Abstract
Neurofeedback using real-time functional magnetic resonance imaging is a technique which supports participants to modify their own brain activity for therapeutic benefit. It has gained attention for its potential as an alternative intervention for a range of mental health issues. However, there is considerable variance in participant success. Understanding the factors involved in this variance could assist with the prediction of outcomes and personalised support. Here, the results of a literature review on this topic and a subsequent secondary data analysis for a therapeutically significant population are presented. Specifically, in Zich and colleagues (under review), adolescent female participants (n = 28) learned to modulate healthy patterns of emotional regulation in a study which collected pre-intervention data on variables to do with mood, IQ, development, initial functional connectivity (IFC) and control beliefs. The current analysis aimed to predict outcomes based on these measures. Differences between participants who improved (learners) and declined (non-learners) in performance were also explored. Principal components analysis reduced the measures into the factors ‘Control’ (mood and control beliefs) and ‘Maturity’, (age, puberty and IQ). Multiple regression analysis with these factors and IFC did not significantly predict performance or change. However, IFC significantly predicted performance (β =-415.75, p = .004, CI = -415.75, -92.37). At a group level, non-learners initially performed above the mean but could not sustain this success. Learners had significantly higher thought control ability and verbal comprehension scores than non-learners. These results and other findings from the literature require confirmation with larger samples. It was concluded that predicting outcomes for individuals may be challenging as individual factors are likely to have complex roles, though initial connectivity readings may predict performance effectively. Implications include the potential for personalised support to improve outcomes for non-regulators. Individual factors should be routinely considered to develop the efficacy of neurofeedback.