A Window to the Mind: Validation of a New Method to Measure Thought Dynamics Using Brain Network Meta-State Transitions
spontaneous thought , functional neuroimaging , dimensionality reduction , neurocinematics , time-varying functional connectivity , event segmentation
In addition to what people are thinking about, researchers are also increasingly interested in how humans flow continuously from one mental state to the next (i.e., the flights and perches of thought; James, 1890). Can we pinpoint these moments of flight directly from neural signals? I drew upon the Human Connectome Project’s Young Adult functional magnetic resonance imaging (fMRI) dataset to characterize the psychological meaning of changes in functional connectivity during movie-viewing and at rest. I began with a representation of brain activity at each timepoint as the set of activations across 15 networks, and used new methods to embed this high-dimensional network representation onto a two-dimensional space of possible network configurations (network meta-states). Furthermore, I identified large jumps between consecutive timepoints in the reduced space, which I call meta-state transitions and should reflect prominent changes in the configuration of active networks. I found that participants’ meta-state transitions were strongly related to the progression of meaning across events within movie stimuli. Meta-state transitions also shared many characteristics across movie and resting fMRI data, including concurrence with activation of brain regions associated with spontaneous thought, suppression by engagement of attention regions, and trait-like rates of occurrence. Based on these features, as well as the centrality of semantics to thought, I argue that meta-state transitions correspond to the initiation of new thoughts, and that characterizing transition features may serve as a direct neural measurement of how one thinks (i.e., their mentation). By exploring neural and behavioural correlates of meta-state transition rate and transition group alignment during movie-viewing, I also illustrate how this approach can contribute insights to emerging research on thought dynamics by bridging the gap between behavioural assessments and traditional neuroimaging analysis techniques.