The relationship between transliminality, hypnotic and imaginative suggestibility, and other personality traits.

To our knowledge, no study has directly examined the link between hypnotic response and the personality trait of transliminality (which is underpinned, for example, by magical ideation, mystical experience, fantasy proneness, absorption, hyperaesthesia). In order to further understand the correlates of suggestibility, the aim of the current project was to investigate whether transliminality is associated with hypnotic and imaginative suggestibility (considering: objective response, subjective response and involuntariness). Another aim was to assess the contribution of transliminality as a predictor of suggestibility when a range of previously studied personality trait measures were considered. Participants completed: the Revised Transliminality Scale, Tellegen Absorption Scale, Creative Experiences Questionnaire, and the Dissociative Experiences Scale II. To avoid context effects, where knowledge or measurement of one trait or ability might influence measurement of another, a separate standalone study was conducted where hypnotic and imaginative (without hypnosis) suggestibility screenings were carried out in-person in small groups using the modified Carleton University Responsiveness to Suggestion Scale. The merging of these two datasets enabled the analyses. Transliminality was weakly correlated with the imaginative suggestibility subjective response measure (r = 0.19). Likewise, weak correlations were found between transliminality and the hypnotic suggestibility response measures (objective, r = 0.21, subjective, r = 0.23, involuntariness, r = 0.24). The multiple regressions (forward selection) reflected the pattern of correlations, with no model for any of the variables, retaining more than a single significant predictor. In summary, this study combination, avoiding context effects, shows transliminality to be a weak predictor of response to suggestion.

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.

Emotional metacognition: stimulus valence modulates cardiac arousal and metamemory.

Emotion alters how we feel, see, and experience the world. In the domain of memory, the emotional valence and arousal of memorised stimuli can modulate both the acuity and content of episodic recall. However, no experiment has investigated whether arousal and valence also influence metacognition for memory (i.e. the process of self-monitoring memories). In a pre-registered study, we applied a novel psychophysiological design together with computational models of metacognition to assess the influence of stimulus valence and arousal on the sensitivity, bias, and efficiency of metamemory. To estimate the role of physiological arousal in mediating these effects, we recorded cardiac measures through pulse oximetry. We found that negative valence substantially decreased both memory performance and subjective confidence, in particular for low arousal words. Simultaneously, we found that emotional valence modulated both heart rate and heart-rate variability (HRV) during recognition memory. Exploratory trial-level analyses further revealed that subjective confidence was encoded in instantaneous heart-rate fluctuations and that this relationship was also modulated by emotional valence. Our results demonstrate that recognition memory and metacognition are influenced by the emotional valence of encoded items and that this correlation is in part related to cardiac activity.

Eigenvector alignment: Assessing functional network changes in amnestic mild cognitive impairment and Alzheimer's disease.

Eigenvector alignment, introduced herein to investigate human brain functional networks, is adapted from methods developed to detect influential nodes and communities in networked systems. It is used to identify differences in the brain networks of subjects with Alzheimer's disease (AD), amnestic Mild Cognitive Impairment (aMCI) and healthy controls (HC). Well-established methods exist for analysing connectivity networks composed of brain regions, including the widespread use of centrality metrics such as eigenvector centrality. However, these metrics provide only limited information on the relationship between regions, with this understanding often sought by comparing the strength of pairwise functional connectivity. Our holistic approach, eigenvector alignment, considers the impact of all functional connectivity changes before assessing the strength of the functional relationship, i.e. alignment, between any two regions. This is achieved by comparing the placement of regions in a Euclidean space defined by the network's dominant eigenvectors. Eigenvector alignment recognises the strength of bilateral connectivity in cortical areas of healthy control subjects, but also reveals degradation of this commissural system in those with AD. Surprisingly little structural change is detected for key regions in the Default Mode Network, despite significant declines in the functional connectivity of these regions. In contrast, regions in the auditory cortex display significant alignment changes that begin in aMCI and are the most prominent structural changes for those with AD. Alignment differences between aMCI and AD subjects are detected, including notable changes to the hippocampal regions. These findings suggest eigenvector alignment can play a complementary role, alongside established network analytic approaches, to capture how the brain's functional networks develop and adapt when challenged by disease processes such as AD.