Feedback Effects on Cognitive Dynamics: Network-Based Insights from EEG Patterns and Behavioral Performance

Fuente: arXiv
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Autori principali: Kiafar, Behdokht, Abrar, Mohammad Fahim, Barmaki, Roghayeh Leila
Natura: Preprint
Pubblicazione: 2026
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author Kiafar, Behdokht
Abrar, Mohammad Fahim
Barmaki, Roghayeh Leila
author_facet Kiafar, Behdokht
Abrar, Mohammad Fahim
Barmaki, Roghayeh Leila
contents This study examines the impact of feedback on Electroencephalography (EEG) activity and performance during the Reading the Mind in the Eyes Test. In a within-subject design, eleven participants completed the test under Feedback and No-Feedback conditions. Using the principles of Epistemic Network Analysis (ENA) and Ordered Network Analysis (ONA), we extend these network-based models to explore the link between neural dynamics and task outcomes. ENA results showed that feedback is associated with stronger connections between higher frequency EEG bands (Beta and Gamma) and correct responses, while the absence of feedback activated lower frequency bands (Theta and Alpha). ONA further disclosed directional shifts toward higher frequency activity preceding correct answers in the Feedback condition, whereas the No-Feedback condition showed more self-connections in lower bands and a higher occurrence of wrong answers, suggesting less effective reasoning strategies without feedback. Both ENA and ONA revealed statistically significant differences between conditions (p = 0.01, Cohen's d > 2). This study highlights the methodological benefits of integrating EEG with ENA and ONA for network analysis, capturing both temporal and relational dynamics, as well as the practical insight that feedback can foster more effective reasoning processes and improve task performance.
format Preprint
id arxiv_https___arxiv_org_abs_2601_05450
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Feedback Effects on Cognitive Dynamics: Network-Based Insights from EEG Patterns and Behavioral Performance
Kiafar, Behdokht
Abrar, Mohammad Fahim
Barmaki, Roghayeh Leila
Human-Computer Interaction
This study examines the impact of feedback on Electroencephalography (EEG) activity and performance during the Reading the Mind in the Eyes Test. In a within-subject design, eleven participants completed the test under Feedback and No-Feedback conditions. Using the principles of Epistemic Network Analysis (ENA) and Ordered Network Analysis (ONA), we extend these network-based models to explore the link between neural dynamics and task outcomes. ENA results showed that feedback is associated with stronger connections between higher frequency EEG bands (Beta and Gamma) and correct responses, while the absence of feedback activated lower frequency bands (Theta and Alpha). ONA further disclosed directional shifts toward higher frequency activity preceding correct answers in the Feedback condition, whereas the No-Feedback condition showed more self-connections in lower bands and a higher occurrence of wrong answers, suggesting less effective reasoning strategies without feedback. Both ENA and ONA revealed statistically significant differences between conditions (p = 0.01, Cohen's d > 2). This study highlights the methodological benefits of integrating EEG with ENA and ONA for network analysis, capturing both temporal and relational dynamics, as well as the practical insight that feedback can foster more effective reasoning processes and improve task performance.
title Feedback Effects on Cognitive Dynamics: Network-Based Insights from EEG Patterns and Behavioral Performance
topic Human-Computer Interaction
url https://arxiv.org/abs/2601.05450