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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.

Decision Making --- Evolution and self --- brain oscillations --- predictive coding --- Psychoanalysis --- Psychopathology --- Sleep and dreaming --- REM sleep --- cognition and perception

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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.

Decision Making --- Evolution and self --- brain oscillations --- predictive coding --- Psychoanalysis --- Psychopathology --- Sleep and dreaming --- REM sleep --- cognition and perception

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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.

Perceptual learning. --- Perceptual Learning --- Bayesian Brain --- predictive coding --- repetition suppression --- refractoriness --- Prediction error --- Attention --- visual mismatch negativity --- stimulus specific adaptation --- vMMN

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"A much-needed synthesis of active inference, a theory of mind that addresses cognition, behavior, intelligence, & mental disorders and which can be extended to explain behavior in all living systems"--

Neurosciences --- Philosophy of mind --- Active Inference --- free energy --- predictive coding --- Bayesian inference --- predictive processing --- planning as inference --- active sensing --- hypothesis testing --- behavior --- theoretical neurobiology --- brain --- computational neuroscience --- perception --- planning --- action --- control. --- Perception. --- Inference. --- Neurobiology. --- Human behavior models. --- Knowledge, Theory of. --- Bayesian statistical decision theory. --- SCIENCE / Life Sciences / Neuroscience --- PSYCHOLOGY / Cognitive Neuroscience & Cognitive Neuropsychology --- PHILOSOPHY / Mind & Body --- Bayes' solution --- Bayesian analysis --- Statistical decision --- Epistemology --- Theory of knowledge --- Philosophy --- Psychology --- Behavioral modeling --- Behavioral models --- Modeling human behavior --- Models of behavior --- Ampliative induction --- Induction, Ampliative --- Inference (Logic) --- Reasoning --- Supraliminal perception --- Cognition --- Apperception --- Senses and sensation --- Thought and thinking --- Methodology

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At the heart of human intelligence rests a fundamental puzzle: How are we incredibly smart and stupid at the same time? No existing machine can match the power and flexibility of human perception, language, and reasoning. Yet, we routinely commit errors that reveal the failures of our thought processes. 'What Makes Us Smart' makes sense of this paradox by arguing that our cognitive errors are not haphazard. Rather, they are the inevitable consequences of a brain optimized for efficient inference and decision making within the constraints of time, energy, and memory - in other words, data and resource limitations. Framing human intelligence in terms of these constraints, Samuel Gershman shows how a deeper computational logic underpins the 'stupid' errors of human cognition.

Cognition --- Cognitive psychology. --- Age factors. --- Psychology, Cognitive --- Cognitive science --- Psychology --- Age factors in cognition --- Ability, Influence of age on --- Cognition. --- Intellect. --- Human intelligence --- Intelligence --- Mind --- Ability --- Thought and thinking --- Accuracy and precision. --- Action potential. --- Ad hoc hypothesis. --- Ad hominem. --- Adaptive bias. --- Almost surely. --- Alternative hypothesis. --- Altruism. --- Ambiguity. --- Analogy. --- Anecdote. --- Approximation. --- Attractiveness. --- Bayes' theorem. --- Bayesian inference. --- Bayesian probability. --- Bayesian. --- Behavior. --- Circular reasoning. --- Cognitive flexibility. --- Cognitive style. --- Commitment device. --- Confidence. --- Confirmation bias. --- Conspiracy theory. --- Controllability. --- Counterintuitive. --- Credibility. --- Decision-making. --- Effectiveness. --- Efficacy. --- Efficiency. --- Efficient coding hypothesis. --- Efficient frontier. --- Estimation. --- Expected value. --- Explanation. --- Fair coin. --- Fair market value. --- Gimmick. --- Guessing. --- Heuristic. --- Hot Hand. --- Human intelligence. --- Hypothesis. --- Illusion of control. --- Inductive bias. --- Inference. --- Intelligent design. --- Learnability. --- Lightness (philosophy). --- Likelihood function. --- Logical extreme. --- Logical reasoning. --- Moral hazard. --- Motivated reasoning. --- Mutual exclusivity. --- Natural approach. --- Normative. --- Observation. --- Observational learning. --- Of Miracles. --- Opportunity cost. --- Optimism bias. --- Optimism. --- Our Choice. --- Pairwise comparison. --- Perfect rationality. --- Physical attractiveness. --- Point estimation. --- Politeness. --- Positive feedback. --- Predictability. --- Prediction. --- Predictive coding. --- Predictive power. --- Principle of rationality. --- Prior probability. --- Probability. --- Prosocial behavior. --- Quantity. --- Rational agent. --- Rational choice theory. --- Rationality. --- Reason. --- Reinforcement learning. --- Result. --- Self-control. --- Sophistication. --- Spontaneous recovery. --- Strong inference. --- Suggestion. --- Theory. --- Thought. --- Truth value. --- Uncertainty. --- Utility. --- Value of information. --- With high probability. --- PSYCHOLOGY / Cognitive Psychology & Cognition --- COMPUTERS / Logic Design