Idan Blank

TL;DR: A synergistic combination of functional MRI methods defines candidate language-specific and MD regions in each subject individually and measures blood oxygen level-dependent signal fluctuations in these regions during two naturalistic conditions, consistent with the hypothesis that these two systems support distinct cognitive functions.

TL;DR: It is found that the most powerful ‘transformer’ networks predict neural responses at nearly 100% and generalize across different datasets and data types (fMRI, ECoG), suggesting that inherent structure – and not just experience with language – crucially contributes to a model’s match to the brain.

TL;DR: Claims about Broca's area should be (re)cast in terms of these (and other, as yet undetermined) functional components, to establish a cumulative research enterprise where empirical findings can be replicated and theoretical proposals can be meaningfully compared and falsified.

TL;DR: Network methods are used, applied to fMRI data collected from 22 human subjects performing a language comprehension task, to reveal the dynamic nature of the language system and suggest a trade-off between a region's specialization and its capacity for flexible network reconfiguration.

TL;DR: It is hypothesized that, whereas the entire language system is in fact sensitive to syntactic complexity, the effects in some regions may be difficult to detect because of the overall lower response to language stimuli, and that such distributed nature of syntactic processing could perhaps imply that syntax is inseparable from other aspects of language comprehension.