Investigating the neural basis of spontaneous thought with fMRI and mindfulness meditation
Bibliographic record
Abstract
One of the most intriguing yet least understood aspects of the human mind is its tendency to give rise to spontaneous, undirected mental processes – thoughts that occur and proceed without our deliberate effort or control. The present dissertation examined the neural basis of spontaneous thought by integrating first-person reports from individuals with extensive introspective training (i.e., mindfulness meditators) with third-person neural measures from fMRI experience sampling procedures. In Experiment 1, time courses of brain activation during self-caught spontaneous thought events revealed that the medial temporal lobe (MTL) was recruited first, suggesting it may be central to the initial generation of spontaneous thoughts. The medial prefrontal cortex (MPFC) showed recruitment next, suggesting it may be important for the subsequent affective elaboration of spontaneous thoughts. The lateral prefrontal cortex (LPFC) showed recruitment last, suggesting it may contribute to further metacognitive evaluation and monitoring of spontaneous thoughts. In Experiment 2, spontaneous thought elaboration events (i.e., when a second thought followed an initial thought) showed increased MPFC activation and decreased MTL activation. Spontaneous thought elaboration may thus engage affective evaluation processes while suppressing associative generation processes. In Experiment 3, spontaneous thoughts reported during high MTL activity (as determined by real-time fMRI software) were associated with meaning-making content such as remembering, planning, and linking concepts. In contrast, spontaneous thoughts reported during low MTL activity were associated with present-centered content such as body sensations, emotions, awareness, and concentration. The level of MTL activation may thus reflect different qualities, but not necessarily different quantities, of spontaneous thought. First-person, introspective information about the timing, sequence, and content of spontaneous thoughts collected in the present experiments helps to refine current accounts of how brain regions consistently implicated in spontaneous thought specifically contribute to its component processes. The present dissertation reflects a step toward expanding the role of first-person, introspective reports in neuroscience in order to enhance our understanding of the full spectrum of human thought.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".