Work

A-maze of Natural Stories: Comprehension and surprisal in the Maze task

Year: 2023

Type: article

Abstract: Behavioral measures of word-by-word reading time provide experimental evidence to test theories of language processing. A-maze is a recent method for measuring incremental sentence processing that can localize slowdowns related to syntactic ambiguities in individual sentences. We adapted A-maze for use on longer passages and tested it on the Natural Stories corpus. Participants were able to comprehend these longer text passages that they read via the Maze task. Moreover, the Maze task yielded useable reaction time data with word predictability effects that were linearly related to surprisal, the same pattern found with other incremental methods. Crucially, Maze reaction times show a tight relationship with properties of the current word, with little spillover of eﬀects from previous words. This superior localization is an advantage of Maze compared with other methods. Overall, we expanded the scope of experimental materials, and thus theoretical questions, that can be studied with the Maze task.

Source: Glossa Psycholinguistics

DOI: 10.5070/g6011190

Authors: Veronica Boyce, Roger Philip Levy

Institutions: Massachusetts Institute of Technology, Stanford University

Language: English

Topic: Neurobiology of Language and Bilingualism

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: diamond

Funders: National Science Foundation, National Institutes of Health, University of California, Irvine, National Institute of Neurological Disorders and Stroke

Awards: CompCog: Noisy-channel processing in human language understanding, Computational Neuroscience of Language Processing in the Human Brain