Spectral and topological analyses of the cortical representation of the head position: Does hypnotizability matter?

Is hypnotic assessment relevant to neurology?

Studies conducted in healthy subjects have clearly shown that different hypnotic susceptibility, which is measured by scales, is associated with different functional equivalence between imagery and perception/action (FE), cortical excitability, and information processing. Of note, physiological differences among individuals with high (highs), medium (mediums), and low hypnotizability scores (lows) have been observed in the ordinary state of consciousness, thus independently from the induction of the hypnotic state, and in the absence of specific suggestions. The potential role of hypnotic assessment and its relevance to neurological diseases have not been fully explored. While current knowledge and therapies allow a better survival rate, there is a constant need to optimize rehabilitation treatments and quality of life. The aim of this paper is to provide an overview of hypnotizability-related features and, specifically, to discuss the hypothesis that the stronger FE, the different mode of information processing, and the greater proneness to control pain and the activity of the immune system observed in individuals with medium-to-high hypnotizability scores have potential applications to neurology. Current evidence of the outcome of treatments based on hypnotic induction and suggestions administration is not consistent, mainly owing to the small sample size in clinical trials and inadequate control groups. We propose that hypnotic assessment may be feasible in clinical routine and give additional cues into the treatment and rehabilitation of neurological diseases.

Does Hypnotizability Affect Neurovascular Coupling During Cognitive Tasks?

The susceptibility to hypnosis is a very pervasive psychophysiological trait characterized by different attentional abilities, information processing, and cardiovascular control. Since near infrared spectroscopy (NIRS) is a good index of neurovascular coupling, we used it during mental computation (MC) and trail making task (TMT) in 13 healthy low-to-medium (med-lows) and 10 healthy medium-to-high hypnotizable (med-highs) participants classified according to the Stanford Hypnotic Susceptibility Scale (SHSS), form A, and characterized for the level of proneness to be deeply absorbed in cognitive tasks by the Tellegen Absorption Scale (TAS). Med-highs reported greater absorption than med-lows. The tissue hemoglobin index (THI) and the tissue oxygenation index (TOI) increased across the tasks only in med-highs who displayed also different time courses of THI and TOI during MC and TMT, which indicates different tasks processing despite the two groups' similar performance. The findings suggest that the med-highs' tissue oxygenation is more finely adjusted to metabolic demands than med-lows'.

Cerebral Blood Flow in Healthy Subjects with Different Hypnotizability Scores

Hypnotizability is a cognitive trait associated with differences in the brachial artery flow-mediated dilatation of individuals with high hypnotizability (highs) and low hypnotizability scores (lows). The study investigated possible hypnotizability-related cerebrovascular differences. Among 24 healthy volunteers, the Stanford Hypnotic Susceptibility Scale Form A identified 13 medium-to-lows (med-lows), 11 medium-to-highs (med-highs), and 1 medium hypnotizable. Hypnotizability did not influence the significant changes produced by the trail making task (TMT), mental arithmetic task (MAT), hyperventilation (HVT), and rebreathing (RBT) on heart rate (HR), arterial blood pressure (ABP), and partial pressure of end-tidal CO₂ (P_ETCO₂), but moderated the correlations between the changes occurring during tasks with respect to basal conditions (Δ) in ABP and P_ETCO₂ with middle cerebral artery flow velocity (MCAv). In HVT, med-lows exhibited a significant correlation between ΔMCAv and ΔP_ETCO₂, and med-highs showed a significant correlation between ΔABP and ΔMCAv. Cerebrovascular reactivity (CVR) and conductance (ΔCVCi) were significantly correlated with ΔMCAv only in med-lows during HVT and RBT. For the first time, cerebrovascular reactivity related to hypnotizability was investigated, evidencing different correlations among hemodynamic variables in med-highs and med-lows.

