Abstract
Neurofeedback has been around for half a century, but despite some promising results it is not yet widely appreciated. Recently, some of the concerns about neurofeedback have been addressed with functional magnetic resonance imaging and magnetoencephalography adding their contributions to the long history of neurofeedback with electroencephalography. Attempts to address other concerns related to methodological issues with new experiments and meta-analysis of earlier studies, have opened up new questions about its efficacy. A key concern about neurofeedback is the missing framework to explain how improvements in very different and apparently unrelated conditions are achieved. Recent advances in neuroscience begin to address this concern. A particularly promising approach is the analysis of resting state of fMRI data, which has revealed robust covariations in brain networks that maintain their integrity in sleep and even anesthesia. Aberrant activity in three brain wide networks (i.e., the default mode, central executive and salience networks) has been associated with a number of psychiatric disorders. Recent publications have also suggested that neurofeedback guides the restoration of “normal” activity in these three networks. Using very recent results from our analysis of whole night MEG sleep data together with key concepts from developmental psychology, cloaked in modern neuroscience terms, a theoretical framework is proposed for a neural representation of the self, located at the core of a double onion-like structure of the default mode network. This framework fits a number of old and recent neuroscientific findings, and unites the way attention and memory operate in awake state and during sleep. In the process, safeguards are uncovered, put in place by evolution, before any interference with the core representation of self can proceed. Within this framework, neurofeedback is seen as set of methods for restoration of aberrant activity in large scale networks. The framework also admits quantitative measures of improvements to be made by personalized neurofeedback protocols. Finally, viewed through the framework developed, neurofeedback’s safe nature is revealed while raising some concerns for interventions that attempt to alter the neural self-representation bypassing the safeguards evolution has put in place.
Highlights
Each one of us likes to be in control
The results we reported recently (Ioannides et al, 2017), suggests that rostral anterior cingulate cortex (rACC) plays a similar role during sleep
The MSRC network, is the closest we are likely to come to a neural representation of the core-self, and this is why we named it the midline self-representation core
Summary
Each one of us likes to be in control. Illness, and psychological disturbances, compromises our mental resources to exercise control. If the evaluation suggests that a change in the protocol or in the way the subject is instructed is likely to bring the desired effect faster, this change should be immediately implemented; it makes no sense, not to make these changes for the sake of sticking to a fixed protocol This brings again the unfairness of the comparison, so we will end this section by considering a more appropriate example, one that is more similar to a clinical case than a neuroscience experiment. It is likely that the inclusion of an irrelevant component (PFT) interfered with the transition of the learning to changes during sleep, a view supported by the fact that PFT was learnt Another example of a difference is the instruction to subjects about how to achieve the increase in SMR. Another important difference in the two protocols, is the component of inhibiting frequency bands (i.e., well outside the reward frequency band) in the Cortoos study (Cortoos et al, 2010) and the absence of such component, with the additional confounding effect of rewarding other frequencies in different trials (the PFT part of the protocol) in the latest Schabus study (Schabus et al, 2017)
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