scholarly journals Discriminative Ocular Artifact Correction for Feature Learning in EEG Analysis

2017 ◽  
Vol 64 (8) ◽  
pp. 1906-1913 ◽  
Author(s):  
Xinyang Li ◽  
Cuntai Guan ◽  
Haihong Zhang ◽  
Kai Keng Ang

2021 ◽  
Author(s):  
Peter E Clayson ◽  
Scott Baldwin ◽  
Harold A Rocha ◽  
Michael J. Larson

In studies of event-related brain potentials (ERPs), numerous decisions about data processing are required to extract ERP scores from continuous data. Unfortunately, the systematic impact of these choices on the data quality and psychometric reliability of ERP scores or even ERP scores themselves is virtually unknown, which is a barrier to the standardization of ERPs. The aim of the present study was to optimize processing pipelines for the error-related negativity (ERN) and error positivity (Pe) by considering a multiverse of data processing choices. A multiverse analysis of a data processing pipeline examines the impact of a large set of different reasonable choices to determine the robustness of effects, such as the impact of different decisions on between-trial standard deviations (i.e., data quality) and between-condition differences (i.e., experimental effects). ERN and Pe data from 298 healthy young adults were used to determine the impact of different methodological choices on data quality and experimental effects (correct vs. error trials) at several key stages: highpass filtering, lowpass filtering, ocular artifact correction, reference, baseline adjustment, scoring sensors, and measurement procedure. This multiverse analysis yielded 3,456 ERN scores and 576 Pe scores per person. An optimized pipeline for ERN included a .01 Hz highpass filter, 15 Hz lowpass filter, ICA-based ocular artifact correction, and a region of interest (ROI) approach to scoring. For Pe, the optimized pipeline included a .10 Hz highpass filter, 30 Hz lowpass filter, regression-based ocular artifact correction, a -200 to 0 ms baseline adjustment window, and an ROI approach to scoring. The multiverse approach can be used to optimize pipelines for eventual standardization, which would support efforts toward establishing normative ERP databases. The proposed process of analyzing the data-processing multiverse of ERP scores paves the way for better refinement, identification, and selection of data processing parameters, ultimately improving the precision and utility of ERPs.



2003 ◽  
Vol 17 (2) ◽  
pp. 69-86 ◽  
Author(s):  
Claudio Babiloni ◽  
Fabio Babiloni ◽  
Filippo Carducci ◽  
Febo Cincotti ◽  
Claudio Del Percio ◽  
...  

Abstract Event-related desynchronization/synchronization (ERD/ERS) at alpha (10Hz), beta (20Hz), and gamma (40Hz) bands and movement-related potentials (MRPs) were investigated in right-handed subjects who were “free” to decide the side of unilateral finger movements (“fixed” side as a control). As a novelty, this “multi-modal” EEG analysis was combined with the evaluation of involuntary mirror movements, taken as an index of “bimanual competition.” A main issue was whether the decision regarding the hand to be moved (“free” movements) could modulate ERD/ERS or MRPs overlying sensorimotor cortical areas typically involved in bimanual tasks. Compared to “fixed” movements, “free” movements induced the following effects: (1) more involuntary mirror movements discarded from EEG analysis; (2) stronger vertex MRPs (right motor acts); (3) a positive correlation between these potentials and the number of involuntary mirror movements; (4) gamma ERS over central areas; and (5) preponderance of postmovement beta ERS over left central area (dominant hemisphere). These results suggest that ERD/ERS and MRPs provide complementary information on the cortical processes belonging to a lateralized motor act. In this context, the results on vertex MRPs would indicate a key role of supplementary/cingulate motor areas not only for bimanual coordination but also for the control of “bimanual competition” and involuntary mirror movements.



2017 ◽  
Vol 27 (4) ◽  
pp. 281-296 ◽  
Author(s):  
Irene Sturm ◽  
Benjamin Blankertz ◽  
Gabriel Curio




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