The landscape of ongoing thought is heterogeneous and shaped by both personal traits and environmental context. Recent work shows that attention and control systems organize experience in response to changing demands, while the default mode network contributes not only to task-negative or episodic content but also to the vividness of experience in both task contexts and spontaneous self-generated states. Multiple neural systems reflect the landscape of ongoing thought, and it is important to distinguish processes that shape how experience unfolds from those that regulate it.
When people are not engaged in an explicit task, they experience a variety of self-generated thoughts, such as planning or reminiscing. Using machine learning to analyze brain activity from resting-state fMRI scans, researchers identified distinct neural states that recur over time. Two of these states predicted different patterns of thinking. One neural state, resembling activity seen during demanding tasks, was linked to problem-solving about the future. Another state, associated with less demanding conditions, was tied to intrusive thoughts about the past. These two states fell at opposite ends of a brain hierarchy related to cognitive demand. The findings show that tracking moment-to-moment changes in brain function can help classify self-generated mental states and that these states align with the brain's response to cognitive tasks.