response. For example, a picture naming task would result in enhanced activation of middle temporal regions for lexical selection, which in turn allows the target lexical representation’s activation to rise above other non-target lexical representations (Munakata et al., 2011). The relevance of these distinctions in cognitive control for the present study is that lexical selection mainly engages local competitive cognitive control, bilingualism may strengthen both (or one of) local and global cognitive control mechanisms, and different conflict paradigms used in empirical research may differentially recruit global and local control. Thus, predictions about the relationship between word retrieval and cognitive control or the influence of bilingualism may be obscured (Baum & Titone, 2014; Colzato et al., 2008).

1.2. Cognitive control and aphasia The literature on cognitive control in PWA, and its link with language abilities is relatively sparse. In Stroop and Flanker arrows tasks, PWA show the typical effect of poorer performance in conditions that evoke response conflict compared to conditions that do not evoke response conflict in monolinguals (Pompon, McNeill, Spencer & Kendall, 2015) and bilinguals (Dash & Kar, 2014; Gray & Kiran, 2016; Green et al., 2010, 2011). The determination of a cognitive control impairment in PWA can be made by comparing the magnitude of difference between conflict and non-conflict conditions relative to healthy controls. Pompon et al. (2015) reported that healthy controls and PWA were about 3% and 5% slower respectively on conflict compared to non-conflict conditions. This could suggest a cognitive control deficit in PWA, however, the overall slowness of PWA (or any other neurologically impaired population) needs to be factored into the difference score (Green et al., 2010). Green et al. (2010) proposed standardizing the difference score when comparing PWA with healthy controls by calculating a conflict ratio (difference between incongruent and congruent trials divided by the congruent trials). Given that most prior studies have not accounted for the overall slowness of brain damaged persons, it is unclear if there is a cognitive control deficit per se in PWA. As for the connection between cognitive control and word retrieval, there are a few single case and small group studies describing a specific patient profile: persons who are either nonfluent, have lesions of the left inferior frontal gyrus (LIFG), and/or have dynamic aphasia (Freedman, Martin, & Biegler, 2004; Hamilton & Martin, 2005; McCarthy & Kartsounis, 2000; Robinson, Blair, & Cipolotti, 1998; Schnur et al., 2009; Schwartz & Hodgson, 2002; Scott & Wilshire, 2010; Thompson-Schill et al., 1998; Wilshire & McCarthy, 2002). The typical patient profile in these studies is a severe nonfluency and severely impaired performance in contexts with high selection demands. For example, Thompson-Schill et al. (1998) described four patients with LIFG damage who were selectively impaired in generating single verbs for nouns that could be associated with a variety of verbs (e.g., cat) but not for nouns that had fewer verb competitors (e.g., scissors). Generating verbs for the former category of nouns requires selection among multiple verb candidates and therefore inhibition of many more verbs than for nouns that have few verb associates. Based on these selection difficulties in patients with LIFG damage/dynamic aphasia, it has been proposed that these patients may have a general deficit in cognitive control mechanisms needed to resolve competition between conflicting representations. Consistent with this claim, two case studies reported exaggerated effects of conflict in the Stroop task (Hamilton & Martin, 2005; Scott & Wilshire, 2010). However, there are other lesion studies that failed to find an association between left frontal damage and impaired conflict resolution (Stuss, Floden, Alexander, Levine, & Katz, 2001; Vendrell et al., 1995). Given that word retrieval deficits are ubiquitous in aphasia, primarily due to weakened lexical-semantic representations, cognitive control likely plays a crucial role in facilitating lexical selection. Conversely, it is conceivable that cognitive control deficits, even if subtle, do not contribute to word retrieval deficits in PWA. The findings thus far are inconclusive. Hence, in this study, we investigate cognitive control in PWA and examine the relationship between cognitive control and word retrieval. Please cite this article in press as: Faroqi-Shah, Y., et al., Cognitive control, word retrieval and bilingual aphasia: Is there a relationship?, Journal of Neurolinguistics (2016), http://dx.doi.org/10.1016/j.jneuroling.2016.07.001

