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Brennan, J. R.

Publications and source records attributed to Brennan, J. R..

2 recordsLinked to original sources

Decoding the Neural Dynamics of Headed Syntactic Structure Building

The brain builds hierarchical phrases during language comprehension; however, the representational details and dynamics of the phrase-building process remain underspecified. This study directly probes whether the neural code of a phrase involves reactivating the syntactic property of a key subcomponent (the "phrasal head"). To this end, we train a part-of-speech sliding-window neural decoder (verb vs. adverb) on EEG signals recorded while participants (N = 30) read sentences in a controlled experiment. The decoder reaches above-chance performance that is spatiotemporally consistent and generalizes to unseen data across sentence positions. Appling the decoder to held-out data yields predicted activation levels for the verbal "head" of a verb phrase at a distant non-head word (adverb); the critical adverb appeared either at the end of a verb phrase or at a sequentially and lexically matched position with no verb phrase boundary. There is stronger verb activation beginning at [~]600 milliseconds at the critical adverb when it appears at a verb phrase boundary; this effect is not modulated by the strength of conceptual association between the two subcomponents in the verb phrase nor does it reflect word predictability. Time-locked analyses additionally reveal a negativity waveform component and increased beta-delta inter-trial phase coherence, both previously linked to linguistic composition, in a similar time window. With a novel application of neural decoding, our findings delineate the temporal dynamics by which the brain encodes phrasal representations by, in part, reactivating the representation of key subcomponents. We thus establish a link between cognitive accounts of phrase structure representations and electrophysiological dynamics.

neuroscience↗

Le Petit Prince: A multilingual fMRI corpus using ecological stimuli

Neuroimaging using more ecologically valid stimuli such as audiobooks has advanced our understanding of natural language comprehension in the brain. However, prior naturalistic stimuli have typically been restricted to a single language, which limited generalizability beyond small typological domains. Here we present the Le Petit Prince fMRI Corpus (LPPC-fMRI), a multilingual resource for research in the cognitive neuroscience of speech and language during naturalistic listening (Open-Neuro: ds003643). 49 English speakers, 35 Chinese speakers and 28 French speakers listened to the same audiobook The Little Prince in their native language while multi-echo functional magnetic resonance imaging was acquired. We also provide time-aligned speech annotation and word-by-word predictors obtained using natural language processing tools. The resulting timeseries data are shown to be of high quality with good temporal signal-to-noise ratio and high inter-subject correlation. Data-driven functional analyses provide further evidence of data quality. This annotated, multilingual fMRI dataset facilitates future re-analysis that addresses cross-linguistic commonalities and differences in the neural substrate of language processing on multiple perceptual and linguistic levels.

neuroscience↗