Meta-analysis of the neural representation of first language and second language
نویسندگان
چکیده
This study reports an activation likelihood estimation meta-analysis of published functional neuroimaging studies of bilingualism. Four parallel meta-analyses were conducted by taking into account the proficiency of participants reported in the studies. The results of the meta-analyses suggest differences in the probabilities of activation patterns between high proficiency and moderate/low proficiency bilinguals. The Talairach coordinates of activation in first language processing were very similar to that of second language processing in the high proficient bilinguals. However, in the low proficient group, the activation clusters were generally smaller and distributed over wider areas in both the hemispheres than the clusters identified in the ALE maps from the high proficient group. These findings draw attention to the importance of language proficiency in bilingual neural representation. The representation of multiple languages in the brain of a bilingual has been a subject of research for more than a century. Many theories exist about how the brain processes first language (L1) and second language (L2). Two general approaches were adopted in the study of the bilingual brain. The first approach has examined the effect of brain damage on language processing in individuals with bilingual aphasia (Fabbro, 1999). Clinical studies have enhanced our knowledge about the patterns of language recovery after stroke in bilinguals. Paradis (1977) proposed five patterns of cross-linguistic recovery in bilingual individuals with aphasia. The five types of classic recovery patterns are (a) parallel recovery, (b) differential recovery, (c) selective recovery, (d) successive recovery, and (e) antagonistic recovery. The recovery patterns provide evidence for distinct and © Cambridge University Press 2011 0142-7164/11 $15.00 Applied Psycholinguistics 32:4 800 Sebastian et al.: Meta-analysis of the neural representation of L1 and L2 overlapping neuroanatomical representation of the languages in the brain. For example, research on parallel recovery after stroke in bilinguals suggests that for many bilinguals and polyglots, the areas involved in processing language may be the same (Albert & Obler, 1978; Fabbro, 1999). However, many researchers interpret selective or differential recovery of one or more language in bilingual or polyglots after stroke as suggesting nonoverlapping cortical representation (Gomez-Tortosa, Martin, Gaviria, Charbel, & Ausman, 1995; Junque, Vendrell, & Vendrell, 1995, pp. 139–176; Nilipourn & Ashayeri, 1989). These studies, however, do not provide any conclusions about specific regions in the brain that are responsible for processing one language versus the other. Another approach to the study of the bilingual brain is of the experimental type, such as electrophysiological investigations (electrocortico stimulation during brain surgery and event-related potentials) and functional neuroimaging studies. Neuroimaging techniques such as position emission tomography (PET) and functional magnetic resonance imaging (fMRI) allow a more direct and noninvasive study of the cortical representation of languages in the brain and can provide a clear indication of the neural regions that may be involved in processing of two languages. A large body of functional neuroimaging studies has been devoted to the investigation of language organization in the intact human brain. The application of these techniques to the study of bilingualism may enable us to investigate the role of several factors that have been considered to influence the neural organization of languages, such as age of L2 acquisition and proficiency in L2. A few reviews have examined the bilingual neuroimaging literature (Abutalebi, 2008; Abutalebi, Cappa, & Perani, 2001, 2005; Indefrey, 2006; Stowe & Sabourin, 2005). Abutalebi et al. (2005, pp. 497–515) reviewed several bilingual neuroimaging studies focusing on the role of age of L2 acquisition and degree of proficiency attained in each of the languages. Using a traditional tabulation of label-reported regions, the authors found that when the degree of proficiency in bilinguals was high, a common language system appeared to be responsible for the processing of both languages. This included the left inferior frontal gyrus, superior and middle temporal gyri, the angular gyrus, and the temporal pole. Lower proficiency in L2 was associated with a more extended network of activation, including foci in the right hemisphere. The authors concluded that, when language proficiency is kept constant, age of acquisition does not seem to have a major impact on neural representation of L2. In another study, Stowe and Sabourin (2005) reviewed eight bilingual neuroimaging studies to explore whether L1 and L2 activated similar neural regions and the extent to which it depended on the age of acquisition. They examined three different language tasks: lexical semantics, syntactic comprehension, and phonological processing. The results indicated that L1 and L2 activated the same typical language areas in the left frontal and temporoparietal regions. In addition, late language learners used the same neural substrates for L2 processing as used for L1 processing. However, the neurological system that underlies language appeared to be used less efficiently for L2 as demonstrated by more extensive activations for L2 compared to L1. They concluded that the subprocesses involved in normal language processing are not utilized optimally in some aspects of L2 processing, at least for the less proficient speakers. Applied Psycholinguistics 32:4 801 Sebastian et al.: Meta-analysis of the neural representation of L1 and L2 The conclusions draw by Stowe and Sabourin (2005) were similar to that drawn by Indefrey (2006). Indefrey (2006) analyzed the results of 30 hemodynamic experiments comparing L1 processing and L2 processing in a range of tasks. The results of the review indicated differences between L1 and L2, but only for subgroups of bilingual speakers. During word production, L1 and L2 engaged the same cortical areas, whereas L2 speakers with late L2 onset or lower proficiency recruited the left inferior frontal cortex more strongly than L1. For word-level semantic processing in comprehension, L2 onset and exposure did not play a major role. By contrast, L2 onset played an important factor for activation differences related to syntactic processing in sentence comprehension. In a recent review, Abutalebi (2008) examined the existing bilingual literature with a narrower focus on the neural correlates of grammatical and lexicosemantic processing in bilinguals. According to the author, neural differences between L1 and L2 existed for grammatical processing and lexicosemantic processing. These differences are particularly prominent in the initial stages of L2 acquisition and/or when L2 is processed with a “nonnativelike” proficiency. The differences between L1 and L2 disappear once a more “nativelike” proficiency is established in L2, reflecting a change in language processing mechanism: from controlled processing for a less proficient L2 to more automatic processing. The above-mentioned reviews suggest that the neural representation of languages in bilinguals is modulated by a number of factors, of which proficiency appears to be the most important factor. However, all these reviews have attempted to synthesize the literature using a descriptive/qualitative approach that inherently relies on author-supplied anatomical labels that may be unduly broad (e.g., left prefrontal cortex). Comparison of reported coordinates across studies can also prove challenging in that localization of a given set of coordinates to a particular neuroanatomical location is dependent on the target brain atlas and corresponding stereotaxic space in which the data set was registered. In the present study, we build upon these prior efforts by using the recently developed activation likelihood estimation (ALE; Eickhoff et al., 2009; Laird, Fox, et al., 2005; Turkeltaub, Eden, Jones, & Zeffiro, 2002) technique to carry out a quantitative, voxelwise meta-analysis of published functional neuroimaging studies on bilingualism. A quantitative meta-analysis can provide a useful method to assess the state of the field and to provide a plan for future research. This technique provides an unbiased, statistically based approach to examine findings across studies, as opposed to the traditional “box score” or label-based qualitative methods (Laird, McMillan, et al., 2005). Activation likelihood estimation was originally developed to identify the brain regions that were consistently activated during speech production (Turkeltaub et al., 2002) using coordinates reported by different functional imaging studies. It assumes that each study reports specific coordinates of activations, which vary due to differences associated with scanners, analyses, paradigms, and intersubject variability. The spatial distribution of these foci is analyzed to determine the regions in which activations are consistently observed, regardless of variability in study design. In activation likelihood estimation, the foci reported by each study are modeled as a probability distribution. Then a map of the whole brain is constructed, assigning to each voxel a value equal to the probability that an activation lies within the voxel. Significance of these Applied Psycholinguistics 32:4 802 Sebastian et al.: Meta-analysis of the neural representation of L1 and L2 values are determined by computing a null distribution obtained by permutation testing, correcting for multiple comparisons by controlling the false discovery rate (FDR). For example, an FDR correction guarantees that in a set of voxels deemed significant for a test of p = .05, the expected proportion of false positives is controlled (Laird, Fox, et al., 2005). The ALE technique has been applied in the study of a variety of imaging areas such as of specific cognitive functions (Derrfuss, Brass, Neumann, & Yves von Cramon, 2005; Krain, Wilson, Arbuckle, Castellanos, & Milham, 2006; Laird, McMillan, et al., 2005; McMillan, Laird, Witt, & Meyerand, 2007; Owen, McMillan, Laird, & Bullmore, 2005; Price, Devlin, Moore, Morton, & Laird, 2005; Tan, Laird, Li, & Fox, 2005), major depressive disorder (Fitzgerald et al., 2006), attention-deficit/hyperactivity disorder (Ellison-Wright, Glahn, Laird, Thelen, & Bullmore, 2008), stuttering (Brown, Lasird, Ingham, Ingham, & Fox, 2005), schizophrenia (Glahn et al., 2005), and obsessive–compulsive disorder (Menzies et al., 2008). In this study we quantitatively analyze the role of L2 proficiency in bilingual neural representation using the ALE technique. The studies are divided into two groups based on the L2 proficiency of the subjects: high proficiency group and low/moderate proficiency group. Our hypothesis is that greater proficiency in a language will be associated with the recruitment of a common overlapping network and focal activation in core regions in the language network, whereas lesser proficiency in a language will be associated with a more distributed network of regions. This same observation, that proficiency induces efficiency (i.e., a more circumscribed network of activation), has been made in numerous neural systems, perhaps most convincingly in studies of motor learning (Ma et al., 2010). The present experiment aimed to examine this issue in the context of functional neuroimaging studies of bilingualism.
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