Brain meta-state transitions demarcate thoughts across task contexts exposing the mental noise of trait neuroticism
Julie Tseng, Jordan Poppenk
Abstract
Researchers have observed large-scale neural meta-state transitions that align to narrative events during movie-viewing. However, group or training-derived priors have been needed to detect them. Here, we introduce methods to sample transitions without any priors. Transitions detected by our methods predict narrative events, are similar across task and rest, and are correlated with activation of regions associated with spontaneous thought. Based on the centrality of semantics to thought, we argue these transitions serve as general, implicit neurobiological markers of new thoughts, and that their frequency, which is stable across contexts, approximates participants' mentation rate. By enabling observation of idiosyncratic transitions, our approach supports many applications, including phenomenological access to the black box of resting cognition. To illustrate the utility of this access, we regress resting fMRI transition rate and movie-viewing transition conformity against trait neuroticism, thereby providing a first neural confirmation of mental noise theory.