Neuroscience
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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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Feedback-driven learning, observed across phylogeny and of clear adaptive value, is frequently operationalized in simple operant conditioning paradigms, but it can be much more complex, driven by abstract representations of success and failure. This study investigates the neural processes involved in processing success and failure during feedback learning, which are not well understood. Data analyzed were acquired during a multisession neurofeedback experiment in which ten participants were presented with, and instructed to modulate, the activity of their orbitofrontal cortex with the aim of decreasing their anxiety. ⋯ Neurofeedback signals of failure correlated early during learning with deactivation in the precuneus/posterior cingulate and neurofeedback signals of success correlated later during learning with deactivation in the medial prefrontal/anterior cingulate cortex. The intensity of the latter deactivations predicted the efficacy of the neurofeedback intervention in the reduction of anxiety. These findings indicate a role for regulation of the default mode network during feedback learning, and suggest a higher sensitivity to signals of failure during the early feedback learning and to signals of success subsequently.
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It is recognized that lower electroencephalography (EEG) frequencies correspond to distributed brain activity over larger spatial regions than higher frequencies and are associated with coordination. In motor processes it has been suggested that this is not always the case. Our objective was to explore this contradiction. ⋯ Comparing the models we observed lower CPL for both rhythms, lower CC in alpha and higher CC in beta when the number of ROIs increased. Also, denser networks with higher SW were correlated with higher number of ROIs. We propose a non-exclusive model where alpha rhythm uses greater wiring costs to engage in local information progression while beta rhythm coordinates the neurophysiological processes in sensorimotor tasks.
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Neurofeedback (NFB) allows subjects to learn self-regulation of neuronal brain activation based on information about the ongoing activation. The implementation of real-time functional magnetic resonance imaging (rt-fMRI) for NFB training now facilitates the investigation into underlying processes. Our study involved 16 control and 16 training right-handed subjects, the latter performing an extensive rt-fMRI NFB training using motor imagery. ⋯ Our study demonstrates that NFB training increases functional connectivity with non-targeted brain areas. These are associated with the training strategy (i.e., SMA) as well as with learning the NFB skill (i.e., aMCC and frontal areas). This detailed description of both the system to be trained and the areas involved in learning can provide valuable information for further optimization of NFB trainings.
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Neurofeedback training involves presenting an individual with a representation of their brain activity and instructing them to alter the activity using the feedback. One potential application of neurofeedback is for patients to alter neural activity to improve function. For example, there is evidence that greater laterality of movement-related activity is associated with better motor outcomes after stroke; so using neurofeedback to increase laterality may provide a novel route for improving outcomes. ⋯ Moreover, the younger cohort was able to maintain the lateralized activity for right hand movements once neurofeedback was removed. The older cohort did not maintain lateralized activity upon feedback removal, with the limitation being that they did not train with their right hand. The results provide evidence that neurofeedback can be used with executed movements to promote lateralized brain activity and thus is amenable for testing as a therapeutic intervention for patients following stroke.