In this paper, we argue that the comparator model is not a satisfactory model of sense of agency (SoA). We present a theoretical argument and experimental studies. We show (1) most studies of SoA neglect a distinction between SoA associated with movements (narrow SoA) and SoA associated with environmental events (broad SoA); (2) the comparator model emerges from experimental studies of sensory consequences narrowly associated with movements; (3) narrow SoA can be explained by a comparator model, but a motor signal (...) model is simpler and explain narrow SoA equally well; and (4) standard experimental paradigms study only broad SoA. Finally, we present results from two experiments, where we have failed to induce illusory narrow SoA in healthy participants. We believe our experimental approaches should have led to illusory SoA, if the comparator model of SoA was correct. The results challenge proponents of the comparator model of narrow SoA. (shrink)

Magnetoencephalography (MEG) and electroencephalography (EEG) are invaluable neuroscientific tools for unveiling human neural dynamics in three dimensions (space, time, and frequency), which are associated with a wide variety of perceptions, cognition, and actions. MEG/EEG also provides different categories of neuronal indices including activity magnitude, connectivity, and network properties along the three dimensions. In the last 20 years, interest has increased in inter-regional connectivity and complex network properties assessed by various sophisticated scientific analyses. We herein review the definition, computation, short history, (...) and pros and cons of connectivity and complex network (graph-theory) analyses applied to MEG/EEG signals. We briefly describe recent developments in source reconstruction algorithms essential for source-space connectivity and network analyses. Furthermore, we discuss a relatively novel approach used in MEG/EEG studies to examine the complex dynamics represented by human brain activity. The correct and effective use of these neuronal metrics provides a new insight into the multi-dimensional dynamics of the neural representations of various functions in the complex human brain. (shrink)