Neurofeedback (NF) training has been described as a way of self-regulating the brain's electrical activity through classical and operant conditioning (Sherlin et al., 2011). However, a growing number of research studies have suggested that there are also more advanced processes involved when learning to control one’s own brainwave activity (Hammer et al., 2012, 2014; Wood et al., 2014). Psychological predictors (e.g., locus of control) (Witte et al., 2014), brainwave baseline values (e.g., resting alpha baselines) (Wan et al., 2014), and morphology of brain structures (e.g., brain matter structures in mid-cingulate and prefrontal regions) (Enriquez-Geppert et al., 2013a) have all been shown to predict successful NF learning. Individuals who are not able to learn to modulate their brainwave activity even after several sessions are classified as non-responders. Enriquez-Geppert et al. (2013b) classified 25% of the experimental group as non-responders, while Lubar et al. (1995) classified 37% as non-responders in their intervention. Since NF has shown great promise for treating a wide variety of psychological disorders (Niv, 2013; Arns et al., 2009) and has also shown positive results regarding improving sports performance (Vernon, 2005; Gruzelier, 2014b) and artistic/creative skills (Gruzelier, 2014b), it is of great importance to further understand what are the predictors for successful NF learning.

Wood et al.'s (2014) theoretical model for self-control of brain activity is based on dual process theory and summarizes the learning process of NF. It is described how there is a combination of automatic (not under voluntary control) and controlled (under voluntary control) information processing involved when learning to modulate one's brainwave activity. This is illustrated by three main circles: organismic, central, and local. The organismic circle refers to all the brain processes which are not under direct voluntary control (i.e., automatic/unconscious cognitive processes), while the central circle refers to the processes which are under voluntary control (i.e., self-talk, directing focus, etc.). The individual’s process capacity in the central controlled circle is limited, so misguided activity here (i.e., internal rumination) can take process capacity away from more functional activities and thereby disturb effective NF learning. The most important circle for NF training is the local circle. This circle refers to all the processes which are directly causing the NF learning and is spread over both central areas (where the controlled processes take place) and organismic areas (where more automatic processes take place). When NF learning is at its peak, the automatic processes dominate. However, when problems in learning occur, self-directed instruction and more controlled functions can help get the learning back on track again. The ultimate learning takes place under two conditions: 1) non-relevant association is avoided between inner states and the reward given, and 2) the client is engaged and focused on the task without distractions. One main point from the model is that you want as much activity in the local control network as possible and less activity everywhere else for the best NF learning to take place.

By investigating psychological and physiological predictors (Johnson & Ivarsson, 2011; Hammer et al., 2014) for successful NF learning, it is reasoned that the findings can guide and optimize future NF interventions. Wood et al. (2014) highlight that optimal NF learning takes place when there is as much activity in the local control network as possible and less activity everywhere else. To get into this state, you have to take both the organismic and central processes into consideration and also acknowledge that you affect these two processes in totally different ways. Sports psychology combined with NF interventions aimed at increasing local control network activity would potentially enhance NF learning. Open focus strategies specifically developed for helping individuals regulate their alpha activity have been reported to increase stress management and attentional capacity (Fehmi & Robbins, 2008). Reid et al. (2013) argued for potential synergy effects of combining NF and HRV biofeedback (HRVB) together. HRVB is a technique where the body’s natural changes in heart rate fluctuations are made visible (Lehrer & Gevirtz, 2014) and it has previously shown potential for decreasing stress levels and risk of sustaining sports injuries in football players (Edvardsson, Ivarsson & Johnson, 2012). It is of great importance to continue better understanding what strategies could predict successful NF learning. This kind of research can potentially help more individuals gain the full advantage of this promising technique in future health and performance interventions.