The role of conscious attention in auditory statistical learning: Evidence from patients with impaired consciousness
Year: 2024
Type: article
Study design: Observational Study
Abstract: The need for attention to enable statistical learning is debated. Testing individuals with impaired consciousness offers valuable insight, but very few studies have been conducted due to the difficulties inherent in such studies. Here, we examined the ability of patients with varying levels of disorders of consciousness (DOC) to extract statistical regularities from an artificial language composed of randomly concatenated pseudowords by measuring frequency tagging in EEG. The objectives were firstly, to assess the automaticity of the segmentation process and the correlations between the level of covert consciousness and statistical learning capacities; secondly, to identify potential new diagnostic indicators. We observed that segmentation abilities were preserved in some minimally conscious patients, suggesting that auditory statistical learning is an inherently automatic low-level process. Due to significant inter-individual variability, word segmentation might not be robust enough for clinical use. In contrast, temporal accuracy of auditory syllable responses correlates strongly with coma severity.
Source: iScience
Authors: Lucas Benjamin, Di Zang, Ana Fló, Zengxin Qi, Pengpeng Su, Wenya Zhou, Liping Wang, Xuehai Wu, Peng Gui, Ghislaine Dehaene-Lambertz
Institutions: Centre National de la Recherche Scientifique, Inserm, Commissariat à l'Énergie Atomique et aux Énergies Alternatives, Université Paris-Saclay, Cognitive Neuroimaging Lab, Shanghai Medical College of Fudan University, Fudan University, China-Japan Friendship Hospital, Huashan Hospital, University of Padua, Chinese Academy of Sciences, Center for Excellence in Brain Science and Intelligence Technology
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,150
OpenAlex ID: W4405309957
