BOLD activity
Research Papers
OpenNFT: An open-source Python/Matlab framework for real-time fMRI neurofeedback training based on activity, connectivity and multivariate pattern analysis
Neurofeedback based on real-time functional magnetic resonance imaging (rt-fMRI) is a novel and rapidly developing research field. It allows for training of voluntary control over localized brain activity and connectivity and has demonstrated promising clinical applications. Because of the rapid technical developments of MRI techniques and the availability of high-performance computing, new methodological advances in rt-fMRI neurofeedback become possible. Here we outline the core components of a novel open-source neurofeedback framework, termed Open NeuroFeedback Training (OpenNFT), which efficiently integrates these new developments. This framework is implemented using Python and Matlab source code to allow for diverse functionality, high modularity, and rapid extendibility of the software depending on the user's needs. In addition, it provides an easy interface to the functionality of Statistical Parametric Mapping (SPM) that is also open-source and one of the most widely used fMRI data analysis software. We demonstrate the functionality of our new framework by describing case studies that include neurofeedback protocols based on brain activity levels, effective connectivity models, and pattern classification approaches. This open-source initiative provides a suitable framework to actively engage in the development of novel neurofeedback approaches, so that local methodological developments can be easily made accessible to a wider range of users.
View Full Paper →Neurofeedback training as a therapy for tinnitus/ Neurofeedback in der Therapie des Tinnitus
Background and objective: Biofeedback is known as a possibility to control physiologic processes like body temperature or heart frequency. Neurofeedback is a form of biofeedback linked to aspects of the electrical activity of the brain such as frequency, location or amplitude of specific EEG activity. It has been successfully used in patients with closed head injury, hyperactivity disorder or epilepsy. Patients/methods: In this study 40 patients with tinnitus were treated with neurofeedback. They trained to upregulate the amplitude of their α-activity and downregulate the amplitude of β-activity during muscle relaxation and acoustic orientation on sounds or music in order to suppress their tinnitus. Results: After 15 sessions of training 24 patients with a duration of their tinnitus for an average of 1 year showed significant increase of α-amplitudes while 16 patients with duration of their tinnitus on an average of 7 years showed a decrease of β-amplitudes without any change in α-activity. After the training all patients had a significant reduction of the score in the tinnitusquestionaire of Göbel and Hiller. In a control-group of 15 persons without tinnitus we didn't see any changes of α- or β-amplitudes during the same training. Conclusions: In conclusion neurofeedback is a new therapy for patients with tinnitus. Patients get the possibility of selfcontrol and therefore of influence on their disease.
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