Search

Eye movement during blinking can be a significant artifact in Event-Related Potentials (ERP) analysis. Blinks produce a positive potential in the vertical electrooculogram (VEOG), spreading towards the posterior direction. Two methods are frequently used to suppress VEOGs: linear regression to subtract the VEOG signal from the electroencephalogram (EEG) and Independent Component Analysis (ICA). However, some information is lost in both. The present algorithm (1) statistically identifies the position of VEOGs in the frontopolar channels; (2) performs EEG averaging for each channel, which results in 'blink templates'; (3) subtracts each template from the respective EEG at each VEOG position, only when the linear correlation index between the template and the segment is greater than a chosen threshold L. The signals from twenty subjects were acquired using a behavioral test and were treated using FilterBlink for subsequent ERP analysis. A model was designed to test the method for each subject using twenty copies of the EEG signal from the subject's mid-central channel (with nearly no VEOG) representing the EEG channels and their respective blink templates. At the same 200 equidistant time points (marks), a signal (2.5 sinusoidal cycles at 1050 ms emulating an ERP) was mixed with each model channel and the respective blink template of that channel, between 500 to 1200 ms after each mark. According to the model, VEOGs interfered with both ERPs and the ongoing EEG, mainly on the anterior medial leads, and no significant effect was observed on the mid-central channel (Cz). FilterBlink recovered approximately 90% (Fp1) to 98% (Fz) of the original ERP and EEG signals for L = 0.1. The method reduced the VEOG effect on the EEG after ERP and blink-artifact averaging in analyzing real signals. The method is straightforward and effective for VEOG attenuation without significant distortion in the EEG signal and embedded ERPs., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Marques Abramov et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Some children with severe microcephaly related to Zika virus infection show affective social-like behavior, such as smiling and rejection to a stranger's lap. Our objective was to check the association between this behavior and the occurrence of Mismatch Response (MMR) in event-related potentials. Twenty eight microcephalic children, aged 1-3 years, were divided in Affect(+) and Affect(-) groups, according to either the presence or absence of affective social-like behavior, respectively, and underwent the OddBall paradigm with vowels as auditory stimuli. MMR was statistically estimated comparing MMR sample means between both groups. The Affect(+) group significantly differed from the Affect(-) group and, as opposed to the latter, showed MMR as Mismatch Negativity (MMN) in the left occipital, left and right posterior temporal, and (especially) the right and median parietal leads. The relationship observed between MMN and affective social-like behavior suggests that these children may have cognitive mechanisms capable of providing some social interaction, despite their profound neurological dysfunction. MMN diagnostic techniques seem to be promising for the triage of microcephalic subjects regarding cognitive functions and for choosing a strategy for some social adaptation., Competing Interests: Declaration of competing interest All authors declare that there are no conflicts of interest., (Copyright © 2022 Elsevier B.V. All rights reserved.)