Combining Different Wearable Devices to Assess Gait Speed in Real-World Settings.

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.

Effects of semantic relationship and preactivation on memory updating.

Semantic relationship modulates working memory (WM) processes by promoting recall but impairing recognition. Updating is a core mechanism of WM responsible for its stability and flexibility; it allows maintenance of relevant information while removing no-longer relevant one. To our knowledge, no studies specifically investigated how WM updating may benefit from the processing of semantically related material. In the current study, two experiments were run with this aim. In Experiment 1, we found an advantage for semantically related words (vs. unrelated) regardless of their association type (i.e., taxonomic or thematic). A second experiment was run boosting semantic association through preactivation. Findings replicated those of Experiment 1 suggesting that preactivation was effective and improved semantic superiority. In sum, we demonstrated that long-term semantic associations benefitted the updating process, or more generally, overall WM function. In addition, pre-activating semantic nodes of a given word appears likely a process supporting WM and updating; thus, this may be the mechanism favoring word process and memorization in a semantically related text.

Atypical holistic processing of facial identity and expression in a case of acquired prosopagnosia.

Typical face perception is mediated by holistic processing (i.e., the simultaneous integration of face parts into a whole representation). People with Acquired Prosopagnosia (AP), who have lost the ability to recognise faces after a brain lesion, should thus show atypical holistic coding. Our aim is to use the composite-face effect (CFE) as a measure of holistic processing in ST, a 48-year-old woman with AP but normal recognition of facial expressions of emotions, and matched healthy control participants. Two experiments examining the CFE for identity (Experiment 1) and for expression of emotions (Experiment 2) were conducted. Contrary to controls, in both experiments, ST showed an atypical (i.e., reversed) CFE, thus suggesting altered holistic mechanisms affecting both components of perceptual judgement. Results also suggest that normal facial expression recognition is achievable even with holistic processing difficulties, possibly through compensatory, part-based, mechanisms.

Awake prone positioning for patients with COVID-19-related respiratory failure: a systematic review and meta-analysis.

The role of awake prone positioning (aPP) in patients with acute hypoxemic respiratory failure is debated. We performed a systematic review and meta-analysis to evaluate the role of aPP in acute respiratory failure related to COronaVIrus Disease-19 (COVID-19). Studies reporting on the clinical course of patients with acute respiratory failure related to COVID-19 treated or not treated by aPP were included in the systematic review and meta-analysis (ProsperoID: CRD42022333211). The primary study outcome was the composite of in-hospital death or orotracheal intubation; the individual components of the primary outcome were secondary study outcomes. The composite of in-hospital death or orotracheal intubation was available for 6 studies (1884 patients), five randomized and one prospective; a significant reduction in the risk of this outcome was observed in patients treated vs. not treated by aPP (33.5% vs. 39.8%; OR 0.73, 95% CI 0.60-0.89; I2 0%). In-hospital death was reported in 34 studies (6808 patients) and occurred in 17.4% vs. 23.5% of patients treated or not treated with aPP (random effect OR 0.60, 95% CI 0.46-0.79; I2 59%); orotracheal intubation was observed in 25.8% vs. 32.7% of patients treated or not treated with aPP (27 studies, 5369 patients; random effect OR 0.85, 95% CI 0.56-1.27; I2 84%). aPP reduces the risk for death or orotracheal intubation in patients with acute respiratory failure related to COVID-19. Further studies should be conducted to confirm the clinical benefit of aPP outside the ICU.Registration Prospero ID: CRD42022333211.

Combining electrodermal activity analysis and dynamic causal modeling to investigate the visual-odor multimodal integration during face perception.

