P194 Strategies for Neurofeedback Success: Exploring the Relationship Between Alpha Power and Mental Effort
Matthew McGowan1, Alison Crilly1, Rongxiang Tang2, Yi-Yuan Tang*1
1College of Health Solutions, Arizona State University, Tempe, United States2 Department of Psychological & Brain Sciences, Texas A&M University, College Station, United States
*Email: yiyuan@asu.edu
Introduction
EEG neurofeedback is a non-invasive neuromodulation technique that enables individuals to regulate brain activity through real-time feedback, promoting cognitive enhancement, emotional regulation, and adaptive brain plasticity. However, it remains unknown which regulation strategies lead to successful neurofeedback. Based on previous research, we hypothesize that effortless strategies (less mental demand and effort) produce neurofeedback success indexed by increased alpha activity in the default mode network [1,2].
Methods
To maximize the effects of neurofeedback, we selected a protocol designed to reward frontal midline Theta (4–8 Hz) to enhance executive function and emotional balance, and central sensorimotor Rhythm (SMR, 12–15 Hz) to promote focus and calmness, while inhibiting posterior midline Beta (16–35 Hz) to reduce stress and improve sensory clarity. This protocol was implemented with two eyes closed (soft music) and one with eyes open (nature scene) sessions. This protocol aims to enhance self-regulation, resilience, and overall brain efficiency, facilitating neurofeedback learning and benefits. This study examined the effects of 10 consecutive neurofeedback sessions reinforcing midline Theta and SMR while inhibiting high Beta in 12 participants(11 with usable data). Behavioral assessments included the NASA Task Load Index (NASA-TLX) and the Rating Scale for Mental Effort (RSME) to evaluate perceived mental workload alongside post-session interviews documenting self-regulation strategies.
Results
RSME results showed significant decreases in mental effort for all three protocols: p= 0.051, p= 0.015, and p=0.011, respectively (10 usable data). We also detected significant reductions in mental demand and effort on the NASA-TLX (p=0.0008, p=0.001 respectively). A negative correlation between posterior parietal alpha power and effort (r=-0.643, p=0.0327) was found, suggesting that higher alpha activity was associated with reduced cognitive workload. Correlation analysis indicated that participants with greater increases in posterior alpha power exhibited smaller reductions in perceived external demand (r=0.650, p=0.030), suggesting that neurofeedback training altered brain activity and reduced effort despite the persistence of task-related demand. Additionally, significant increases in frontal and posterior midline alpha power (p=0.011, p=0.013) suggested enhanced default mode network activity.
Discussion
These findings suggest that neurofeedback training promotes neural efficiency and cognitive ease, reinforcing the effectiveness of an effortless strategy for learning self-regulation of brain activity. By facilitating effortless engagement, neurofeedback may optimize neural adaptation, enhancing brain plasticity, cognitive efficiency, and self-regulation.
Acknowledgements
This work is supported by the ONR N000142412270 and NIH R33 AT010138.
References
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