Topological Features of Electroencephalography are Robust to Re-referencing and Preprocessing

Electroencephalography (EEG) is among the most widely diffused, inexpensive, and adopted neuroimaging techniques. Nonetheless, EEG requires measurements against a reference site(s), which is typically chosen by the experimenter, and specific pre-processing steps precede analyses. It is therefore valuable to obtain quantities that are minimally affected by reference and pre-processing choices. Here, we show that the topological structure of embedding spaces, constructed either from multi-channel EEG timeseries or from their temporal structure, are subject-specific and robust to re-referencing and pre-processing pipelines. By contrast, the shape of correlation spaces, that is, discrete spaces where each point represents an electrode and the distance between them that is in turn related to the correlation between the respective timeseries, was neither significantly subject-specific nor robust to changes of reference. Our results suggest that the shape of spaces describing the observed configurations of EEG signals holds information about the individual specificity of the underlying individual's brain dynamics, and that temporal correlations constrain to a large degree the set of possible dynamics. In turn, these encode the differences between subjects' space of resting state EEG signals. Finally, our results and proposed methodology provide tools to explore the individual topographical landscapes and how they are explored dynamically. We propose therefore to augment conventional topographic analyses with an additional-topological-level of analysis, and to consider them jointly. More generally, these results provide a roadmap for the incorporation of topological analyses within EEG pipelines.

From mathematics to medicine: A practical primer on topological data analysis (TDA) and the development of related analytic tools for the functional discovery of latent structure in fMRI data

fMRI is the preeminent method for collecting signals from the human brain in vivo, for using these signals in the service of functional discovery, and relating these discoveries to anatomical structure. Numerous computational and mathematical techniques have been deployed to extract information from the fMRI signal. Yet, the application of Topological Data Analyses (TDA) remain limited to certain sub-areas such as connectomics (that is, with summarized versions of fMRI data). While connectomics is a natural and important area of application of TDA, applications of TDA in the service of extracting structure from the (non-summarized) fMRI data itself are heretofore nonexistent. “Structure” within fMRI data is determined by dynamic fluctuations in spatially distributed signals over time, and TDA is well positioned to help researchers better characterize mass dynamics of the signal by rigorously capturing shape within it. To accurately motivate this idea, we a) survey an established method in TDA (“persistent homology”) to reveal and describe how complex structures can be extracted from data sets generally, and b) describe how persistent homology can be applied specifically to fMRI data. We provide explanations for some of the mathematical underpinnings of TDA (with expository figures), building ideas in the following sequence: a) fMRI researchers can and should use TDA to extract structure from their data; b) this extraction serves an important role in the endeavor of functional discovery, and c) TDA approaches can complement other established approaches toward fMRI analyses (for which we provide examples). We also provide detailed applications of TDA to fMRI data collected using established paradigms, and offer our software pipeline for readers interested in emulating our methods. This working overview is both an inter-disciplinary synthesis of ideas (to draw researchers in TDA and fMRI toward each other) and a detailed description of methods that can motivate collaborative research.

An evolutionary approach to hypnotizability

We propose here an evolutionary interpretation of the presence of highly hypnotizable persons (highs) among the general population. Current experimental evidence suggests the presence of stronger functional equivalence between imagery and perception, non-opioid cognitive control of pain, favorable cardiovascular asset, and greater interoceptive sensitivity in highs. We hypothesize that these characteristics were greatly relevant to our ancestors' survival, and that they may have facilitated the natural selection of individuals who are now named "highs" due to one of their side effects - the proneness to accept suggestions - as part of the reported physiological features. Unfortunately, our theoretical hypothesis cannot be currently experimentally proven. We believe, however, that looking at hypnotizability in a naturalistic, evolutionary perspective may emphasize the importance of its physiological correlates in daily life and in the prediction of the outcome of medical treatments.

Homological scaffold via minimal homology bases

The homological scaffold leverages persistent homology to construct a topologically sound summary of a weighted network. However, its crucial dependency on the choice of representative cycles hinders the ability to trace back global features onto individual network components, unless one provides a principled way to make such a choice. In this paper, we apply recent advances in the computation of minimal homology bases to introduce a quasi-canonical version of the scaffold, called minimal, and employ it to analyze data both real and in silico. At the same time, we verify that, statistically, the standard scaffold is a good proxy of the minimal one for sufficiently complex networks.