Objective. This study presents a novel methodological approach for incorporating information related to the peripheral sympathetic response into the investigation of neural dynamics. Particularly, we explore how hedonic contextual olfactory stimuli influence the processing of neutral faces in terms of sympathetic response, event-related potentials and effective connectivity analysis. The objective is to investigate how the emotional valence of odors influences the cortical connectivity underlying face processing and the role of face-induced sympathetic arousal in this visual-olfactory multimodal integration.Approach. To this aim, we combine electrodermal activity (EDA) analysis and dynamic causal modeling to examine changes in cortico-cortical interactions.Results. The results reveal that stimuli arising sympathetic EDA responses are associated with a more negative N170 amplitude, which may be a marker of heightened arousal in response to faces. Hedonic odors, on the other hand, lead to a more negative N1 component and a reduced the vertex positive potential when they are unpleasant or pleasant. Concerning connectivity, unpleasant odors strengthen the forward connection from the inferior temporal gyrus (ITG) to the middle temporal gyrus, which is involved in processing changeable facial features. Conversely, the occurrence of sympathetic responses after a stimulus is correlated with an inhibition of this same connection and an enhancement of the backward connection from ITG to the fusiform face gyrus.Significance. These findings suggest that unpleasant odors may enhance the interpretation of emotional expressions and mental states, while faces capable of eliciting sympathetic arousal prioritize identity processing.

Deep learning applied to EEG source-data reveals both ventral and dorsal visual stream involvement in holistic processing of social stimuli.

Perception of social stimuli (faces and bodies) relies on "holistic" (i.e., global) mechanisms, as supported by picture-plane inversion: perceiving inverted faces/bodies is harder than perceiving their upright counterpart. Albeit neuroimaging evidence suggested involvement of face-specific brain areas in holistic processing, their spatiotemporal dynamics and selectivity for social stimuli is still debated. Here, we investigate the spatiotemporal dynamics of holistic processing for faces, bodies and houses (adopted as control non-social category), by applying deep learning to high-density electroencephalographic signals (EEG) at source-level. Convolutional neural networks were trained to classify cortical EEG responses to stimulus orientation (upright/inverted), separately for each stimulus type (faces, bodies, houses), resulting to perform well above chance for faces and bodies, and close to chance for houses. By explaining network decision, the 150-200 ms time interval and few visual ventral-stream regions were identified as mostly relevant for discriminating face and body orientation (lateral occipital cortex, and for face only, precuneus cortex, fusiform and lingual gyri), together with two additional dorsal-stream areas (superior and inferior parietal cortices). Overall, the proposed approach is sensitive in detecting cortical activity underlying perceptual phenomena, and by maximally exploiting discriminant information contained in data, may reveal spatiotemporal features previously undisclosed, stimulating novel investigations.

Visual attention and memory in professional traders.

Professional traders need to process a large amount of visual information in their daily activity to judge how risky it is to trade specific investment products. Despite some studies investigating the effects of display clutter on traders, visual attention and memory were never investigated in controlled experimental tasks in this population. Following a preliminary study with 30 participants, visual selective attention and visual working memory were measured and compared between two groups of 15 traders and 15 non-traders (salespeople, acting as a control group) from a large-scale banking group in three experimental tasks measuring selective attention in complex visual contexts, simulating display clutter situations (Visual search), cognitive interference (Stroop task), and a delayed recall visual working memory task. In the Visual search task, traders displayed faster response times (RTs) than non-traders for small display sets, while their performance overlapped for large sets. In the Stroop task, traders showed faster RTs than non-traders but were nevertheless affected by cognitive interference. The memory task highlighted no significant differences between the groups. Therefore, this study found an advantage in traders' attention when processing visual information in small sets with no retention. This result could influence trading activity-determining an immediate use of relevant visual information in decision making-and traders' display layout organization.

Face pareidolia is enhanced by 40 Hz transcranial alternating current stimulation (tACS) of the face perception network.

