Group analysis and classification of working memory task conditions using electroencephalogram cortical currents during an n-back task

Frontiers in Neuroscience(2023)

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摘要
Electroencephalographic studies of working memory have demonstrated cortical activity and oscillatory representations without clarifying how the stored information is retained in the brain. To address this gap, we measured scalp electroencephalography data, while participants performed a modified n-back working memory task. We calculated the current intensities from the estimated cortical currents by introducing a statistical map generated using Neurosynth as prior information. Group analysis of the cortical current level revealed that the current amplitudes and power spectra were significantly different between the modified n-back and delayed match-to-sample conditions. Additionally, we classified information on the working memory task conditions using the amplitudes and power spectra of the currents during the encoding and retention periods. Our results indicate that the representation of executive control over memory retention may be mediated through both persistent neural activity and oscillatory representations in the beta and gamma bands over multiple cortical regions that contribute to visual working memory functions.
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关键词
working memory, EEG, hierarchical Bayesian estimation, sparse logistic regression, artifact
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