Alice in the Language Localizer Wonderland (language localizers for diverse languages)
Citation
If you are using any of the Alice-based localizers, please reference the following paper:
Malik-Moraleda, S.*, Ayyash, D.*, Gallée, J., Affourtit, J., Hoffmann, M., Mineroff, Z., Jouravlev, O., & Fedorenko, E. (2022). An investigation across 45 languages and 12 language families reveals a universal language network. Nature Neuroscience.
https://doi.org/10.1038/s41593-022-01114-5.
Overview
As we discuss in more detail here, at the core of our approach is the reliance on “functional localizers”—robust paradigms that target particular brain areas or networks and ensure that the same areas are identified across individuals, studies, and research groups. This ability to consistently refer to the same brain areas (of relevance here are language-responsive areas) is key for establishing a cumulative research enterprise, as needed for ultimately understanding the representations and computations that underlie language processing.
We also believe that in order to truly understand the nature of human language and its neural implementation, it is critical to examine typologically diverse languages. Doing so can enable researchers to i) evaluate the cross-linguistic generality of claims about the language network (Malik-Moraleda, Ayyash et al., 2022), ii) search for potential differences in the neural mechanisms of language processing among speakers of languages that vary along some dimension of interest, and iii) examine phenomena that are only present in a small number of languages. In addition, being able to identify language-responsive areas in speakers of diverse languages can be helpful to clinicians (e.g. for pre-surgical functional mapping).
Inspired by these goals, several years ago, we have begun developing language localizers for diverse languages, which we are making available here.
Experimental script
A general MATLAB Psychtoolbox script that works with materials in any language is available for download here. Instructions on how to run the script, including audio file setup, is in the documentation at the top of the file “AliceLocalizer.m”. You must have MATLAB 2013b or later with Psychtoolbox installed.
Experimental materials
We are using Lewis Carroll’s “Alice in Wonderland” because this book has been translated into dozens of languages. Our materials consist of 24-28 short passages (15-30 sec long) and 1-3 long passages (~5-6 min long). We chose to use the auditory modality in order to make the localizers child-friendly as well as useable in illiterate populations. All the materials are recorded by a female (again, for child-friendliness reasons) native speaker.
The localizer contrast relies on the intact speech > acoustically degraded speech contrast. For each language, the download directory will include: i) 24 intact passages, ii) 24 corresponding degraded passages, iii) 1 long passage, and iv) some additional short and long passages (available for some languages). The long passages can be used for investigating inter-regional functional correlations. For details on the validation of this contrast and showing its similarity to our more traditional language localizer contrast (sentences > nonword sequences, Fedorenko et al., 2010), please see Scott et al. (2017) (for additional evidence, see Malik-Moraleda, Ayyash et al., 2022).
The language localizers are available for over 40 languages. If you use these localizers, please reference this paper: Malik-Moraleda, Ayyash et al., (2022).
Help us create localizers for more languages
We are continuing to work on developing localizers for additional languages. Here is a link to a google spreadsheet where we are keeping track of our efforts. If you are interested in helping us create localizers for any of these, or any other languages, please contact Ev Fedorenko.
