Neurofeedback Tunes Scale-Free Dynamics in Spontaneous Brain Activity

Abstract

Brain oscillations exhibit long-range temporal correlations (LRTCs), which reflect the regularity of their fluctuations: low values representing more random (decorrelated) while high values more persistent (correlated) dynamics. LRTCs constitute supporting evidence that the brain operates near criticality, a state where neuronal activities are balanced between order and randomness. Here, healthy adults used closed-loop brain training (neurofeedback, NFB) to reduce the amplitude of alpha oscillations, producing a significant increase in spontaneous LRTCs post-training. This effect was reproduced in patients with post-traumatic stress disorder, where abnormally random dynamics were reversed by NFB, correlating with significant improvements in hyperarousal. Notably, regions manifesting abnormally low LRTCs (i.e., excessive randomness) normalized toward healthy population levels, consistent with theoretical predictions about selforganized criticality. Hence, when exposed to appropriate training, spontaneous cortical activity reveals a residual capacity for "self-tuning" its own temporal complexity, despite manifesting the abnormal dynamics seen in individuals with psychiatric disorder. Lastly, we observed an inverse-U relationship between strength of LRTC and oscillation amplitude, suggesting a breakdown of long-range dependence at high/low synchronization extremes, in line with recent computational models. Together, our findings offer a broader mechanistic framework for motivating research and clinical applications of NFB, encompassing disorders with perturbed LRTCs.

Closed-loop brain training: the science of neurofeedback

“…Remarkably, there is emerging evidence for homeostatic reversal or 'rebound' of neural function after neurofeedback training 61 . For instance, after undergoing alpha desynchronization neurofeedback, individuals with post-traumatic stress disorder showed a rebound in EEG synchronization 62 , which may be explained by the fact that such individuals present with abnormally decreased alpha power at baseline. However, it is not clear to what extent homeostatic plasticity affects long-term changes in brain activity and behaviour, as evidence exists for such changes after periods of days 63 , months 33,64 and even years after training 65 .…”

Eyes-Closed Resting EEG Predicts the Learning of Alpha Down-Regulation in Neurofeedback Training

“…This result coincided with alpha down-regulation NF from Ros et al (2013) in which the alpha in the first training run with three min in healthy participants was significant lower than that in the pre-baseline, and the alpha in the post-baseline after 30 min training rebounded to pre-baseline level. No significant change in resting alpha may be attributed to short NF duration or small session number since only one NF session with about 30 min was performed in previous studies (Ros et al, 2013, 2016; Alves-Pinto et al, 2017) and only two 15-min sessions were conducted in this work. However, multiple NF sessions with much longer training duration, such as six NF sessions with 20 min each, also showed no significant changes in resting alpha amplitude (Ros et al, 2017).…”

“…In general, EEG learning is usually evaluated by the training parameter change within sessions, across sessions, or within sessions compared to baselines (Gruzelier, 2014c; Wan et al, 2014; Nan et al, 2015; Reichert et al, 2015; Zuberer et al, 2015). With respect to alpha down-regulation NF, although Ros and colleagues did not directly use the term “alpha learning” or “NF learning,” they reported the comparison of alpha amplitude between NF session and resting baseline (Ros et al, 2010, 2013, 2016), which was actually one type of alpha learning assessment. Since it has been observed that alpha also shows reduction in sham NF group compared to resting baseline (Ros et al, 2013) whereas this study did not include sham NF group for comparison, the alpha change between NF session and resting baseline may increase the difficulty to identify real NF effects on alpha.…”

“…Although some studies reported that alpha amplitude was smaller in one 30-min session when compared with resting baseline (Ros et al, 2013) or it reduced across two 15-min NF sessions (Wan et al, 2016), the within-session learning that describes alpha dynamic change within sessions is not clear yet. Moreover, previous work mainly reported the alpha learning at the group level whereas the inter-individual difference in alpha learning was little known (Ros et al, 2010, 2013, 2014b, 2016; Wan et al, 2016). …”

Tuning Up the Old Brain with New Tricks: Attention Training via Neurofeedback

“…Additional success has been reported using EEG-based NF for attention training and WM in young adults (Egner and Gruzelier, 2001; Zoefel et al, 2011; Ros et al, 2013, 2014), in post-traumatic stress disorder (Ros et al, 2016), and in older dementia patients (e.g., Surmeli et al, 2016). We summarize some of the recent studies on attention or WM training in older and younger adults in Table 1.…”