“…Recent research has begun identifying shared computational principles between the way the human brain and DLMs represent and process natural language. In particular, several studies have used contextual embeddings derived from DLMs to successfully model human behavior as well as neural activity measured by fMRI, EEG, MEG, and ECoG during natural speech processing (Antonello et al, 2021; Caucheteux & King, 2022; Goldstein et al, 2022; Heilbron et al, 2020; Hollenstein et al, 2021; Schwartz et al, 2019; Toneva & Wehbe, 2019). Furthermore, recent studies have shown that similarly to DLMs, the brain incorporates prior context into the meaning of individual words (Jain & Huth, 2018; Caucheteux et al, 2021a; Schrimpf et al, 2021), spontaneously predicts forthcoming words (Goldstein, Zada et al, 2022), and computes post-word-onset prediction error signals (Donhauser & Baillet, 2020; Willems et al, 2016; Heilbron et al, 2020; Goldstein, Zada et al, 2022).…”