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1.3. Cognitive control and bilingualism The crucial role of cognitive control in bilingual speakers rests on two findings. First, both languages of bilinguals are active & Miozzo, 2010; Costa, Miozzo, & Caramazza, 1999; Hermans, Bongaerts, De Bot, & Schreuder, 1998; at all times (Colome Marian & Spivey, 2003). And secondly, the non-target language needs to be suppressed in order to avoid cross-language intrusions. Language production (in bilinguals) engages cognitive control at two levels: a global (language schema) level at which the relative activation of L1 (first language) and L2 (second language) is modulated, and a local (word selection) level that modulates the relative activation of specific lexical representations (de Groot, 2011). By this account, bilinguals should show a stronger association between cognitive control and word retrieval performance. The bilingual inhibitory control advantage (BICA) hypothesis proposes that the increased cognitive demands associated with language control in bilinguals provide widespread advantages in cognitive control (Green, 1998).1,2 The bilingual advantage in cognitive control is most commonly tested using verbal and nonverbal conflict tasks such as Stroop and Flanker arrows respectively (e.g., Blumenfeld & Marian, 2014). Researchers draw parallels between inhibition of the non-target language by bilinguals and inhibition of prepotent response modes in paradigms such as Stroop and Flanker arrows: both engage selective response inhibition (Green & Abutalabi, 2013). Numerous studies in the past decade have compared bilingual and monolingual performance on conflict tasks, and have examined factors such as language proficiency (of bilinguals), type of conflict (verbal or nonverbal), and age (for example, ndez, Costa-Faidella, & Sebasti s, 2009; Paap & Greenberg, Bialystok, Craik, Klein, & Viswanathan, 2004; Costa, Herna an-Galle 2013). In summary, this large body of literature has revealed mixed results; while some studies found a bilingual inhibitory advantage (Bialystok, 2006; Bialystok et al., 2004; Martin-Rhee & Bialystok, 2008; Prior & Macwhinney, 2009), others failed to find support for the BICA (Bialystok, Martin, & Viswanathan, 2005; Costa et al., 2009; Kousaie & Phillips, 2011; Paap & Greenberg, 2013; non-verbal inhibition studies reviewed in; Hilchey & Klein, 2011). In some studies, bilinguals were found to outperform monolinguals in all trials (conflict and non-conflict), suggesting an overall advantage in attending to task relevant information. In other studies, the bilingual advantage was found only when the paradigm included both conflict and non-conflict trials (but not when all trials were non-conflict; Bialystok et al., 2004; Costa et al., 2009) or when bilinguals were highly proficient (Bialystok & Majumder, 1998; Luk & Bialystok, 2013). In general, the Stroop task shows more robust support of BICA than nonlinguistic conflict tasks such as Flanker and Simon tasks. As for bilingual persons with aphasia (BPWA), one study compared monolingual and bilingual persons with aphasia (Penn, Frankel, Watermeyer, & Russell, 2010). Penn et al. (2010) found no difference3 in Stroop performance between two BPWA and seven monolingual persons with aphasia (MPWA). Three other studies, compared BPWA with bilingual neurologically healthy controls (Gray & Kiran, 2016; Green et al., 2010, 2011). Green et al. (2010, 2011) found an exaggerated disadvantage in conflict trials in one BPWA (compared to controls), while the other two BPWA performed within the range of bilingual controls. Gray and Kiran (2016) reported that nine BPWA were slower overall than healthy controls, but did not report the magnitude of difference between conflict and non-conflict trials. Dash and Kar (2014) reported linguistic and non-linguistic conflict tasks in four BPWA, who showed high inter-individual variability, but there was no control comparison group. In summary, sorting through the vast body of diverse findings on BICA in adults reveals the following: 1) evidence in favor of BICA is weak for nonverbal paradigms such as Flanker, Simon and antisaccade tasks (Paap & Greenberg, 2013; reviewed in; Blumenfeld & Marian, 2014; Hilchey & Klein, 2011). 2) BICA is more frequently supported for verbal conflict (e.g., Stroop task) in young adults (e.g., Bialystok et al., 2008; Costa et al., 2009) although there are a few conflicting findings (e.g., Kousaie & Phillips, 2011). 3) Performance on non-verbal conflict is uncorrelated with performance on verbal conflict, raising the question whether verbal and nonverbal paradigms engage similar cognitive control mechanisms (Dash & Kar, 2014; Kousaie & Phillips, 2011; Paap & Greenberg, 2013; Stins, Polderman, Boomsma, & de Geus, 2005). 4) It is unclear if BICA persists after brain damage, as in BPWA compared to MPWA. Finally, given that BICA is presumed to arise from the constant need to suppress cross-language lexical activation, the link between word retrieval success and cognitive control remains elusive. 1.4. Research questions and predictions The aim of this study was to delineate the interplay between cognitive control, bilingualism, and word retrieval in aphasia. This was addressed by posing three questions. First, we sought to examine if cognitive control deficits are prevalent in persons with aphasia relative to age-matched neurologically healthy individuals (as measured by the Stroop task). Our working hypothesis was an absence of a frank deficit in PWA. The basis of this hypothesis stems from research identifying right frontal (Vendrell et al., 1995) and bilateral superior medial frontal lesions (Stuss et al., 2001) for exaggerated Stroop effects following brain damage, and mainly activations of anterior cingulate for conflict resolution (Piai et al., 2013). Typical lesions in aphasia

1 Recent views on the influence of bilingualism suggest more widespread cognitive benefits beyond cognitive control (Baum & Titone, 2014; Kroll & Bialystok, 2013; reviewed in; Bialystok, 2009), but in this paper, we focus only on cognitive control given its relatively direct relationship with lexical retrieval. 2 While Green (1998) used the term inhibitory control, we use the more general term cognitive control in this paper, except when referring to Green’s hypothesis. 3 Penn et al. (2010) set the significance threshold at p ¼ 0.1 and concluded that there was a significant difference between bilinguals and monolinguals. But here, we use the more traditional significance cut off of p < 0.05.



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rarely encompass these above mentioned brain regions. Rather, lesions of the left peri-Sylvian (fronto-temporo-parietal) regions are associated with aphasia (Damasio & Geschwind, 1984; Dronkers, Wilkins, Van Valin, Redfern, & Jaeger, 2004; Faroqi-Shah et al., 2014; Mirman et al., 2015). However, based on findings that brain damage generally affects Stroop task performance (de Bruijn et al., 2014; Dimoska-Di Marco, McDonald, Kelly, Tate & Johnstone, 2011; Wiener, Connor, & Obler, cs, 2013), we predicted an inhibitory weakness. By inhibitory weakness we mean 2004; Zakari as, Keresztes, Demeter, & Luka diminished but not overly exaggerated performance relative to healthy controls. Second, we tested if there is a bilingual advantage in cognitive control in PWA, as predicted by Green’s (1998) bilingual inhibitory control advantage (BICA) hypothesis. To examine the effects of bilingualism, we recruited highly proficient bilingual speakers who had a robust history of managing two languages and thus are more likely to experience plasticity of cognitive control as a result of bilingualism (Abutalebi, Canini, Della Rosa, Green & Weekes, 2015; Diependaele, Lemhofer, & Brysbaert, 2013). We used the Stroop task (Stroop, 1935) to examine cognitive control because empirical evidence of the bilingual cognitive advantage is more robust for the verbal conflict of Stroop rather than for non-linguistic tasks such as Simon, Flanker and anti-saccade (reviewed in Blumenfeld & Marian, 2014; Hilchey & Klein, 2011). Bilingual language production models propose that the effects of bilingualism on cognitive control are domain general, that is, both linguistic and non-linguistic (Green, 1998). Our choice of the Stroop task was based on the strength of empirical evidence on bilingual advantage, and not because we question domain generality. There are three possible scenarios of BICA in aphasia: 1) If left peri-Sylvian damage has little effect on cognitive control per se (due to non-overlap with cognitive control substrates, according to our general hypothesis for aphasia above), then we would find the same pattern of bilingual-monolingual difference in neurologically healthy (NH) adults and PWA (Abutalebi & Green, 2007). So, if demographically matched NH persons show a bilingual advantage, we could expect BICA in aphasia. It is crucial to answer this question in relation to NH adults because of the somewhat unreliable findings of Stroop effects in NH adults (Kousaie & Phillips, 2011). 2) Alternately, one could argue that the effect of acute left hemisphere damage more than obliterates any cognitive advantage afforded by bilingualism. Then we would expect absence of BICA in PWA. Third, we investigated the relationship between cognitive control and word retrieval in aphasia. The rationale for hypothesizing a relationship between cognitive control and word retrieval was as follows. If lexical selection (and concomitant interference suppression) in aphasia relies on the same domain general cognitive mechanisms that are engaged for resolving conflict in Stroop task, then there will be negative correlation between word retrieval and Stroop effect. That is, those PWA with the best cognitive control (least affected by conflict trials) would also be the ones with the best word retrieval (least affected by lexical competition). Further, if bilingual speakers’ increased necessity to resolve lexical selection strengthens the same cognitive mechanisms as conflict resolution in the Stroop task, then we would expect a stronger negative correlation for BPWA compared to MPWA (consistent with BICA, and Bialystok et al., 2008). 2. Methods 2.1. Participants Persons with aphasia and neurologically healthy controls were recruited for the study. Group demographics are provided in Table 1. There were three groups of PWA: 18 English-speaking MPWA residing in the United States, 10 English-dominant

