Abstract

Meta-analyses are a method by which to increase the statistical power and generalizability of neuroimaging findings. In the neurolinguistics literature, meta-analyses have the potential to substantiate hypotheses about L1 and L2 processing networks and to reveal differences between the two that may escape detection in individual studies. Why then is there so little consensus between the reported findings of even the most recently published and most highly powered meta-analyses? Limitations in the literature, such as the absence of a common method to define and measure descriptive categories (e.g., proficiency level, degree of language exposure, age of acquisition, etc.) are often cited. An equally plausible explanation lies in the technical details of how individual meta-analyses are conducted. This paper provides a review of recent meta-analyses, with a discussion of their methodological choices and the possible effect those choices may have on the reported findings.

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