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Record W3176717525 · doi:10.1089/brain.2020.0777

The Relationship Between Functional Connectivity and Interoceptive Sensibility

2021· article· en· W3176717525 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBrain Connectivity · 2021
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsUniversity of ManitobaUniversity of Winnipeg
Fundersnot available
KeywordsSensibilityInteroceptionPsychologyInsulaFunctional magnetic resonance imagingCognitionNeuroscienceResting state fMRINeural correlates of consciousnessFunctional connectivityDefault mode networkCognitive psychologyFunctional imagingAudiologyPerceptionMedicine

Abstract

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Background: Interoceptive signals related to changes in heartbeat, respiration, and gastric functioning continuously feedback to the brain. The interpretation of these signals influences several cognitive, affective, and motoric functions. Previous research has highlighted the distinction between the ability to accurately detect interoceptive information (i.e., interoceptive accuracy) and an individual's beliefs about his or her interoceptive abilities (i.e., interoceptive sensibility). Although numerous studies have delineated the neural substrates of interoceptive accuracy, less is known about the brain areas involved with interoceptive sensibility. Materials and Methods: In the current study, 28 healthy participants completed the Multidimensional Assessment of Interoceptive Awareness (MAIA), a self-report measure of interoceptive sensibility, before undergoing a 7-min resting-state functional magnetic resonance imaging scan. IRB ethics approval was obtained prior to data collection. Results: Overall MAIA scores, as well as scores on its eight subscales, were entered as covariates in subsequent region-of-interest and independent-component analyses. These analyses yielded three key results. First, interoceptive sensibility was negatively correlated with the functional connectivity of visual regions. Second, the cerebellar resting-state network showed positive correlations with two MAIA subscales, suggesting that this structure plays a role in interoceptive functions. Finally, the functional connectivity of the insula, a structure critical for interoceptive accuracy, was not correlated with any of the MAIA scores. Conclusion: These results demonstrate that the brain areas associated with individual differences in interoceptive sensibility show relatively little overlap with those involved with the accurate detection of interoceptive information. The current research demonstrates that individual differences in interoceptive sensibility (i.e., self-reported sensitivity to interoceptive information) are related to differences in resting-state functional connectivity. These data also indicate that the brain areas related to interoceptive sensibility are different than the brain areas involved with interoceptive accuracy (i.e., the objective detection of interoceptive signals). This latter finding suggests that although the insula is critical for many interoceptive processes, our subjective beliefs about our interoceptive abilities involve other neural structures, particularly visual regions and the cerebellum.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.672

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.058
GPT teacher head0.312
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it