Table 1 Demographic information of participants. Standard deviations are in parenthesis. Group

N, Age Education Female (years) (years)

Time post onset

Aphasia severitya,b

Aphasia typea

Location, language background

Monolingual Aphasia (MPWA)

18, 6

16.2 (2.9)

5.9 (2.9)

76.7 (14.7)

USA, English speakers

16.9 (2.1)

7.9 (4.2)

74.8 (10.4)

16.9 (3)

4.4 (2.9)

75 (20.1)

11 Broca’s, 5 Anomic, 2 other 3 Broca’s, 6 Anomic, 1 other 8 Broca’s, 2 other

62.7 (8.3) Bilingual Aphasia English Dominant 10, 3 61.6 (BPWA-EngDom) (16.6) Bilingual Aphasia Tamil-English 10, 2 69.7 (BPWA-TamEng) (6.5) Monolingual Neurologically Healthy 18, 10 61.4 (MNH) (5.3) Bilingual Healthy English Dominant 10, 5 64.5 (BNH-EngDom) (7.1) Bilingual Healthy Tamil English (BNH- 10, 5 59.4 TamEng) (4.3) a b

16.7 (3.3) 15.9 (3.1) 17.4 (2.1)

USA, English L1 or Dominant Language, other L2 India, Tamil L1, English L2 USA, 10 monolingual English speakers USA, English L1 or Dominant Language, other L2 India, Tamil L1, English L2

Western Aphasia Battery (Kertesz, 2007, for English; or Kumar, 2007, for Tamil). Maximal score of 100 indicates no impairment.


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BPWA residing in the United States, and 10 BPWA residing in India. The BPWA residing in India were Tamil4 (L1) and English (L2) bilinguals. The non-dominant languages of the English-dominant BPWA included Russian, French, Hungarian (Magyar) and Spanish. We recruited three groups of neurologically healthy (NH) controls who were matched for age and education with the three PWA groups, 18 English-speaking monolingual neurologically healthy (MNH), 10 English-dominant bilinguals (BNH-EngDom), and 10 Tamil-English bilinguals (BNH-TamEng). All PWA experienced a single left hemisphere cerebrovascular stroke of the middle cerebral artery resulting in a diagnosis of aphasia. They were at least six months post-onset at the time of testing. To confirm the presence and severity of aphasia, participants were administered the Western Aphasia Battery-Revised (WAB-R; Kertesz, 2007). For Tamil-English BPWA, the Tamil adaptation of the WAB was also used (Kumar, 2007). There was no significant difference in L1 and L2 aphasia severity for Tamil-English bilinguals as measured by the Aphasia Quotient (AQ) of Western Aphasia Battery (Mann-Whitney U test, ns), indicating that these BPWA had parallel recovery in both languages (Paradis, 1995). The presence of verbal apraxia was tested using the verbal apraxia subtest from the Boston Diagnostic Aphasia Examination (BDAE-3; Goodglass, Kaplan, & Barresi, 2000). No participants reported any coexisting neurological conditions, and passed screenings for color blindness (for the Stroop task), hearing (ANSI, 1969) and vision (10/20 on a Snellen chart). MPWA and BPWA did not differ in age (62.7 vs. 65.7 years), time post-onset (5.9 vs. 6.9 years), aphasia severity (76.7 vs. 74.9 on a scale of 0e100, as determined by the Aphasia Quotient of WAB-R, maximum ¼ 100), or auditory comprehension (5.8 vs. 5.8, composite score on WAB-R, maximum ¼ 10) (all p values > 0.05). None of the BPWA showed pathological code switching (although occasional instances during lexical search were observed in some participants). All bilingual speakers had a high proficiency of bilingualism, as determined by self-reported language proficiency questionnaires (Birdsong, Gertken, & Amengual, 2012; Marian, Blumenfeld, & Kaushanskaya, 2007). High proficiency was defined as a score ranging from 100 to þ100 in the Bilingual Language Profile5 (BLP, Birdsong et al., 2012) and a rating of greater than 7 out of 10 in the Language Experience and Proficiency Questionnaire (LEAP-Q, Marian et al., 2007). 2.2. Procedure Participants were tested individually after providing informed consent. After completion of background testing, the experimental tasks were presented in a counter-balanced sequence across participants in order to minimize order effects. Testing was completed either in a single session or over two sessions, depending on participants’ fatigue. Background testing (described in Section 2.1) included questionnaires on demographic information, language background (Birdsong et al., 2012 or Marian et al., 2007) and screening for color blindness, hearing and vision for all participants and tests for aphasia (WAB) and verbal apraxia (BDAE-3) for PWA. 2.2.1. Cognitive control A computerized version of the Stroop Color Word Test (Golden, 1978) was used in English for all participants and additionally in Tamil for the Tamil-English BPWA. In the Stroop task, the words red, green, and yellow were used as test stimuli and the word plan was used as a neutral stimulus. The Tamil translations of the stimuli were used in the Tamil version of the task. For every color word there was one congruent condition (for example, indicating red when the word red is printed in red colored font), one incongruent condition (for example, indicating red when the word red is printed in green colored font) and one neutral condition (indicating the font color of the word plan). There were nine conditions (three colors x three conditions) with 20 trials in each condition, giving 60 each of congruent, incongruent and neutral trials (total 180 trials). The presentation order of trials was pseudo-randomized, ensuring no repetition of the target word and condition on adjacent trials to avoid negative priming from the previous trial. The task was presented in six blocks of 30 trials each, with a 30 s break between blocks. Even though a verbal response mode has been used in many past studies of Stroop (MacLeod, 1991), we used a nonverbal (keyboard press) response because persons with aphasia are likely to produce semantic errors in naming or be slow to name due to non-fluency and apraxia (Neill, 1977). All participants were instructed to press a key on the keyboard that corresponded to the font color of each word using their left hand. A left hand response was used because right hand paresis or paralysis could occur from left hemisphere stroke for PWA. On the keyboard, a corresponding color sticker was used on three keys (Y, K and F). Each trial began with the fixation cross for 800 ms (ms), followed by 250 ms of a blank interval, and the stimulus. Each stimulus remained on the screen for 3000 ms. There was an interstimulus interval of 500 ms (blank screen) before the next trial. Nine practice trials were administered for task familiarization. 2.2.1.1. Data analysis. Accuracy and response times were obtained. Response time (RT) analysis was performed after excluding incorrect responses and outliers (all RTs that were 2.5 standard deviations above or below a participant’s mean RT or 2000 ms). Consistent with prior studies (e.g., Bialystok et al., 2008), we computed the Stroop Effect (SE), calculated as the difference between incongruent and congruent conditions. In addition, we calculated Conflict Ratios (CR), to enable direct comparison between healthy controls and persons with aphasia (Green et al., 2010). Conflict Ratio is a normalized score that

