Temporal dynamics of animacy categorization in the brain of patients with mild cognitive impairment.

Autor: Karimi H; Department of Stem Cells and Developmental Biology, Cell Science Research Center, Royan Institute for Stem Cell Biology and Technology, ACECR, Tehran, Iran.; Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, Iran., Marefat H; School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran., Khanbagi M; Department of Stem Cells and Developmental Biology, Cell Science Research Center, Royan Institute for Stem Cell Biology and Technology, ACECR, Tehran, Iran., Kalafatis C; South London & Maudsley NHS Foundation Trust, London, United Kingdom.; Department of Old Age Psychiatry, King's College London, London, United Kingdom.; Cognetivity Ltd, London, United Kingdom., Modarres MH; Cognetivity Ltd, London, United Kingdom., Vahabi Z; Department of Geriatric Medicine, Ziaeian Hospital, Tehran University of Medical Sciences, Tehran, Iran.; Memory and Behavioral Neurology Division, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran., Khaligh-Razavi SM; Department of Stem Cells and Developmental Biology, Cell Science Research Center, Royan Institute for Stem Cell Biology and Technology, ACECR, Tehran, Iran.; Cognetivity Ltd, London, United Kingdom.
Jazyk: angličtina
Zdroj: PloS one [PLoS One] 2022 Feb 23; Vol. 17 (2), pp. e0264058. Date of Electronic Publication: 2022 Feb 23 (Print Publication: 2022).
DOI: 10.1371/journal.pone.0264058
Abstrakt: Electroencephalography (EEG) has been commonly used to measure brain alterations in Alzheimer's Disease (AD). However, reported changes are limited to those obtained from using univariate measures, including activation level and frequency bands. To look beyond the activation level, we used multivariate pattern analysis (MVPA) to extract patterns of information from EEG responses to images in an animacy categorization task. Comparing healthy controls (HC) with patients with mild cognitive impairment (MCI), we found that the neural speed of animacy information processing is decreased in MCI patients. Moreover, we found critical time-points during which the representational pattern of animacy for MCI patients was significantly discriminable from that of HC, while the activation level remained unchanged. Together, these results suggest that the speed and pattern of animacy information processing provide clinically useful information as a potential biomarker for detecting early changes in MCI and AD patients.
Competing Interests: SKR and CK serve as the CSO and CMO at Cognetivity ltd., and HModarres as the lead data scientist. These affiliations do not alter our adherence to PLOS ONE policies on sharing data and materials. Other authors declared no competing interests.
Databáze: MEDLINE
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