AUTHOR=Farabbi Andrea , Mainardi Luca 

TITLE=Assessing the impact of stimulation environment and error probability on ErrP EEG response, detection and subject attention: an explorative study

JOURNAL=Frontiers in Virtual Reality

VOLUME=5

YEAR=2024

URL=https://www.frontiersin.org/journals/virtual-reality/articles/10.3389/frvir.2024.1433082

DOI=10.3389/frvir.2024.1433082

ISSN=2673-4192

ABSTRACT=<sec><title>Objective</title><p>This study aims to investigate the impact of stimulus environments (Virtual Theatre vs Monitor) and error probabilities (<inline-formula id="inf1"><mml:math id="m1" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>20</mml:mn><mml:mi>%</mml:mi></mml:mrow></mml:math></inline-formula> vs <inline-formula id="inf2"><mml:math id="m2" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>50</mml:mn><mml:mi>%</mml:mi></mml:mrow></mml:math></inline-formula>) on attentional states, Error Potentials (ErrP), and machine learning classification performance.</p></sec><sec><title>Approach</title><p>EEG signals were recorded using different protocols, and features were extracted for subsequent analysis from single-trial response and attention level was computed from the second preceding error processing stimulation.</p></sec><sec><title>Results</title><p>The results indicate significant differences across conditions: the Monitor environment consistently elicited higher and faster ErrP responses and elevated attentional states compared to Virtual Theatre. Additionally, classification performance in the Monitor environment outperformed Virtual Theatre consistently. Further analysis revealed that the <inline-formula id="inf3"><mml:math id="m3" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>20</mml:mn><mml:mi>%</mml:mi></mml:mrow></mml:math></inline-formula> error probability protocol yielded increased ErrP responses, heightened attentional states, and superior classification performance compared to the <inline-formula id="inf4"><mml:math id="m4" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>50</mml:mn><mml:mi>%</mml:mi></mml:mrow></mml:math></inline-formula> protocol. Classification performance under the <inline-formula id="inf5"><mml:math id="m5" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>20</mml:mn><mml:mi>%</mml:mi></mml:mrow></mml:math></inline-formula> error probability condition consistently exceeded <inline-formula id="inf6"><mml:math id="m6" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>75</mml:mn><mml:mi>%</mml:mi></mml:mrow></mml:math></inline-formula> validation and test sets. Moreover, a significant correlation between attention-related features and ErrP characteristics was observed, highlighting the intricate relationship between error processing and attentional engagement.</p></sec><sec><title>Relevance</title><p>These findings underscore the importance of considering stimulus environments and error probabilities in cognitive neuroscience research and machine learning applications. Understanding these factors can inform experimental design and model development, ultimately advancing our comprehension of cognitive processes and enhancing real-world applications of machine learning algorithms.</p></sec>