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Tamil is a Dravidian language native to the Indian sub-continent and is spoken in Southern India, parts of Sri Lanka and Singapore. In the BLP, possible language dominance scores range from 200 to þ200, with 0 indicating perfectly balanced bilingualism.



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accounts for the overall slower response speed and lower accuracy of PWA relative to NH, and is calculated as the difference between incongruent and congruent trials divided by the congruent trials. Mathematically, this is the Stroop effect divided by performance of the congruent condition. Stroop effects and conflict ratios were calculated for both accuracy and response speed. Inspection of the data for incongruent trials revealed a high speed accuracy trade-off: there was a significant negative correlation between response speed and accuracy for persons with aphasia (Pearson product moment correlations, r ¼ 0.8 for MPWA, p < 0.01; r ¼ 0.6 for BPWA, p < 0.01) but not for healthy participants (r ¼ 0.4 for MNH, r ¼ 0.27 for BNH, ns). Therefore the inverse efficiency score (IES) was calculated for incongruent trials by dividing the response time with proportion error (Bruyer & Brysbaert, 2011; Townsend & Ashby, 1978). IES is a way of combining speed and accuracy information when there is a high speed-accuracy trade-off. A larger value of IES reflects poorer efficiency. To summarize, we computed three measures of Stroop performance: Stroop effect, conflict ratio and inverse efficiency score. 2.2.2. Word retrieval Word retrieval in PWA was measured using the object naming and category fluency subtests of the WAB-R (Kertesz, 2007) for all participants and WAB-Tamil (Kumar, 2007) for Tamil-English BPWA. Object naming requires participants to name 20 common objects (e.g., book, ball, knife, cup, watch, comb). Participants were given 20 seconds to name each object. According to the scoring criteria of WAB-R, three points are given for a spontaneous correct response, hence the maximum possible score is 60. Two points are given for a phonemic paraphasia (e.g., pook for book) and one point if the participant is able to name the object following phonemic or tactile cues. Category fluency involves naming as many animals as possible in 1 min. Participants were prompted to continue after 30 seconds if necessary. The total score is the number of non-unique animals named in 1 min and can be compared to published age-group norms (Brickman et al., 2005; Gladsjo et al., 1999). These nonspeeded measures were used to accommodate non-fluency and because of their frequent clinical use. In object naming, lexical representations are accessed via the visual modality whereas category fluency relies on a search through one’s semantic network. While both tasks depend on inhibition of competing lexical representations, category fluency recruits greater cognitive control because it involves re-activation of previously inhibited responses (e.g., cat may be inhibited while selecting dog, but needs to be reactivated for selecting cat as the next response and dog needs to be suppressed). To address the first research question on cognitive control impairment in aphasia, we compared performance on the Stroop task between persons with aphasia and their respective neurologically healthy control group (monolingual English, bilingual English-dominant and bilingual Tamil-English). The second research question regarding the bilingual inhibitory control advantage hypothesis was addressed with two comparisons: monolingual English versus bilingual English-dominant NH, and monolingual English versus bilingual English-dominant PWA. To answer the third research question about the relationship between cognitive control and word retrieval in aphasia, correlations between Stroop performance and WAB word retrieval performance were computed separately for MPWA and each of the two BPWA groups. 3. Results 3.1. Stroop task: influence of aphasia and bilingualism First, we examined if PWA were sensitive to task instructions and were not showing a response bias by calculating d-prime (d0 ) values based on the proportion of accurate responses and false alarms (Green & Swets, 1966). The mean (SD) d0 values were 3.66 (1.02), 2.4 (1.7) and 3.23 (1.2) for congruent, incongruent and neutral trials respectively, which indicate good sensitivity to the task. Consistent with the Stroop effect, d0 values for incongruent trials were lower than other trials types. There was no difference between monolingual and bilingual PWA d0 values (t-tests, all p > 0.2). The accuracy and response times of each participant group are given in Table 2. As is evident from Table 2, PWA had lower accuracy and slower response times (RT) compared to their matched NH group (computed on arc-sine transformed accuracies and log-transformed RTs, all p values > 0.05). This finding is unsurprising for persons with brain damage. The crucial measure was the relative performance during conflict trials versus congruent trials, after such between-group variability is controlled. Hence, we report statistical comparisons of conflict ratio and IES, which respectively account for the overall poorer performance and speed-accuracy trade-off of PWA relative to NH groups (also minimizing Type I error). Unless specifically stated, the Tamil-English bilingual groups’ (BPWA-TamEng and BNH-TamEng) performance was examined in their L1 (Tamil). 3.1.1. Comparing aphasic and healthy groups Table 3 shows that persons with aphasia scored worse than their matched neurologically healthy control groups as measured by larger accuracy conflict ratios and larger inverse efficiency scores (all Mann-Whitney Us < 16, p < 0.05). The accuracy conflict ratio difference between BNH-EngDom and BPWA-EngDom was not significant but the RT conflict ratio was significantly different for these two groups (Mann-Whitney U ¼ 15, p < 0.05). The accuracy conflict ratio differences showing impaired performance of persons with aphasia is illustrated in Fig. 1. In other words, PWA performed worse than their matched NH groups in at least one measure. 3.1.2. Evaluating the bilingual inhibitory control advantage hypothesis The outcomes of the statistical comparisons are given in Table 4. It is important to note that the three bilingual groups did not show any inherent performance differences as indicated by their speed and accuracy on neutral trials (Kruskal Wallis Please cite this article in press as: Faroqi-Shah, Y., et al., Cognitive control, word retrieval and bilingual aphasia: Is there a relationship?, Journal of Neurolinguistics (2016), http://dx.doi.org/10.1016/j.jneuroling.2016.07.001

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Table 2 Proportion accuracy (Acc), response speed (RT) in milliseconds, Stroop effect, conflict ratio and inverse efficiency score for different trial types for each participant group. Numbers in parenthesis indicate standard deviation.

