Foundation and Practice of Neurofeedback for the Treatment of Epileps

Department of Neurobiology, School of Medicine, UCLA, USA.
Applied Psychophysiology and Biofeedback (Impact Factor: 1.13). 04/2006; 31(1):21-35. DOI: 10.1007/s10484-006-9002-x
Source: PubMed


This review provides an updated overview of the neurophysiological rationale, basic and clinical research literature, and current methods of practice pertaining to clinical neurofeedback. It is based on documented findings, rational theory, and the research and clinical experience of the authors. While considering general issues of physiology, learning principles, and methodology, it focuses on the treatment of epilepsy with sensorimotor rhythm (SMR) training, arguably the best established clinical application of EEG operant conditioning. The basic research literature provides ample data to support a very detailed model of the neural generation of SMR, as well as the most likely candidate mechanism underlying its efficacy in clinical treatment. Further, while more controlled clinical trials would be desirable, a respectable literature supports the clinical utility of this alternative treatment for epilepsy. However, the skilled practice of clinical neurofeedback requires a solid understanding of the neurophysiology underlying EEG oscillation, operant learning principles and mechanisms, as well as an in-depth appreciation of the ins and outs of the various hardware/software equipment options open to the practitioner. It is suggested that the best clinical practice includes the systematic mapping of quantitative multi-electrode EEG measures against a normative database before and after treatment to guide the choice of treatment strategy and document progress towards EEG normalization. We conclude that the research literature reviewed in this article justifies the assertion that neurofeedback treatment of epilepsy/seizure disorders constitutes a well-founded and viable alternative to anticonvulsant pharmacotherapy.

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    • "Neurofeedback training provides subjects with information about the activation of a specific brain region in order to facilitate a learning process aiming at self-regulation of this targeted activation. The concept has successfully been applied in various clinical fields (Lubar and Shouse, 1976; Sterman and Egner, 2006; Arns et al., 2009; Tan et al., 2009; Kim and Birbaumer, 2014). Due to its clinical abundance and ease of use electroencephalography (EEG) is still the most widely used method to derive a feedback signal (FS) for training. "
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    ABSTRACT: BACKGROUND: This study investigated the level of self-regulation of the somato-motor cortices (SMC) attained by an extended functional MRI (fMRI) neurofeedback training. Sixteen healthy subjects performed 12 real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback training sessions within 4 weeks, involving motor imagery of the dominant right as well as the non-dominant left hand. Target regions of interests in the SMC were individually localized prior to the training by overt finger movements. The feedback signal was defined as the difference between fMRI activation in the contra- and ipsilateral SMC and visually presented to the subjects. Training efficiency was determined by an off-line GLM analysis determining the fMRI percent signal changes in the somato-motor cortex (SMC) target areas accomplished during the neurofeedback training. Transfer success was assessed by comparing the pre- and post-training transfer task, i.e. the neurofeedback paradigm without the presentation of the feedback signal. Group results show a distinct increase in feedback performance in the transfer task for the trained group compared to a matched untrained control group, as well as an increase in the time course of the training, indicating an efficient training and a successful transfer. Individual analysis revealed that the training efficiency was not only highly correlated to the transfer success but also predictive. Trainings with at least 12 efficient training runs were associated with a successful transfer outcome. A group analysis of the hemispheric contributions to the feedback performance showed that it is mainly driven by increased fMRI activation in the contralateral SMC, although some individuals relied on ipsilateral deactivation. Training and transfer results showed no difference between left and right hand imagery, with a slight indication of more ipsilateral deactivation in the early right hand trainings.
    Frontiers in Human Neuroscience 10/2015; 9. DOI:10.3389/fnhum.2015.00547 · 3.63 Impact Factor
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    • "The approach taken in the current study utilized neurofeedback training (NFT), an operant conditioning of brain electrical oscillations (Sterman and Egner 2006). NFT allows real-time information of brain activity to be fed back visually to a user by means of a computer in a closed loop, enabling control and natural operation of brain oscillations across cortical networks in vivo and in near real-time (Nowlis and Kamiya 1970; Wolpaw et al. 2002; Neuper et al. 2009). "
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    ABSTRACT: Neurofeedback training (NFT) approaches were investigated to improve behavior, cognition and emotion regulation in children with autism spectrum disorder (ASD). Thirteen children with ASD completed pre-/post-assessments and 16 NFT-sessions. The NFT was based on a game that encouraged social interactions and provided feedback based on imitation and emotional responsiveness. Bidirectional training of EEG mu suppression and enhancement (8-12 Hz over somatosensory cortex) was compared to the standard method of enhancing mu. Children learned to control mu rhythm with both methods and showed improvements in (1) electrophysiology: increased mu suppression, (2) emotional responsiveness: improved emotion recognition and spontaneous imitation, and (3) behavior: significantly better behavior in every-day life. Thus, these NFT paradigms improve aspects of behavior necessary for successful social interactions.
    Journal of Autism and Developmental Disorders 07/2015; DOI:10.1007/s10803-015-2523-5 · 3.06 Impact Factor
    • "Neurofeedback training, as a therapeutic treatment, improves the symptoms of the patients. Previous studies had been shown that NFT has positive therapeutic effects in various neurological disorders such as epilepsy (Sterman and Egner 2006; Tan et al. 2009), attention-deficit/hyperactivity disorder (ADHD) (Arns et al. 2009; Beauregard and Levesque 2006; Lubar 2003). "
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    ABSTRACT: The benefits of clinical neurofeedback training are well known, however, its adverse side-effects are less studied. This research focuses on the transient adverse side effects of neurofeedback training via a double-blind, sham/controlled methodology. Thirty healthy undergraduate students volunteers were randomly divided into three treatment groups: increasing a modified Sensory Motor Rhythm, increasing Upper Alpha, and Sham/control group who receive a random reward. The training sessions were administered for a total of ten sessions. Questionnaires of transient adverse side effects were completed by all volunteers before each session. The results suggest that similar to most medical treatments, neurofeedback can cause transient adverse side effects. Moreover, most participants reported experiencing some side effects. The side effects can be divided into non-specific side effect, associated with the neurofeedback training in general and specific ones associated with the particular protocol. Sensory Motor Rhythm protocol seems to be the most sensitive to side effects.
    Applied Psychophysiology and Biofeedback 05/2015; 40(3). DOI:10.1007/s10484-015-9289-6 · 1.13 Impact Factor
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