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Dissociation of the Confounding Influences of Expectancy and Integrative Difficulty Residing in Anomalous Sentences in Event-related Potential Studies

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Information-Restricted Neural Language Models Reveal Different Brain Regions' Sensitivity to Semantics, Syntax, and

Alexandre Pasquiou^1,2, Yair Lakretz¹, Bertrand Thirion²

¹Cognitive Neuroimaging Unit (UNICOG), NeuroSpin, National Institute of Health and Medical Research (Inserm) and French Alternative Energies and Atomic Energy Commission (CEA), Frédéric Joliot Life Sciences Institute, Paris-Saclay University, Gif-sur-Yvette, France.

Neurobiology of Language (Cambridge, Mass.)

|December 25, 2023

Summary

This summary is machine-generated.

Brain regions for language processing are sensitive to both syntax and semantics, with varying effects across hemispheres. Our novel method using information-restricted language models reveals distinct spatial organizations for syntactic and semantic processing.

Keywords:

LLM context encoding models fMRI semantics syntax

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Transcranial Direct Current Stimulation tDCS of Wernicke's and Broca's Areas in Studies of Language Learning and Word Acquisition

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Published on: July 13, 2019

Area of Science:

Neuroscience
Psycholinguistics
Computational Linguistics

Background:

Understanding the neural basis of language comprehension, specifically the separation versus integration of syntactic and semantic processing, is a key neurolinguistic question.
Previous research has explored brain regions involved in lexical and supra-lexical language processing, but the precise interplay between syntax and semantics remains debated.

Purpose of the Study:

To investigate the extent to which syntactic and semantic information are processed in distinct or overlapping brain regions during speech comprehension.
To develop and apply a novel approach using information-restricted neural language models to probe the neural encoding of linguistic features.

Main Methods:

Trained lexical (GloVe) and supra-lexical (GPT-2) language models on text corpora with selectively removed syntactic or semantic information.
Used features from these information-restricted models to predict functional magnetic resonance imaging (fMRI) time courses of participants listening to naturalistic text.
Manipulated contextual information size for GPT-2 to analyze supra-lexical processing integration windows.

Main Results:

Most language comprehension brain regions responded to both syntactic and semantic features, but with varying relative importance.
Semantic and syntactic features showed more spatial dissociation in the left hemisphere compared to the right.
The right hemisphere demonstrated sensitivity to longer contextual information than the left hemisphere.

Conclusions:

The brain employs a complex organization for syntactic and semantic processing, with both shared and distinct neural substrates.
Information-restricted language models offer a powerful tool to dissect the neural representation of linguistic information.
Findings contribute to understanding the spatial organization of language processing in the human brain, particularly hemispheric differences in context integration.