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

2026-01-09

arXiv.org

AI Summary

This study investigates how feedback modulates the neurocognitive mechanisms underlying theory-of-mind tasks. By recording participants’ electroencephalographic (EEG) activity during the “Reading the Mind in the Eyes” task under conditions with and without feedback, the authors extend Epistemic Network Analysis (ENA) and Ordered Network Analysis (ONA) to EEG data for the first time, enabling a systematic examination of the temporal–structural relationships between high- and low-frequency neural oscillations and behavioral performance. The findings reveal that feedback significantly strengthens network connectivity between beta/gamma-band high-frequency activity and correct responses, thereby enhancing inferential efficiency. In contrast, the absence of feedback is associated with dominant theta/alpha low-frequency activity and a higher error rate (p = 0.01, Cohen’s d > 2). This work offers novel methodological and neural evidence for understanding feedback-driven cognitive regulation.

Technology Category

• Cognitive Modeling & Cognitive Systems: Neural Spike Coding
• Humans and AI: Brain-Sensing and Analysis
• Game Theory and Economic Paradigms: Behavioral Game Theory

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Social Networks and Social Media: Social media analysis through the lenses of networks
• Web Mining and Content Analysis: Content-based information diffusion

Abstract

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.

Problem

• feedback
• EEG
• cognitive dynamics
• behavioral performance
• neural dynamics

Innovation

• Epistemic Network Analysis
• Ordered Network Analysis
• EEG dynamics
• feedback effects
• cognitive reasoning