Monolingual Neurologically Healthy (MNH)

Acc RT Bilingual Neurologically Healthy (BNH-EngDom) Acc RT Bilingual Neurologically Healthy-TamEng (L1) Acc RT Bilingual Neurologically Healthy-TamEng (L2) Acc RT Monolingual Aphasia (MPWA) Acc RT Bilingual Aphasia-EngDom Acc RT Bilingual Aphasia-TamEng (L1) Acc RT Bilingual Aphasia-TamEng (L2) Acc RT

Congruent

Incongruent

Neutral

Stroop effect

Conflict ratio IES

0.99 (0.07) 990.4 (229.3) 0.99 (0.06) 925.2 (43.1) 0.99 (0.02) 933.2 (45.1) 0.99 (0.02) 977.58 (148.5) 0.96 (0.07) 1375.75 (406.7) 0.97 (0.06) 1345.5 (377) 0.92 (0.02) 1070 (124.4) 0.93 (0.02) 1130 (125.4)

0.98 (0.17) 1172.8 (271) 0.98 (0.05) 1018.4 (29.1) 0.97 (0.05) 1044.4 (25.9) 0.98 (0.01) 1124.8 (124.9) 0.81 (0.27) 1561.36 (487.1) 0.85 (0.22) 1445 (447.3) 0.81 (0.04) 1254 (234) 0.77 (0.04) 1345 (310.8)

1 (0) 1060.6 (258.8) 0.99 (0.02) 972.8 (38.7) 0.99 (0.02) 982.8 (42.7) 0.99 (0.01) 1032.77 (173.1) 0.9 (0.16) 1471.25 (528.8) 0.93 (0.08) 1375.6 (290.1) 0.91 (0.03) 1104.6 (121.4) 0.91 (0.02) 1201 (154.92)

0.01 (0.01) 182.4 (187.5) 0.01 (0.02) 93.2 (46.9) 0.01 (0.02) 111.2 (56.9) 0.02 (0.04) 147.21 (51.2) 0.15 (0.22) 185.61 (160.4) 0.26 (0.5) 99.5 (117) 0.11 (0.2) 183.2 (97.2) 0.11 (0.12) 215.6 (113.6)

0.01 (0.01) 0.2 (0.2) 0.005 (0.006) 0.11 (0.05) 0.005 (0.006) 0.12 (0.06) 0.02 (0.04) 0.15 (0.04) 0.17 (0.26) 0.13 (0.09) 0.26 (0.5) 0.07 (0.07) 0.14 (0.08) 0.17 (0.1) 0.15 (0.1) 0.18 (0.09)

1190.5 (280) 1001.6 (118.6) 1070 (30.5) 1219 (360) 3123 (4161.2) 2127 (1848) 1554.3 (285) 1758 (355.8)

Table 3 Results of healthy control versus aphasia comparisons. Statistically significant comparisons are reported (p < 0.05), ns ¼ not significant. Comparison

Accuracy conflict ratio

RT conflict ratio

Inverse efficiency score

MNH vs MPWA BNH-EngDom vs BPWA-EngDom BNH-TamEng vs BPWA-TamEng (L1) BNH-TamEng vs BPWA-TamEng (L2)

MNH better, t(34) ¼ 2.5 ns BNH better, Mann-Whitney U ¼ 1 BNH better, Mann-Whitney U ¼ 1

ns BNH better, Mann-Whitney U ¼ 15 ns ns

MNH better, t(34) ¼ 2.1 ns BNH better, Mann-Whitney U ¼ 3 BNH better, Mann-Whitney U ¼ 5

0.3 Healthy

Conflict Rao (RT)

0.25

Aphasia

0.2 0.15 0.1 0.05 0 Monolingual

Bil-TamEng

Bil-EngDom

Fig. 1. Conflict ratios calculated from accuracy for monolingual and bilingual healthy adults and persons with aphasia. Persons with aphasia performed worse (higher conflict ratio) than matched healthy adults.

H(2) ¼ 1.4, ns). Both neurologically healthy bilingual groups (BNH-EngDom and BNH-Tamil-Eng) had a smaller RT conflict ratio than the MNH group (Mann-Whitney U ¼ 18 and 21 respectively, p < 0.05), indicating superior cognitive control for healthy bilinguals. Accuracy conflict ratio and IES comparisons between monolingual and bilingual NH groups did not reach statistical significance, which is expected given that NH participants generally complete the Stroop task with high accuracy. In sum, the RT conflict ratio differences support the BICA in healthy individuals. The three PWA groups were significantly different in RT conflict ratio (Kruskal Wallis H(2) ¼ 7.8, p < 0.05, mean of ranks for BPWA-TamEng, BPWA-EngDom and MPWA are 25.7, 12 and 20.3 respectively), but not in accuracy conflict ratio or IES. Paired comparisons showed that BPWA-EngDom performed significantly better than MPWA (Mann-Whitney U ¼ 45, p < 0.05), confirming the BICA. BPWA-TamEng versus MPWA failed to reach significance (Mann-Whitney U ¼ 118, ns). The two bilingual aphasia groups differed significantly from each other, with significantly better BPWA-EngDom performance compared to BPWA-TamEng in L1 (RT conflict ratio, Mann-Whitney U ¼ 16, p < 0.05) and L2 (accuracy conflict ratio, Mann-Whitney U ¼ 15.5 p < 0.05). Monolingual versus bilingual PWA comparisons were also conducted in the L2 of BPWA-TamEng (English). The results were similar to that of L1 comparisons reported earlier (see Table 4). To summarize, RT conflict ratio was Please cite this article in press as: Faroqi-Shah, Y., et al., Cognitive control, word retrieval and bilingual aphasia: Is there a relationship?, Journal of Neurolinguistics (2016), http://dx.doi.org/10.1016/j.jneuroling.2016.07.001


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Table 4 Results of bilingual versus monolingual comparisons. Statistically significant comparisons are reported (p < 0.05), ns ¼ not significant. Comparison

