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A meta-analytic perspective on data sharing and reproducibility in cognitive neuroscience of sign language

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Trettenbrein,  Patrick
Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Zaccarella,  Emiliano
Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Trettenbrein, P., & Zaccarella, E. (2019). A meta-analytic perspective on data sharing and reproducibility in cognitive neuroscience of sign language. Talk presented at Workshop on "Doing Reproducible and Rigorous Science with Deaf Children, Deaf Communities, and Sign Languages: Challenges and Opportunities". Humboldt University Berlin, Germany. 2019-09-23 - 2019-09-23.


Cite as: https://hdl.handle.net/21.11116/0000-0004-C210-E
Abstract
The acquisition of most neuroimaging data and especially magnetic resonance imaging (MRI) data is laborious and cost-intensive. Nevertheless, the practice of data sharing is not commonplace in the field of cognitive neuroscience of sign language. We have recently completed the first ever meta-analysis of the neuroimaging literature on sign language to identify brain regions consistently involved in processing of sign language across studies and paradigms (Trettenbrein et al., forthcoming), in the course of which we encountered a variety of obstacles relating to data sharing and reproducibility. This presentation will recapitulate the issues we faced when carrying out our meta-analysis. Against this background, we will discuss how adopting Open Science practices and infrastructure for data sharing and reproducibility that are already established in neuroimaging at large may benefit future (meta-analytic) work. We end by sketching how Open Science ideas have been implemented in our own ongoing work on sign language.