Figures
7.1The Bilingual Interactive Activation (BIA) model (Dijkstra & van Heuven, 1998).
7.2The translation distractor effect (positive numbers equal an inhibitory effect of translation distractors) for trilinguals naming pictures in their L2 English, depending on SOA, distractor modality, and distractor language (Schriefers & Lemhöfer, in press).
7.3The Revised Hierarchical Model of bilingual word translation (Kroll & Stewart, 1994).
9.1Distribution of random effect sizes for two critical conditions (Determiner use and Adverb placement), showing that Russian–German L3 learners of English are different from both of the corresponding L2 groups (Kolb et al., 2022).
9.2Distribution of individual accuracy scores on subject-verb agreement by group: Bilingual (2L1 Norwegian/Russian–L3 English), Norwegian (L1 Norwegian–L2 English), Russian (L1 Russian–L2 English) (Jensen et al., 2021: 13).
11.1Language choice in the trilingual child Tommaso (German, Italian, Swiss German) (Einfeldt, 2022).
18.1Visual enhancement technique with a focus on German and English word order (Hahn & Angelovska, 2017: 309).
20.1Schematic of four cognitive control tasks widely used in bilingualism research – the Stroop Task, Simon Task, Attention Network Test (ANT), and Go/No-Go task.
20.2Medial view of the brain regions associated with cognitive control.
20.3Language experience exists along a multidimensional continuum, with individual variability in proficiency, usage, age of acquisition, and more.
21.1Schematic overview of studies showing evidence in favor and against the hypothesis about the protective effects of the bilingual experience.
22.2A mid-sagittal (a), lateral (b), and mid-axial (c) view of a template brain, indicating the main GM regions discussed in this chapter. WM, and how it differentiates from cortical and subcortical GM, is visible in (c) (Pliatsikas, 2019: 230–251). © John Wiley & Sons 2019.
29.1Illustration of 10, 50, 100, and 300 samples from the posterior for π. The vertical line represents thetrue value of π.
29.2Illustrative chains converging to the same parameter space.
29.3Illustrative chains not converging to the same parameter space.
29.4How our prior can affect our conclusions (posterior) (Garcia, 2021: ch. 10).
29.5How our prior can affect our conclusions (posterior) (Garcia, 2021: ch. 10).
29.6How our prior can affect our conclusions (posterior) (Garcia, 2021: ch. 10).
29.7Preference for high attachment by group (population and sample). Associated error bars represent bootstrapped confidence intervals.
29.8Posterior distributions for our intercept and slope. Shaded areas represent the 95 percent HDI in the posterior confidence intervals.
29.9Trace plot showing well-mixed chains for both parameters of interest.
29.10Sensitivity analysis with multiple priors for β0 (μ and σ). Dashed line represents the true (population) value. Shaded area represents ROPE.
29.11Percentage of highest density interval contained within ROPE. Less is better.