Accuracy conflict ratio

RT conflict ratio

Inverse efficiency score

Neurologically healthy MNH vs BNH-EngDom MNH vs BNH-TamEng (L1)

ns ns

BNH better, Mann-Whitney U ¼ 14 BNH better, Mann-Whitney U ¼ 21

ns

BNH better, Mann-Whitney U ¼ 18

ns BNH better, Mann-Whitney U¼7 ns

ns

Kruskal Wallis H(2) ¼ 7.8

ns ns

Kruskal Wallis H(2) ¼ 7.1

BPWA-EngDom better, Mann-Whitney U ¼ 45 ns BPWA-EngDom better, Mann-Whitney U ¼ 16 Kruskal Wallis H(2) ¼ 7.8

MPWA better, Mann-Whitney U ¼ 140 BPWA-EngDom better, Mann-Whitney U ¼ 20 L1 better, Mann-Whitney U ¼ 90

ns ns BPWA-EngDom better, Mann-Whitney ns U ¼ 15.5 ns ns

MNH vs BNH-TamEng (L2) Persons with aphasia MPWA vs BPWA-EngDom vs BPWATamEng (L1) MPWA vs BPWA-EngDom MPWA vs BPWA-TamEng (L1) BPWA-EngDom vs BPWA-TamEng (L1) MPWA vs BPWA-EngDom vs BPWATamEng (L2) MPWA vs BPWA-TamEng (L2) BPWA-EngDom vs BPWA-TamEng (L2) BPWA-TamEng L1 vs L2

ns

ns ns ns

B ¼ bilingual, M ¼ monolingual, NH ¼ neurologically healthy, PWA ¼ persons with aphasia, L1 ¼ first language, L2 ¼ second language.

sensitive to between group differences, BICA was supported in the following comparisons: between bilingual versus monolingual neurologically healthy persons and bilingual-English dominant versus monolingual PWA. Among the PWA groups, BPWA-EngDom had superior cognitive control performance (lowest RT conflict ratio), followed by MPWA, and BPWATamEng fared the worst in cognitive control (Fig. 2). 3.2. Relation between word retrieval and cognitive control in aphasia PWA were impaired on both word retrieval measures (see Table 5). Object naming scores averaged 67% (M ¼ 41.8 out of 60, SD ¼ 12.5, range 21e60). Category fluency averaged 7.4 animals per minute (SD ¼ 4.5, range: 3e20), which is much lower than the range of 14e19 for neurologically healthy persons in the 40e70 year age group (Brickman et al., 2005; Gladsjo et al., 1999). Category fluency and object naming were significantly positively correlated in all PWA groups (Spearman’s correlations all p values 0.05). In summary, although the two word retrieval measures were strongly correlated with each other, word retrieval was not associated with cognitive control for any PWA group. 4. Discussion This study had three goals, to investigate the integrity of cognitive control in persons with aphasia, to test the bilingual inhibitory control advantage (BICA) hypothesis in aphasia, and to examine if word retrieval was associated with cognitive control in aphasia. To address these goals, cognitive control was assessed using the Stroop task and word retrieval was

Fig. 2. Conflict ratios calculated from reaction ties for monolingual and bilingual healthy adults and persons with aphasia. Healthy monolinguals performed worse (higher conflict ratio) than both bilingual groups. Monolinguals with aphasia performed worse than English-dominant bilinguals with aphasia.


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Y. Faroqi-Shah et al. / Journal of Neurolinguistics xxx (2016) 1e15 Table 5 Word retrieval scores of persons with aphasia. Standard deviations are in parenthesis.

Monolingual Aphasia Bilingual Aphasia-English Dominant Bilingual Aphasia-TamilEnglish-L1 Bilingual Aphasia-TamilEnglish-L2 Normative scores a

Category fluency

Object naming

7.17 (4.4) 10.4 (5.3) 4.9 (1.2) 4.9 (0.8) 16e19

41.28 (12.5) 48.9 (13.5) 36 (8.4) 31.9 (5.9) 60

From Brickman et al. (2005) and Gladsjo et al. (1999).

measured using category fluency and object naming. We found a cognitive control deficit in PWA relative to healthy controls for response accuracy and inverse efficiency score, a bilingual advantage in healthy adults and English-Dominant bilingual aphasia, and no significant association between word retrieval and cognitive control for persons with aphasia. These findings are discussed in the following sections.

4.1. Cognitive control in aphasia It is notable that PWA’s mean accuracy exceeded 90% for congruent and neutral trials, and 80% for incongruent trials, indicating preserved ability to perform the Stroop task. Nevertheless, PWA were less accurate than matched healthy controls across all trial types, and made significantly more errors in incongruent relative to congruent trials (82% vs. 95%) than did the healthy group (98% vs. 99%). The finding of lower Stroop accuracy is consistent with some prior research that compared aphasia and healthy controls (de Bruijn et al., 2014; Wiener et al., 2004; Zakari as et al., 2013) and contrasts with studies that failed to find an accuracy disadvantage in aphasia (Green et al., 2010; Scott & Wilshire, 2010). Other studies of Stroop task in aphasia either did not report accuracy (Biegler et al., 2008; Hamilton & Martin, 2005; Revonsuo & Laine, 1996) or did not include a neurologically healthy control group (Dash & Kar, 2014; Kong, Abutalebi, Lam, & Weekes, 2014; Penn et al., 2010). In terms of response speed, PWA were slower than healthy adults for all trial types, which is consistent with other studies of response speed on the Stroop task (de Bruijn et al., 2014; Pompon et al., 2015; Scott & Wilshire, 2010; Wiener et al., 2004; s et al., 2013) and in other cognitive tasks (Purdy, 2002). In addition, PWA performance was characterized by a Zakaria strong speed-accuracy trade-off, determined by the high negative correlation between speed and accuracy for the incongruent condition (Wickelgren, 1977), which was not seen in the NH group. Therefore we computed a composite efficiency score (Bruyer & Brysbaert, 2011) for incongruent trials and found lower efficiency for PWA compared to healthy adults, indicating weakened cognitive control in aphasia. Further, persons with Broca’s aphasia were not any worse on cognitive control than other persons with aphasia. In addition to statistically addressing the speed-accuracy tradeoff and using normalized measures like the conflict ratio, this research addressed other interpretive confounds of prior investigations of cognitive control in aphasia by including agematched healthy adults and a manual response mode. In some prior studies of cognitive control in aphasia, there was no healthy comparison group (Dash & Kar, 2014; Penn et al., 2010) or healthy participants were younger than PWA (e.g., Green et al., 2010). Given the overall detriment in response speed that occurs with aging6 (Bugg, DeLosh, Davalos, & Davis, 2007; Ludwig, Borella, Tettamanti & de Ribaupierre, 2010; Verhaeghen & De Meersman, 1998; West & Alain, 2000) and with aphasia (Purdy, 2002), comparison of normalized measures across demographically matched PWA and NH increases the reliability of the current findings (similar to Hamilton & Martin, 2005; Pompon et al., 2015; Revonsuo & Laine, 1996). Measurement of oral color naming response times for the Stroop task creates an inherent bias against PWA relative to healthy controls (Hamilton & Martin, 2005; Penn et al., 2010; Pompon et al., 2015; Scott & Wilshire, 2010). Hence we used s et al., 2013). manual response mode (similar to Green et al., 2010, 2011; Revonsuo & Laine, 1996; Wiener et al., 2004; Zakaria Within studies that used a manual response mode, it is not always clear whether right or left hand was used to account for right-sided weakness that frequently occurs in PWA, and if the response hand was consistent across PWA and control groups. In the present study, left hand response was used by both groups in order to control for right hand weakness in PWA. Considering the overall experimental methods of the current study, it can be reliably concluded that cognitive control mechanisms are weak and inefficient in aphasia, as measured by the ability to resolve interference in the Stroop task. This finding is consistent with another recent robust sample-sized study of PWA (Pompon et al., 2015) and adds to body of evidence that Stroop performance is diminished following brain damage, such as stroke (de Bruijn et al., 2014) and traumatic brain injury (Dimoska-Di Marco et al., 2011). Thus, cognitive control efficiency could be altered by focal and diffuse brain damage resulting from different etiologies. While cognitive control could be impaired by different mechanisms across etiologies, such as global goal-directed control in traumatic brain injury versus local competition in aphasia, the finding has significance for understanding language behaviors and individual variability in aphasia (Green et al., 2010; Lambon Ralph, Snell, Fillingham, Conroy & Sage, 2010; Novick, Trueswell, & Thompson-Schill, 2010; Penn et al., 2010; Wiener et al., 2004;

