About this Research Topic
Human performance can reach near optimal levels in even hard problems. At the highest levels of learning and practice, we become highly productive, intrinsically motivated, with attention finely tuned to the task at hand. Such phenomena have been described by the subjective experience of Flow in the short term; and the development of expert performance in the long term. Other theories relevant to high performance or optimal experience include e.g. neural efficiency, the Zone, dual process theory, to name a few.
In this Research Topic, we aim to define the fundamental cognitive processes of high performance, which we describe using the generic term high performance cognition (HPC), and map those processes to their neural correlates. The Topic will address: Are there cognitive processes that are specific to high performance contexts (in different stages of learning), but also general to all or many performance-domains? How does HPC arise from neural activity? How does it, in turn, give rise to experiential states such as Flow, the Zone, and expert capabilities?
We invite theoretical (mathematical, computational, conceptual) or empirical (experimental, observational) contributions that increase understanding of HPC and its neural basis. Contributions can reveal workings of HPC in representative tasks (via behavioural or physiological observations), discuss how HPC gives rise to subjective experience (such as Flow), how it relates to learning and the development of expertise, or discuss how HPC is situated in the relevant theories.
This problem can be approached from several directions. One can ask, as much prior literature has done, which neural or cognitive states are observed when individuals are measured in HPC conditions, e.g. in tasks that induce self-reported Flow, or during expert performance. On the other hand, one can propose theoretical modes of high-performance cognition, such as exploration-driven practice and exploitation-driven peak performance, and examine them empirically. One can also explore computational models of cognitive activity, such as maximally-efficient information processing in the brain.
The methodologies in these approaches involve experimental manipulation, observation studies, reporting on phenomenology; modelling and machine learning; and measurement of behaviour, psychophysiology, brain imaging, testing and self-reports, observation and interview. All these methods have value; combining them likely brings further benefits. We thus especially welcome multi-disciplinary, multi-modal contributions that push the methodological boundaries of what has gone before.
Therefore we welcome Original Research reports and Systematic Reviews, but also all other article formats such as Mini-reviews and Reviews, Hypothesis and Theory papers, and Perspectives. We are especially interested in contributions that move beyond the descriptive, and support explanatory theory building, e.g. by proposing novel testable hypotheses for HPC, or by describing a model of contributing cognitive mechanisms, at any level of detail.
This Research Topic will help build the foundation for a HPC theory, the ultimate goal of which is to: (a) provide a novel ‘framework’ to integrate prior art, including valid empirical observations and theoretical insights; and thereby (b) support a more comprehensive explanation of human performance spanning levels of explanation from phenomenal to neural.
Keywords: Flow, Psychophysiology, Expert Performance, Cognitive Neuroscience, High Performance Cognition
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.