SPECIAL COLLECTION: UNDERSTANDING INVOLUNTARY THOUGHT AND AFFECT THROUGH BIG DATA AND AI: Tracking the Dynamics of the Stream of Thought Reveals Its Function

The mind constantly roves through the landscape of thought. Why does the mind spend so much time wandering, daydreaming, feeling, and spontaneously thinking? And what are the consequences when the stream of thought runs astray? To answer these questions, much of prior work has focused on the content of thought—what people think about when their mind is free to explore. This past work has identified several potential functions of spontaneous thought in the domains of memory, goal pursuit, and emotion regulation. However, the content of spontaneous thought is only one piece of the puzzle. To understand the functions of spontaneous thought, we also need to study the dynamics of thought—how the mind jumps, near and far, fast and slow, with direction and at random. Advances in natural language processing now allow researchers to track thought dynamics on ever larger behavioral data sets. We propose that tracking the dynamics of thought opens new opportunities for understanding how and why thought enables memory optimization, emotion regulation, and goal pursuit. We describe how to apply approaches from computational modeling and network science to think-aloud data to test hypotheses about the function of thought. Finally, we review how tracking thought dynamics can offer insight into the maladaptive patterns that define clinical and affective disorders and the adaptive patterns that contribute to creativity. Broadly, this narrative review offers an integrative, generative, and testable approach for discovering new principles that govern how thought flows and discusses its practical applications, for instance, in creativity and mental health research.