6 The healthy controls in this study were significantly slower than college aged young adults tested using the same experimental setup (Baughman, 2013).



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Zakari as et al., 2013). It has been suggested that domain general mechanisms such as cognitive control exert an influence on language in aphasia especially because PWA’s language symptomatology and recovery are only partially predicted by lesion location and size (Hope, Seghier, Leff & Price, 2013). For example, perseveration, which refers to repeated production of a previously produced response by a PWA, could result from difficulty in suppressing a prior lexical or conceptual activation (Frankel, Penn, & Ormond-Brown, 2007; Penn et al., 2010). Auditory comprehension errors could arise from difficulty in resolving among multiple lexical cohorts: Wiener et al. (2004) found a strong association between Stroop interference suppression and auditory comprehension severity in five individuals with aphasia. In two case studies, patients with severe difficulty in producing multiword utterances compared to single words were also severely impaired on conflict trials in the Stroop task (Hamilton & Martin, 2005; Scott & Wilshire, 2010). By demonstrating inefficient cognitive control in this group of PWA, this study highlights the importance of considering the influence of cognitive control on language on aphasia. However, further research is needed to delineate the nature of the relationship between cognitive control and specific language behaviors in aphasia. 4.2. Bilingual inhibitory control advantage (BICA) This study tested Green’s (1998) hypothesis that bilingualism affords an advantage in cognitive control in healthy adults and aphasia (Green et al., 2010). Among neurologically healthy adults, we found a bilingual advantage in RT conflict ratio. This finding supports prior BICA among older highly proficient bilingual adults (Bialystok et al., 2008; Kousaie, Sheppard, Lemieuz, Monetta, & Taler, 2014; Mohamed Zied et al., 2004; approaching significance in Green et al., 2010; but see Kousaie and Phillips, 2012 for absence of BICA). In the current study, the healthy monolinguals and bilinguals were primarily nonimmigrants, obviating the concern about comparing non-immigrant monolinguals with immigrant bilinguals in some past research (Chertkow et al., 2010; Gollan, Salmon, Montoya, & Galasko, 2011; Gollan, Slattery, et al., 2011; Kousaie & Phillips, 2012). This bilingual advantage in older bilinguals is consistent with research showing superiority in a broader range of cognitive measures such as the Simon task (Bialystok et al., 2004), task switching (Gold, Kim, Johnson, Kryscio, & Smith, 2013), and longitudinal decline in clinically used cognitive screens (Kave, Eyal, Shorek, & Cohen-Mansfield, 2008). For persons with aphasia, BICA was supported for English dominant BPWA, but not Tamil-English BPWA. Thus the two BPWA groups differed from each other in cognitive. As shown in Table 1, the two BPWA groups did not differ from each other in age, education, overall aphasia severity. Hence, demographic differences are unlikely to have resulted in the different behavior of the two groups. One possible explanation is spoken language dominance and literacy differences and the nature of the Stroop task. Schooling and work-place written communication is mostly conducted in English in India. Hence TamilEnglish bilinguals might have stronger reading fluency in their L2 (English) compared to their L1 (Tamil) although they may be have the reverse pattern of better spoken fluency in L1 compared to L2. This opposing pattern between spoken and reading proficiency might have exacerbated in PWA and could have influenced the Stroop task, which relies on rapid reading of words. BPWA-EngDom did not have this confound between written and spoken proficiency and hence may have shown the classic bilingual advantage. Although null effects need to be interpreted cautiously, a second explanation or the absence of BICA in BPWA-TamEng can be drawn within the context of two other findings from this study: the presence of BICA in Tamil-English bilingual healthy adults and the overall cognitive control inefficiency in PWA. It appears that the cognitive control inefficiency consequent to aphasia eliminates any (pre-stroke) bilingual advantage. In other words, for BPWA-TamEng, the magnitude of cognitive control disadvantage following aphasia is larger than the magnitude of advantage afforded by high proficiency bilingualism. Given that English dominant bilinguals, both with and without aphasia, showed a bilingual advantage in the Stroop task, the most straightforward interpretation is that BICA can persist even in after left hemisphere damage, particularly when the language of reading (Stroop) is also one’s dominant language (cf: BPWA-TamEng). The cognitive control differences in the two BPWA remind us of the importance of cross-linguistic and cross-cultural replication of research. 4.3. Relation between word retrieval and cognitive control in aphasia In the present study, word retrieval was significantly impaired in persons with aphasia when compared to published norms for both object naming and category fluency (Brickman et al., 2005; Gladsjo et al., 1999; Kertesz, 2007). This was expected, given that word retrieval deficits are a cardinal symptom of aphasia (Schuell & Jenkins, 1961). Secondly, comparing MPWA and BPWA-EngDom, there was no difference in word retrieval success as a function of bilingualism. While there is no prior group level comparison of word retrieval in monolingual and bilingual aphasia to provide a context for this finding, this result contrasts with the well-documented bilingual disadvantage for word retrieval in neurologically healthy speakers (Bialystok et al., 2008; Gollan, Montoya, Fennema-Notestine, & Morris, 2005). However, this finding that aphasic bilinguals’ word retrieval is on par with matched monolinguals with aphasia adds to the body of literature showing no bilingual language disadvantage in other language impairments such as specific language impairment (Paradis, Crago, Genesee, & Rice, 2003) and autism spectrum disorder (Hambly & Fombonne, 2012). Given bilingual speakers’ need to select words from among two languages, this absence of a bilingual disadvantage in aphasia was unexpected. The better than expected performance of BPWA could not be attributed to a lower severity of aphasia because the two groups did not differ in overall aphasia severity, comprehension scores or demographic measures (Section 2.1). The potential explanation that BPWA-EngDom are able to compensate for their bilingual lexical disadvantage by Please cite this article in press as: Faroqi-Shah, Y., et al., Cognitive control, word retrieval and bilingual aphasia: Is there a relationship?, Journal of Neurolinguistics (2016), http://dx.doi.org/10.1016/j.jneuroling.2016.07.001

