Within-Person Modulation of Neural Networks following Interoceptive Awareness Training through Mindful Awareness in Body-Oriented Therapy (MABT): A Pilot Study
Bibliographic record
Abstract
Interoception, the representation of the body's internal state, is increasingly recognized for informing subjective wellbeing and promoting regulatory behavior. However, few empirical reports characterize interoceptive neural networks, and fewer demonstrate changes to these networks in response to an efficacious intervention. Using a two-group randomized controlled trial, this pilot study explored within-participant neural plasticity in interoceptive networks following Mindful Awareness in Body-oriented Therapy (MABT). Participants (N = 22) were assigned to either 8 weeks of MABT or to a no-treatment control and completed baseline and post-intervention assessments that included subjective interoceptive awareness (MAIA) and neuroimaging of an interoceptive awareness task. MABT was uniquely associated with insula deactivation, increased functional connectivity between the dorsal attention network and the somatomotor cortex, and connectivity changes correlated positively with changes in subjective interoception. Within the MABT group, changes in subjective interoception interacted with changes in a predefined anterior cingulate seed region to predict changes in right middle insula activity, a putative primary interoceptive representation region. While the small sample size requires the replication of findings, results suggest that interoceptive training enhances sensory-prefrontal connectivity, and that such changes are commensurate with enhanced interoceptive awareness.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".