346 Developing standardized, neurophysiologically informed EEG neurofeedback protocols: A translational neuroscience approach

Objectives/Goals: EEG neurofeedback is a promising neuromodulation approach for improving mental health outcomes but lacks standardized, neurophysiologically-grounded treatment protocols. This study uses high-density EEG (hdEEG) analyses to identify neural network patterns that inform development of evidence-based pediatric neurofeedback protocols. Methods/Study Population: This translational neuroscience project leverages resting-state hdEEG data and behavioral assessments from 600 six-year-old children in the Beginnings study (Arkansas Children’s Research Institute; Andres, NCT00616395). Analyses will identify functional and effective connectivity patterns across major brain networks – Default Mode (DMN), Salience (SN), and Central Executive (CEN) – using graph theoretical metrics, phase-locking values, and multivariate analyses. Identified network patterns will be linked with neuropsychological measures, including the Child Behavior Checklist (CBCL), to inform development of standardized neurofeedback protocol recommendations grounded in developmental neuroscience. Results/Anticipated Results: We anticipate identifying distinct patterns of functional connectivity that predict variation in children’s emotional and behavioral functioning. Findings are expected to highlight network patterns – particularly within emotion regulation and executive control circuits – that can guide neurofeedback protocol design. Anticipated products include neurophysiologically informed recommendations for standardized frequency bands, target networks, and protocol parameters to support future clinical trial development. This project represents a key T1 translational step toward establishing a neuroscience-based framework for EEG neurofeedback treatment protocols. Discussion/Significance of Impact: By integrating neurophysiological and behavioral data to guide protocol development, this work addresses a critical translational gap in the EEG neurofeedback literature. Findings will establish a foundation for standardized, evidence-based neurofeedback interventions that could improve accessibility and efficacy in clinical settings.