Localizer tasks
Language network localizer (reading)
Participants read sentences and nonword sequences. The sentences>nonwords contrast can be used to localize high-level language processing brain regions (Fedorenko et al., 2010), i.e., regions that support lexico-semantic and combinatorial (syntactic and semantic) processes (e.g., Fedorenko et al., 2012, Fedorenko et al., 2016 , Fedorenko et al., 2020, Shain and Kean, 2024).
Language network localizer (listening)
Participants listen to short auditory passages (excerpts from interviews, etc.) and acoustically degraded versions of these passages. The intact>degraded contrast localizes high-level language processing brain regions (see Scott et al., 2017 for evidence that this contrast identifies the same areas as the sentences>nonwords contrast in reading), i.e., regions that support lexico-semantic and combinatorial (syntactic and semantic) processes.
MD (and DMN) (spatial working memory) network localizer
Participants see a 3x4 grid, and squares appear in various locations sequentially (one at a time in the easier condition, and two at a time in the harder condition). Participants have to keep track of the locations. At the end of each trial, they are presented with two sets of locations and asked to choose the set they just saw. They are given feedback on whether they answered correctly. The harder>easier contrast can be used to localize the domain-general executive control brain regions in the frontal and parietal cortex that form the Multiple Demand (MD) network (e.g., Duncan, 2010, 2013; Fedorenko et al., 2013). These regions support diverse executive functions like working memory and cognitive control. The easier>harder or easier>fixation contrasts can be used to localize the Default Mode Network (DMN) (e.g., Buckner et al., 2008; Buckner & DiNicola, 2018; see Mineroff & Blank et al., 2018 for evidence that the easier>harder contrast in this paradigm robustly identifies DMN regions).
For any other localizers used in our work, please contact Ev (evelina9@mit.edu)
