5/ In the language network, we can reliably decode stimulus (sentences vs. nonwords), and more accurately than we can decode task.
In contrast, in the MD network, task is better decoded than stimulus type.

4/ Task demands do increase responses in the language network, but reading sentences accompanied by active tasks also strongly recruits the Multiple Demand (MD) network, which is sensitive to task demands.

3/ The activations are remarkably consistent within individuals across tasks (and, as reported before, variable across individuals).

2/ Across all six tasks, the language network is strongly engaged by the sentences > non-words contrast.

1/ We ran six versions of a language localizer, ranging from passive reading to sentiment judgments.

Excited to introduce funROI: A Python package for functional ROI analyses of fMRI data!

funroi.readthedocs.io/en/latest/

#fMRI #Neuroimaging #Python #OpenScience

Work w @neuranna.bsky.social

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