When attention falters: brain, breathing, and behavioral signals of lapses in interoceptive attention

preprint OA: closed
Full text JSON View at publisher
Full text 2,851 characters · extracted from oa-doi-fallback · 2 sections · click to expand

Abstract

Mindlbody practices like meditation and yoga involve paying attention to breathing sensations. During these practices, individuals report “interoceptive lapses,” moments when attention drifts away from internal bodily sensations. While lapses in attention to the external world have been widely studied, little is known about the physiological and neural mechanisms of interoceptive lapses. Interoceptive lapses may share markers with exteroceptive lapses—such as reaction time variability and default-mode network (DMN) connectivity—but may also depend on distinct brain systems and breathing physiology. Here we examined behavioral, physiological and neural signals preceding lapses in a sample of 93 adolescents enriched for GAD and depression symptoms. Participants performed a 20-minute breath counting task in the fMRI scanner with simultaneous breath recordings. Lapses were defined as moments when counting errors occurred. The sample was split into training and validation sets to test machine learning models predicting attentional lapses. The strongest predictors were timing and variability of button responses (AUCs > 0.75). Breathing variability and breathing–behavior synchronization showed smaller but generalizable predictive value (AUCs < 0.65). Whole-brain connectivity models also predicted lapses (AUC ≈ 0.65), incorporating the DMN, dorsal and ventral attention, and somatomotor networks. Further, models that included brain connectivity marginally outperformed behavior-only models. Comparisons to previous exteroceptive findings indicate some common markers (e.g., reaction time variability) and some unique markers (e.g., selective perceptual coupling with attentional networks). Although limited by the clinical sample and lack of a control task, these results highlight brain–body markers of interoceptive attention that may inform real-time monitoring during mind-body interventions. Competing Interest Statement CAW has received consulting fees from King & Spalding law firm for unrelated work. In the past 3 years, RPA has received consulting fees and equity from Get Sonar Inc. He also has received consulting fees from RPA Health Consulting, Inc. and Covington & Burling LLP, which is representing a social media company in litigation. He also serves on the scientific advisory board for the Jake Collective. He also has received funding from AFSP, the Morgan Stanley Foundation, NIMH, and the Erick Shirley Foundation. All other authors report no biomedical financial interests or potential conflicts of interest. Footnotes

Introduction

and Discussion are revised to better contextualize exteroceptive and interoceptive distinctions, highlight breath variability findings, and recognize limitations. A sensitivity analysis to GAD subjects is now included, as well as statistical tests of incremental validity.

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

Ask this paper AI returns verbatim quotes from the full text · source: oa-doi-fallback

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2026) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

Source provenance

europepmc
last seen: 2026-05-20T01:45:00.602351+00:00