Work

Language-derived mental object load suppresses posterior alpha power

Year: 2026

Type: article

Abstract: Language and vision are two primary source modalities of information for humans. To uncover shared and unique mental representations across linguistic and visual inputs, one approach is to test the extent to which a certain neural signature is shared. In the current EEG study, we tested whether the response profile of posterior alpha power – a neural signature well-studied for visual working memory – generalizes to non-visual linguistic input. Employing a novel imagine-one-then-more paradigm in a large EEG sample ( N = 52), we found that increasing the number of imagined objects derived from a non-visual linguistic source – auditory speech during eye closure – led to greater suppression of left posterior alpha power, and that this suppression plateaued beyond ∼ 3 objects. This response profile closely mirrors effects previously observed for visually-derived representations. As posterior alpha power likely reflects the representational load of slots/pointers or spatial attention in moment-to-moment cognition, our study thus provides novel insights into the specific representational facets shared across language and vision.

Source: Journal of Neurolinguistics

DOI: 10.1016/j.jneuroling.2026.101383

Authors: Xinchi Yu, Utku Türk, Allison Dods, Xing Tian, Ellen Lau

Institutions: Institut für Medizinische Psychologie, University of Maryland, College Park, Ludwig-Maximilians-Universität München, New York University Shanghai, East China Normal University

Language: English

Topic: Neural dynamics and brain function

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: hybrid

Estimated APC paid: $3,430

Funder: National Science Foundation