Neural symphony of flow experience: Evidence for high-dimensional metastable dynamics

Abdelrahman B. M. Eldaly; Kris Zhangguang Kang; Fiona Fui-Hoon Nah; Leanne Lai-Hang Chan; Keng Leng Siau; Xiao Fan Liu; Richard Huskey; Langtao Chen; Tejaswini Yelamanchili; René Weber

doi:10.1016/j.neuroimage.2026.122049

Neural symphony of flow experience: Evidence for high-dimensional metastable dynamics

Abdelrahman B. M. Eldaly
, Kris Zhangguang Kang
, Fiona Fui-Hoon Nah
, Leanne Lai-Hang Chan
, Keng Leng Siau
, Xiao Fan Liu
, Richard Huskey
, Langtao Chen
, Tejaswini Yelamanchili
, René Weber^*

^*Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

4 Downloads (CityUHK Scholars)

Abstract

Flow, an optimal experience characterized by deep immersion and engagement in an activity, has been extensively studied in behavioral research. However, its neural dynamic mechanism remains poorly understood. In a within-subject video gaming experiment, we captured neural activity underlying flow, boredom, and anxiety using a 64-channel electroencephalogram (EEG) system. Compared to boredom and anxiety, flow exhibits the highest global functional connectivity, metastability, and dimensionality of dynamic functional connectivity patterns, suggesting that flow is a highly adaptable process that is supported by high-dimensional neural dynamics. Unlike previous studies that focused on identifying static or localized brain activity, we examine the neural dynamic patterns of flow and propose the Global Dynamic Flow Model that characterizes flow as a high-dimensional, global metastable neural activity. Our study offers novel insights into the role of high-dimensionality and global metastability in brain activity associated with the flow experience.

© 2026 The Author(s)

Original language	English
Article number	122049
Journal	NeuroImage
Volume	338
Online published	11 Jun 2026
DOIs	https://doi.org/10.1016/j.neuroimage.2026.122049
Publication status	Published - Sept 2026

Research Keywords

Flow experience
Global dynamic flow model
Dynamic functional connectivity
Complex networks
Metastability
Dimensionality

Publisher's Copyright Statement

This full text is made available under CC-BY-NC-ND 4.0. https://creativecommons.org/licenses/by-nc-nd/4.0/

Access Output

10.1016/j.neuroimage.2026.122049

496976722.pdfFinal Published version, 812 KBLicence: CC BY-NC-ND

Other Access Options

Check CityUHK Library

Permanent Link

Right click to copy link

Cite this

@article{b2c52d2c5d764d6ea80d7d284479d016,

title = "Neural symphony of flow experience: Evidence for high-dimensional metastable dynamics",

abstract = "Flow, an optimal experience characterized by deep immersion and engagement in an activity, has been extensively studied in behavioral research. However, its neural dynamic mechanism remains poorly understood. In a within-subject video gaming experiment, we captured neural activity underlying flow, boredom, and anxiety using a 64-channel electroencephalogram (EEG) system. Compared to boredom and anxiety, flow exhibits the highest global functional connectivity, metastability, and dimensionality of dynamic functional connectivity patterns, suggesting that flow is a highly adaptable process that is supported by high-dimensional neural dynamics. Unlike previous studies that focused on identifying static or localized brain activity, we examine the neural dynamic patterns of flow and propose the Global Dynamic Flow Model that characterizes flow as a high-dimensional, global metastable neural activity. Our study offers novel insights into the role of high-dimensionality and global metastability in brain activity associated with the flow experience. {\textcopyright} 2026 The Author(s)",

keywords = "Flow experience, Global dynamic flow model, Dynamic functional connectivity, Complex networks, Metastability, Dimensionality",

author = "Eldaly, \{Abdelrahman B. M.\} and Kang, \{Kris Zhangguang\} and Nah, \{Fiona Fui-Hoon\} and Chan, \{Leanne Lai-Hang\} and Siau, \{Keng Leng\} and Liu, \{Xiao Fan\} and Richard Huskey and Langtao Chen and Tejaswini Yelamanchili and Ren{\'e} Weber",

year = "2026",

month = sep,

doi = "10.1016/j.neuroimage.2026.122049",

language = "English",

volume = "338",

journal = "NeuroImage",

issn = "1053-8119",

publisher = "Elsevier Inc.",

}

TY - JOUR

T1 - Neural symphony of flow experience

T2 - Evidence for high-dimensional metastable dynamics

AU - Eldaly, Abdelrahman B. M.

AU - Kang, Kris Zhangguang

AU - Nah, Fiona Fui-Hoon

AU - Chan, Leanne Lai-Hang

AU - Siau, Keng Leng

AU - Liu, Xiao Fan

AU - Huskey, Richard

AU - Chen, Langtao

AU - Yelamanchili, Tejaswini

AU - Weber, René

PY - 2026/9

Y1 - 2026/9

N2 - Flow, an optimal experience characterized by deep immersion and engagement in an activity, has been extensively studied in behavioral research. However, its neural dynamic mechanism remains poorly understood. In a within-subject video gaming experiment, we captured neural activity underlying flow, boredom, and anxiety using a 64-channel electroencephalogram (EEG) system. Compared to boredom and anxiety, flow exhibits the highest global functional connectivity, metastability, and dimensionality of dynamic functional connectivity patterns, suggesting that flow is a highly adaptable process that is supported by high-dimensional neural dynamics. Unlike previous studies that focused on identifying static or localized brain activity, we examine the neural dynamic patterns of flow and propose the Global Dynamic Flow Model that characterizes flow as a high-dimensional, global metastable neural activity. Our study offers novel insights into the role of high-dimensionality and global metastability in brain activity associated with the flow experience. © 2026 The Author(s)

AB - Flow, an optimal experience characterized by deep immersion and engagement in an activity, has been extensively studied in behavioral research. However, its neural dynamic mechanism remains poorly understood. In a within-subject video gaming experiment, we captured neural activity underlying flow, boredom, and anxiety using a 64-channel electroencephalogram (EEG) system. Compared to boredom and anxiety, flow exhibits the highest global functional connectivity, metastability, and dimensionality of dynamic functional connectivity patterns, suggesting that flow is a highly adaptable process that is supported by high-dimensional neural dynamics. Unlike previous studies that focused on identifying static or localized brain activity, we examine the neural dynamic patterns of flow and propose the Global Dynamic Flow Model that characterizes flow as a high-dimensional, global metastable neural activity. Our study offers novel insights into the role of high-dimensionality and global metastability in brain activity associated with the flow experience. © 2026 The Author(s)

KW - Flow experience

KW - Global dynamic flow model

KW - Dynamic functional connectivity

KW - Complex networks

KW - Metastability

KW - Dimensionality

UR - http://www.scopus.com/inward/record.url?scp=105042473702&partnerID=8YFLogxK

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-105042473702&origin=recordpage

UR - https://www.webofscience.com/wos/woscc/full-record/WOS:001804940500001

U2 - 10.1016/j.neuroimage.2026.122049

DO - 10.1016/j.neuroimage.2026.122049

M3 - RGC 21 - Publication in refereed journal

SN - 1053-8119

VL - 338

JO - NeuroImage

JF - NeuroImage

M1 - 122049

ER -

Neural symphony of flow experience: Evidence for high-dimensional metastable dynamics

Abstract

Research Keywords

Publisher's Copyright Statement

Access Output

Other Access Options

Permanent Link

Other Files and Links

Fingerprint

Cite this