Bradshaw, AR;
Thompson, PA;
Wilson, AC;
Bishop, DVM;
Woodhead, ZVJ;
(2017)
Measuring language lateralisation with different language tasks: a systematic review.
PEERJ
, 5
(e3929)
10.7717/peerj.3929.
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Abstract
Language lateralisation refers to the phenomenon in which one hemisphere (typically the left) shows greater involvement in language functions than the other. Measurement of laterality is of interest both to researchers investigating the neural organisation of the language system and to clinicians needing to establish an individual’s hemispheric dominance for language prior to surgery, as in patients with intractable epilepsy. Recently, there has been increasing awareness of the possibility that different language processes may develop hemispheric lateralisation independently, and to varying degrees. However, it is not always clear whether differences in laterality across language tasks with fMRI are reflective of meaningful variation in hemispheric lateralisation, or simply of trivial methodological differences between paradigms. This systematic review aims to assess different language tasks in terms of the strength, reliability and robustness of the laterality measurements they yield with fMRI, to look at variability that is both dependent and independent of aspects of study design, such as the baseline task, region of interest, and modality of the stimuli. Recommendations are made that can be used to guide task design; however, this review predominantly highlights that the current high level of methodological variability in language paradigms prevents conclusions as to how different language functions may lateralise independently. We conclude with suggestions for future research using tasks that engage distinct aspects of language functioning, whilst being closely matched on non-linguistic aspects of task design (e.g., stimuli, task timings etc); such research could produce more reliable and conclusive insights into language lateralisation. This systematic review was registered as a protocol on Open Science Framework: https://osf.io/5vmpt/.
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