Laureate Institute for Brain Research, 6655 S Yale Ave, Tulsa, OK 74136, USA.
Laureate Institute for Brain Research, 6655 S Yale Ave, Tulsa, OK 74136, USA; Oxley College of Health & Natural Sciences, The University of Tulsa, 800 S Tucker Dr, Tulsa, OK 74104, USA.
Biol Psychol. 2024 Sep;191:108825. doi: 10.1016/j.biopsycho.2024.108825. Epub 2024 May 31.
Recent Bayesian theories of interoception suggest that perception of bodily states rests upon a precision-weighted integration of afferent signals and prior beliefs. In a previous study, we fit a computational model of perception to behavior on a heartbeat tapping task to test whether aberrant precision-weighting could explain misestimation of cardiac states in psychopathology. We found that, during an interoceptive perturbation designed to amplify afferent signal precision (inspiratory breath-holding), healthy individuals increased the precision-weighting assigned to ascending cardiac signals (relative to resting conditions), while individuals with anxiety, depression, substance use disorders, and/or eating disorders did not. In this pre-registered study, we aimed to replicate and extend our prior findings in a new transdiagnostic patient sample (N = 285) similar to the one in the original study. As expected, patients in this new sample were also unable to adjust beliefs about the precision of cardiac signals - preventing the ability to accurately perceive changes in their cardiac state. Follow-up analyses combining samples from the previous and current study (N = 719) also afforded power to identify group differences between narrower diagnostic categories, and to examine predictive accuracy when logistic regression models were trained on one sample and tested on the other. With this confirmatory evidence in place, future studies should examine the utility of interoceptive precision measures in predicting treatment outcomes and test whether these computational mechanisms might represent novel therapeutic targets.
最近的内感受知觉贝叶斯理论表明,身体状态的感知是基于传入信号和先验信念的精确加权整合。在之前的一项研究中,我们拟合了一个感知的计算模型,以测试行为在心跳敲击任务上,以测试异常的精度加权是否可以解释精神病理学中心脏状态的错误估计。我们发现,在设计用于放大传入信号精度的内感受扰动(吸气屏息)期间,健康个体增加了分配给上升心脏信号的精度加权(相对于休息条件),而焦虑、抑郁、物质使用障碍和/或饮食障碍个体则没有。在这项预先注册的研究中,我们旨在在与原始研究中相同的新的跨诊断患者样本(N=285)中复制和扩展我们之前的发现。正如预期的那样,新样本中的患者也无法调整对心脏信号精度的信念——这阻止了他们准确感知心脏状态变化的能力。对来自之前和当前研究的样本(N=719)进行的后续分析也提供了在更窄的诊断类别之间识别组间差异的能力,并检验了当逻辑回归模型在一个样本上进行训练并在另一个样本上进行测试时的预测准确性。有了这些确认性的证据,未来的研究应该检验内感受精度测量在预测治疗结果方面的效用,并测试这些计算机制是否可能代表新的治疗靶点。