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relying more strongly on cognitive control (BICA) was not supported because we did not find a significant correlation between Stroop and word retrieval performance. We had predicted a stronger correlation for BPWA relative to MPWA. However, neither groups’ correlations reached statistical significance. We had expected that at least category fluency performance would be associated with cognitive control given that category fluency engages a multistep cyclical retrieval process that includes monitoring and suppression of generated items to prevent repetitions and errors, self-generation of category cues to access new items, clustering (of subcategories such as farm animals) and switching (to a different subcategory such as wild animals) (Rosen & Engle, 1997; Troyer, Moscovitch, & Winocur, 1997). Therefore, category fluency relies on cognitive control, especially goal-directed inhibition and suppression of (local) lexical competition. In healthy adults, it is associated with a variety of executive function measures in healthy adults such as task switching (Troyer et al., 1997) and working memory (Rosen & Engle, 1997; Unsworth, Spillers, & Brewer, 2010). Similarly, Stroop performance is hypothesized to engage goal-directed inhibition to respond to the font color (MacLeod, 1991) and semantic competition between the colors of the font and word (Catena, Fuentes, & Tudela, 2002; Herd, Banich & O’Reilly, 2006; Sturz, Green, Locker, & Boyer, 2013). Evidence for empirical associations between category fluency and Stroop (or other cognitive control measures) in monolinguals is mixed, while some studies found an association (Ardila, Pineda & Rosselli, 2000; Fisk & Sharp, 2004), others have not (Bialystok et al., 2008; Fournier-Vicente, Larigauderie, & Gaonac’h, 2008; Unsworth et al., 2010). Our findings in PWA are consistent with these latter studies of healthy adults that found no association between Stroop and category fluency. There are several potential explanations for lack of association between word retrieval and Stroop task in PWA. One is that the weakened cognitive control in PWA is no longer available to support word retrieval. Hence, the two are not numerically associated. Second, it could be that although the same mechanisms of cognitive control are utilized for the Stroop task and word retrieval, these are utilized to different extents. Conflict trials in the Stroop task create a semantic competition between semantics of the word color and font color (Sturz et al., 2013), and/or a response competition between indicating the word or font color (MacLeod, 1991). This conflict is resolved primarily by goal-directed proactive inhibition, along with a complementary (and possibly lesser) contribution of reactive inhibition within the semantic system (Goldfarb & Henik, 2006; Sturz et al., 2013). In word retrieval, the contribution of the reactive inhibition within the semantic system may be higher than the need for goal directed inhibition. A third possibility is that the metric of measurement needs to be different. For instance, the number of semantic errors in PWA, or word retrieval speed may be more closely associated with cognitive control (Shao et al., 2012). Finally, it is possible that cognitive control is more closely associated with other language abilities, but not word retrieval. Indeed, as mentioned earlier, the evidence for an association between cognitive control and word retrieval has been mixed in healthy adults. Some language functions that are likely to be more closely associated with cognitive control because of evidence from neurologically healthy controls are language comprehension bilinguals relative to monolinguals (Blumenfeld & Marian, 2013; Kaushanskaya, Blumenfeld, & Marian, 2011; Novick et al., 2010; Vuong & Martin, 2013), bilingual language switching (Linck, Hoshino, & Kroll, 2008), and narrative language (Pivneva, Palmer, & Titone, 2012). Future research is needed to elucidate which language functions are most closely associated with (which measures of) cognitive control in healthy adults and PWA. 5. Conclusions The present study found an interplay between the presence of aphasia, bilingualism and cognitive control. We found that persons with aphasia have a weakness in cognitive control and word retrieval, although the two are not numerically correlated. We also found support for Green’s bilingual inhibitory control advantage in healthy persons and English dominant bilinguals with aphasia, but not for Tamil-English bilinguals. Tamil-English bilingual PWA performed similar to monolingual PWA. These findings demonstrate how left peri-Sylvian brain damage modulates the relationship between cognitive control and bilingualism: the degree of cognitive control disadvantage following aphasia for some bilinguals (e.g., Tamil-English group) is greater than the degree of advantage afforded by high proficiency bilingualism. In other words, bilingualism is only one of the many factors that enhance cognitive control (Valian, 2015). It is now understood that a complex interplay of lifestyle and intellectual activities (such as music, aerobic activity and education) contribute to cognitive control and cognitive reserve; and bilingualism is only one of these factors (Bialystok, Craik, & Luk, 2012; Valian, 2015). While this study demonstrates that cognitive control is weakened in persons with aphasia, future research is needed to elucidate if and how this impacts language functions.

Acknowledgements Preliminary findings of this study were presented at the 2014 Academy of Aphasia Conference, Miami, FL. Partial data for this study were derived from the Doctoral dissertation of Monica Sampson (supported by University of Maryland Dissertation completion supplement award) and Masters thesis of Susan Baughman (supported by a SPARC funding from the American Speech-Language-Hearing Association). We thank Robert Slevc and anonymous reviewers for comments on earlier versions of this paper. Please cite this article in press as: Faroqi-Shah, Y., et al., Cognitive control, word retrieval and bilingual aphasia: Is there a relationship?, Journal of Neurolinguistics (2016), http://dx.doi.org/10.1016/j.jneuroling.2016.07.001


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