The neuropsychological measure (EEG) of flow under conditions of peak performance

Abstract

Flow is a mental state characterised by a feeling of energised focus, complete involvement and success when fully immersed in an activity. The dimensions of and the conditions required for flow to occur have been explored in a broad spectrum of situational contexts. The close relationship between flow and peak performance sparked an interest in ways to induce flow. However, any process of flow induction requires a measure to trace the degree to which flow is in fact occurring. Self-reports of the flow experience are subjective and provide ad hoc information. Psycho-physiological measures, such as EEG, can provide objective and continuous indications of the degree to which flow is occurring. Unfortunately few studies have explored the relationships between psycho-physiological measures and flow. The present study was an attempt to determine the EEG correlates of flow under conditions of peak performance. Twenty participants were asked to perform a continuous visuomotor task 10 times. Time taken per task was used as an indicator of task performance. EEG recordings were done concurrently. Participants completed an Abbreviated Flow Questionnaire (AFQ) after each task and a Game Flow Inventory (GFI) after having finished all 10 tasks. On completion, performance times and associated flow scores were standardised where after the sample was segmented into a high flow - peak performance and a low flow - low performance level. Multi-variate analysis of variance (MANOVA) was conducted on the performance, flow and EEG data to establish that a significant difference existed between the two levels. In addition, a one-way analysis of variance between high and low flow data was conducted for all variables and main effects were established. Inter-correlations of all EEG data at both levels were then conducted across four brain sites (F3, C3, P3, O1). In high flow only, results indicated increased lobeta power in the sensorimotor cortex together with a unique EEG pattern showing beta band synchronisation between the prefrontal and sensori-motor areas and de-synchronisation between all other areas, while all other frequencies (delta, theta, alpha, lobeta, hibeta, and gamma) remained synchronised across all scalp locations. These findings supported a theoretical neuropsychological model of flow.