Hypnotizability is a psychophysiological trait measured by scales and associated with several differences, including interoceptive accuracy and the morpho‐functional characteristics of interoception‐related brain regions. The aim of the study was to assess whether the amplitude of the heartbeat evoked cortical potential (HEP), a correlate of interoceptive accuracy, differs in participants with low (lows) and high (highs) hypnotizability scores (assessed by the Stanford Hypnotic Susceptibility Scale, Form A) before and after the induction of hypnosis.ECG and EEG were monitored in 16 highs and 15 lows during an experimental session, including open eyes baseline (B), closed eyes relaxation (R), hypnotic induction (IND), neutral hypnosis (NH), and post session baseline (Post). No significant difference was observed between groups and conditions in autonomic variables. The HEP amplitude was lower in highs than in lows at the right parietal site, likely due to hypnotizability related differences in the functional connection between the right insula and parietal cortex. It increased in highs and decreased in lows across the session, possibly due to the highs' preeminently internally directed attention and to the lows' possible disengagement from the task. Since interoception is involved in several cognitive‐emotional functions, its hypnotizability related differences may contribute to the variability of experience and behavior in daily life.

Objective.The emotional response to olfactory stimuli implies the activation of a complex cascade of events triggered by structures lying in the limbic system. However, little is known about how this activation is projected up to cerebral cortex and how different cortical areas dynamically interact each other.Approach.In this study, we acquired EEG from human participants performing a passive odor-perception task with odorants conveying positive, neutral and negative valence. A novel methodological pipeline integrating global field power (GFP), independent component analysis (ICA), dipole source localization was applied to estimate effective connectivity in the challenging scenario of single-trial low-synchronized stimulation.Main results.We identified the brain network and the neural paths, elicited at different frequency bands, i.e. θ(4−7Hz) , α(8−12Hz) and β(13−30Hz) , involved in odor valence processing. This brain network includes the orbitofrontal cortex (OFC), the cingulate gyrus (CgG), the superior temporal gyrus (STG), the posterior cingulate cortex/precuneus (PCC/PCu) and the parahippocampal gyrus (PHG). It was analyzed using a time-varying multivariate autoregressive model to resolve time-frequency causal interactions. Specifically, the OFC acts as the main node for odor perception and evaluation of pleasant and unpleasant stimuli, whereas no specific path was observed for a neutral stimulus.Significance.The results introduce new evidences on the role of the OFC during hedonic perception and underpin its specificity during the odor valence assessment. Our findings suggest that, after the odor onset different, bidirectional interactions occur between the OFC and other brain regions associated with emotion recognition/categorization and memory according to the stimulus valence. This outcome unveils how the hedonic olfactory network dynamically changes based on odor valence.

Previous studies have identified several brain regions involved in the sympathetic response and its integration with pain, cognition, emotions and memory processes. However, little is known about how such regions dynamically interact during a sympathetic activation task. In this study, we analyzed EEG activity and effective connectivity during a cold pressor test (CPT). A source localization analysis identified a network of common active sources including the right precuneus (r-PCu), right and left precentral gyri (r-PCG, l-PCG), left premotor cortex (l-PMC) and left anterior cingulate cortex (l-ACC). We comprehensively analyzed the network dynamics by estimating power variation and causal interactions among the network regions through the direct directed transfer function (dDTF). A connectivity pattern dominated by interactions in $$\alpha$$α (8–12) Hz band was observed in the resting state, with r-PCu acting as the main hub of information flow. After the CPT onset, we observed an abrupt suppression of such $$\alpha$$α -band interactions, followed by a partial recovery towards the end of the task. On the other hand, an increase of $$\delta$$δ -band (1–4) Hz interactions characterized the first part of CPT task. These results provide novel information on the brain dynamics induced by sympathetic stimuli. Our findings suggest that the observed suppression of $$\alpha$$α and rise of $$\delta$$δ dynamical interactions could reflect non-pain-specific arousal and attention-related response linked to stimulus’ salience.

Assessing mobility in daily life can provide significant insights into several clinical conditions, such as Chronic Obstructive Pulmonary Disease (COPD). In this paper, we present a comprehensive analysis of wearable devices’ performance in gait speed estimation and explore optimal device combinations for everyday use. Using data collected from smartphones, smartwatches, and smart shoes, we evaluated the individual capabilities of each device and explored their synergistic effects when combined, thereby accommodating the preferences and possibilities of individuals for wearing different types of devices. Our study involved 20 healthy subjects performing a modified Six-Minute Walking Test (6MWT) under various conditions. The results revealed only little performance differences among devices, with the combination of smartwatches and smart shoes exhibiting superior estimation accuracy. Particularly, smartwatches captured additional health-related information and demonstrated enhanced accuracy when paired with other devices. Surprisingly, wearing all devices concurrently did not yield optimal results, suggesting a potential redundancy in feature extraction. Feature importance analysis highlighted key variables contributing to gait speed estimation, providing valuable insights for model refinement.

Augmented reality (AR) head mounted displays (HMDs) combine user’s natural view of the real world with virtual data. Thus, they might be particularly suited to guide manual tasks as in computer-aided-surgery. However, the typical focal plane of commercial devices is outside the user’s peripersonal space (i.e. the space containing reachable objects), limiting the performance of manual-task guidance. Specifically, known issues such as the "vergence-accomodation-conflict" and the "focus-rivalry" may lead to visual fatigue and mental workload worsening task performance. Here, we exploit EEG recordings during a "connecting-the-dots" task performed with and without AR to study the effects of mental workload associated with AR-related visual fatigue. First, we quantify the reduction of users’ performance based on starting and end points gap errors. Then, we investigate the effects on AR usage on cortical activity through the analysis of EEG power and Frontal Alpha Asymmetry (FAA) index. Although preliminary, EEG power results suggest that mental workload associated with AR usage may derive from enhanced difficulty associated with the task.

Hypnotic susceptibility is a major factor influencing the study of the neural correlates of hypnosis using EEG. In this context, while its effects on the response to hypnotic suggestions are undisputed, less attention has been paid to “neutral hypnosis” (i.e., the hypnotic condition in absence of suggestions). Furthermore, although an influence of opened and closed eye condition onto hypnotizability has been reported, a systematic investigation is still missing. Here, we analyzed EEG signals from 34 healthy subjects with low (LS), medium (MS), and (HS) hypnotic susceptibility using power spectral measures (i.e., TPSD, PSD) and Lempel-Ziv-Complexity (i.e., LZC, fLZC). Indeed, LZC was found to be more suitable than other complexity measures for EEG analysis, while it has been never used in the study of hypnosis. Accordingly, for each measure, we investigated within-group differences between rest and neutral hypnosis, and between opened-eye/closed-eye conditions under both rest and neutral hypnosis. Then, we evaluated between-group differences for each experimental condition. We observed that, while power estimates did not reveal notable differences between groups, LZC and fLZC were able to distinguish between HS, MS, and LS. In particular, we found a left frontal difference between HS and LS during closed-eye rest. Moreover, we observed a symmetric pattern distinguishing HS and LS during closed-eye hypnosis. Our results suggest that LZC is better capable of discriminating subjects with different hypnotic susceptibility, as compared to standard power analysis.