Learning to Relax and Attend: Investigating Methods to Analyze Neurofeedback Data from Nepalese Children’s Mind-Full Sessions

Mind-Full (Nepal) consists of three neurofeedback (NF) games designed to help young children living in extreme poverty learn to self-regulate relaxation and attention. In this thesis, I present the methodological process used to analyze the Mind-Full's log data that was collected from a field-study conducted in Nepal (Antle et al., 2015). The results of this analysis showed that there was no significant improvement in relaxation, attention and game performance of the children across sessions in all three games. There was no correlation between the dependent measures derived from headset generated relaxation/attention indices and brainwave amplitudes. I discuss reasons for these findings, grounded in the previous NF studies. Based on my results and previous works, I recommend approaches to data analysis methods for future NF studies including how to pre-process data, choose dependent measures and sample sessions for across sessions analysis.