Predicting the Intensity of the Flow State Using EEG and fNIRS Biomarkers

Abstract

The experience referred to as “flow” is characterized by complete immersion in an activity and achievement of excellent performance. Thus far, methods for assessing the intensity of the flow state have mostly been subjective, although an objective and dynamic evaluation method could help identify the actual engagement of an individual in a task or activity. Using electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), we investigated cortical biomarkers to assess the intensity of the flow experience in 13 young adult participants. To induce flow experiences of varying intensities, we asked the participants to play Tetris at three difficulty levels (easy, optimal, and hard), with the optimal level determined based on each individual’s skill. Subjective ratings revealed that the most intense flow state was achieved under optimal conditions. We found a significant negative correlation between the subjective intensity of flow and β wave activity recorded via EEG in the left middle temporal region, indicating that more intense flow experience was associated with suppressed β wave activity. Furthermore, fNIRS measurements of oxygenated hemoglobin dynamics revealed significant brain activity related to the flow experience in the primary motor, premotor, primary somatosensory, and dorsolateral prefrontal cortices. We further developed a linear regression model to predict the intensity of flow experience over time based on the selected cortical responses. Our model demonstrated excellent predictive performance, achieving a mean correlation coefficient of 0.86 ± 0.03 (maximum: 0.97, minimum: 0.59) between the measured and predicted flow intensities. Our results support the use of EEG and fNIRS biomarkers as objective measures of the intensity of flow experiences.