Validation of eyes-closed resting alpha amplitude predicting neurofeedback learning of upregulation alpha activity

Abstract

Neurofeedback training (NFT) enables users to learn self-control of EEG activity of interest and then to create many benefits on cognitive function. A considerable number of nonresponders who fail to achieve successful NFT have often been reported in the within-session prediction. This study aimed to investigate successful EEG NFT of upregulation alpha activity in terms of trainability, independence, and between-session predictability validation. Forty-six participants completed 12 training sessions. Spectrotemporal analysis revealed the upregulation success on brain activity of 8–12 Hz exclusively to demonstrate trainability and independence of alpha NFT. Three learning indices of between-session changes exhibited significant correlations with eyes-closed resting state (ECRS) alpha amplitude before the training exclusively. Through a stepwise linear discriminant analysis, the prediction model of ECRS’s alpha frequency band amplitude exhibited the best accuracy (89.1%) validation regarding the learning index of increased alpha amplitude on average. This study performed a systematic analysis on NFT success, the performance of the 3 between-session learning indices, and the validation of ECRS alpha activity for responder prediction. The findings would assist researchers in obtaining insight into the training efficacy of individuals and then attempting to adapt an efficient strategy in NFT success.

Mental strategies and resting state EEG: Effect on high alpha amplitude modulation by neurofeedback in healthy young adults

“…Specifically, we found that individuals with higher high alpha amplitude during the pre-training resting state increased their amplitude the most. This finding supports the work of other alpha NFB training studies linking resting state EEG with neuromodulation success and extends it to the high alpha frequency (Su et al, 2021;Nan et al, 2018;Wan et al, 2014). As discussed by previous authors (Su et al, 2021;Wan et al, 2014), this association could be explained by the cortical inhibitory role of the alpha frequency (Klimesch et al, 2007).…”

“…Indeed, the amplitude of the signal measured during the resting state EEG or the first session seems to be a reliable predictor of an individual's ability to modulate this signal, in that the higher the level of baseline activity, the greater the modulation. This has been observed for the alpha (Su et al, 2021;Wan et al, 2014), sensorimotor rhythm (SMR, Blankertz et al, 2010;Li et al, 2021;Reichert et al, 2015;Weber et al, 2011) and low beta bands (12-15 Hz, Nan et al, 2015;Sho'ouri, 2021). Interestingly, although most of the cited studies aimed to increase the amplitude of the target signal during the resting state, one study (Nan et al, 2018) showed that a lower amplitude of the trained alpha frequency also predicted the ability to decrease it during NFB training.…”

“…The different methods used may thus introduce bias or render comparison between studies difficult (Chiang et al, 2008;Corcoran et al, 2018;Goljahani et al, 2012). In the field of NFB, studies target both the IAF (Alexeeva et al, 2012 ;Bazanova et al, 2013 ;Bobby & Prakash, 2017 ;Escolano et al, 2014 ;Grosselin et al, 2021 ;Hanslmayr et al, 2005 ;Nan et al, 2012 ;Wan et al, 2014 ;Zoefel et al, 2011) and the standard alpha frequency (Berger & Davelaar, 2018 ;Biswas & Ray, 2019 ;Bobby & Prakash, 2017 ;Brickwedde et al, 2019 ;Cho et al, 2008 ;Chow et al, 2017 ;Dekker et al, 2014 ;Guez et al, 2015 ;Hsueh et al, 2016 ;Lee et al, 2019 ;Nan et al, 2013 ;Nan et al, 2020 ;Naas et al, 2019 ;Nawaz et al, 2022 ;Peeters et al, 2014 ;Peng et al, 2020 ;Ros et al, 2010 ;Ros et al, 2013 ;Su et al, 2021 ;Takabatake et al, 2021 ;Wei et al, 2017). The advantage of IAF over standard alpha frequency, however, has still little empirical validation.…”

Systematic Review and Meta-Analysis on the Effects of Neurofeedback Training of Theta Activity on Working Memory and Episodic Memory in Healthy Population

“…However, a duration of over 20 min would be required. Compared with the NFT of alpha activity, a successful alpha NFT on memory needed a sample size of >10, alpha NFT on memory was more effective in healthy young adults than in the elderly, a training strategy with visual feedback and a mental strategy was beneficial for evoking the region of the parietal cortex [ 48 ], and the efficacy of alpha NFT on EM needed at least >10 training sessions with a duration of >20 min per session [ 36 ]. In a previous study conducted on fifteen heathy young adults, the results concerning alpha NFT suggested that positive effects were found for 12 sessions of NFT with a 25 min duration [ 49 ].…”

Remote neurocognitive interventions for attention-deficit/hyperactivity disorder – opportunities and challenges

“…Wiemers et al, 2019), suggesting that there might be individual differences to the treatment effects of cognitive training in AD/HD. The individual difference may also be true for other forms of neurocognitive training, for example, NFT (Arns et al, 2012;Su et al, 2021), VNS (Brá zdil et al, 2019), and tES (Chew et al, 2015). Also, it appears that both behavioral and brain measures carry unique value in predicting intervention effects (Michelini et al, 2022;Nemmi et al, 2016).…”