Two systems of resting state connectivity between the insula and cingulate cortex
Bibliographic record
Abstract
The insula and cingulate cortices are implicated in emotional, homeostatic/allostatic, sensorimotor, and cognitive functions. Non-human primates have specific anatomical connections between sub-divisions of the insula and cingulate. Specifically, the anterior insula projects to the pregenual anterior cingulate cortex (pACC) and the anterior and posterior mid-cingulate cortex (aMCC and pMCC); the mid-posterior insula only projects to the posterior MCC (pMCC). In humans, functional neuroimaging studies implicate the anterior insula and pre/subgenual ACC in emotional processes, the mid-posterior insula with awareness and interoception, and the MCC with environmental monitoring, response selection, and skeletomotor body orientation. Here, we tested the hypothesis that distinct resting state functional connectivity could be identified between (1) the anterior insula and pACC/aMCC; and (2) the entire insula (anterior, middle, and posterior insula) and the pMCC. Functional connectivity was assessed from resting state fMRI scans in 19 healthy volunteers using seed regions of interest in the anterior, middle, and posterior insula. Highly correlated, low-frequency oscillations (< 0.05 Hz) were identified between specific insula and cingulate subdivisions. The anterior insula was shown to be functionally connected with the pACC/aMCC and the pMCC, while the mid/posterior insula was only connected with the pMCC. These data provide evidence for a resting state anterior insula-pACC/aMCC cingulate system that may integrate interoceptive information with emotional salience to form a subjective representation of the body; and another system that includes the entire insula and MCC, likely involved in environmental monitoring, response selection, and skeletomotor body orientation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".