Predictive coding (PC) is a neurocognitive concept, according to which the brain does not process the whole qualia of external information, but only residual mismatches occurring between incoming information and an individual, inner model of the world. At the time of issue initiation, I expected an essential focus on mismatch signals in the brain, especially those captured by neurophysiologic oscillations. This was because one most plausible approach to the PC concept is to identify and validate mismatch signals in the brain. Announcing the topic revealed a much deeper consideration of intelligible minds of researchers. It turned out that what was of fundamental interest was which brain mechanisms support the formation, maintenance and consolidation of the inner model determining PC. Is PC a dynamic construct continuously modulated by external environmental or internal mental information? The reader will be delighted to get acquainted with the current views and understanding of eminent scholars in the field. It will be challenging to discover the realm of sleep where both physiological, energy preserving and mental qualia principles build on the inner models to shape and transform the self. And where neurophysiologic oscillations may both transmit external information and translate inner models from state to state to preserve the self-continuity and compactness.

Brain oscillations, or neural rhythms, reflect widespread functional connections between large-scale neural networks, as well as within cortical networks. As such they have been related to many aspects of human behaviour. An increasing number of studies have demonstrated the role of brain oscillations at distinct frequency bands in cognitive, sensory and motor tasks. Consequentially, those rhythms also affect diverse aspects of human communication. On the one hand, this comprises verbal communication; a field where the understanding of neural mechanisms has seen huge advances in recent years. Speech is inherently organised in a rhythmic manner. For example, time scales of phonemes and syllables, but also formal prosodic aspects such as intonation and stress, fall into distinct frequency bands. Likewise, neural rhythms in the brain play a role in speech segmentation and coding of continuous speech at multiple time scales, as well as in the production of speech. On the other hand, human communication involves widespread and diverse nonverbal aspects where the role of neural rhythms is far less understood. This can be the enhancement of speech processing through visual signals, thought to be guided via brain oscillations, or the conveying of emotion, which results in differential rhythmic modulations in the observer. Additionally, body movements and gestures often have a communicative purpose and are known to modulate sensorimotor rhythms in the observer. This Research Topic of Frontiers in Human Neuroscience highlights the diverse aspects of human communication that are shaped by rhythmic activity in the brain. Relevant contributions are presented from various fields including cognitive and social neuroscience, neuropsychiatry, and methodology. As such they provide important new insights into verbal and non-verbal communication, pathological changes, and methodological innovations.

Neuroscience has made considerable progress in figuring out how the brain works. We know much about the molecular-genetic and biochemical underpinnings of sensory and motor functions, and recent neuroimaging work has opened the door to investigating the neural underpinnings of higher-order cognitive functions, such as memory, attention, and even free will. In these types of investigations, researchers apply specific stimuli to induce neural activity in the brain and look for the function in question. However, there may be more to the brain and its neuronal states than the changes in activity we induce by applying particular external stimuli. In Volume 1 of Unlocking the Brain, Georg Northoff presents his argument for how the brain must code the relationship between its resting state activity and stimulus-induced activity in order to enable and predispose mental states and consciousness. By presupposing such a basic sense of neural code, the author ventures into different territories and fields of current neuroscience, including a comprehensive exploration of the features of resting state activity as distinguishable from and stimulus-induced activity; sparse coding and predictive coding; and spatial and temporal features of the resting state itself. This yields a unique and novel picture of the brain, and will have a major and lasting impact on neuroscientists working in neuroscience, psychiatry, and related fields.

A new theory is taking hold in neuroscience. It is the theory that the brain is essentially a hypothesis-testing mechanism, one that attempts to minimise the error of its predictions about the sensory input it receives from the world. It is an attractive theory because powerful theoretical arguments support it, and yet it is at heart stunningly simple. Jakob Hohwy explains and explores this theory from the perspective of cognitive science and philosophy. The key argument throughout The Predictive Mind is that the mechanism explains the rich, deep, and multifaceted character of our conscious perception. It also gives a unified account of how perception is sculpted by attention, and how it depends on action. The mind is revealed as having a fragile and indirect relation to the world. Though we are deeply in tune with the world we are also strangely distanced from it. The first part of the book sets out how the theory enables rich, layered perception. The theory's probabilistic and statistical foundations are explained using examples from empirical research and analogies to different forms of inference. The second part uses the simple mechanism in an explanation of problematic cases of how we manage to represent, and sometimes misrepresent, the world in health as well as in mental illness. The third part looks into the mind, and shows how the theory accounts for attention, conscious unity, introspection, self and the privacy of our mental world.

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.

The nervous system is the product of biological evolution and is shaped by the interplay between extrinsic factors determining the ecology of animals, and by intrinsic processes that dictate the developmental rules that give rise to adult functional structures. This special topic is oriented to develop an integrative view from behavior and ecology to neurodevelopmental processes. We address questions such as how do sensory systems evolve according to ecological conditions? How do neural networks organize to generate adaptive behavior? How does cognition and brain connectivity evolve? What are the developmental mechanisms that give rise to functional adaptation? Accordingly, the book is divided in three sections, (i) Evolution of sensorimotor systems; (ii) Cognitive computations and neural circuits, and (iii) Development and brain evolution. We hope that this initiative will support an interdisciplinary program that addresses the nervous system as a unified organ, subject to both functional and developmental constraints, where the final outcome results of a compromise between different parameters rather than being the result of several single variables acting independently of each other.