Pareidolia refers to the perception of ambiguous sensory patterns as carrying a specific meaning. In its most common form, pareidolia involves human-like facial features, where random objects or patterns are illusionary recognized as faces. The current study investigated the neurophysiological correlates of face pareidolia via transcranial alternating current stimulation (tACS). tACS was delivered at gamma (40 Hz) frequency over critical nodes of the "face perception" network (i.e., right lateral occipito-temporal and left prefrontal cortex) of 75 healthy participants while completing four face perception tasks ('Mooney test' for faces, 'Toast test', 'Noise pareidolia test', 'Pareidolia task') and an object perception task ('Mooney test' for objects). In this single-blind, sham-controlled between-subjects study, participants received 35 min of either Sham, Online, (40Hz-tACS_ON), or Offline (40Hz-tACS_PRE) stimulation. Results showed that face pareidolia was causally enhanced by 40Hz-tACS_PRE in the Mooney test for faces in which, as compared to sham, participants more often misperceived scrambled stimuli as faces. In addition, as compared to sham, participants receiving 40Hz-tACS_PRE showed similar reaction times (RTs) when perceiving illusory faces and correctly recognizing noise stimuli in the Toast test, thus not exhibiting hesitancy in identifying faces where there were none. Also, 40Hz-tACS_ON induced slower rejections of face pareidolia responses in the Noise pareidolia test. The current study indicates that 40 Hz tACS can enhance pareidolic illusions in healthy individuals and, thus, that high frequency (i.e., gamma band) oscillations are critical in forming coherent and meaningful visual perception.

The Evolution of Psychological and Behavioral Consequences of Self-Isolation During Lockdown: A Longitudinal Study Across United Kingdom and Italy.

Introduction: Several countries imposed nationwide or partial lockdowns to limit the spread of COVID-19 and avoid overwhelming hospitals and intensive care units. Lockdown may involve restriction of movement, stay-at-home orders and self-isolation, which may have dramatic consequences on mental health. Recent studies demonstrated that the negative impact of lockdown restrictions depends on a wide range of psychological and socio-demographic factors. Aims: This longitudinal study aimed to understand how internal factors such as personality and mindfulness traits, and external factors, such as daily habits and house features, affect anxiety, depression and general wellbeing indicators, as well as cognitive functions, during the course of a lockdown. Methods: To address these questions, 96 participants in Italy and the United Kingdom filled out a survey, once a week for 4 weeks, during the first-wave lockdowns. The survey included questions related to their habits and features of the house, as well as validated questionnaires to measure personality traits, mindful attitude and post-traumatic symptoms. Indicators of wellbeing were the affective state, anxiety, stress and psychopathological indices. We also measured the emotional impact of the pandemic on cognitive ability by using two online behavioral tasks [emotional Stroop task (EST) and visual search]. Results: We found that internal factors influenced participants' wellbeing during the first week of the study, while external factors affected participants in the last weeks. In the first week, internal variables such as openness, conscientiousness and being non-judgmental toward one's own thoughts and emotions were positively associated with wellbeing; instead, neuroticism and the tendency to observe and describe one's own thoughts and emotions had detrimental effects on wellbeing. Toward the end of the study, external variables such as watching television and movies, browsing the internet, walking the dog, and having a balcony showed a protective value, while social networking and engaging in video calls predicted lower values of wellbeing. We did not find any effects of wellbeing on cognitive functioning. Conclusion: Recognizing specific traits and habits affecting individuals' wellbeing (in both short and long terms) during social isolation is crucial to identify people at risk of developing psychological distress and help refine current guidelines to alleviate the psychological consequences of prolonged lockdowns.

Mindfulness-based online intervention increases well-being and decreases stress after Covid-19 lockdown.

Mindfulness interventions were shown to be effective in improving well-being and reducing perceived stress in several conditions. These effects were also found in online mindfulness-based training, especially in employees in organizational environments. The aim of this study was to test the effectiveness of an online mindfulness intervention on healthy employees, especially after the first Italian Covid-19 lockdown. Participants in the intervention group underwent an 8-week mindfulness online training program based on the Mindfulness-Based Stress Reduction (MBSR) protocol compared to a control (no-intervention) group. All participants filled in weekly surveys for the whole intervention duration via online questionnaires to measure their habits, mindfulness (FFMQ-15), emotion regulation (ERQ), positive and negative affect (PANAS), depression, anxiety and stress (DASS-21), resilience (RSA) and insomnia (ISI). 69 participants in the intervention group and 63 in the no-treatment control group were considered in the longitudinal analyses. We found significant differences between the intervention and control groups over time in the measures of mindfulness (in particular the nonreactivity subscale), positive affect, depression, and insomnia. Moreover, we found that the frequency of practice and ease perceived in practicing were positively correlated to several indices of well-being (mindfulness, positive affect, cognitive reappraisal) and negatively correlated to several indices of stress (negative affect, depression, anxiety, stress, insomnia, expressive suppression). These results show the importance and effectiveness of online mindfulness training programs to cope with stress among employees, especially after the Covid-19 lockdown.

