N100, N200, and P300 Auditory Event-Related Potentials Depending on Handedness and Response Tasks such as Button Pressing and Mental Counting

Kim, Jinsook; Lee, Kieun; Lee, Eunsung

doi:10.21848/asr.200059

Cited by 1 publication

(1 citation statement)

References 22 publications

(32 reference statements)

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“…Selective-attention ERP examines the cognitive performance using auditory oddball paradigm, which elicits P300 in response to the target intonations through the use of prompt button pushing. This motoric response can cause a distinct movementrelated potential, which has been reported to interfere with the topography of P300 and alter its amplitude in comparison with the silent-count task (Salisbury et al, 2001;van Vliet et al, 2014;Kim et al, 2020). Despite these reported influences on P300 with button-pushing behavior, for old participants with as many as 64 deviant stimuli, the button-press was an optimal task touse the counts of correct and erroneous responses as the two salient variables in evaluating cognitive performance.…”

Section: Discussionmentioning

confidence: 99%

Predicting Dementia With Prefrontal Electroencephalography and Event-Related Potential

Doan

Choi

et al. 2021

Front. Aging Neurosci.

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Objective: To examine whether prefrontal electroencephalography (EEG) can be used for screening dementia.Methods: We estimated the global cognitive decline using the results of Mini-Mental Status Examination (MMSE), measurements of brain activity from resting-state EEG, responses elicited by auditory stimulation [sensory event-related potential (ERP)], and selective attention tasks (selective-attention ERP) from 122 elderly participants (dementia, 35; control, 87). We investigated that the association between MMSE and each EEG/ERP variable by using Pearson’s correlation coefficient and performing univariate linear regression analysis. Kernel density estimation was used to examine the distribution of each EEG/ERP variable in the dementia and non-dementia groups. Both Univariate and multiple logistic regression analyses with the estimated odds ratios were conducted to assess the associations between the EEG/ERP variables and dementia prevalence. To develop the predictive models, five-fold cross-validation was applied to multiple classification algorithms.Results: Most prefrontal EEG/ERP variables, previously known to be associated with cognitive decline, show correlations with the MMSE score (strongest correlation has |r| = 0.68). Although variables such as the frontal asymmetry of the resting-state EEG are not well correlated with the MMSE score, they indicate risk factors for dementia. The selective-attention ERP and resting-state EEG variables outperform the MMSE scores in dementia prediction (areas under the receiver operating characteristic curve of 0.891, 0.824, and 0.803, respectively). In addition, combining EEG/ERP variables and MMSE scores improves the model predictive performance, whereas adding demographic risk factors do not improve the prediction accuracy.Conclusion: Prefrontal EEG markers outperform MMSE scores in predicting dementia, and additional prediction accuracy is expected when combining them with MMSE scores.Significance: Prefrontal EEG is effective for screening dementia when used independently or in combination with MMSE.

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Section: Discussionmentioning

confidence: 99%