Abstract

The brain is characterized by extensive recurrent connectivity within and between areas. This recurrent connectivity enables various patterns of arrhythmic (non-oscillatory) and rhythmic (oscillatory) neural activity that are temporally coordinated between regions. What role do these distinct dynamics play in the large-scale integration of perceptual and predictive information? In this talk, I will discuss how information theory combined with EEG , ECoG, and computational modelling can help us uncover large-scale neural patterns of non-oscillatory activity during perception and prediction. In the first series of studies, I will show how non-oscillatory rather than oscillatory dynamics encode perceptual and predictive information across sensory modalities in different species. In the second part, I will discuss how non-oscillatory dynamics encode synergistic (complementary) rather than redundant (common) information between brain areas during visual and auditory predictive processing. These empirical and theoretical observations will provide new insights into the functional role of non-oscillatory dynamics during the large-scale integration of perceptual and predictive information.