Neuroscience
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Review
Using Recent BCI Literature to Deepen our Understanding of Clinical Neurofeedback: A Short Review.
In their recent paper, Alkoby et al. (2017) provide the readership with an extensive and very insightful review of the factors influencing NeuroFeedback (NF) performance. These factors are drawn from both the NF literature and the Brain-Computer Interface (BCI) literature. Our short review aims to complement Alkoby et al.'s review by reporting recent additions to the BCI literature. ⋯ Since BCIs and NF share a common goal (i.e., learning to modulate specific neurophysiological patterns), similar cognitive and neurophysiological processes are likely to be involved during the training process. Thus, the literature on BCI training may help (1) to deepen our understanding of neurofeedback training processes and (2) to understand the variables that influence the clinical efficacy of NF. This may help to properly assess and/or control the influence of these variables during randomized controlled trials.
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There is a growing body of evidence pointing at several types of motor abnormalities found in attention-deficit/hyperactivity disorder (ADHD). In this article we review findings stemming from different paradigms, and suggest an interweaving approach to the different stages involved in the motor regulation process. We start by reviewing various aspects of motor abnormalities found in ADHD and related brain mechanisms. ⋯ Additionally we discuss EMG-Biofeedback interventions targeted at feedback on motor activity. Further we review physical activity and motor interventions aimed at improving motor difficulties, associated with ADHD. These kinds of interventions are shown to be helpful not only in aspects of physical ability, but also in enhancing cognition and executive functioning.
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Despite the success of neurofeedback treatment in many cases, the variability in the efficacy of the treatment is high, and some studies report that a significant proportion of subjects does not benefit from it. Quantifying the extent of this problem is difficult, as many studies do not report the variability among subjects. ⋯ A possible explanation for treatment ineffectiveness lies in the necessity to adapt the treatment protocol to the individual subject. We therefore discuss the use of personalized neurofeedback protocols as a potential way to reduce the inefficacy problem.
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Randomized Controlled Trial
Neurofeedback training effects on inhibitory brain activation in ADHD: a matter of learning?
Neurofeedback training (NF) is a promising non-pharmacological treatment for ADHD that has been associated with improvement of attention-deficit/hyperactivity disorder (ADHD)-related symptoms as well as changes in electrophysiological measures. However, the functional localization of neural changes following NF compared to an active control condition, and of successful learning during training (considered to be the critical mechanism for improvement), remains largely unstudied. Children with ADHD (N=16, mean age: 11.81, SD: 1.47) were randomly assigned to either slow cortical potential (SCP, n=8) based NF or biofeedback control training (electromyogram feedback, n=8) and performed a combined Flanker/NoGo task pre- and post-training. ⋯ Subjects who were successful learners (n=9) also showed increased activation in an extensive inhibitory network irrespective of the type of training. Activation increased in an extensive inhibitory network following NF training, and following successful learning through NF and control biofeedback. Although this study was only powered to detect large effects and clearly requires replication in larger samples, the results suggest a crucial role for learning effects in biofeedback trainings.
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Drug addiction is a major health problem worldwide. Recent neuroimaging studies have shed light into the underlying mechanisms of drug addiction as well as its consequences to the human brain. The most vulnerable, to heroin addiction, brain regions have been reported to be specific prefrontal, parietal, occipital, and temporal regions, as well as, some subcortical regions. ⋯ In the current manuscript, we comprehensively review and discuss existing resting-state neuroimaging findings classified into three overlapping and interconnected groups: functional connectivity alterations, structural deficits and abnormal topological properties. Moreover, behavioral traits of heroin-addicted individuals as well as the limitations of the currently available studies are also reviewed. Finally, in need of a contemporary therapy a multimodal therapeutic approach is suggested using classical treatment practices along with current neurotechonologies, such as neurofeedback and goal-oriented video-games.