  Virtual reality finds various applications in productivity, entertainment,
and training scenarios requiring working memory and attentional resources.
Working memory relies on prioritizing relevant information and suppressing
irrelevant information through internal attention, which is fundamental for
successful task performance and training. Today, virtual reality systems do not
account for the impact of working memory loads resulting in over or
under-stimulation. In this work, we designed an adaptive system based on EEG
correlates of external and internal attention to support working memory task
performance. Here, participants engaged in a visual working memory N-Back task,
and we adapted the visual complexity of distracting surrounding elements. Our
study first demonstrated the feasibility of EEG frontal theta and parietal
alpha frequency bands for dynamic visual complexity adjustments. Second, our
adaptive system showed improved task performance and diminished perceived
workload compared to a reverse adaptation. Our results show the effectiveness
of the proposed adaptive system, allowing for the optimization of distracting
elements in high-demanding conditions. Adaptive systems based on alpha and
theta frequency bands allow for the regulation of attentional and executive
resources to keep users engaged in a task without resulting in cognitive
overload.
