We investigate whether more accurate representation of syntactic
information in Transformer-based language models is
associated with better alignment to brain activity. We use fMRI
recordings from a large dataset (MOUS) of a Dutch sentence
reading task, and perform Representational Similarity Analysis
to measure alignment with 2 mono- and 3 multilingual
language models. We focus on activity in a region known
for syntactic processing (the Left posterior Medial Temporal
Gyrus). We correlate model-brain similarity scores with the
accuracy of dependency structures extracted from model internal
states using a labelled structural probe. We report three key
findings: 1) Accuracy of syntactic dependency representations
correlates with brain similarity, 2) The link between brain similarity
and dependency accuracy persists regardless of sentence
complexity, although 3) Sentence complexity decreases dependency
accuracy while increasing brain similarity. These results
highlight how interpretable, linguistic features such as syntactic
dependencies can mediate the similarity between language
models and brains