Isaac N Treves, Clare Shaffer, Alexandra L Decker, Nigel Jaffe, Anna O Tierney, Randy P Auerbach, Christian A Webb
{"title":"When attention falters: Brain, breathing, and behavioral signals of lapses in interoceptive attention.","authors":"Isaac N Treves, Clare Shaffer, Alexandra L Decker, Nigel Jaffe, Anna O Tierney, Randy P Auerbach, Christian A Webb","doi":"10.3758/s13415-026-01467-5","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":50672,"journal":{"name":"Cognitive Affective & Behavioral Neuroscience","volume":" ","pages":""},"PeriodicalIF":3.6000,"publicationDate":"2026-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cognitive Affective & Behavioral Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3758/s13415-026-01467-5","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BEHAVIORAL SCIENCES","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
Cognitive, Affective, & Behavioral Neuroscience (CABN) offers theoretical, review, and primary research articles on behavior and brain processes in humans. Coverage includes normal function as well as patients with injuries or processes that influence brain function: neurological disorders, including both healthy and disordered aging; and psychiatric disorders such as schizophrenia and depression. CABN is the leading vehicle for strongly psychologically motivated studies of brain–behavior relationships, through the presentation of papers that integrate psychological theory and the conduct and interpretation of the neuroscientific data. The range of topics includes perception, attention, memory, language, problem solving, reasoning, and decision-making; emotional processes, motivation, reward prediction, and affective states; and individual differences in relevant domains, including personality. Cognitive, Affective, & Behavioral Neuroscience is a publication of the Psychonomic Society.