Application of Latent Growth Curve modeling to predict individual trajectories during neurofeedback treatment for tinnitus

Abstract

Tinnitus is a heterogeneous phenomenon indexed by various EEG oscillatory profiles. Applying neurofeedback (NFB) with the aim of changing these oscillatory patterns not only provides help for those who suffer from the phantom percept, but a promising foundation from which to probe influential factors. The reliable attribution of influential factors that potentially predict oscillatory changes during the course of NFB training may lead to the identification of subgroups of individuals that are more or less responsive to NFB training. The present study investigated oscillatory trajectories of delta (3-4Hz) and individual alpha (8.5-12Hz) during 15 NFB training sessions, based on a Latent Growth Curve framework. First, we found the desired enhancement of alpha, while delta was stable throughout the NFB training. Individual differences in tinnitus-specific variables and general-, as well as health-related quality of life predictors were largely unrelated to oscillatory change prior to and across the training. Only the predictors age and sex at baseline were clearly related to slow-wave delta, particularly so for older female individuals who showed higher delta power values from the start. Second, we confirmed a hierarchical cross-frequency association between the two frequency bands; however, in opposing directions to those anticipated in tinnitus. The establishment of individually tailored NFB protocols would boost this therapy's effectiveness in the treatment of tinnitus. In our analysis, we propose a conceptual groundwork toward this goal of developing more targeted treatment.