Decoding meaning composition during naturalistic language comprehension
Keywords
Loading...
Authors
Issue Date
2022-06-22
Language
en
Document type
Journal Title
Journal ISSN
Volume Title
Publisher
Title
ISSN
Volume
Issue
Startpage
Endpage
DOI
Abstract
Human language allows for the combination of individual word meanings into more complex
expressions. This capacity, meaning composition, and its neural bases have been studied
typically using tightly controlled stimuli. The current study aimed to extend this body of
research, asking if and to what extent findings from studies deploying tightly controlled
stimuli generalise to more naturalistic contexts. Twenty-four participants listened to 45
minutes of audiobooks annotated for word onset, part of speech, and dependency relations
while magnetoencephalography (MEG) was recorded. We used a series of decoding analyses
to examine the multivariate neural responses to composition-related features. Our analyses
were designed to isolate composition-related operations and representations whilst
controlling for possible confounds such as linear word order, word distance, word position,
and part of speech. We show that (1) composition-related features were uniquely reflected in
the low frequency content of neural readout and (2) the coding of compositional features is in
part time stable and in part time varying. Overall, our work shows that combining analysis
techniques from engineering with temporally resolved neuroimaging grounded in theory
yields new insights into the brain bases of meaning composition.
Description
Citation
Supervisor
Faculty
Faculteit der Sociale Wetenschappen