functional network
Research Papers
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 →Latest Developments in Live Z-Score Training: Symptom Check List, Phase Reset, and Loreta Z-Score Biofeedback
Advances in neuroscience are applied to the clinical applications of EEG neurofeedback by linking symptoms to functional networks in the brain. This is achieved by reviews of the last 20 years of functional neuroimaging studies of brain networks related to clinical disorders based on positron emission tomography, functional MRI, diffusion tensor imaging, and EEG/MEG inverse solutions. Considerable consistency exists between different imaging modalities because of the property of functional localization and the existence of large clusters of connections in the brain representing network modules and hubs. Reviewed here is new method of EEG neurofeedback called Z-Score Neurofeedback, and it is demonstrated how real-time comparison to an age-matched population of healthy subjects simplifies protocol generation and allows clinicians to target modules and hubs that indicate dysregulation and instability in networks related to symptoms. Z-score neurofeedback, by measuring the distance from the center of the healthy age-matched population, increases specificity in operant conditioning and provides a guide by which extreme Z-score outliers are linked to symptoms and then reinforced toward states of greater homeostasis and stability. The goal is increased efficiency of information processing in brain networks related to the patient's symptoms. The unique advantage of EEG over other neuroimaging methods is high temporal resolution in which the fine temporal details of phase lock and phase shift between large masses of neurons is quantified and can be modified by Z-score neurofeedback to address the patient's symptoms. The latest developments in Z-score neurofeedback are a harbinger of a bright future for clinicians and, most important, patients that suffer from a variety of brain dysfunctions.
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