Understanding action concepts from videos and brain activity through subjects' consensus.

In this paper, we investigate brain activity associated with complex visual tasks, showing that electroencephalography (EEG) data can help computer vision in reliably recognizing actions from video footage that is used to stimulate human observers. Notably, we consider not only typical "explicit" video action benchmarks, but also more complex data sequences in which action concepts are only referred to, implicitly. To this end, we consider a challenging action recognition benchmark dataset-Moments in Time-whose video sequences do not explicitly visualize actions, but only implicitly refer to them (e.g., fireworks in the sky as an extreme example of "flying"). We employ such videos as stimuli and involve a large sample of subjects to collect a high-definition, multi-modal EEG and video data, designed for understanding action concepts. We discover an agreement among brain activities of different subjects stimulated by the same video footage. We name it as subjects consensus, and we design a computational pipeline to transfer knowledge from EEG to video, sharply boosting the recognition performance.

Mental health in the post-lockdown pandemic phase: Relief or exacerbation of psychological distress? A cross-sectional study in the general population in Italy.

This study is one of the first aiming at investigating the mental health in the post-lockdown period in an Italian adult population and detecting demographic and psychological predictors for a worse outcome. 1401 participants answered a web-based survey including the Emotional Reaction Questionnaire (ERQ), the Positive Affect and Negative Affect Scale (PANAS), the Impact of Event Scale-Revised (IES-R), the General Health Questionnaire (GHQ), the Depression, Anxiety and Stress Scale (DASS-21), and the Dutch Work Addiction Scale (DUWAS). Simple slope analyses highlighted that women, lower age, and suppression were related to higher scores for the PANAS negative affect scale, the DASS-21, the IES-R, the GHQ, and the DUWAS. In our sample, 1.2% of participants showed depressive symptoms, 0.5% anxiety symptoms, and 2% stress symptoms. Moreover, 5.4% of participants reported post-traumatic symptoms and 15% signs of psychological distress. Compared with data on the lockdown period, our results show lower levels of depressive, anxiety, and stress symptoms, possibly due to the slackening of preventive measures adopted since June. Despite this, post-traumatic symptoms and signs of psychological distress were still present. Our data suggest the necessity to monitor psychological adaption over time in general and at-risk subjects.

Estimating Successful Internal Mobility: A Comparison Between Structural Equation Models and Machine Learning Algorithms.

Internal mobility often depends on predicting future job satisfaction, for such employees subject to internal mobility programs. In this study, we compared the predictive power of different classes of models, i.e., (i) traditional Structural Equation Modeling (SEM), with two families of Machine Learning algorithms: (ii) regressors, specifically least absolute shrinkage and selection operator (Lasso) for feature selection and (iii) classifiers, specifically Bagging meta-model with the k-nearest neighbors algorithm (k-NN) as a base estimator. Our aim is to investigate which method better predicts job satisfaction for 348 employees (with operational duties) and 35 supervisors in the training set, and 79 employees in the test set, all subject to internal mobility programs in a large Italian banking group. Results showed average predictive power for SEM and Bagging k-NN (accuracy between 61 and 66%; F1 scores between 0.51 and 0.73). Both SEM and Lasso algorithms highlighted the predictive power of resistance to change and orientation to relation in all models, together with other personality and motivation variables in different models. Theoretical implications are discussed for using these variables in predicting successful job relocation in internal mobility programs. Moreover, these results showed how crucial it is to compare methods coming from different research traditions in predictive Human Resources analytics.

