Over the past decade, resting state functional connectivity has shown great promise as a diagnostic and prognostic tool when applied to neurological and psychiatric populations. For example, the integrity of the default mode network - among other large-scale brain networks - has emerged as a common target of neurological disease and psychopathology. Despite this explosion in research, relatively little is understood about the cognitive characteristics of the mind at rest, and most inquiries have relied on retrospective self-report questionnaires that pose challenges for clinical populations with memory or metacognitive deficits. Understanding how different people mentally structure their idle thoughts may shed light on existing clinical neuroscience findings. Furthermore, the resting state is common context in daily life, and the lack of external stimulation during rest periods may foster the emergence of dysfunctional and/or impoverished thoughts for individuals with mental health or neurological conditions. Considering these important gaps, we conducted a line of research quantifying clinical and demographic sources of variability in resting state cognition.

Across three studies, resting state cognition was captured by training adults to voice aloud their thoughts in real time across 7-10 minute rest periods in the lab, the MRI scanner, and participants’ own home. Participants were audio recorded using this think aloud technique, while efforts to minimize thought censorship were also employed. Audio-recorded speech was then transcribed and analyzed for content and dynamic characteristics by external coders and automated text analysis. Relevant characteristics were isolated and examined in relation to variability across participants in trait rumination, divergent thinking (a measure of creativity assessed with a separate Alternate Uses Task), as well as age.

Across studies, the think aloud paradigm in resting state contexts showed promising ecological validity. Participants reported a low degree of thought censorship and a moderate-to-high degree of similarity of thoughts to everyday life. Additionally, total word counts across the transcripts were similar to typical rates of natural speech. Notable variability across participants also emerged in the content and dynamic characteristics of resting state thought.

Increased trait rumination was associated with the emergence of brooding in real time, including a) more negative, self-focused, and past-oriented thoughts, as well as b) dynamic signatures marked by an attraction towards negative conceptual states, and c) a narrowing of conceptual scope following negative content. In contrast, more creative individuals exhibited a pattern of exploration and curiosity in their idle thoughts, with thought transitions characterized as more loosely associative. Finally, older adults generated more linguistic diversity in their use of positive emotional words (a novel marker of emotional granularity), accompanied by increases in psychological well-being.

Taken together, these studies highlight substantial demographic and clinical sources of variability in resting state cognition, with important implications for resting state functional connectivity findings. They also offer a promising methodological tool and theoretical framework to promote further research in neuropsychology and related fields.