Hypnotizability-Related Asymmetries: A Review

Hypnotizability is a dispositional trait reflecting the individual ability to modify perception, memory and behavior according to imaginative suggestions. It is measured by validated scales that classify the general population in high (highs), medium (mediums) and low (lows) hypnotizable persons, predicts the individual proneness to respond to suggestions, and is particularly popular in the field of the cognitive control of pain and anxiety. Different hypnotizability levels, however, have been associated with specific brain morpho-functional characteristics and with peculiarities in the cognitive, sensorimotor and cardiovascular domains also in the ordinary state of consciousness and in the absence of specific suggestions. The present scoping review was undertaken to summarize the asymmetries observed in the phenomenology and physiological correlates of hypnosis and hypnotizability as possible indices of related hemispheric prevalence. It presents the findings of 137 papers published between 1974 and 2019. In summary, in the ordinary state of consciousness, behavioral, neurophysiological and neuroimaging investigations have revealed hypnotizability related asymmetries mainly consisting of pre-eminent left hemisphere information processing/activation in highs, and no asymmetries or opposite directions of them in lows. The described asymmetries are discussed in relation to the current theories of hypnotizability and hypnosis.

Exact topological inference of the resting-state brain networks in twins

A cycle in a brain network is a subset of a connected component with redundant additional connections. If there are many cycles in a connected component, the connected component is more densely connected. Whereas the number of connected components represents the integration of the brain network, the number of cycles represents how strong the integration is. However, it is unclear how to perform statistical inference on the number of cycles in the brain network. In this study, we present a new statistical inference framework for determining the significance of the number of cycles through the Kolmogorov-Smirnov (KS) distance, which was recently introduced to measure the similarity between networks across different filtration values by using the zeroth Betti number. In this paper, we show how to extend the method to the first Betti number, which measures the number of cycles. The performance analysis was conducted using the random network simulations with ground truths. By using a twin imaging study, which provides biological ground truth, the methods are applied in determining if the number of cycles is a statistically significant heritable network feature in the resting-state functional connectivity in 217 twins obtained from the Human Connectome Project. The MATLAB codes as well as the connectivity matrices used in generating results are provided at http://www.stat.wisc.edu/∼mchung/TDA.

In this paper, we propose a new topological distance based on the Kolmogorov-Smirnov (KS) distance that is adapted for brain networks, and compare them against other topological network distances including the Gromov-Hausdorff (GH) distances. KS-distance is recently introduced to measure the similarity between networks across different filtration values by using the zeroth Betti number, which measures the number of connected components. In this paper, we show how to extend the method to the first Betti number, which measures the number of cycles. The performance analysis was conducted using random network simulations with ground truths. Using a twin imaging study, which provides biological ground truth (of network differences), we demonstrate that the KS distances on the zeroth and first Betti numbers have the ability to determine heritability.

Spectral and topological analyses of the cortical representation of the head position: Does hypnotizability matter?

INTRODUCTION

The aim of this exploratory study was to assess the EEG correlates of head positions (which have never been studied in humans) in participants with different psychophysiological characteristics, as encoded by their hypnotizability scores. This choice is motivated by earlier studies suggesting different processing of vestibular/neck proprioceptive information in subjects with high (highs) and low (lows) hypnotizability scores maintaining their head rotated toward one side (RH).

METHODS

We analyzed EEG signals recorded in 20 highs and 19 lows in basal conditions (head forward) and during RH using spectral analysis, which captures changes localized to specific recording sites, and topological data analysis (TDA), which instead describes large-scale differences in processing and representing sensorimotor information.

RESULTS

Spectral analysis revealed significant differences related to head position for alpha 1, beta 2, beta 3, and gamma bands, but not to hypnotizability. TDA instead revealed global hypnotizability-related differences in the strengths of the correlations among recording sites during RH. Significant changes were observed in lows on the left parieto-occipital side and in highs in right frontoparietal region. Significant differences between the two groups were found in the occipital region, where changes were larger in lows than in highs.

CONCLUSIONS

This study reports finding of the EEG correlates of changes in the head posture for the first time, indicating that hypnotizability is related to the head posture representation/processing on large-scale networks and that spectral and topological data analyses provide complementary results.