Eye contact during joint attention with a humanoid robot modulates oscillatory brain activity.

Eye contact established by a human partner has been shown to affect various cognitive processes of the receiver. However, little is known about humans' responses to eye contact established by a humanoid robot. Here, we aimed at examining humans' oscillatory brain response to eye contact with a humanoid robot. Eye contact (or lack thereof) was embedded in a gaze-cueing task and preceded the phase of gaze-related attentional orienting. In addition to examining the effect of eye contact on the recipient, we also tested its impact on gaze-cueing effects (GCEs). Results showed that participants rated eye contact as more engaging and responded with higher desynchronization of alpha-band activity in left fronto-central and central electrode clusters when the robot established eye contact with them, compared to no eye contact condition. However, eye contact did not modulate GCEs. The results are interpreted in terms of the functional roles involved in alpha central rhythms (potentially interpretable also as mu rhythm), including joint attention and engagement in social interaction.

Robot Gaze Behavior Affects Honesty in Human-Robot Interaction.

As the use of humanoid robots proliferates, an increasing amount of people may find themselves face-to-"face" with a robot in everyday life. Although there is a plethora of information available on facial social cues and how we interpret them in the field of human-human social interaction, we cannot assume that these findings flawlessly transfer to human-robot interaction. Therefore, more research on facial cues in human-robot interaction is required. This study investigated deception in human-robot interaction context, focusing on the effect that eye contact with a robot has on honesty toward this robot. In an iterative task, participants could assist a humanoid robot by providing it with correct information, or potentially secure a reward for themselves by providing it with incorrect information. Results show that participants are increasingly honest after the robot establishes eye contact with them, but only if this is in response to deceptive behavior. Behavior is not influenced by the establishment of eye contact if the participant is actively engaging in honest behavior. These findings support the notion that humanoid robots can be perceived as, and treated like, social agents, since the herein described effect mirrors one present in human-human social interaction.

I Am Looking for Your Mind: Pupil Dilation Predicts Individual Differences in Sensitivity to Hints of Human-Likeness in Robot Behavior.

The presence of artificial agents in our everyday lives is continuously increasing. Hence, the question of how human social cognition mechanisms are activated in interactions with artificial agents, such as humanoid robots, is frequently being asked. One interesting question is whether humans perceive humanoid robots as mere artifacts (interpreting their behavior with reference to their function, thereby adopting the design stance) or as intentional agents (interpreting their behavior with reference to mental states, thereby adopting the intentional stance). Due to their humanlike appearance, humanoid robots might be capable of evoking the intentional stance. On the other hand, the knowledge that humanoid robots are only artifacts should call for adopting the design stance. Thus, observing a humanoid robot might evoke a cognitive conflict between the natural tendency of adopting the intentional stance and the knowledge about the actual nature of robots, which should elicit the design stance. In the present study, we investigated the cognitive conflict hypothesis by measuring participants' pupil dilation during the completion of the InStance Test. Prior to each pupillary recording, participants were instructed to observe the humanoid robot iCub behaving in two different ways (either machine-like or humanlike behavior). Results showed that pupil dilation and response time patterns were predictive of individual biases in the adoption of the intentional or design stance in the IST. These results may suggest individual differences in mental effort and cognitive flexibility in reading and interpreting the behavior of an artificial agent.

Anodal tDCS effects over the left dorsolateral prefrontal cortex (L-DLPFC) on the rating of facial expression: evidence for a gender-specific effect.

