Prediction underlying comprehension of human motion: an analysis of Deaf signer and non-signer EEG in response to visual stimuli

Frontiers in Neuroscience

Neuroscience

Evie A. Malaia¹  Sean C. Borneman¹  Joshua D. Borneman²  Ronnie B. Wilbur³  Julia Krebs⁴ 

[1] Department of Communicative Disorders, University of Alabama, Tuscaloosa, AL, United States;Department of Linguistics, Purdue University, West Lafayette, IN, United States;Department of Linguistics, Purdue University, West Lafayette, IN, United States;Department of Speech, Language, and Hearing Sciences, Purdue University, West Lafayette, IN, United States;Linguistics Department, University of Salzburg, Salzburg, Austria;Centre for Cognitive Neuroscience, University of Salzburg, Salzburg, Austria;

关键词: sign language;    predictive processing;    entrainment;    EEG;    optical flow;    motion;    comprehension;   

DOI  :  10.3389/fnins.2023.1218510

 received in 2023-05-12, accepted in 2023-09-27,  发布年份 2023

来源: Frontiers

【 摘 要 】

IntroductionSensory inference and top-down predictive processing, reflected in human neural activity, play a critical role in higher-order cognitive processes, such as language comprehension. However, the neurobiological bases of predictive processing in higher-order cognitive processes are not well-understood.MethodsThis study used electroencephalography (EEG) to track participants' cortical dynamics in response to Austrian Sign Language and reversed sign language videos, measuring neural coherence to optical flow in the visual signal. We then used machine learning to assess entropy-based relevance of specific frequencies and regions of interest to brain state classification accuracy.ResultsEEG features highly relevant for classification were distributed across language processing-related regions in Deaf signers (frontal cortex and left hemisphere), while in non-signers such features were concentrated in visual and spatial processing regions.DiscussionThe results highlight functional significance of predictive processing time windows for sign language comprehension and biological motion processing, and the role of long-term experience (learning) in minimizing prediction error.

【 授权许可】

Unknown   
Copyright © 2023 Malaia, Borneman, Borneman, Krebs and Wilbur.