Dr Eddy Davelaar studied at Maastricht University in the Netherlands and completed simultaneously a degree in Biological Health Sciences and a degree in Psychology. He continued his PhD studies at Birkbeck, University London on the topic of computational modelling of human memory. After a post-doctoral period involving modelling perception, attention, and language, he returned to Birkbeck as a Lecturer in 2006, where he is currently an Associate Professor in Cognitive Science. He conducts research on cognitive aging, neurofeedback, and develops with his colleague an integrated qualitative-quantitative methodology that can be applied to neurofeedback research and practice.
PhD
Eddy Davelaar
Understanding (and improving) neurofeedback efficacy: a multidisciplinary endeavour
Presentation Abstract:
In this talk, I will present our theoretical (and empirical) work aimed at answering the question “How does neurofeedback work?” The research is guided by the recently formulated multi-stage theory of neurofeedback learning (Davelaar, 2018). The following examples will be explored. First, giving instructions to trainees has typically been discouraged in the literature on grounds that trainees are inconsistent in their strategy use, have no knowledge about their strategies, and strategies do not work for everyone. Yet, we find that in the case of frontal alpha upregulation, converging verbal reports emerged that are amenable for guided neurofeedback (Davelaar, et al., 2018). These results require using the explicitation-interview as a research methodology followed by a cognitive classification of the reports. Second, the typical study has a pre- and post-training session of cognitive tests (and perhaps even a QEEG). I will demonstrate that analysing the cognitive data beyond the superficial averaged response time and accuracy uncovers cognitive changes that are specific to certain theoretically-motivated EEG frequencies (Davelaar, 2017). Thus, SMR training and midfrontal theta upregulation show differential influences on first-and second-order attention. In addition, upregulating frontal alpha or midfrontal theta have opposite effects on information processing that are referred to as non-decision processes, such as feature extraction. Finally, I will present a roadmap for how pre- and post-training QEEG (and intra-training EEG recordings) can be analysed to investigate the effects on brain circuitry, which after all is the main aim of neurofeedback training.
In sum, the development of an explicit theoretical model opens the door for the field of neurofeedback to adopt formal qualitative and quantitative methodologies from cognitive science and tackle research questions that were hitherto beyond the field’s reach.