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Hale, J. T.

Publications and source records attributed to Hale, J. T..

3 recordsLinked to original sources

Rapid visual form-based processing of (some) grammatical features in parallel reading: An EEG study in English

Theories of language processing - and typical experimental methodologies - emphasize the word-by-word processing of sentences. This paradigm is good for approximating speech or careful text reading, but arguably, not for the common, cursory glances used while reading short sentences (e.g., cellphone notifications, social media posts). How can we interpret a sentence in a single glance? In an electroencephalography (EEG) study, brain responses to grammatical sentences (the dogs chase a ball) presented for 200ms diverged from non-lexical consonant strings (thj rjxb zkhtb w lhct) [~]160ms post-sentence onset and from scrambled constructions (a dogs chase ball the) [~]250ms post-sentence onset, demonstrating - at different time points - rapid recognition and cursory analysis of linguistic stimuli. In the grammatical sentences, unigram probability correlated with EEG data [~]150-300ms post-sentence onset, and probability of the word given its context estimated by BERT correlated with EEG data after [~]700-800ms. EEG responses did not diverge between grammatical sentences and their counterparts with ungrammatical agreement (the dogs chases a ball), although EEG responses did diverge for plural vs. singular morphology at [~]200ms. These results suggest that at-a-glance reading is possible, based on coactivation of individual lexical items, morphological structures, and constituent structure at [~]200-300ms, but that words are not integrated into a coherent syntactic/semantic analysis, as evidenced by the substantially later responses to BERT probability and the absence of sensitivity to agreement errors.

neuroscience↗

Long-distance linguistic dependencies in Chinese and English brains

Are the brain bases of language comprehension the same across all human languages, or do these bases vary in a way that corresponds to differences in linguistic typology? English and Mandarin Chinese attest such a typological difference in the domain of relative clauses. Using fMRI with English and Chinese participants, who listened to the same translation-equivalent story, we analyzed neuroimages time-aligned to object-extracted relative clauses in both languages. In a GLM analysis of these naturalistic data, comprehension was selectively associated with increased hemodynamic activity in left posterior temporal lobe, angular gyrus, inferior frontal gyrus, precuneus, and posterior cingulate cortex in both languages. This result suggests the processing of object-extracted relative clauses is subserved by a common collection of brain regions, regardless of typology. However, there were also regions that were activated uniquely in our Chinese participants albeit not to a significantly greater degree. These were in the temporal lobe. These Chinese-specific results could reflect structural ambiguity-resolution work that must be done in Chinese but not English ORCs.

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↗