A framework for neurophysiological experiments on flow states

Oliver Durcan, Peter Holland, Joydeep Bhattacharya
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Abstract

Csikszentmihalyi’s concept of the “flow state” was initially discovered in experts deeply engaged in self-rewarding activities. However, recent neurophysiology research often measures flow in constrained and unfamiliar activities. In this perspective article, we address the challenging yet necessary considerations for studying flow state’s neurophysiology. We aggregate an activity-autonomy framework with several testable hypotheses to induce flow, expanding the traditional “challenge skill balance” paradigm. Further, we review and synthesise the best methodological practices from neurophysiological flow studies into a practical 24-item checklist. This checklist offers detailed guidelines for ensuring consistent reporting, personalising and testing isolated challenge types, factoring in participant skills, motivation, and individual differences, and processing self-report data. We argue for a cohesive approach in neurophysiological studies to capture a consistent representation of flow states. The Perspective presents an activity autonomy framework to distinguish experimental activity characteristics and discusses best practices for studying the neurophysiological correlates of flow.

Abstract Image

流动状态神经生理学实验框架
西克森特米哈伊(Csikszentmihalyi)的 "流动状态 "概念最初是在专家们深入参与自我奖励活动时发现的。然而,最近的神经生理学研究通常是在受限和不熟悉的活动中测量流动状态。在这篇视角文章中,我们探讨了研究流动状态的神经生理学所面临的挑战和必要的考虑因素。我们将活动-自主框架与几个可检验的假说结合起来,以诱导流动,从而扩展了传统的 "挑战技能平衡 "范式。此外,我们还回顾并总结了神经生理学流动研究中的最佳方法,并将其归纳为一份包含 24 个项目的实用核对表。该清单为确保报告的一致性、个性化和测试孤立的挑战类型、考虑参与者的技能、动机和个体差异以及处理自我报告数据提供了详细的指导。我们主张在神经生理学研究中采用连贯一致的方法来捕捉流动状态。透视》提出了一个活动自主性框架来区分实验活动特征,并讨论了研究流动的神经生理学相关性的最佳实践。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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