Breathing in waves: Understanding respiratory-brain coupling as a gradient of predictive oscillations.

Breathing plays a crucial role in shaping perceptual and cognitive processes by regulating the strength and synchronisation of neural oscillations. Numerous studies have demonstrated that respiratory rhythms govern a wide range of behavioural effects across cognitive, affective, and perceptual domains. Additionally, respiratory-modulated brain oscillations have been observed in various mammalian models and across diverse frequency spectra. However, a comprehensive framework to elucidate these disparate phenomena remains elusive. In this review, we synthesise existing findings to propose a neural gradient of respiratory-modulated brain oscillations and examine recent computational models of neural oscillations to map this gradient onto a hierarchical cascade of precision-weighted prediction errors. By deciphering the computational mechanisms underlying respiratory control of these processes, we can potentially uncover new pathways for understanding the link between respiratory-brain coupling and psychiatric disorders.

The respiratory resistance sensitivity task: An automated method for quantifying respiratory interoception and metacognition.

The ability to sense, monitor, and control respiration - e.g., respiratory interoception (henceforth, respiroception) is a core homeostatic ability. Beyond the regulation of gas exchange, enhanced awareness of respiratory sensations is directly related to psychiatric symptoms such as panic and anxiety. Indeed, chronic breathlessness (dyspnea) is associated with a fourfold increase in the risk of developing depression and anxiety, and the regulation of the breath is a key aspect of many mindfulness-based approaches to the treatment of mental illness. Physiologically speaking, the ability to accurately monitor respiratory sensations is important for optimizing cardiorespiratory function during athletic exertion, and can be a key indicator of illness. Given the important role of respiroception in mental and physical health, it is unsurprising that there is increased interest in the quantification of respiratory psychophysiology across different perceptual and metacognitive levels of the psychological hierarchy. Compared to other more popular modalities of interoception, such as in the cardiac domain, there are relatively few methods available for measuring aspects of respiroception. Existing inspiratory loading tasks are difficult to administer and frequently require expensive medical equipment, or offer poor granularity in their quantification of respiratory-related perceptual ability. To facilitate the study of respiroception, we here present a new, fully automated and computer-controlled apparatus and psychophysiological method, which can flexibly and easily measure respiratory-related interoceptive sensitivity, bias and metacognition, in as little as 30 min of testing, using easy to make 3D printable parts.

The heart rate discrimination task: A psychophysical method to estimate the accuracy and precision of interoceptive beliefs.

Interoception - the physiological sense of our inner bodies - has risen to the forefront of psychological and psychiatric research. Much of this research utilizes tasks that attempt to measure the ability to accurately detect cardiac signals. Unfortunately, these approaches are confounded by well-known issues limiting their validity and interpretation. At the core of this controversy is the role of subjective beliefs about the heart rate in confounding measures of interoceptive accuracy. Here, we recast these beliefs as an important part of the causal machinery of interoception, and offer a novel psychophysical "heart rate discrimination" method to estimate their accuracy and precision. By applying this task in 223 healthy participants, we demonstrate that cardiac interoceptive beliefs are more biased, less precise, and are associated with poorer metacognitive insight relative to an exteroceptive control condition. Our task, provided as an open-source python package, offers a robust approach to quantifying cardiac beliefs.

Evidence From Meta-Analysis Supports Ictal Magnetoencephalographic Source Imaging as an Accurate Method in Presurgery Evaluation of Patients With Drug-Resistant Epilepsy.

BACKGROUND.: Successful epilepsy surgery relies on localization and removal of the brain area responsible for initializing the seizures called the epileptogenic zone (EZ). Intracranial EEG (icEEG) is gold standard of this localization but has several limitations like invasiveness and limited covered area. A noninvasive method with accurate localization precision is therefore desirable. The aim of this article is to investigate the following hypotheses: (1) Ictal onset zone as localized by magnetic source imaging (iMSI) can reliably localize the EZ in focal epilepsy and (2) this localization is as good as that of icEEG. METHODS.: Six original studies and a total of 59 unique patients were included in a meta-analysis. RESULTS.: Sensitivity and specificity of iMSI based on surgery outcome were 77% (95% CI 60%-90%) and 75% (95% CI 53%-90%), respectively. Specificity of iMSI was statistically higher than that of icEEG. There was no significant difference between sensitivity of iMSI and icEEG. CONCLUSION.: The meta-analysis supports that iMSI is an accurate method, achieving similar sensitivity and higher specificity than icEEG. However, at present the use of the method is limited by short recording times. A limitation that might be overcome in the future using technical advances.