Pittsburgh Sleep Quality Index (PSQI)
Research Papers
A Randomized Controlled Trial Comparing Neurofeedback and Cognitive-Behavioral Therapy for Insomnia Patients: Pilot Study
Insomnia is a common disease that negatively affects patients both mentally and physically. While insomnia disorder is mainly characterized by hyperarousal, a few studies that have directly intervened with cortical arousal. This study was conducted to investigate the effect of a neurofeedback protocol for reducing cortical arousal on insomnia compared to cognitive-behavioral treatment for insomnia (CBT-I). Seventeen adults with insomnia, free of other psychiatric illnesses, were randomly assigned to neurofeedback or CBT-I. All participants completed questionnaires on insomnia [Insomnia Severity Index (ISI)], sleep quality [Pittsburgh Sleep Quality Index (PSQI)], and dysfunctional cognition [Dysfunctional Beliefs and Attitudes about Sleep Scale (DBAS-16)]. The neurofeedback group showed decreases in beta waves and increases in theta and alpha waves in various areas of the electroencephalogram (EEG), indicating lowered cortical arousal. The ISI and PSQI scores were significantly decreased, and sleep efficiency and sleep satisfaction were increased compared to the pre-treatment scores in both groups. DBAS scores decreased only in the CBT-I group (NF p = 0.173; CBT-I p = 0.012). This study confirmed that neurofeedback training could alleviate the symptoms of insomnia by reducing cortical hyperarousal in patients, despite the limited effect in reducing cognitive dysfunction compared to CBT-I.
View Full Paper →Real-Time fMRI Neurofeedback Training Changes Brain Degree Centrality and Improves Sleep in Chronic Insomnia Disorder: A Resting-State fMRI Study
Background Chronic insomnia disorder (CID) is considered a major public health problem worldwide. Therefore, innovative and effective technical methods for studying the pathogenesis and clinical comprehensive treatment of CID are urgently needed. Methods Real-time fMRI neurofeedback (rtfMRI-NF), a new intervention, was used to train 28 patients with CID to regulate their amygdala activity for three sessions in 6 weeks. Resting-state fMRI data were collected before and after training. Then, voxel-based degree centrality (DC) method was used to explore the effect of rtfMRI-NF training. For regions with altered DC, we determined the specific connections to other regions that most strongly contributed to altered functional networks based on DC. Furthermore, the relationships between the DC value of the altered regions and changes in clinical variables were determined. Results Patients with CID showed increased DC in the right postcentral gyrus, Rolandic operculum, insula, and superior parietal gyrus and decreased DC in the right supramarginal gyrus, inferior parietal gyrus, angular gyrus, middle occipital gyrus, and middle temporal gyrus. Seed-based functional connectivity analyses based on the altered DC regions showed more details about the altered functional networks. Clinical scores in Pittsburgh sleep quality index, insomnia severity index (ISI), Beck depression inventory, and Hamilton anxiety scale decreased. Furthermore, a remarkable positive correlation was found between the changed ISI score and DC values of the right insula. Conclusions This study confirmed that amygdala-based rtfMRI-NF training altered the intrinsic functional hubs, which reshaped the abnormal functional connections caused by insomnia and improved the sleep of patients with CID. These findings contribute to our understanding of the neurobiological mechanism of rtfMRI-NF in insomnia treatment. However, additional double-blinded controlled clinical trials with larger sample sizes need to be conducted to confirm the effect of rtfMRI-NF from this initial study.
View Full Paper →To spindle or not to spindle: A replication study into spindling excessive beta as a transdiagnostic EEG feature associated with impulse control
Background Frontocentral Spindling Excessive Beta (SEB), a spindle-like beta-activity observed in the electroencephalogram (EEG), has been transdiagnostically associated with more problems with impulse control and sleep maintenance. The current study aims to replicate and elaborate on these findings. Methods Participants reporting sleep problems (n = 31) or Attention-Deficit/Hyperactivity Disorder (ADHD) symptoms (n = 48) were included. Baseline ADHD-Rating Scale (ADHD-RS), Pittsburgh Sleep Quality Index (PSQI), Holland Sleep Disorder Questionnaire (HSDQ), and EEG were assessed. Analyses were confined to adults with frontocentral SEB. Results Main effects of SEB showed more impulse control problems (d = 0.87) and false positive errors (d = 0.55) in participants with SEB. No significant associations with sleep or interactions with Sample were observed. Discussion This study partially replicates an earlier study and demonstrates that participants exhibiting SEB report more impulse control problems, independent of diagnosis. Future studies should focus on automating SEB classification and further investigate the transdiagnostic nature of SEB.
