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

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Abstract
Mind–body practices like meditation and yoga, which are widely used to support mental health, involve paying attention to internal bodily sensations like the breath. During these practices, individuals often report "interoceptive lapses," moments when attention drifts away from the body. 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 attention lapses — such as reaction time variability and changes in 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 a training and validation sample, and machine learning models predicting attentional lapses were tested. The strongest predictors were timing and variability of button responses (AUCs > 0.75). Breathing variability and breathing–behavior coupling 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.
Funding Information
  • NCCIH (R01AT011002)
  • NIMH (R01MH116969)
  • NIMH (K23MH108752)

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