Brain states and individual differences

Rhythms, learning, and cognitive strategies

People differ in how they learn and organize information. In a co-authored iScience study, we related resting-state MEG to verbal learning and encoding strategies. The work examines spectral features across cortical regions and their relationship with memory performance and the ways people group information.

This places individual variation at the center: a useful account of brain dynamics should help explain why people approach the same cognitive task differently, as well as how their activity changes during the task.

Changes in conscious experience

I also co-authored work on auto-induced cognitive trance, a self-induced non-ordinary state of consciousness. That study compares resting and trance EEG using aperiodic spectral activity, Lempel–Ziv complexity, and sample entropy, together with machine-learning analyses. It is available as a preprint under review.

Across these collaborations, spectral and complexity measures describe complementary aspects of ongoing activity. They connect with the neural-dynamics methods I use in decision-making and clinical EEG, without treating different populations or states as the same experiment.