View Full Paper →A multicenter effectiveness trial of QEEG-informed neurofeedback in ADHD: Replication and treatment prediction
Introduction: Quantitative Electroencephalogram-(QEEG-)informed neurofeedback is a method in which standard neurofeedback protocols are assigned, based on individual EEG characteristics in order to enhance effectiveness. Thus far clinical effectiveness data have only been published in a small sample of 21 ADHD patients. Therefore, this manuscript aims to replicate this effectiveness in a new sample of 114 patients treated with QEEG-informed neurofeedback, from a large multicentric dataset and to investigate potential predictors of neurofeedback response. Methods: A sample of 114 patients were included as a replication sample. Patients were treated with standard neurofeedback protocols (Sensori-Motor-Rhythm (SMR), Theta-Beta (TBR), or Slow Cortical Potential (SCP) neurofeedback), in combination with coaching and sleep hygiene advice. The ADHD Rating Scale (ADHD-RS) and Pittsburgh Sleep Quality Index (PSQI) were assessed at baseline, every 10th session, and at outtake. Holland Sleep Disorder Questionnaire (HSDQ) was assessed at baseline and outtake. Response was defined as ≥25% reduction (R25), ≥50% reduction (R50), and remission. Predictive analyses were focused on predicting remission status. Results: In the current sample, response rates were 85% (R25), 70% (R50), and remission was 55% and clinical effectiveness was not significantly different from the original 2012 sample. Non-remitters exhibited significantly higher baseline hyperactivity ratings. Women who remitted had significantly shorter P300 latencies and boys who remitted had significantly lower iAPF's. Discussion: In the current sample, clinical effectiveness was replicated, suggesting it is possible to assign patients to a protocol based on their individual baseline QEEG to enhance signal-to-noise ratio. Furthermore, remitters had lower baseline hyperactivity scores. Likewise, female remitters had shorter P300 latencies, whereas boys who remitted have a lower iAPF. Our data suggests initial specificity in treatment allocation, yet further studies are needed to replicate the predictors of neurofeedback remission.
View Full Paper →Comparison of the Effectiveness of Cognitive Behavioral Therapy and Neurofeedback: Reducing Insomnia Symptoms
INTRODUCTION: The term sleep disorder refers to difficulty in initiating sleep, maintaining it or a relaxing sleep despite having enough time to sleep. Cognitive behavioral therapy is a non-drug multi-dimensional treatment that targets behavioral and cognitive factors of this disorder. Some pieces of research have shown that psychiatric and neurological disorders can be distinguished from distinct EEG patterns and neuro-feedback can be used to make a change in these patterns. This study aimed to compare the cognitive behavioral therapy and neuro-feedback in the treatment of insomnia.METHODS: The sample included people, who had already been diagnosed insomnia by a psychiatrist in Isfahan, Iran. Random sampling was employed to choose the participants. Pittsburg sleep quality index (PSQI) was used for the selection of the participants, too. The sample included 40 patients who were randomly selected and interviewed and then diagnostic tests performed on the PSQI, and then they were divided into 3 groups. Data were analyzed using ANOVA. Following the implementation of the independent effect of the treatment was significant and one-way ANOVA with post hoc test L.S.D were carried out on CBT and controls (p = 0.001), CBT, neuro-feedback therapy (p = 0.003), neuro-feedback treatment and control (p = 0.001).RESULTS: It was shown that there was a significant difference between the groups. Based on the descriptive statistics of the 2 abovementioned treatments, neuro-feedback therapy in first position and cognitive-behavioral therapy were most effective in the second position, and the control group showed the lowest efficiency.CONCLUSIONS: Both treatments were significantly effective, and so we can use both neuro-feedback and CBT for the treatment of insomnia.
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