The accurate recognition of others' facial expressions is a core skill for social interactions. The left Dorsolateral Prefrontal Cortex (L-DLPFC) represents a key node in the network for facial emotion recognition. However, its specific role is still under debate. As such, the aim of the current neuromodulation study was to assess the causal role of the L-DLPFC in humans' rating of facial expressions of emotions and implicit attitudes toward other races. In this sham-controlled single-blind between-subject experiment, we offline administered L-DLPFC transcranial direct current stimulation (tDCS) to 69 healthy participants who were divided into three groups of 23 (each receiving anodal 1 mA tDCS, anodal 2 mA tDCS, or Sham), before completing an "Emotion Rating task and two Implicit Association Tests (IATs). The former required the intensity rating of 192 faces (half black and half white) displaying happiness, sadness, anger, or fear. The IATs were designed to assess participants' automatic associations of positive or negative attributes with racial contents. Results on the Emotion Rating task showed participants' gender-specific effect of tDCS. Specifically, a gender bias, with only males showing a tendency to underestimate negative emotions was found in Sham, and absent in the tDCS groups. When considering the race of the stimuli, females but not males in Sham exhibited a racial bias, that is, the tendency to overestimate negative emotions of other-race faces. Again, the bias disappeared in the tDCS groups. Concerning the IATs, no significant effects emerged. We conclude that the L-DLPFC plays a critical role in humans' rating of facial expressions, and for variability in other-race emotional judgements. These results shed light on the neural bases of the human emotional system and its gender-related differences, and have potential implications for interventional settings.

The human brain reveals resting state activity patterns that are predictive of biases in attitudes toward robots.

The increasing presence of robots in society necessitates a deeper understanding into what attitudes people have toward robots. People may treat robots as mechanistic artifacts or may consider them to be intentional agents. This might result in explaining robots' behavior as stemming from operations of the mind (intentional interpretation) or as a result of mechanistic design (mechanistic interpretation). Here, we examined whether individual attitudes toward robots can be differentiated on the basis of default neural activity pattern during resting state, measured with electroencephalogram (EEG). Participants observed scenarios in which a humanoid robot was depicted performing various actions embedded in daily contexts. Before they were introduced to the task, we measured their resting state EEG activity. We found that resting state EEG beta activity differentiated people who were later inclined toward interpreting robot behaviors as either mechanistic or intentional. This pattern is similar to the pattern of activity in the default mode network, which was previously demonstrated to have a social role. In addition, gamma activity observed when participants were making decisions about a robot's behavior indicates a relationship between theory of mind and said attitudes. Thus, we provide evidence that individual biases toward treating robots as either intentional agents or mechanistic artifacts can be detected at the neural level, already in a resting state EEG signal.

Theta- and Gamma-Band Activity Discriminates Face, Body and Object Perception.

Face and body perception is mediated by configural mechanisms, which allow the perception of these stimuli as a whole, rather than the sum of individual parts. Indirect measures of configural processing in visual cognition are the face and body inversion effects (FIE and BIE), which refer to the drop in performance when these stimuli are perceived upside-down. Albeit FIE and BIE have been well characterized at the behavioral level, much still needs to be understood in terms of the neurophysiological correlates of these effects. Thus, in the current study, the brain's electrical activity has been recorded by a 128 channel electroencephalogram (EEG) in 24 healthy participants while perceiving (upright and inverted) faces, bodies and houses. EEG data were analyzed in both the time domain (i.e., event-related potentials-ERPs) and the frequency domain [i.e., induced theta (5-7 Hz) and gamma (28-45 Hz) oscillations]. ERPs amplitude results showed increased N170 amplitude for inverted faces and bodies (compared to the same stimuli presented in canonical position) but not for houses. ERPs latency results showed delayed N170 components for inverted (vs. upright) faces, houses, but not bodies. Spectral analysis of induced oscillations indicated physiological FIE and BIE; that is decreased gamma-band synchronization over right occipito-temporal electrodes for inverted (vs. upright) faces, and increased bilateral frontoparietal theta-band synchronization for inverted (vs. upright) faces. Furthermore, increased left occipito-temporal and right frontal theta-band synchronization for upright (vs. inverted) bodies was found. Our findings, thus, demonstrate clear differences in the neurophysiological correlates of face and body perception. The neurophysiological FIE suggests disruption of feature binding processes (decrease in occipital gamma oscillations for inverted faces), together with enhanced feature-based attention (increase in frontoparietal theta oscillations for inverted faces). In contrast, the BIE may suggest that structural encoding for bodies is mediated by the first stages of configural processing (decrease in occipital theta oscillations for inverted bodies).