Abstract
Despite the increasing popularity of neurofeedback, its mechanisms of action are still poorly understood. This study aims to describe the processes underlying implicit electroencephalographic neurofeedback. Fifty-two healthy volunteers were randomly assigned to a single session of infra-low frequency neurofeedback or sham neurofeedback, with electrodes over the right middle temporal gyrus and the right inferior parietal lobule. They observed a moving rocket, the speed of which was modulated by the waveform derived from a band-limited infra-low frequency filter. Immediately before and after the session, the participants underwent a resting-state fMRI. Network-based statistical analysis was applied, comparing post- vs. pre-session and real vs. sham neurofeedback conditions. As a result, two phenomena were observed. First, we described a brain circuit related to the implicit neurofeedback process itself, consisting of the lateral occipital cortex, right dorsolateral prefrontal cortex, left orbitofrontal cortex, right ventral striatum, and bilateral dorsal striatum. Second, we found increased connectivity between key regions of the salience, language, and visual networks, which is indicative of integration in sensory processing. Thus, it appears that a single session of implicit infra-low frequency electroencephalographic neurofeedback leads to significant changes in intrinsic brain connectivity.
Highlights
An important clinical application of modern neuroscience research is the development of neuromodulation
When selecting regions of interest (ROI) for the attention hypothesis, we aimed to examine attention-related networks that are consistently identified in the resting-state functional magnetic resonance imaging (fMRI) sessions and looked to the CONN Networks atlas which was derived by the CONN toolbox developers from the Human Connectome Project data (N = 497)
The follow-up network-based statistic (NBS) analysis performed for each group separately at identical statistical thresholds revealed a set of four increasing connections in the NF group
Summary
An important clinical application of modern neuroscience research is the development of neuromodulation. A computerized training is performed based on a neurophysiological signal, such as electroencephalography (EEG) or functional magnetic resonance imaging (fMRI). Some researchers wonder whether the observed improvements are due to the neurophysiological intervention per se or are related to nonspecific effects, such as behavioral or suggestion therapy, and call for proper controlled studies (Thibault et al, 2018; Lubianiker et al, 2019; Sorger et al, 2019). A recent high quality randomized controlled study demonstrated the efficacy of slow cortical potential EEG neurofeedback in children with attention-deficit and hyperactivity disorder (Strehl et al, 2017). In addition to evaluating its efficacy, it is important to continue the research targeted at describing the mechanisms of neurofeedback and developing relevant neuroscientific models
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