Topic: causal interactions

In recent years it has become increasingly clear that (Shannon) information is a central resource for organisms, akin in importance to energy. Any decision that an organism or a subsystem of an organism takes involves the acquisition, selection, and processing of information and ultimately its concentration and enaction. It is the consequences of this balance that will occupy us in this talk. This perception-action loop picture of an agent's life cycle is well established and expounded especially in the context of Fuster's sensorimotor hierarchies. Nevertheless, the information-theoretic persp

Normal brain function results from directed causal interactions between brain regions. However, the large-scale spatial and temporal structure of these interactions remains unclear. Lagged correlations between the activity of different brain regions may reflect their directed causal interactions. Thus, we combined magnetoencephalography (MEG) and machine learning approaches to characterize and disentangle the structure of lagged correlations in the human brain. We computed lagged correlations between all pairs of cortical regions and frequencies of neural activity. We employed curvature-regul