On Repeat offers an in-depth inquiry into music's repetitive nature. Drawing on a diverse array of fields, it sheds light on a range of issues from repetition's use as a compositional tool to its role in characterizing our behavior as listeners, and considers related implications for repetition in language, learning, and communication.

Current theories of visual change detection emphasize the importance of conscious attention to detect unexpected changes in the visual environment. However, an increasing body of studies shows that the human brain is capable of detecting even small visual changes, especially if such changes violate non-conscious probabilistic expectations based on repeating experiences. In other words, our brain automatically represents statistical regularities of our visual environmental. Since the discovery of the auditory mismatch negativity (MMN) event-related potential (ERP) component, the majority of research in the field has focused on auditory deviance detection. Such automatic change detection mechanisms operate in the visual modality too, as indicated by the visual mismatch negativity (vMMN) brain potential to rare changes. VMMN is typically elicited by stimuli with infrequent (deviant) features embedded in a stream of frequent (standard) stimuli, outside the focus of attention. In this research topic we aim to present vMMN as a prediction error signal. Predictive coding theories account for phenomena such as mismatch negativity and repetition suppression, and place them in a broader context of a general theory of cortical responses. A wide range of vMMN studies has been presented in this Research Topic. Twelve articles address roughly four general sub-themes including attention, language, face processing, and psychiatric disorders. Additionally, four articles focused on particular subjects such as the oblique effect, object formation, and development and time-frequency analysis of vMMN. Furthermore, a review paper presented vMMN in a hierarchical predictive coding framework. Each paper in this Research Topic is a valuable contribution to the field of automatic visual change detection and deepens our understanding of the short term plasticity underlying predictive processes of visual perceptual learning.

MICHAEL S. GAZZANIGA The investigation of the human brain and mind involves a myriad of ap proaches. Cognitive neuroscience has grown out of the appreciation that these approaches have common goals that are separate from other goals in the neural sciences. By identifying cognition as the construct of interest, cognitive neuro science limits the scope of investigation to higher mental functions, while simultaneously tackling the greatest complexity of creation, the human mind. The chapters of this collection have their common thread in cognitive neuroscience. They attack the major cognitive processes using functional stud ies in humans. Indeed, functional measures of human sensation, perception, and cognition are the keystone of much of the neuroscience of cognitive sci ence, and event-related potentials (ERPs) represent a methodological "coming of age" in the study of the intricate temporal characteristics of cognition. Moreover, as the field of cognitive ERPs has matured, the very nature of physiology has undergone a significant revolution. It is no longer sufficient to describe the physiology of non-human primates; one must consider also the detailed knowledge of human brain function and cognition that is now available from functional studies in humans-including the electrophysiological studies in humans described here. Together with functional imaging of the human brain via positron emission tomography (PET) and functional magnetic resonance imaging (fMRI), ERPs fill our quiver with the arrows required to pierce more than the single neuron, but the networks of cognition.