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Updated: Jun 24, 2026

Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control
Published on: July 5, 2015
When attention falters: Brain, breathing, and behavioral signals of lapses in interoceptive attention
Isaac N Treves1, Clare Shaffer2, Alexandra L Decker3
1Department of Psychiatry, Columbia University, Herbert Pardes 2412, 1051 Riverside Drive, New York City, NY, 10040, USA. Isaac.Treves@nyspi.columbia.edu.
Abstract:
Mind‑body practices, such as 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. 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-min 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. Furthermore, 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.
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