Flow is characterized by a high level of intrinsic reward that results from a balance between task difficulty and individual ability. The Synchronization Theory of Flow offers an explanation for the neural basis of this process. It predicts an energetically-optimized, brain-network organization between cognitive control and reward regions when task difficulty and individual ability are balanced. While initial results provide support for structural predictions, the many-to-many connectivity and energetic optimality hypotheses remain untested. Our study addresses this gap. Subjects played a video game while undergoing functional magnetic resonance imaging. We experimentally manipulated task difficulty and individual ability. Using graph theoretical analyses, we show that the balanced-difficulty condition (compared to low- or high-difficulty) was associated with the highest average network degree in the fronto-parietal control network (implicated in cognitive control) and had the lowest global efficiency value, indicating low metabolic cost, and thereby testing Synchronization Theory’s core predictions.
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Huskey et al. (2018) studied this question.
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