Utilizing Neurofeedback for the Treatment of Insomnia: A Feasibility Study
[Thesis]
Garcia, Diego A.
Gevirtz, Richard
Alliant International University
2019
80 p.
Ph.D.
Alliant International University
2019
Insomnia is a significant public health problem impacting individual's daily life (Straten, Zweerde, Kleiboer, Cuijpers, Morin & Lancee, 2018). In fact, approximately 33%-50% of the adult US population has suffered from symptoms of insomia (Ancoli-Israel, 1999). Despite insomnia's devastating effects, current treaments such as medications and cognitive behavioral therapy have major limitations. These include side effects, marginal efficacy rates in the case of medications, or the continuation of some impairment following CBT-I treatment (Longo & Johnson, 2000; Wilson & Nutt, 2008; Morin, Culbert & Schartz, 1994). Neurofeedback is a form of biofeedback which brain activity via electroencephalography (EEG) is measured and fed back to a participant in real time as a visual or auditory representation in order to self-regulate brain activity (Sitaram et al., 2018). In a handful of pilot studies, the instrumental conditioning of the sensorimotor rhythm (SMR; 12-15 Hz) utilizing neurofeedback over central brain regions has been preliminarily shown to have positive behavioral impacts on sleep. The aims of this study were to further investigate the therapeutic potential and feasibility of neurofeedback for the symptoms of insomnia. Participants (n=13) received 20 sessions of neurofeedback aimed to up-regulate SMR over the right central parietal region at scalp site C4 (10-20 international classification system). Analysis of variance was used to compare participants on self-report and sleep-tracking data on measures of sleep latency, overall sleep quality, fatigue, hyperarousal, and physiological measures of heart rate variability. Subjects were screened and selected based on strict inclusion and exclusion parameters, which included meeting criteria for an insomnia disorder. Participants were individuals suffering from severe insomnia that had made previous attempts at improving sleep with little success. Results indicate significant improvements on some variables of sleep for both self-report questionnaires and sleep tracking data. On the PSQI, group means indicate overall statistically significant findings for global sleep score (p < 001). Sleep tracking data indicated statistically significant findings for total sleep time only (p < .05). Self report measures of fatigue and hyper-arousal also demonstrated significant findings (p < 001). Heart rate variability data did not demonstrate significant findings. The results of this study corroborate previous pilot studies indicating that SMR neurofeedback may help improve aspects of sleep quality. Research investigating insomnia is especially important since it has been categorized as an epidemic in the US (Hammer, Colbert, Brown, & Illoi, 2011). Forthcoming research studies of SMR neurofeedback should incorporate follow-up measurements to track whether improvements sustain over time, include larger sample sizes, include a control group, and carefully measure increases in SMR over the course of training to ensure that the treatment is successful.