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Record W4281709601 · doi:10.1101/2022.05.27.493743

Interoceptive Awareness of the Breath Preserves Dorsal Attention Network Activity amidst Widespread Cortical Deactivation: A Within-Participant Neuroimaging Study

2022· preprint· en· W4281709601 on OpenAlexaff
Norman A. S. Farb, Zoey Zuo, Cynthia Price

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersNational Center for Advancing Translational SciencesNational Institutes of HealthUniversity of Washington
KeywordsInteroceptionPsychologyInsulaInsular cortexNeuroimagingNeuroscienceAnterior cingulate cortexNeural correlates of consciousnessFunctional magnetic resonance imagingBrain activity and meditationCognitive psychologyMagnetoencephalographyCognitionElectroencephalographyPerception

Abstract

fetched live from OpenAlex

Abstract Interoception, the representation of the body’s internal state, serves as a foundation for emotion, motivation, and wellbeing. Yet despite its centrality in human experience, the neural mechanisms of interoception are poorly understood. The Interoceptive/Exteroceptive Attention Task (IEAT) is a novel neuroimaging paradigm that compares behavioral tracking of the respiratory cycle (Active Interoception) to tracking of a visual stimulus (Active Exteroception). Twenty-two healthy participants completed the IEAT during two separate scanning sessions (N = 44) as part of a randomized control trial of Mindful Awareness in Body-oriented Therapy (MABT). Compared to Exteroception, Interoception deactivated somatomotor and prefrontal regions. Greater interoceptive sensibility (MAIA scale) predicted sparing from deactivation along the anterior cingulate cortex (ACC) and left-lateralized language regions. The right insula—typically described as a primary interoceptive cortex—was only implicated by its further deactivation during an exogenously paced respiration condition (Active Matching). Psychophysiological interaction analysis characterized Active Interoception as promoting greater ACC connectivity with lateral frontal and parietal regions commonly referred to as the Dorsal Attention Network. Interoception of the breath may therefore involve reduced cortical activity but greater connectivity , with greater sensibility sparing cortical inhibition within well-characterized attentional networks. In contrast to a literature that relates detection of liminal signals such as the heartbeat to anterior insula activity, attention towards accessible body sensations such as the breath may lead to a low activity, high connectivity state in which sensory signals from the body may be better discerned. Significance Statement Interoception, the representation of the body’s internal state, is poorly understood compared to the external senses, with existing neuroimaging studies failing to match task difficulty between interoceptive and exteroceptive tasks. The present study used a novel fMRI task to compare interoceptive and exteroceptive attention, and how this distinction was moderated by self-reported interoceptive awareness. The results implicate three novel interoceptive mechanisms: interoception reduces cortical activity while increasing connectivity , wherein awareness is linked to preserved activation of the brain’s salience network and left-lateralized language regions. These findings characterize interoception as a lower activity state in which awareness depends upon the ability to notice and report on body signals typically obscured by the processing of exteroceptive information and other forms of cognition.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.039
GPT teacher head0.290
Teacher spread0.250 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2022
Admission routes1
Has abstractyes

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