Uncovering a stability signature of brain dynamics associated with meditation experience using massive time-series feature extraction

Previous research has examined resting electroencephalographic (EEG) data to explore brain activity related to meditation. However, previous research has mostly examined power in different frequency bands. The practical objective of this study was to comprehensively test whether other types of time-series analysis methods are better suited to characterize brain activity related to meditation. To achieve this, we compared >7000 time-series features of the EEG signal to comprehensively characterize brain activity differences in meditators, using many measures that are novel in meditation research. Eyes-closed resting-state EEG data from 49 meditators and 46 non-meditators was decomposed into the top eight principal components (PCs). We extracted 7381 time-series features from each PC and each participant and used them to train classification algorithms to identify meditators. Highly differentiating individual features from successful classifiers were analysed in detail. Only the third PC (which had a central-parietal maximum) showed above-chance classification accuracy (67 %, pFDR = 0.007), for which 405 features significantly distinguished meditators (all pFDR < 0.05). Top-performing features indicated that meditators exhibited more consistent statistical properties across shorter subsegments of their EEG time-series (higher stationarity) and displayed an altered distributional shape of values about the mean. By contrast, classifiers trained with traditional band-power measures did not distinguish the groups (pFDR > 0.05). Our novel analysis approach suggests the key signatures of meditators’ brain activity are higher temporal stability and a distribution of time-series values suggestive of longer, larger, or more frequent non-outlying voltage deviations from the mean within the third PC of their EEG data. The higher temporal stability observed in this EEG component might underpin the higher attentional stability associated with meditation. The novel time-series properties identified here have considerable potential for future exploration in meditation research and the analysis of neural dynamics more broadly

Cat owners’ anthropomorphic perceptions of feline emotions and interpretation of photographs

Background: Many cat owners describe the relationship with their cat in anthropomorphic terms like child or best friend. Attributing such human social roles to cats might influence the interpretation of cat behavior and communicative cues. Method: Over 1800 Dutch cat owners filled out an online survey concerning the relationship with, and behavior of, their own cat and beliefs about the emotional lives of cats in general. Owners were also presented with seven photographs of cats (four with reliable cues to identify an emotion and three neutral ones). Results: 52 % of the respondents described the relationship with their cat in human terms such as family member (52 %), as a child (27 %) or as best friend (6 %) while 14 % described their cat as a pet animal. Owners who described the relationship with their cat in human terms, more often a) assigned complex social emotions (such as jealousy and compassion) to cats and b) assigned emotions to neutral photographs. Owners with a realistic perception of cat emotions were better at correctly identifying the emotional photographs. Moreover, owners that attributed complex social emotions to cats in general had a higher tendency to attribute emotions to the neutral photographs. Conclusion: Our study shows that the correct interpretation of feline emotional cues from photographs are negatively associated with owners’ anthropomorphic perception of cats. This study highlights the importance of educating owners about natural cat behavior and realistic views of the emotional life of (their) cats

The 4C framework:Towards a holistic understanding of consumer engagement with augmented reality

Augmented Reality (AR) is an emerging concept that impacts many disciplines, such as business, marketing, tourism, gaming, human-computer interaction, and manufacturing. Surprisingly, many scholarly and practical discussions overlook the fundamental primary factors that distinguish AR from other concepts, namely, that it involves a computing device that integrates virtual content into a consumer's perception of the real world in a specific context. The current article addresses this gap in the literature by proposing the 4C framework (based on the 4Cs: consumer, content, context, and computing device; pronounced: foresee) that highlights the importance of, and interplay among these four factors. Building on configurational theory, the framework calls for the systematic identification of additional AR-relevant factors across the 4Cs. Scholars can use this framework to systematically identify research gaps and variables of interest. Practitioners across various disciplines can employ the framework to systematically assess, communicate, and develop AR use cases

Lysophosphotidylinositols (LysoPIs) are upregulated following human ß-cell loss and act to potentiate insulin release

In this study, we identified new lipid species associated with the loss of pancreatic ß-cells triggering diabetes. We performed lipidomics measurements on serum from prediabetic mice lacking ß-cell prohibititin-2 (ß-Phb2-/-, a model of monogenic diabetes), in patients without previous history of diabetes but scheduled for pancreaticoduodenectomy resulting in the acute reduction of their ß-cell mass (about 50%), and in patients with type 2 diabetes. We found higher lysophosphatidylinositols (LysoPIs) as the main circulating lipid species altered in prediabetic mice. The changes were confirmed in the patients with acute reduction of their ßcell mass and in type 2 diabetes. Increased LysoPIs significantly correlated with HbA1c (reflecting glycemic control), fasting glycemia, and disposition index; without correlation with insulin resistance or obesity in type 2 diabetic humans. INS-1E ß-cells as well as pancreatic islets isolated from non-diabetic mice and human donors exposed to exogenous LysoPIs showed potentiated glucose-stimulated and basal insulin secretion. Finally, addition of exogenous LysoPIs partially rescued impaired glucose-stimulated insulin secretion in islets from mice and humans in the diabetic state. Overall, LysoPIs appear as lipid species being upregulated in the prediabetic stage associated with the loss of ß-cells and supporting the secretory function of the remaining ß-cells

The effect of cations and epigallocatechin gallate on in vitro salivary lubrication

Ionic valency influences oral processing by changing salivary behavior and merits more attention since little is known. In this study, the influence of three ionic valences (monovalent, divalent and trivalent), ionic strength and epigallocatechin gallate (EGCG) on lubricating properties of saliva were investigated. Tribological measurements were used to characterize the lubrication response of KCl, MgCl2, FeCl3, and AlCl3 in combination with EGCG to the ex vivo salivary pellicle. KCl at 150 mM ionic strength provided extra lubrication via hydration lubrication. Contrarily, trivalent salts aggregated together with the salivary mucins via ionic cross-link interactions, which led to a decrease in salivary lubrication. FeCl3 and AlCl3 affected the salivary lubrication differently, which was attributed to changes in the pH. Finally, in presence of EGCG, FeCl3 interacted with EGCG via chelating interactions, preventing salivary protein aggregation. This resulted in less desorption of the salivary film, retaining the lubrication ability of salivary proteins.</p